First national tuberculosis patient cost survey in Lao People's Democratic Republic: Assessment of the financial burden faced by TB-affected households and the comparisons by drug-resistance and HIV status.

BACKGROUND: Tuberculosis (TB) patients incur large costs for care seeking, diagnosis, and treatment. To understand the magnitude of this financial burden and its main cost drivers, the Lao People's Democratic Republic (PDR) National TB Programme carried out the first national TB patient cost survey in 2018-2019.
METHOD: A facility-based cross-sectional survey was conducted based on a nationally representative sample of TB patients from public health facilities across 12 provinces. A total of 848 TB patients including 30 drug resistant (DR)-TB and 123 TB-HIV coinfected patients were interviewed using a standardised questionnaire developed by the World Health Organization. Information on direct medical, direct non-medical and indirect costs, as well as coping mechanisms was collected. We estimated the percentage of TB-affected households facing catastrophic costs, which was defined as total TB-related costs accounting for more than 20% of annual household income. RESULT: The median total cost of TB care was US$ 755 (Interquartile range 351-1,454). The costs were driven by direct non-medical costs (46.6%) and income loss (37.6%). Nutritional supplements accounted for 74.7% of direct non-medical costs. Half of the patients used savings, borrowed money or sold household assets to cope with TB. The proportion of unemployment more than doubled from 16.8% to 35.4% during the TB episode, especially among those working in the informal sector. Of all participants, 62.6% of TB-affected households faced catastrophic costs. This proportion was higher among households with DR-TB (86.7%) and TB-HIV coinfected patients (81.1%).
CONCLUSION: In Lao PDR, TB patients and their households faced a substantial financial burden due to TB, despite the availability of free TB services in public health facilities. As direct non-medical and indirect costs were major cost drivers, providing free TB services is not enough to ease this financial burden. Expansion of existing social protection schemes to accommodate the needs of TB patients is necessary.

Introduction

Tuberculosis (TB) is one of the major public health concerns globally [1]. TB patients usually incur a substantial financial cost for care seeking, diagnosis, and treatment [2]. Poverty is already known to be linked to a higher risk of TB infection and disease, delays in diagnosis, and poor treatment adherence, which can result in adverse treatment outcomes and the development of multi-drug resistant (MDR)-TB [2-5]. TB also worsens poverty as TB patients often lose the ability to work, leading to income loss [5-7]. In addition, households affected by TB will often mobilize funds for TB treatment by dissaving, selling assets, or taking out loans, which makes them poorer, and traps them in a cycle of poverty and disease [8-10].

Considering the global burden of TB and the social, human and financial consequences of TB, the World Health Organization (WHO) has developed the End TB Strategy, which outlines the ambitious goal of ending the TB epidemic worldwide by 2030 [11]. Recognizing the need to address the financial burden due to TB, the Strategy promotes assessment of TB patient costs and set a target of zero “catastrophic costs” for TB-affected families, in the context of Universal Health Coverage, in addition to two traditional epidemiological targets (reduced incidence and deaths) [11].

To establish the baseline against which to monitor the progress towards the elimination of catastrophic costs, WHO recommends that a nationally representative survey be carried out. These surveys are prioritised for the 30 high TB burden countries [11]. In 2015, WHO developed a generic protocol and data collection tool to support countries in planning and implementing the national TB patient cost surveys, which were later refined and published as a handbook in 2017 [12]. The WHO-recommended data collection tool is designed to collect a range of cost data including direct medical costs (i.e. costs for medical consultations, examinations, drugs, and hospitalization), direct non-medical costs (i.e. transportation, foods and accommodation), and indirect costs (i.e. loss of income). Based on this information, catastrophic costs attributable to TB can be calculated. “Catastrophic costs due to TB” refers to medical and non-medical out-of-pocket payments and indirect costs exceeding a given threshold (e.g. 20%) of the household’s income [11, 12].

The Lao PDR National TB Programme (NTP) has developed their National TB Strategic Plan 2017–2020 which is aligned with the WHO’s End TB Strategy and the Regional Framework for Action on Implementation of the End TB Strategy in the Western Pacific 2016–2020 [11, 13]. One of the key indicators is: “Zero TB affected families facing catastrophic costs due to TB” [14]. It was therefore prerequisite for the NTP to conduct a national TB patient cost survey to establish a baseline of the target and inform policies and strategies. The study objectives were to assess the financial burden of TB from the patient perspective and to estimate the proportion of households experiencing catastrophic costs due to TB, by drug-susceptibility and HIV status. This survey also assessed major cost drivers of patients’ expenditure during TB episode and associated risk factors for facing catastrophic costs due to TB.

Method

Study setting

Lao PDR is a landlocked country surrounded by China, Viet Nam, Cambodia, and Thailand, and the majority of the country is mountainous and forested [15, 16]. The population size was 6.9 million in 2017, and the majority of the population (60%) live in rural areas [17]. The country is divided into one capital city (Vientiane Capital) and 17 provinces. The capital is located on the banks of Mekong river nearby to the border with Thailand, and the population size was 820,940 in 2015 [18]. Lao PDR has gross domestic product (GDP) growth average at 7.8%, and is a lower middle income country with US$ 14.5 billion in Gross National Income (GNI) and a gross national income per capita of US$ 2,150 per annum in 2016 [19].

Lao PDR has a high burden of TB [1]. The first national TB prevalence survey in Lao PDR, conducted in 2010–2011, revealed that the prevalence of bacteriologically confirmed pulmonary TB was estimated at 237 cases per 100,000 population [20]. According to the WHO’s estimates, the TB incidence rate remained high in 2018, at 162 cases per 100,000 population (all forms of TB), while the incidence rate of HIV positive TB and Multidrug-/rifampicin-resistant TB (MDR/RR-TB) were 10 and 2.2 cases per 100,000 respectively [1, 21]. The TB mortality rate in Lao PDR was 33.8 cases per 100,000 population in 2017 [1, 21].

In Lao PDR, approximately 20% of the total population work in the formal sector and are covered by a comprehensive benefit schemes such as State Authority for Social Security (SASS) and Social Security Organization (SSO) under the National Social Security Fund (NSSF). The NSSF includes health insurance, sickness benefits, and unemployment benefits [22]. The tax-based National Health Insurance (NHI) scheme was launched in 2016. The NHI covered 60% of the population as of 2016, and the coverage was expected to reach more than 70% in 2017 [23]. The national health insurance bureau has recently reported that the coverage reached 79.3% in 2019. All health services defined by the Essential Health Service Package (EHSP) at public health facilities in the country are covered by the NHI scheme [24, 25]. Costs for TB diagnosis and treatment and hospitalization for all TB patients are covered by the NTP and NHI who cover the cost of sputum examinations including smear, culture and Xpert MTB/RIF (a rapid molecular test), testing and counselling for HIV, and anti-TB drugs for all TB patients including second-line drugs [25]. Eleven of 25 central and provincial hospitals provide both integrated TB and HIV services, including the provision of both TB treatment and Anti-Retroviral Therapy (ART) [26-28].

Study design, population, and sample size

Following the WHO recommended study design, we conducted a facility-based cross-sectional survey and extrapolated costs in the patient’s current TB treatment phase (i.e. intensive or continuation) to assess the total costs associated with a diagnosis of TB and ongoing TB care [12]. We used a cluster sampling strategy to ensure a nationally representative sample. The primary sampling unit was the Basic Management Unit (BMU) of the NTP; these are 165 district, provincial, and central hospitals [1, 12]. A total of 25 BMUs was randomly selected by a probability proportional to size (PPS) method applying the TB case notification in 2017 for each BMU [1]. With a design effect of 2.0, an estimated catastrophic cost prevalence of 50%, and a precision level of 5%, the required sample size was 725. We assumed incidence of 50% catastrophic costs in Lao PDR from the previous TB patient cost surveys conducted in the Western Pacific Region (Philippines: 35%, Vietnam: 63%, Mongolia: 70% with an unweighted average of 56%) [29]. An estimated prevalence of 50% provided the most conservative sample size. In addition to this nationally representative sample, we enrolled additional and operationally feasible quotas of 120 TB-HIV co-infected patients and 30 DR-TB (i.e. MDR-TB or RR-TB) patients to assess the difference in the financial burden of TB comparing drug-resistant and drug-susceptible TB patients and for patients with and without TB-HIV co-infection. We enrolled all the patients on DR-TB treatment at the time of interview in the country (total sampling). For TB-HIV patients, assuming estimated proportion of catastrophic costs at 80% with 10% precision and design effect of 2, the sample size was estimated at 122.

All eligible TB patients were those who were currently on TB treatment linked to the NTP (including adults and children) who had received at least 14 days of treatment in either the intensive or continuation phase of TB treatment. The participants were selected randomly from TB log-book at each facility. If a child was recruited, we interviewed the parent of the child participant. We excluded people who were treated in facilities that are unlinked to the NTP (i.e. private facilities which do not report TB cases to the NTP).

Data collection

We used a standardised questionnaire developed by WHO, adapted this to the country context, and translated into the local language. Twelve interviewers were recruited through an open recruitment process. We conducted a 3-day training for all staff and interviewers involved in the survey in October 2018, and the interview tool was piloted during the training using the Ona online platform [30]. We then undertook face-to-face interviews with randomly selected TB patients at health facilities during their facility visits and entered responses directly into tablets using the ONA online platform [12, 30].

The questionnaire included questions on different types of direct medical costs (e.g. medical consultation, laboratory tests, medications, hospitalization), direct non-medical costs (e.g. transportation, food, accommodation, and nutritional supplements such as vitamin supplements and/or additional foods other than regular diets) and indirect costs (income loss and time lost for care seeking). We also collected demographic and clinical information, information on health care utilization, household assets, coping mechanisms (e.g. dissaving, borrowing, sold assets), and perceived social and financial impacts of a TB diagnosis and care. Each patient was interviewed once and reported on expenditures and time spent for care seeking, coping mechanism, and household assets and income during the current treatment phase (e.g. either the intensive phase or the continuation phase). Total time spent for care seeking was estimated by multiplying time loss for the last visit with frequency of visits per month and the duration of TB treatment. For patients interviewed in the intensive phase, retrospective data on costs and time spent for care seeking before TB diagnosis were also collected, however these questions were not asked of patients in the continuation phase. Data collection was conducted between December 2018 until January 2019, followed by the additional data collection for DR-TB and TB-HIV co-infected patients which was carried out in May and June 2019.

Data analysis

For continuous data, median, mean, inter-quartile range (IQR), 95% confidence interval (95%CI) were presented, and for categorical data, frequencies were calculated. The median values were used to present information on costs and incomes, due to the skewness of the data. We assessed the difference between DS-TB and DR-TB using Fisher’s exact test for categorical data and the Welsh T-test or two-sample Wilcoxon rank-sum test for continuous data. Statistical significance was defined as p<0.05, and statistical analyses and data visualizations were performed using Stata 15.2 (StataCorp 2018) and R4.0.2 (CRAN: Comprehensive R Archive Network at https://cran.r-project.org/). Due to different sampling methods for nationally representative sample and additional sample of DR-TB and TB-HIV coinfected patients, statistical tests were performed only in nationally representative sample. All cost and income data were collected in the local currency (Lao Kip) and then were converted into US$ for analysis at the rate of 8,495 Kip per 1 US$ (oanda.com).

For patient cost data, we calculated median costs with IQR stratified by different cost types (direct medical and direct non-medical costs and indirect costs) from the time of onset of TB symptom until the TB treatment completion. Since we collected only the costs of TB treatment incurred during the treatment phase patients were in at the time of the interview, the costs of the other treatment phase for were extrapolated based on the median costs incurred by other patients in that treatment phase at the time of the interview. For example, to estimate pre-treatment costs and costs during TB intensive phase for patients who were in continuation phase at the time of interview, the median costs of pre-treatment costs and intensive phase were taken from the patients who were in intensive phase at the time of interview. In this calculation for extrapolating costs, costs from DS-TB and DR-TB patients, and patients with and without hospitalizations were considered separately. We estimated income loss in TB patients’ households using the income prior to the current TB episode and that at the time of interview (output approach). Monthly self-reported income was used as the primary method for determining household income. However, we also computed predicted annual household income based on a linear regression analysis using household asset information (as we collected information on household assets in the questionnaire). 20% of annual household income was used as the threshold to define catastrophic costs due to TB, consistent with the definition proposed by WHO [12]. Clustering effects associated with sampling method were adjusted in estimating overall proportion of catastrophic costs using the svy command in Stata software. An additional sensitivity analysis was conducted to assess how varying the threshold (to different percentages from 0% to 100%) affected the proportion of catastrophic costs faced by TB-affected households.

Then we carried out a univariate logistic regression analysis to identify demographic and clinical factors associated with facing catastrophic costs due to TB. The sample used in this regression excluded the additional patients recruited who had MDR-TB and TB-HIV co-infection. We included variables in our multivariate logistic regression analysis, if they were significant at the 10% level (P<0.10) in univariate analyses. Clustering effects associated with sampling method were adjusted both in univariate and multivariate analyses using the svy command in Stata software.

Ethical approval

The survey was approved by the Ethics Review Committee of the WHO Regional Office for the Western Pacific (WHO/WPRO) (Ref: 2018.10.LAO.4.STB) and the Lao PDR National Ethics Committee for Health Research (Ref: 091/NECHR). Written informed consent was obtained from all the survey participants before the commencement of the interview. For participants aged < 15 years of age, we obtained written informed consent from a parent or guardian.

Results

Study population

A total of 848 TB patients participated in the survey, and of these 725 patients (717 DS-TB and 8 DR-TB) were enrolled as a nationally representative sample (the national sample) and 123 patients (22 DR-TB and 101 TB-HIV) were enrolled as an additional sample (). In the national sample, 59.7% were male, and the mean age was 50.4 years. 0.8% were children aged under 15 years old. The proportion of HIV positive patients was 2.6%, while 32.0% had unknown HIV status. The demographic characteristics of the national sample were similar to the data observed and reported in NTP routine surveillance. The proportion of participants with no education or had only attended primary school was 41.2%, and 61.9% had informal paid jobs before their TB diagnosis. The majority of participants (75.9%, N = 550) reported that they were not covered by any health insurance, and only (6.2%, N = 45) were insured by SSO or SASS. The mean household size was 5.7 individuals with a median monthly household income of US$ 235 (IQR: 118–471).

No significant differences were observed in socio-demographic factors when comparing patients with DS-TB from the national sample and patients with DR-TB. In all TB-HIV patients with additional sample (N = 123), the mean age of 33.8 years was considerably lower than the nationally representative sample (the mean age of 50.4 years), and the median monthly household income of US$ 353 was higher than other groups ().

In the national sample, 97.9% were newly diagnosed, and 62.8% were in the continuation phase of TB treatment (). The majority (94.2%) had pulmonary TB, and 68.2% were bacteriologically confirmed. The proportion of patients who were taking TB treatment in a public health centre or a district hospital was 71.0% in the national sample. On the other hand, most of the DR-TB and TB-HIV coinfected patients were receiving TB treatment in provincial or central hospitals (DR-TB: 100% and TB-HIV: 96.7%) with a high incidence of hospitalization during the current treatment phase compared to patients with DS-TB (national sample DR-TB: 75.0% and DS-TB: 11.4% p<0.001. With additional samples, all DR-TB: 90.0% and all TB-HIV: 38.2%).

The median number of weeks reported from the onset of TB symptoms until initiation of TB treatment was 4 weeks, with an average of 1.8 visits to a health facility before a TB diagnosis was made (the maximum number of visits was 19). Just over one third (30.4%, N = 79) of 260 patients who were in the intensive phase initiated their care seeking at private healthcare providers such as traditional healers, private pharmacies, clinics and/or hospitals. The large majority of patients in the national sample (97.7%) were self-administering TB medications, while half of DR-TB patients were receiving directly observed therapy (DOT) while they were hospitalized in the TB ward (national sample, DS-TB: 1.8%, DR-TB: 50.0%, p<0.001. With additional sample, all DR-TB: 56.7%, all TB-HIV: 12.2%). Therefore, visits for drug pick-up was most frequent (15.6 times) in the national sample and for patients with DS-TB, while DR-TB patients had more DOT visits (136.4 times) during TB treatment.

Time loss for care seeking

The median total time loss for care seeking for TB patients and their caregivers from the onset of TB symptoms until the completion of TB treatment was 95 hours (IQR: 79–139) and 1 hour (IQR: 0–13), respectively, with a significantly larger time loss for DR-TB patients when compared to DS-TB patients in the national sample (patients: DS-TB 95 hours (IQR: 79–139), DR-TB 1,327 hours (IQR: 665–2,517), p = 0.006) (). Time loss associated with the pre-diagnosis period and hospitalization was also significantly longer among DR-TB patients compared to DS-TB (Pre-diagnosis: DS-TB 9 hours (IQR: 3–44), DR-TB 40 hours (IQR: 32–270), p = 0.050. Hospitalization: DS-TB 76 hours (IQR: 37–158), DR-TB 755 hours (IQR: 301–1,088), p = 0.026). No significant differences were observed in time loss in caregivers in the national sample. With additional sample, TB-HIV patients also reported a considerably longer time spent on hospitalization (patients: 122 hours (IQR: 83–220)).

Estimated total costs borne by TB patient and their households

The total median cost incurred for TB care was US$ 755 (IQR: US$ 351–1,454); equivalent to 3.2 times the average monthly salary of TB patients in the survey (). Only 9.2% of costs were incurred before a TB diagnosis. The largest cost driver was direct non-medical costs (46.6%), followed by indirect costs (37.6%) and direct medical costs (15.8%) (). In particular, the costs for special foods and nutritional supplements other than the patients regular diet was high, comprising 34.8% of total costs. Total costs were nearly double for TB-HIV co-infected patients and triple for patients with DR-TB (DR-TB: US$ 2,243, TB-HIV: US$ 1,633) compared to DS-TB patients (US$ 748). The high costs among DR-TB and TB-HIV co-infected patients were largely attributed to nutritional supplements outside their normal diet and income loss during TB treatment, while TB-HIV co-infected patients had a relatively large proportion of direct medical costs (DR-TB: nutritional supplement 49.7%, income loss 35.1%) (TB-HIV: nutritional supplement 23.3%, income loss 39.2%, direct medical costs 26.2%) ().

Reported coping mechanisms and social consequences

In the national sample, half (49.9%) of households relied on savings, loans, and/or selling assets to cope with the financial burden and consequences of TB (), while this figure was higher for DR-TB patients (56.7%) and TB-HIV co-infected patients (65.0%). One fifth (N = 147, 20.3%) of households experienced food insecurity, 29.5% lost a job, and 10.3% experienced social exclusion due to TB. The proportion of TB-affected households who experienced separation or divorce from their partners or who had interrupted schooling for their children was significantly higher among DR-TB patients (separation/divorce: DS-TB 2.1%, DR-TB 12.5%, p = 0.046) (interrupted schooling: DS-TB 1.4%, DR-TB 12.5%, p = 0.011).

More than half of the national sample (54.5%) reported that TB care had a moderate, severe, or very severe financial impact on their household, and 56.3% perceived that TB treatment impoverished their households, when compared to their baseline financial position (). These proportions were significantly higher among DR-TB patients in the national sample (financial impact: DS-TB 54.2%, DR-TB 87.5%, p = 0.002. Impoverishment: DS-TB 56.0%, DR-TB 87.5%, p = 0.026).

The proportion of patients who became unemployed more than doubled when comparing the baseline situation to the situation at the time of interview (16.8% to 35.4%), while the proportion of employment in the informal sector decreased from 61.9% to 43.6% (). The proportion of formal employment decreased from 10.8% to 8.8% when comparing the same time periods. Only one (0.1%) of the national sample utilized sick leave, and four (0.4%) received social welfare, including an unemployment benefit. Among DR-TB patients, who were eligible to receive support for food and transportation from the NTP, only three (10.0%) reported that they received these TB specific financial supports.

Proportion of households facing catastrophic costs

In the national sample, the proportion of TB affected households facing catastrophic costs was 62.6% (95% CI 57.6%-67.3%) at the threshold at 20% of annual household income. With additional sample, the proportion of DR-TB and TB-HIV coinfected patients who experienced catastrophic costs was substantially higher than DS-TB patients; DS-TB: 62.3% (95%CI: 57.4% - 67.0%), DR-TB: 86.9% (73.8% - 99.6%), and TB-HIV: 81.1% (95%CI: 74.1% - 88.2%) (). The overall incidence of catastrophic costs ranged from 47.3% to 82.2% when changing the threshold from 10% to 30% of annual household income ().

Median total costs and proportion of households facing catastrophic costs due to TB using 20% threshold of annual household income by drug resistance and HIV status.

* Error bars show 95% confidence interval for proportion of catastrophic costs. ** Overall proportion of catastrophic costs were adjusted for all variables in the final model as well as for clustering effects associated with sampling method.

Risk factors for households experiencing catastrophic costs

After adjusting for potential confounders and covariates, wealth quintile was the only factor which was associated with the probability of incurring catastrophic costs in multivariate analyses (). Households in lower wealth quintiles had a significantly higher incidence of facing catastrophic costs compared to those in the highest wealth quintile (Lowest wealth quintile: 90.6%, OR = 28.8, p<0.001. 2nd lowest wealth quintile: 73.1%, OR = 6.0, p<0.001. Middle wealth quintile: 56.9%, OR = 3.0, p<0.001. 2nd highest wealth quintile: 53.0%, OR = 2.7, p = 0.001. Highest wealth quintile (Ref): 27.5%).

Discussion

This survey was the first national TB patient cost survey in Lao PDR. It assessed the magnitude and the main drivers of costs faced by TB patients and their households, designed to aid in the development of policies and interventions to reduce the financial barriers associated with TB care. This survey also establishes a baseline against which to monitor progress towards the elimination of catastrophic costs due to TB in Lao PDR, aligned to the targets in their National TB Strategic Plan and the End TB Strategy [11, 12].

Although free TB services are provided in public health facilities in Lao PDR, 62.2% of DS-TB, 86.7% of DR-TB, and 81.1% of TB-HIV co-infected patients incurred catastrophic costs. A TB diagnosis and care cost households US$ 755 which was equivalent to more than 3 times the average monthly salary of TB patients in the survey. The main cost driver was direct non-medical costs followed by income loss. To cope with the economic burden, half (49.9%) of patients had to rely on savings (21.4%), borrowing money (26.3%) or selling assets (17.7%), which has the potential to cause prolonged negative impacts on their lives [31]. The key findings of this survey will contribute to open the doors for effective policy dialogues at the national level with multisectoral partners to improve TB service delivery and financing to reduce financial burden due to TB. As of July 2019, 14 countries including Lao PDR had completed a national TB patient cost survey and of those, 8 countries are in Asia (China, Fiji, Lao PDR, Mongolia, Myanmar, Philippines, Timor-Leste, Viet Nam). The proportion of TB-affected households who faced catastrophic costs in this survey was similar to the figures in Mongolia (68%), Myanmar (60%) and Vietnam (63%) [1, 32]. In our survey, a high proportion of catastrophic costs was reported from DR-TB patients and their households, which is consistent with the results from other countries (ranging from 67% to 100%). Similar to the Lao PDR survey, the main contributor to total patient costs was direct non-medical costs in Fiji and Viet Nam. The survey in Lao PDR was the first national survey to assess costs and catastrophic costs among TB-HIV co-infected patients, and the proportion of TB-affected households who faced catastrophic costs was as high as that of DR-TB. This result has highlighted the necessity to assess patient costs in households with TB-HIV co-infected patients and to facilitate interventions to minimize the financial burden especially in countries with a high burden of TB-HIV coinfection. Integrated services for TB and HIV was provided only at 11 of 25 central and provincial hospitals, and therefore patients with TB-HIV coinfection had to travel to those hospitals that are usually located far from their residences compared to public health centers or district hospitals, or had to have separate facility visits for TB and HIV treatments [26-28]. Enhancing and decentralizing integrated services for TB and HIV would be necessary to mitigate the financial burden in TB-HIV coinfected patients.

Nutritional supplements other than the patient’s regular diet comprised (34.8%) of all direct non-medical costs in Lao PDR. Malnutrition is a common clinical finding in TB patients and also a risk factor for developing active TB [33, 34]. Due to a bi-directional association between having TB and malnutrition, TB patients often lose their appetite and body weight when they develop TB, and can then become malnourished due to metabolic changes during TB treatment [35-37]. Patients and their households may believe or be advised that eating protein rich foods enhances the effectiveness of TB treatment leading them to buy additional foods that might lead TB-affected households to spend a relatively large amount on food or other nutritional supplements [38]. In TB patient cost surveys in Kenya and Ghana, body mass index (BMI) of the survey participants was calculated, and more than half of the participants in the survey were severely (BMI<16.5) or moderately (BMI<18.5) malnourished, and direct non-medical costs were also a main cost driver as they were in Lao PDR [39]. The results in Kenya and Ghana highlight the necessity to investigate the prevalence of malnutrition and the need to enhance nutritional support for TB patients [39].

In Lao PDR, the NTP implements a cash transfer programme for DR-TB patients that provides US$ 5 per day to support expenses for food and transportation. However, only 10% of the participants with DR-TB in this survey reported that they received such support. Similarly, in Cambodia, an existing government scheme that provides poor people with transportation and food costs associated with their health-seeking to public health facilities was largely underutilized [40]. Also, it is not known how this cash transfer programme in Lao PDR contributes to TB patients’ nutritional recovery. Although WHO recommends systematic nutritional assessment and counselling for TB patients [41], such services are not systematically provided for TB patients in Lao PDR, and nutritional status such as weight, height, and BMI were not investigated in this survey. The National Nutrition Strategy 2016–2020 prepared by the National Nutrition Centre has a strategic objective to prevent TB related malnutrition by managing and controlling acute malnutrition associated with TB [42]. Enhancing collaboration between TB and nutrition programmes is imperative to have a better understanding of TB patient’s nutritional status and to improve nutritional support for TB patients.

Although only 9.2% of total costs was incurred before TB diagnosis, this survey revealed that TB patients needed to visit health facilities on average 1.8 times before they were diagnosed, with a median delay of 4 weeks from the onset of TB symptoms to diagnosis. 36% of TB patients sought care at private facilities and half of them visited private facilities multiple times before TB diagnosis. The treatment delay that we observed was in the range of results obtained in other national TB patient cost surveys (0.14 weeks in Timor-Leste, 2.9 weeks in Kenya, 4 weeks in Ghana, 6.2 weeks in Viet Nam) [32, 39, 43, 44] Streamlining the TB patient pathway by enhancing the referral system and improving linkages with the private sector at all facility levels will likely minimize diagnostic delay and patient costs. Implementing active case finding (ACF) may result in a shorter delay in TB diagnosis compared to facility based passive case finding (PCF) as well as reduction in costs incurred by TB patients [45, 46]. A study in Cambodia comparing TB patient costs between ACF and PCF revealed that costs before TB diagnosis was significantly lower among patients detected with ACF compared to those with PCF whereas no difference was found in costs during TB treatment [40]. Furthermore, increasing awareness of the NHI would be also important to have early diagnosis of TB. Our study showed a considerably low recognition of NHI coverage among TB patients (75.9% reported no insurance) even though the NHI was implemented in 2016 (2 years back from the time of this study). This low recognition of NHI could be a barrier to use healthcare services in public facilities after having TB symptoms.

Currently, free TB services are provided in public health facilities in Lao PDR with financial support from the Global Fund in addition to government funding, and therefore the direct medical costs had a relatively smaller impact on total TB patient costs in this survey (15.8%). Ensuring the future sustainability of free and high-quality TB services in this country is key to minimize the delay in TB diagnosis and initiating TB treatment and to reduce the out-of-pocket expenditure for the direct medical costs for TB.

The proportion of patients who were unemployed increased when comparing patient’s employment status pre and post TB diagnosis. Patients who were working in the informal sector, which consisted of 61.9% of the survey population, were more likely to have lost their jobs, and currently there is no unemployment protection scheme for those working in the informal sector in Lao PDR. Implementing an additional cash transfer programme would be one option to address this issue. In Vietnam, after conducting TB patient cost survey, the NTP implemented an innovative financial support scheme, so called “Patients Support Foundation to End Tuberculosis (PASTB)” for TB patients in poverty using a short message service (SMS) [47]. In this campaign, every SMS will transfer US$0.8 to the foundation to provide financial support for TB patients [47]. In addition to the financial supports during TB treatment, the post-treatment socio-economic recovery (e.g. re-employment after TB treatment) is also important to minimize long-term or permanent financial impacts due to TB. However, no studies assessing long-term economic shocks in TB-affected households after completion of TB treatment (e.g. permanent job loss, continuous social exclusion) are published yet except for an on-going study in African countries [48]. Therefore, more evidences around post-treatment economic impacts due to TB are required especially in Asian contexts. On the other hand, TB patients who are employed in the formal sector are eligible for unemployment and sickness benefits that are provided by NSSF. The sickness benefit covers 70% of the employee’s salary in the first 6 months of sick leave, and the rate decreases to 60% after the first 6 months [22]. However, only one TB patient in this survey received this sickness benefit. The current claim mechanism requires TB patients or their household members to visit district or provincial offices that are usually located far from the patient’s community. Re-designing the claim mechanism in collaboration with NSSF may facilitate wider access to the sickness benefit, thus minimizing TB patient costs.

In addition, the national HIV/AIDS Control and Prevention law implemented since 2010, prohibits discrimination or stigmatization towards people living with HIV/AIDS, including firing healthy HIV positive persons from their jobs [49]. There may be a need to explore collaboration with the labour and corporate sectors, as well as civil society, to investigate workplace policies and to advocate for stronger legal frameworks such as enactment of a TB law, with provisions to protect people with TB from being fired, such as the case with the HIV law.

This survey has several limitations. First, this survey was a cross-sectional study and the estimated total costs were based on an extrapolation method [12]. Longitudinal methods which incorporate information from multiple interviews with each patient over time may reflect the true costs of TB illness, although this method would be more complex and lengthy. Estimated costs incurred by TB patients and their households might be affected by recall bias if only recalled once and when recalling costs that were incurred in the past. Also, some of the total patient costs were extrapolated from the costs incurred by patients in the intensive phase or those in continuation phase. This crude extrapolation method may result in over or under estimation of costs and the overall incidence of catastrophic costs. Second, 123 additional patients (22 DR-TB patients and 101 TB-HIV coinfected patients) were enrolled with purposive sampling at different time (in May-June 2019) separately from the 725 nationally representative sample (in December 2018-January 2019). Thus, statistical comparison between two samples were not carried out for this reason. Furthermore, although we conducted statistical tests comparing various factors between DS-TB and DR-TB patients in the national sample, the number of DR-TB patients in the national sample was very few (N = 8) and not enough especially for risk factor analysis for facing catastrophic costs. Third, study participants were enrolled only from NTP engaged facilities. Therefore, costs incurred by patients receiving TB treatment in private facilities unlinked to the NTP are not captured in this survey, and those patients may have different socio-demographic characteristics and may face different costs. In Lao PDR, however, there was only a limited number of private health facilities, and all the individuals with suspected TB who were identified in private facilities should be referred to public health facilities and initiate TB treatment in public facilities. Fourth, the sampled facilities were randomly selected based on the number of TB case notifications in 2017. This sampling method tended to not select districts with a small number of TB case notifications where the accessibility to healthcare services might be limited. The findings of this survey may underestimate costs due to limited sampling of the population who have issues in accessing health care. Fifth, this survey assessed costs incurred from the time of symptom onset to the end of TB treatment. Therefore, costs after TB treatment has finished were not included.

Conclusions

The results of the survey showed that although TB diagnosis and treatment are provided free of charge in Lao PDR, TB patients and their households incur substantial costs when they are diagnosed with TB and they also lack financial protection. As non-medical and indirect costs accounted for more than 80% of the total costs, providing free TB services is not enough, and expansion of existing social protection mechanisms and/or implementation of new interventions for TB patients are necessary to mitigate this financial burden and reduce the proportion of households who experience catastrophic costs associated with TB.

Survey instrument for Lao PDR National TB patient cost survey.

(PDF)

Click here for additional data file.

List of selected provinces and number of clusters for a tuberculosis patient cost survey in Lao PDR.

(DOCX)

Click here for additional data file.

Post-hoc analysis of the incurrence of catastrophic costs by treatment facility.

(DOCX)

Click here for additional data file.

Types of household assets used for imputing household income and the proportion of participants for whom imputed income had to be employed.

(DOCX)

Click here for additional data file.

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

30 Sep 2020

PONE-D-20-27870

First national tuberculosis patient cost survey in Lao People’s Democratic Republic: Assessment of the financial burden faced by TB-affected households and the comparisons by drug-resistance and HIV status

PLOS ONE

Dear Dr. Yamanaka,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

This is an important piece of operational research, which adds to the growing body of evidence on the huge socioeconomic impact of TB, especially in low-income countries. However, there are some limitations that require addressing prior to re-submission.

Please address Reviewer 1 and 2's comments with special focus on:

1) The criteria for selection and the statistical robustness/limitations of the chosen analyses of the population affected by DR-TB and HIV-TB (please also indicate/consider involvement of a trained statistician)

2) Clarification on data collected including hospitalisation costs, lost income, and carer/time costs, and a description of how missing data was handled

3) Enhancing your description of regression analysis including whether there was adjustment for clustering / intra-cluster coefficients

We look forward to receiving a revised version of the manuscript for further review.

Please submit your revised manuscript by Nov 14 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Tom E. Wingfield

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information.

3. Please describe in further detail, how you accounted for clustering in your statistical analysis and aslso discuss whether you applied survey weights to ensure that estimates were nationally representative.

4.We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

5. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 3 in your text; if accepted, production will need this reference to link the reader to the Table.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Review: PONE-D-20-27870

Introduction.

1. The introduction section is still too long. I suggest authors to shorten this part and directly introduce the Lao, a country that is the focus area of this paper instead of bringing up the Lao part at the end of the intro section.

2. Paragraph 5 (Lines 70-78). This para is more likely the basis for discussion, and is redundant later in discussion part. I suggest to remove this para from intro section and elaborate the data in discussion section.

Methods

3. Study setting. Authors may shorten this part, but explain more on how TB services are delivered in the Lao. What are facilities that deliver the services (public only, or also private; primary care level or only secondary/hospital)? What is the link between facilities and the NTP or NHI? What are cost items covered by the NTP and the NHI; any differences? Self-administered/Directly observed therapy?

4. Sampling (lines 134-135). “..,we enrolled additional and operationally feasible quotas of 120 TB-HIV co-infected patients and 30 DR-TB (i.e. MDR-TB or RR-TB).” What is the basis of this sampling size and quota?

5. Is it not clear if the 25-cluster was randomized from a number of clusters, or it is a total number of clusters in the Lao? How were subjects enrolled (randomly, consecutively, etc)?

6. Inclusion (lines 139-142). Why did authors include children in this study? The TB diagnostic tests for children are different with those for adults and unspecific symptoms and signs occur in many cases. These may lead to a higher cost for diagnosis. They are also more likely to having no job, then we can’t see patients’ financial burden caused in this group. The proportion is very few (0.8%). Is it possible to rule out this group? If it is not possible, authors need to provide a reasonable basis in the method section, analyze the differences between children and adults, and discuss it later in discussion section.

Results

7. The number of DR-TB patients in national representative sample is very few (n=8). We then see some cells are empty (e.g., occupation, insurance type, facility type). In Table 3, only one DR-TB was included in analysis. Are they sufficient number for authors to do inference analysis to see the difference between DS-TB and DR-TB? Please consult to statistician regarding this issue: what is the best way to display it fairly.

8. Authors used clustered sampling method. Do authors need to adjust with the sampling method by using random effects and, for example, generalized linear mixed model for analyses? Please consult to statistician regarding this issue.

9. It seems that nutritional supplement played a significant role in costs incurred by patients. Authors need to define ‘nutritional support’ in methods section or below the table so that readers can easily understand what this term means.

10. Table 4. Why did not authors display costs incurred by guardian(s)? Also, indirect costs in pre-diagnosis phase: are they missed?

11. Table 7. Put ‘Ref’ or ‘1’ in OR column for reference variables.

12. Table 7. Authors analyzed determinants of catastrophic costs for mixed group (DS and DR-TB). The costs in DR-TB group were much higher than the costs incurred by DS-TB group. Why did authors mix the groups in the analyses instead of separate the groups? Since the number of DR-TB subjects are very few, it may be enough to analyze it in descriptive way rather than using regression? Please consult statistician regarding this issue.

Discussion

13. Lines 368: “In Lao PDR, the NTP implements a cash transfer programme for DR-TB patients that provides US$ 5 per day to support expenses for food and transportation.” Was the cash transfer included in costs calculation? Please also confirm it in method section including how the transfer is delivered (condition, unconditional, etc.).

Additional

14. Please avoid using number at the first word in sentence.

15. The paper readability is acceptable, but still need further English language editing.

Reviewer #2: Summary of the study

This study reported the results of the first national patient cost survey conducted in Lao PDR. The survey was also the first survey to assess the rate of catastrophic cost incurrence among TB-HIV patients. The study found that at least two-thirds of surveyed TB-affected families suffered catastrophic costs (higher in MDR-TB and TB-HIV patients), which was in line with comparator countries in the region. It concludes with the need for implementation of interventions, social protection mechanisms and policy development to achieve the WHO End TB Strategy of zero TB-affected families suffering from catastrophic costs.

Overall assessment

This manuscript presented highly relevant results that should be published and will contribute to the evidence base on incurred cost per episode of TB in Lao. It was very well written with only minor spelling and grammatical issues as well as the occasional extraneous space. There are a number of concerns and issues that will require explanation and revision of the manuscript as outlined below. Once these issues are satisfactorily addressed, the manuscript can be approved for publication.

Detailed comments

Introduction

- Line 80: Please describe any prior costing work done in Laos regarding healthcare in general and for TB in particular, if any, besides using the WHO patient cost survey tool.

Methods

- Line 132: Please add text to justify the selection of 50% catastrophic cost incurrence in your sample size estimate.

- Line 133: Please describe the reason for separating the initial nationally representative sample and the additional sample, and particularly please describe whether the 30 MDR-TB patients from the additional sampling were included in the DS-TB vs MDR-TB comparisons as well as the regression analysis. If they were excluded, please explain why.

- Lines 139-143: Please describe the standard treatment length of MDR-TB in Laos and among the MDR-TB cases included on the survey. Especially note if any patients were on shortened MDR-TB regimen. Please do the same for extra-pulmonary TB and provide the average/median treatment duration for the 52 EP-TB patients in the study.

- Line 158: It is not clear how conducting each survey only once minimizes recall bias. Instead, a longitudinal survey may have been the more appropriate way to minimize recall bias. As such, perhaps remove the phrase “To minimize recall bias.”

- Lines 159-160: Presumably you asked about income prior to the current episode of TB (as per WHO patient cost tool) along with current income, so it is probably best to list that here as well.

- Lines 161-162: Please describe how you treated caregiver time loss and costs, i.e., were these included in the cost calculation.

- Lines 161-162: Please mention and explain further how time loss was translated into monetary value (i.e., human capital approach, minimum hourly wage...).

- Lines 161-162: Please describe how you treated caregiver time loss and costs, i.e., were these included in the cost calculation.

- Lines 162-164: Since pre-treatment costs were not asked of participants in the CP (62.8% of participants), clearly describe the assumptions made in the extrapolation of pre-treatment costs for the whole sample.

- Lines 187-188: Please describe how you treated missing values in the responses (besides the imputed household income).

- Lines 187-188: Please describe how you treated hospitalization costs and whether you were able to track any hospitalization costs after the survey was performed (but before the end of treatment).

- Lines 187-188: If household assets were used for imputation of HH income, please furnish supplemental information on the types, frequencies and regression results for the imputed HH income as well as the proportion of participants for whom imputation had to be employed

- Lines 187-188 & 194-198: Did your regression analysis for imputation of HH income and for evaluation of association of patient covariates with catastrophic cost incurrence account for clustering effects and intra cluster correlation from your sampling strategy? If it did, please describe in further detail in the paper the regression methods used. If not, please re-fit your model using appropriate specifications including a description of how you arrived at the final model specifications or explain why you chose not to account for ICC

- Line 195-196: Please describe and provide examples how including the additional sample of MDR-TB and TB-HIV participants would have affected the regression analysis.

- Line 317: Please describe wealth quintile in this section rather than the results and elaborate on what "based on household income" means. If it is simply quintiles of Household income then please explain and label it so, since wealth can include other tangible and intangible factors.

Results

- Lines 216-217: It is very surprising to see the proportion of participants without health insurance reported as 75.9% when the national statistics claim that insurance coverage is 60%, 70% or even 79.3% in 2019. Please furnish the Insurance coverage rate among TB patients notified by the Lao NTP to understand if there is any bias in the study sample.

- Lines ibid: If the average national insurance coverage among TB patients is really as low as found in the patient first survey, please include this fact in the study setting section.

- Line 228: The proportion of TB patients in the results treated at public health and district facilities states 61% for the national sample, while the table shows 71%. Please review all of your numbers again and ensure there is internal consistency.

- Lines 228-229: Please provide a post-hoc analysis (as supplemental information) of the CC incurrence in the subpopulation of the 29.9% of participants treated at the provincial/national facilities. For this post-hoc analysis, test whether the subpopulations are significantly different from each other.

- Lines 239-240: Given that 97.7% of the national sample was treated under SAT, please provide information on treatment monitoring standards under national TB treatment guidelines in the methods. Please discuss and clarify the root cause behind the high rate of income loss under SAT.

- Line 580: Please describe the discrepancies in sample sizes between the total participant figure (n=725) in the national sample and respondents for time loss due to TB (n=292).

Discussion

- Line 337: please reference any sources that have formally assessed and linked dissavings and asset sale to prolonged negative impact on their lives.

- Line 391: Please rephrase the word minimal perhaps as 16% of one's income is not necessarily minimal, especially for low income households.

- Line 392: "Ensuring the future sustainability of free and high-quality TB services..." is perhaps more of a basic essential for a TB program rather than a strong discussion point. Sustained free and high-quality TB services is the bare minimum expectation and without it, there should be no End TB Strategy. As this paragraph talks about diagnostic delay and direct medical costs, perhaps identify interventions from the literature that have shown to reduce these barriers to care. One such place could be line 389, which should include an example or at minimum a few references.

- Line 398: The discussion of informally employed participants seems insufficient and a disproportional amount of text is dedicated to formally employed persons who comprise less than 10% of the sample. Hence, please expand the discussion on informally employed participants. Specifically, in the absence of any unemployment protection schemes, which in LMIC often only apply after having paid into the scheme through formal employment, the question for informally employed persons is how fast they were able to recover and pick up their employment again. Informal employment usually has lower barriers to entry into the job market (e.g., rag picking, selling lottery tickets, street-side parking attendants, etc), so perhaps the discussion can allude to the current lack of evidence on post-treatment socioeconomic recovery.

- Lines 175-177 & Lines 425-428: The reasoning for not conducting statistical analysis between DS-TB patients (n=717) and TB/HIV patients (n=123) or even MDR-TB patients (n=30) when you performed statistical comparisons between DS-TB and MDR-TB (n=8) within the national sample is not clear. The reasoning for not performing statistical comparisons between the methods and discussion also seem discordant. As such, please rephrase to provide a more plausible reason for the lack of statistical comparison with the additional sample.

- Line 427: Please remove the word "due".

- Line 432: Please change "suspected TB cases" to persons with presumptive/suspected TB to avoid the use of stigmatizing language.

- Line 434: "Therefore, we assumed that the impact of this exclusion criteria would be minimal." - to be able to make this assumption, it would be necessary to have information on the proportion of missed cases and proportion treated in the private sector (onion model). Please furnish this information or consider rephrasing to not state a potentially false assumption.

- Lines 435-436: this is a very good and critical point. Please provide a map/table in the supplemental information of sample sizes by geography to identify any potential source for bias.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: Review PLOS - AF.docx

Click here for additional data file.

13 Oct 2020

Response to Reviewers’ Comments:

Thank you for your positive response to our journal submission. We appreciate the constructive feedback and have strove to incorporate your feedback into our journal article. The itemized responses are as follows:

Reviewer 1

1 The introduction section is still too long. I suggest authors to shorten this part and directly introduce the Lao, a country that is the focus area of this paper instead of bringing up the Lao part at the end of the intro section.

Thank you for your suggestion. We deleted para 2 and para 5

2 Paragraph 5 (Lines 70-78). This para is more likely the basis for discussion, and is redundant later in discussion part. I suggest to remove this para from intro section and elaborate the data in discussion section.

Since the discussion already has similar statements, we simply deleted the para

3 Authors may shorten this part, but explain more on how TB services are delivered in the Lao. What are facilities that deliver the services (public only, or also private; primary care level or only secondary/hospital)? What is the link between facilities and the NTP or NHI? What are cost items covered by the NTP and the NHI; any differences? Self-administered/Directly observed therapy?

Thank you for the comment. In Lao PDR, TB treatment is predominantly provided at public health facilities. For DS-TB patients, the treatment is provided in 164 TB units including 5 central hospitals in Vientiane Capital, 17 provincial hospitals and 142 district hospitals with self-administered therapy while all the DR-TB patients are hospitalized at 3 provincial hospitals with PMDT throughout the treatment period.

TB diagnosis and treatment in health facilities is supported by NTP free of charge to patients including diagnostic tests (direct microscopy and molecular test) and first and second-line anti-TB medications. If available, health insurance schemes (NHI) may cover some other services (e.g. hospitalization fees for DS-TB patients).

Besides, NTP supports DR-TB patients for transportation to health facility, hospitalization for the full treatment duration, laboratory examinations (e.g. LPA second line, initial culture, EKG, biological tests) before treatment start and for treatment response monitoring, adverse drug event (ADE) prevention and monitoring, ancillary medicines and daily food allowance.

4 Sampling (lines 134-135). “..,we enrolled additional and operationally feasible quotas of 120 TB-HIV co-infected patients and 30 DR-TB (i.e. MDR-TB or RR-TB).” What is the basis of this sampling size and quota?

As set by the WHO End TB Strategy, countries have to report the proportion of TB patients who faced catastrophic costs due to TB through a survey enrolling a nationally representative sample of TB patients. Our main survey sample was designed to produce this indicator for the global monitoring and the data collection was conducted from December 2018 to January 2019.

Apart from this nationally representative sample, the National TB Progamme of Lao PDR had a keen interest in having additional samples to understand the economic burden incurred by TB patients who received treatment for drug-resistant TB, as well as those having TB-HIV coinfection. For DR-TB patients, we enrolled all the patients on DR-TB treatment at the time of interview in the country (total sampling). For TB-HIV patients, assuming estimated proportion of catastrophic costs: 80% with 10% precision and design effect of 2, the sample size was estimated at 122. We added this sentences in the method section.

5 Is it not clear if the 25-cluster was randomized from a number of clusters, or it is a total number of clusters in the Lao? How were subjects enrolled (randomly, consecutively, etc)?

Out of 165 BMUs in Lao PDR, a total of 25 BMUs (clusters) was randomly selected by a probability proportional to size (PPS) method applying the TB case notification in 2017 for each BMU. The participants were enrolled also randomly from TB log-book at each facility.

6 Inclusion (lines 139-142). Why did authors include children in this study? The TB diagnostic tests for children are different with those for adults and unspecific symptoms and signs occur in many cases. These may lead to a higher cost for diagnosis. They are also more likely to having no job, then we can’t see patients’ financial burden caused in this group. The proportion is very few (0.8%). Is it possible to rule out this group? If it is not possible, authors need to provide a reasonable basis in the method section, analyze the differences between children and adults, and discuss it later in discussion section.

This study followed the WHO methodology to measure the catastrophic costs due to TB defined by the WHO End TB Strategy. The WHO methodology recommends including patients in all age groups in the sampling frame including children.

This is because the survey is intended to measure economic impact at the household level regardless of whether a patient is adult or child. By using the same instrument, interviews are conducted with guardians for child patients. All income and cost information are relevant when measured at the household level (e.g. costs incurred for the care for their children, lost incomes/jobs, and coping mechanisms in their households) and consequences can be serious because the guardians have to put time and resources for the care of the children. As rightly pointed out, the proportion of childhood patients was small (0.8%) but we believe it is appropriate to keep these observations as per the WHO methodology.

7 The number of DR-TB patients in national representative sample is very few (n=8). We then see some cells are empty (e.g., occupation, insurance type, facility type). In Table 3, only one DR-TB was included in analysis. Are they sufficient number for authors to do inference analysis to see the difference between DS-TB and DR-TB? Please consult to statistician regarding this issue: what is the best way to display it fairly.

Thank you for your suggestion.

First, we apologize there were errors in table 3. The number of patients for the analysis was 717 DS-TB and 8 DR-TB same as in other tables. We corrected the error.

Regarding the statistical analysis, considering the small sample size, we used Fisher’s exact test for comparing categorial variables. Even with a limited sample size for DR-TB patients, some categories in table 2,3,5,6 showed significant differences between DS-TB and DR-TB. Therefore, we would like to keep the analytical method as it is currently shown.

As rightly pointed out, the DR-TB group (N=8) of the main sample may not be appropriately powered to make statistical inference. As mentioned above (No.4), the purpose of this sample is to serve as a nationally representative sample, rather than (not primarily for) disaggregated analysis. Therefore, we agree that there is a limitation on to what extent we could look into details of the result especially for DR-TB group (in a sense, the disaggregation of national sample is more for looking into DS-TB group).

To compliment this limitation, the study included the additional samples of DR-TB (N=30) and TB-HIV coinfected patients (N=123) and presented in the same table where relevant.

We will revise relevant parts of text to incorporate above points.

8 Authors used clustered sampling method. Do authors need to adjust with the sampling method by using random effects and, for example, generalized linear mixed model for analyses? Please consult to statistician regarding this issue.

Thank you for your suggestion. We took the adjustment for clustering into account in the analysis. Considering changes in ORs with the adjustment, we changed the table 7 with results with the adjustment for sampling method. Also, after adjusting sampling method, the overall % of catastrophic costs was changed to 62.6% (0.1% increase from the previous result). We also changed figure 2 accordingly.

9 It seems that nutritional supplement played a significant role in costs incurred by patients. Authors need to define ‘nutritional support’ in methods section or below the table so that readers can easily understand what this term means.

Thank you for your suggestion. We added a definition of nutritional supplements in the method section as “nutritional supplements such as vitamin supplements and/or additional foods other than regular diets”.

10 Table 4. Why did not authors display costs incurred by guardian(s)? Also, indirect costs in pre-diagnosis phase: are they missed?

In the data collection, we asked each costs incurred by patients and guardians (if applicable) as the purpose is to estimate total costs incurred by the households, and therefore, each cost component already included the costs incurred by guardians.

The WHO handbook proposes two methods in estimating indirect cost: output approach and human capital approach. For the former, time spent by patients or guardians for accessing and receiving care will be summed up and monetised thus it is possible to have disaggregation by time (e.g. before and after diagnosis) and by service.

The latter approach, output approach, uses income loss, which is the difference of reported income after and before TB diagnosis. By nature of this definition, income loss cannot be disaggregated as it represents the reduction of income during the whole duration of treatment as a single value.

The WHO handbook advises countries to choose either of the methods considering the specific country context.

In our study, although we used both approaches for initial analysis, we decided to employ output approach for our main analysis through a consultation process with government representatives, national and international experts. The main reason was that the loss of income apparently captured social consequences of TB-affected household (e.g. job loss) much more than the simple sum of “lost hours”.

Therefore the result presented in this paper uses output approach with a single value that represents the loss of income for the entire episode of TB.

11 Table 7. Put ‘Ref’ or ‘1’ in OR column for reference variables.

We added Ref for each reference variable in the table.

12 Table 7. Authors analyzed determinants of catastrophic costs for mixed group (DS and DR-TB). The costs in DR-TB group were much higher than the costs incurred by DS-TB group. Why did authors mix the groups in the analyses instead of separate the groups? Since the number of DR-TB subjects are very few, it may be enough to analyze it in descriptive way rather than using regression? Please consult statistician regarding this issue.

Thank you for your suggestion. Even though the limited number of the sample with DR-TB (and relatively large p-value), it has still value to show the high OR to face catastrophic costs among DR-TB patients compared to DS-TB patients, and therefore we would keep the analysis as it is without excluding DR-TB patients.

13 Lines 368: “In Lao PDR, the NTP implements a cash transfer programme for DR-TB patients that provides US$ 5 per day to support expenses for food and transportation.” Was the cash transfer included in costs calculation? Please also confirm it in method section including how the transfer is delivered (condition, unconditional, etc.).

Thank you for your comment. When we did interviews to healthcare workers in PMDT, we realized that some portion of the transferred cash (USD 5 per day) was taken by the health facilities to provide daily meals to DR-TB patients in TB ward, and only the rest were given to the patients (or their household members). Therefore it was difficult to distinguish the amount for food and others. Another reason is, as in line 270, that only 10% of DR-TB patients reported that they were receiving TB-specific cash transfer or supports though all of them supposed to be eligible to receive it. To avoid under-estimation of the costs (or over-estimation of impact of the cash transfer system), we did not deduct the amount of cash transfer from the estimated costs.

Reviewer 2

1 Line 80: Please describe any prior costing work done in Laos regarding healthcare in general and for TB in particular, if any, besides using the WHO patient cost survey tool.

No cost surveys or studies related to TB were conducted from patient perspective prior to this survey.

Other OOP studies exist particularly for MCH e.g.:

- Health care expenditure for hospital-based delivery care in Lao PDR” BMC Research Notes volume 5, Article number: 30 (2012)

- The Impact of Out-of-Pocket Expenditures on Families and Barriers to Use of Maternal and Child Health Services in the Lao People’s Democratic Republic: Evidence from the Lao Expenditure and Consumption Survey 2007–2008 RETA–6515 Country Brief. Manila: Asian Development Bank.

2 Line 132: Please add text to justify the selection of 50% catastrophic cost incurrence in your sample size estimate.

We assumed incidence of 50% catastrophic costs in Lao PDR from the previous TB-PCS in the WPR (PHL: 35%, VNM: 63%, MNG: 70%), and the unweighted average was 56%. We added this sentence in the method section. In addition, an estimated prevalence of 50% will provide the most conservative sample size.

3 Line 133: Please describe the reason for separating the initial nationally representative sample and the additional sample, and particularly please describe whether the 30 MDR-TB patients from the additional sampling were included in the DS-TB vs MDR-TB comparisons as well as the regression analysis. If they were excluded, please explain why.

The reasons for separating two samples are:

1. Due to different sampling method. The national samples were enrolled with cluster randomized sampling to ensure the national representativeness. On the other hand, the additional samples of DR-TB and TB-HIV co-infected patients were purposively enrolled from the facilities where provide treatment for DR-TB and ART.

2. Different sampling period. The data collection for the national samples was conducted in December 2018 to January 2019 while that for the additional samples were separately carried out in May and June 2019.

4 Lines 139-143: Please describe the standard treatment length of MDR-TB in Laos and among the MDR-TB cases included on the survey. Especially note if any patients were on shortened MDR-TB regimen. Please do the same for extra-pulmonary TB and provide the average/median treatment duration for the 52 EP-TB patients in the study.

Although both conventional and shorter regimens were available at the time of this survey, all DR-TB patients in our study were being treated with shorter regimen. We added the comparison of treatment duration in table 2.

5 Line 158: It is not clear how conducting each survey only once minimizes recall bias. Instead, a longitudinal survey may have been the more appropriate way to minimize recall bias. As such, perhaps remove the phrase “To minimize recall bias.”

Thank you for this suggestion. We removed the phrase.

6 Lines 159-160: Presumably you asked about income prior to the current episode of TB (as per WHO patient cost tool) along with current income, so it is probably best to list that here as well.

Thank you for your suggestion. We added a sentence “We estimated income loss in TB patients’ households using the income prior to the current TB episode and that at the time of interview (output approach).”

7 Lines 161-162: Please describe how you treated caregiver time loss and costs, i.e., were these included in the cost calculation.

Since the estimation of income loss in patient’s households was carried out using output approach (based on reported household income), caregiver (or household member’s) time loss was not translated into monetary value and not used for estimating income loss.

However, cost incurred by caregivers and/or household members (such as transportation, food, accommodation for accompanying with TB patients to visit health facilities) were included in the cost calculation.

8 Lines 161-162: Please mention and explain further how time loss was translated into monetary value (i.e., human capital approach, minimum hourly wage...).

Please see the response above (No.7).

9 Lines 162-164: Since pre-treatment costs were not asked of participants in the CP (62.8% of participants), clearly describe the assumptions made in the extrapolation of pre-treatment costs for the whole sample.

Thank you for your suggestion. We added a sentence:

“For example, to estimate pre-treatment costs and costs during TB intensive phase for patients who were in continuation phase at the time of interview, the median costs of pre-treatment costs and intensive phase were taken from the patients who were in intensive phase at the time of interview. In this calculation for extrapolating costs, costs from DS-TB and DR-TB patients, and patients with and without hospitalizations were considered separately.”

10 Lines 187-188: Please describe how you treated missing values in the responses (besides the imputed household income).

First, when the tablet-based questionnaire was developed and adapted to Lao context, we set restrictions not to miss essential data during data collection. Then, the data was intensively checked by Yamanaka T for data cleaning and validation. During the validation process, identified missing data and outliers were returned to survey implementers and data collectors and corrected.

11 Lines 187-188: Please describe how you treated hospitalization costs and whether you were able to track any hospitalization costs after the survey was performed (but before the end of treatment).

Following the recommended method by the WHO (and in the handbook for TB patient cost survey), the costs for hospitalization was simply extrapolated until the end of the current treatment phase

12 Lines 187-188: If household assets were used for imputation of HH income, please furnish supplemental information on the types, frequencies and regression results for the imputed HH income as well as the proportion of participants for whom imputation had to be employed

We added the information as supplementary material 3

13 Lines 187-188 & 194-198: Did your regression analysis for imputation of HH income and for evaluation of association of patient covariates with catastrophic cost incurrence account for clustering effects and intra cluster correlation from your sampling strategy? If it did, please describe in further detail in the paper the regression methods used. If not, please re-fit your model using appropriate specifications including a description of how you arrived at the final model specifications or explain why you chose not to account for ICC

Thank you for your suggestion. We took the adjustment into account in the analysis. Considering changes in ORs with the adjustment, we changed the table 7 with results with the adjustment for sampling method. Also, after adjusting sampling method, the overall % of catastrophic costs was changed to 62.6% (0.1% increase from the previous result). We also changed figure 2 accordingly.

14 Line 195-196: Please describe and provide examples how including the additional sample of MDR-TB and TB-HIV participants would have affected the regression analysis.

If the national samples and additional samples were enrolled in a same sampling method, and all the samples were included in the logistic regression analysis, statistical significance in drug-resistance status and HIV status in % of facing catastrophic costs could have been shown in table 7. However, due to the different sampling framework, we excluded the additional samples from statistical comparisons and risk factor analysis.

15 Line 317: Please describe wealth quintile in this section rather than the results and elaborate on what "based on household income" means. If it is simply quintiles of Household income then please explain and label it so, since wealth can include other tangible and intangible factors.

Thank you for your suggestion. We removed the phrase.

16 Lines 216-217: It is very surprising to see the proportion of participants without health insurance reported as 75.9% when the national statistics claim that insurance coverage is 60%, 70% or even 79.3% in 2019. Please furnish the Insurance coverage rate among TB patients notified by the Lao NTP to understand if there is any bias in the study sample.

Thank you for your comment.

There is no bias in the coverage since the NHI covers all the population regardless of TB or not. The result of this survey revealed a less recognition of NHI coverage in TB patients although the NHI was implemented in 2016 (2 years back from the time of this survey).

17 Lines ibid: If the average national insurance coverage among TB patients is really as low as found in the patient first survey, please include this fact in the study setting section.

Please see the response above (No. 16).

18 Line 228: The proportion of TB patients in the results treated at public health and district facilities states 61% for the national sample, while the table shows 71%. Please review all of your numbers again and ensure there is internal consistency.

We apologize this typo, and it is corrected.

19 Lines 228-229: Please provide a post-hoc analysis (as supplemental information) of the CC incurrence in the subpopulation of the 29.9% of participants treated at the provincial/national facilities. For this post-hoc analysis, test whether the subpopulations are significantly different from each other.

Thank you for your suggestion. Supplemental material 4 is added for this supplementary analysis and no significant difference in incurrence of catastrophic costs was found (p-value: 0.197).

20 Lines 239-240: Given that 97.7% of the national sample was treated under SAT, please provide information on treatment monitoring standards under national TB treatment guidelines in the methods. Please discuss and clarify the root cause behind the high rate of income loss under SAT

Although DOT by a health worker is recommended as a treatment monitoring standard in National TB guidelines to ensure adherence, in practice TB patients are often living far and manage to collect TB drugs intermittently from nearest facilities (frequency of visits: once a week to once a month), and take the TB medications with village volunteer or family member support only.

The reasons of income loss are:

1. Even with self-administered therapy, patients (and/or their household members) have to visit facilities for the drug pick-up

2. Patients can lose their jobs due to being too unwell to work or their household members can lose their jobs (and/or time to work) to support TB patients in their households.

21 Line 580: Please describe the discrepancies in sample sizes between the total participant figure (n=725) in the national sample and respondents for time loss due to TB (n=292).

We are sorry for this typo, and we corrected this error.

22 Line 337: please reference any sources that have formally assessed and linked dissavings and asset sale to prolonged negative impact on their lives.

We added a reference.

23 Line 391: Please rephrase the word minimal perhaps as 16% of one's income is not necessarily minimal, especially for low income households.

Thank you for your suggestion. We rephrased it to “the direct medical costs had relatively smaller impact on total TB patient costs in this survey (15.8%)”

24 Line 392: "Ensuring the future sustainability of free and high-quality TB services..." is perhaps more of a basic essential for a TB program rather than a strong discussion point. Sustained free and high-quality TB services is the bare minimum expectation and without it, there should be no End TB Strategy. As this paragraph talks about diagnostic delay and direct medical costs, perhaps identify interventions from the literature that have shown to reduce these barriers to care. One such place could be line 389, which should include an example or at minimum a few references.

Thank you for your suggestion. We added statements as;

“Implementing active case finding (ACF) may result in a shorter delay in TB diagnosis compared to facility based passive case finding (PCF) as well as reduction in costs incurred by TB patients [44, 45]. A study in Cambodia comparing TB patient costs between ACF and PCF revealed that costs before TB diagnosis was significantly lower among patients detected with ACF compared to those with PCF whereas no difference was found in costs during TB treatment [39]. Furthermore, increasing awareness of the NHI would be also important to have early diagnosis of TB. Our study showed a considerably low recognition of NHI coverage among TB patients (75.9% reported no insurance) even though the NHI was implemented in 2016 (2 years back from the time of this study). This low recognition of NHI could be a barrier to use healthcare services in public facilities after having TB symptoms.”

25 Line 398: The discussion of informally employed participants seems insufficient and a disproportional amount of text is dedicated to formally employed persons who comprise less than 10% of the sample. Hence, please expand the discussion on informally employed participants. Specifically, in the absence of any unemployment protection schemes, which in LMIC often only apply after having paid into the scheme through formal employment, the question for informally employed persons is how fast they were able to recover and pick up their employment again. Informal employment usually has lower barriers to entry into the job market (e.g., rag picking, selling lottery tickets, street-side parking attendants, etc), so perhaps the discussion can allude to the current lack of evidence on post-treatment socioeconomic recovery.

Thank you for your suggestion. We added discussions as:

“Implementing an additional cash transfer programme would be one option to address this issue. In Vietnam, after conducting TB patient cost survey, the NTP implemented an innovative financial support scheme, so called “Patients Support Foundation to End Tuberculosis (PASTB)” for TB patients in poverty using a short message service (SMS) [46]. In this campaign, every SMS will transfer US$0.8 to the fund to provide financial support for TB patients [46]. In addition to the supports during TB treatment, the post-treatment socio-economic recovery (e.g. re-employment after TB treatment) is also important to minimize long-term or permanent financial impacts due to TB. However, no studies assessing long-term economic shocks in TB-affected households after completion of TB treatment (e.g. permanent job loss, continuous social exclusion) are published yet except for an on-going study in African countries [47]. More evidences around post-treatment economic impacts due to TB are required especially in Asian contexts.”

26 Lines 175-177 & Lines 425-428: The reasoning for not conducting statistical analysis between DS-TB patients (n=717) and TB/HIV patients (n=123) or even MDR-TB patients (n=30) when you performed statistical comparisons between DS-TB and MDR-TB (n=8) within the national sample is not clear. The reasoning for not performing statistical comparisons between the methods and discussion also seem discordant. As such, please rephrase to provide a more plausible reason for the lack of statistical comparison with the additional sample.

The reasons for not conducting statistical analysis with two samples are:

1. Due to different sampling method. The national samples were enrolled with cluster randomized sampling to ensure the national representativeness. On the other hand, the additional samples of DR-TB and TB-HIV co-infected patients were purposively enrolled from the facilities where provide treatment for DR-TB and ART.

2. Different sampling period. The data collection for the national samples was conducted in December 2018 to January 2019 while that for the additional samples were separately carried out in May and June 2019.

We rephrase the limitation as:

“Second, 123 additional patients (22 DR-TB patients and 101 TB-HIV coinfected patients) were enrolled with purposive sampling at different time (in May-June 2019) separately from the 725 nationally representative sample (in December 2018-January 2019). Thus, statistical tests comparing them with the national sample were not carried out for this reason.”

27 Line 427: Please remove the word "due".

We removed the word.

28 Line 432: Please change "suspected TB cases" to persons with presumptive/suspected TB to avoid the use of stigmatizing language.

We changed it to “all the individuals with suspected TB”.

29 Line 434: "Therefore, we assumed that the impact of this exclusion criteria would be minimal." - to be able to make this assumption, it would be necessary to have information on the proportion of missed cases and proportion treated in the private sector (onion model). Please furnish this information or consider rephrasing to not state a potentially false assumption.

Thank you for your suggestion. We removed the sentence “Therefore, we assumed that the impact of this exclusion criteria would be minimal.”

30 Lines 435-436: this is a very good and critical point. Please provide a map/table in the supplemental information of sample sizes by geography to identify any potential source for bias

Thank you for your suggestion. We included a map and a table showing the number of clusters in each province as supplementary material 2.

Submitted filename: Response to Reviewers_v4.docx

Click here for additional data file.

22 Oct 2020

PONE-D-20-27870R1

First national tuberculosis patient cost survey in Lao People’s Democratic Republic: Assessment of the financial burden faced by TB-affected households and the comparisons by drug-resistance and HIV status

PLOS ONE

Dear Dr. Yamanaka,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please address the outstanding comments made by Reviewer 1, which include: clarifying the additional sampling, discussing the limitations of the DR-TB sampling and sample size, interpreting the findings of the HIV-TB co-infected population in the cohort, and rectifying Figure issues.

Please submit your revised manuscript by Dec 06 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Tom E. Wingfield

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Authors have responded almost all of previous comments. However, some points remain for improvement.

1. The reasons of using additional sample remains inconsistent and confusing. In lines 111-113, authors wrote that additional respondents were aimed “to assess the difference in the financial burden of TB comparing drug-resistant and drug-susceptible TB patients and for patients with and without TB-HIV co-infection”. However, in lines 156-158, authors stated “Due to different sampling methods for nationally representative sample and additional sample of DR-TB and TB-HIV coinfected patients, statistical tests were performed only in nationally representative sample.” Did authors mean the “assessing the difference” as only in a descriptive way?

2. Authors added a group of TB-HIV, but lacked of discussion on this group in discussion section. It is better to discuss the findings in this group if authors thought that adding this group to the sample is really needed.

3. The number of DR-TB patients in national sample were very few and were considerably not enough for statistical comparison. Better if authors mention this shortage in limitation.

4. Table 3 : Some cells show hours lost in negative values, e.g. -212.2-515. It seems odd, and better to show the values in median (range) instead of mean (95% CI).

5. Figure 3 is missing.

6. Avoid writing numbers at the beginning of a sentence.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

22 Oct 2020

Reviewer 1

1 The reasons of using additional sample remains inconsistent and confusing. In lines 111-113, authors wrote that additional respondents were aimed “to assess the difference in the financial burden of TB comparing drug-resistant and drug-susceptible TB patients and for patients with and without TB-HIV co-infection”. However, in lines 156-158, authors stated “Due to different sampling methods for nationally representative sample and additional sample of DR-TB and TB-HIV coinfected patients, statistical tests were performed only in nationally representative sample.” Did authors mean the “assessing the difference” as only in a descriptive way?

Thank you for your comment. Yes, we aimed at assessing the costs among DR-TB and TB-HIV co-infected patients only in a descriptive way due to the different sampling method and also limited number of samples for DR-TB (even though we enrolled total samples at the time of the survey).

2 Authors added a group of TB-HIV, but lacked of discussion on this group in discussion section. It is better to discuss the findings in this group if authors thought that adding this group to the sample is really needed.

Thank you for your suggestion. We added a discussion for TB-HIV as:

Integrated services for TB and HIV was provided only at 11 of 25 central and provincial hospitals, and therefore patients with TB-HIV coinfection had to travel to those hospitals that are usually located far from their residences compared to public health centers or district hospitals, or had to have separate facility visits for TB and HIV treatments [26-28]. Enhancing and decentralizing integrated services for TB and HIV would be necessary to mitigate the financial burden in TB-HIV coinfected patients.

3 The number of DR-TB patients in national sample were very few and were considerably not enough for statistical comparison. Better if authors mention this shortage in limitation.

Thank you for the comment. We added following sentences for limitation 2 as:

Furthermore, although we conducted statistical tests comparing various factors between DS-TB and DR-TB patients in the national sample, the number of DR-TB patients in the national sample was very few (N=8) and not enough especially for risk factor analysis for facing catastrophic costs.

4 Table 3 : Some cells show hours lost in negative values, e.g. -212.2-515. It seems odd, and better to show the values in median (range) instead of mean (95% CI).

Thank you for your suggestion. We revised table 3 (from mean to median)

5 Figure 3 is missing.

We attached all the figures in the submission

6 Avoid writing numbers at the beginning of a sentence.

We revised those sentences (mainly in result section).

Submitted filename: Response to Reviewers_2_v1.docx

Click here for additional data file.

22 Oct 2020

First national tuberculosis patient cost survey in Lao People’s Democratic Republic: Assessment of the financial burden faced by TB-affected households and the comparisons by drug-resistance and HIV status

PONE-D-20-27870R2

Dear Dr. Yamanaka,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Tom E. Wingfield

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

29 Oct 2020

PONE-D-20-27870R2

First national tuberculosis patient cost survey in Lao People’s Democratic Republic: Assessment of the financial burden faced by TB-affected households and the comparisons by drug-resistance and HIV status

Dear Dr. Yamanaka:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Tom E. Wingfield

Academic Editor

PLOS ONE

Table 1

Socio-demographic characteristics of participants of the national TB patient cost survey by drug resistance and HIV status, Lao PDR, 2018–2019.

Characteristics		Nationally representative sample							With additional sample
		DS-TB		DR-TB		P-value	All		All DR-TB		All TB-HIV
		n = 717		n = 8			n = 725		n = 30		n = 123
Gender	Female	291	(40.6%)	1	(12.5%)	0.153	292	(40.3%)	14	(46.7%)	40	(32.5%)
	Male	426	(59.4%)	7	(87.5%)		433	(59.7%)	16	(53.3%)	83	(67.5%)
Age	mean (95%CI)	50.5	(49.3–51.7)	41.4	(27.3–55.4)	0.125	50.4	(49.2–51.6)	44.7	(38.6–50.8)	33.8	(32.0–35.7)
HIV status	Negative	466	(65.0%)	8	(100.0%)	0.103	474	(65.4%)	27	(90.0%)	0	(0.0%)
	Positive	19	(2.6%)	0	(0.0%)		19	(2.6%)	2	(6.7%)	123	(100.0%)
	Unknown	232	(32.4%)	0	(0.0%)		232	(32.0%)	1	(3.3%)	0	(0.0%)
Patient's education level	No education	177	(24.7%)	0	(0.0%)	0.136	177	(24.4%)	7	(23.3%)	5	(4.1%)
	Primary school	265	(37.0%)	2	(25.0%)		267	(36.8%)	11	(36.7%)	34	(27.6%)
	Secondary/High school	181	(25.2%)	5	(62.5%)		186	(25.7%)	8	(26.7%)	63	(51.2%)
	Vocational, University and higher	73	(10.2%)	1	(12.5%)		74	(10.2%)	4	(13.3%)	14	(11.4%)
	Other	21	(2.9%)	0	(0.0%)		21	(2.9%)	0	(0.0%)	6	(4.9%)
Occupation (pre-disease)	Not employed	122	(17.0%)	0	(0.0%)	0.245	122	(16.8%)	2	(6.7%)	5	(4.1%)
	Employed (formal)	78	(10.9%)	0	(0.0%)		78	(10.8%)	3	(10.0%)	30	(24.4%)
	Employed (informal)	443	(61.8%)	6	(75.0%)		449	(61.9%)	20	(66.7%)	77	(62.6%)
	Retired/student/housework	70	(9.8%)	2	(25.0%)		72	(9.9%)	5	(16.7%)	7	(5.7%)
	Other	4	(0.6%)	0	(0.0%)		4	(0.6%)	0	(0.0%)	3	(2.4%)
Insurance type	None	543	(75.7%)	7	(87.5%)	1.000	550	(75.9%)	26	(86.7%)	99	(80.5%)
	National Health Insurance (NHI)	32	(4.5%)	0	(0.0%)		32	(4.4%)	2	(6.7%)	6	(4.9%)
	Community-Based Health Insurance (CBHI)	81	(11.3%)	1	(12.5%)		82	(11.3%)	1	(3.3%)	0	(0.0%)
	Health Equity Fund (HEF)	6	(0.8%)	0	(0.0%)		6	(0.8%)	0	(0.0%)	3	(2.4%)
	Social Security Organization (SSO)	3	(0.4%)	0	(0.0%)		3	(0.4%)	0	(0.0%)	4	(3.3%)
	State Authority for Social Security (SASS)	42	(5.9%)	0	(0.0%)		42	(5.8%)	1	(3.3%)	5	(4.1%)
	Private health insurance	10	(1.4%)	0	(0.0%)		10	(1.4%)	0	(0.0%)	2	(1.6%)
	Other	0	(0.0%)	0	(0.0%)		0	(0.0%)	0	(0.0%)	3	(2.4%)
Household size	mean (95%CI)	5.7	(5.5–5.9)	4.5	(3.7–5.3)	0.170	5.7	(5.5–5.9)	4.6	(3.8–5.4)	4.4	(4.1–4.7)
Monthly household income	median (IQR), in US$	235	(118–471)	235	(141–347)	0.726	235	(118–471)	235	(118–494)	353	(200–589)

IQR: Interquartile range, 95% CI: 95% confidence interval, DS-TB: drug-susceptible TB, DR-TB: drug-resistant TB.

Table 2

Clinical characteristics of participants of the national TB patients cost survey by drug resistance and HIV status, Lao PDR, 2018–2019.

Characteristics		Nationally representative sample							With additional sample
		DS-TB		DR-TB		P-value	All		All DR-TB		All TB-HIV
		n = 717		n = 8			n = 725		n = 30		n = 123
Treatment phase	Intensive phase	265	(37.0%)	5	(62.5%)	0.156	270	(37.2%)	19	(63.3%)	50	(40.7%)
	Continuation phase	452	(63.0%)	3	(37.5%)		455	(62.8%)	11	(36.7%)	73	(59.3%)
Treatment category	New	702	(97.9%)	8	(100.0%)	1.000	710	(97.9%)	24	(80.0%)	121	(98.4%)
	Relapse	12	(1.7%)	0	(0.0%)		12	(1.7%)	2	(6.7%)	0	(0.0%)
	Loss to follow-up or treatment after failure	2	(0.3%)	0	(0.0%)		2	(0.3%)	4	(13.3%)	1	(0.8%)
Type and diagnosis of TB	Pulmonary TB (Bacteriologically Confirmed)	488	(68.1%)	7	(87.5%)	0.646	495	(68.3%)	28	(93.3%)	42	(34.1%)
	Pulmonary TB (Clinically diagnosed)	191	(26.6%)	1	(12.5%)		192	(26.5%)	2	(6.7%)	67	(54.5%)
	Extra pulmonary TB	38	(5.3%)	0	(0.0%)		38	(5.2%)	0	(0.0%)	14	(11.4%)
Planned treatment duration	6 months	715	(97.7%)	0	(0.0%)	<0.001***	715	(98.6%)	0	(0.0%)	123	(100.0%)
	9 months	0	(0.0%)	8	(100.0%)		8	(1.1%)	30	(100.0%)	0	(0.0%)
	12 months	2	(0.3%)	0	(0.0%)		2	(0.3%)	0	(0.0%)	0	(0.0%)
Registered facility type	Public health centre	133	(18.5%)	0	(0.0%)	0.136	133	(18.3%)	0	(0.0%)	0	(0.0%)
	District hospital	382	(53.3%)	0	(0.0%)		382	(52.7%)	0	(0.0%)	4	(3.3%)
	Provincial hospital	134	(18.7%)	4	(50.0%)		138	(19.0%)	12	(40.0%)	56	(45.5%)
	Central, military or police hospital	68	(9.5%)	4	(50.0%)		72	(9.9%)	18	(60.0%)	63	(51.2%)
From onset of symptom until diagnosis	median (IQR), in weeks	4	(2–7)	8	(2–8)	0.672	4	(2–8)	2	(1–8)	2	(1–4)
Hospitalization	Hospitalized at time of interview	7	(1.0%)	6	(75.0%)	<0.001***	13	(1.8%)	27	(90.0%)	9	(7.3%)
	Hospitalized (current phase)	82	(11.4%)	6	(75.0%)	<0.001***	88	(12.1%)	27	(90.0%)	47	(38.2%)
	Times hospitalized (current phase)	1.3	(1.1–1.5)	1.0	(1.0–1.0)	0.449	1.3	(1.1–1.4)	1.0	(0.9–1.1)	1.2	(1.1–1.3)
Mode of TB treatment	Self administered	704	(98.2%)	4	(50.0%)	<0.001***	708	(97.7%)	13	(43.3%)	107	(87.0%)
	Directly observed therapy	13	(1.8%)	4	(50.0%)	<0.001***	17	(2.3%)	17	(56.7%)	15	(12.2%)
Number of health facility visits, mean (95%CI)	Pre-disease	1.8	(1.6–2.1)	2.4	(0.3–4.5)	0.498	1.8	(1.6–2.1)	1.8	(1.1–2.6)	1.5	(1.2–1.9)
	Directly observed therapy	2.6	(1.1–4.1)	136.4	(14.5–258.3)	<0.001***	4.1	(2.0–6.2)	137.1	(85.8–188.4)	18.6	(8.9–28.3)
	Drug pick-up	16.1	(15.0–17.2)	15.8	(11.4–20.3)	0.962	15.6	(14.8–16.3)	18.7	(17.4–20.0)	12.6	(10.5–14.7)
	Follow-up	2.4	(2.0–2.8)	0.2	(-0.3–0.6)	0.274	2.4	(2.0–2.8)	0.8	(-0.4–2.0)	1.6	(0.8–2.5)

* Significant difference (0.01 ≤ p < 0.05).

** Significant difference (0.001 ≤ p < 0.01).

*** Significant difference (p < 0.001).

IQR: Interquartile range, 95% CI: 95% confidence interval, DS-TB: drug-susceptible TB, DR-TB: drug-resistant TB.

Table 3

Time loss for TB care seeking in participants of the national TB patients cost survey by drug resistance and HIV status, Lao PDR, 2018–2019.

Time loss due to TB (working hour basis)		Nationally representative sample							With additional sample
		DS-TB		DR-TB		P-value	All		All DR-TB		All TB-HIV
		n = 717		n = 8			n = 725		n = 30		n = 123
Hours lost by patient, median (IQR)	Overall	95	(79–139)	1,327	(665–2,517)	0.006**	95	(79–139)	1,418	(1,219–2,194)	122	(83–220)
	Pre-diagnosis	9	(3–44)	40	(32–270)	0.050*	10	(3–47)	10	(4–40)	24	(6–53)
	Hospitalization	76	(37–158)	755	(301–1,088)	0.026*	78	(38–165)	858	(694–1,088)	185	(66–453)
	Directly observed therapy	65	(30–130)	39	(27–45)	0.306	45	(30–65)	23	(23–45)	15	(4–30)
	Drug pick-up	9	(4–17)	2	(1–10)	0.023*	9	(4–17)	2	(1–3)	13	(6–26)
	Follow-up	1	(0–4)	0	(0–4)	0.291	1	(0–4)	0	(0–0)	0	(0–0)
Hours lost by caregiver, median (IQR)	Overall	1	(0–13)	2	(0–301)	0.616	1	(0–13)	0	(0–0)	0	(0–52)
	Hospitalization	102	(39–206)	541	(61–1,209)	0.185	104	(42–305)	964	(541–1,789)	337	(68–765)
	Directly observed therapy	39	(0–130)	45	(45–45)	0.826	42	(15–97)	45	(45–45)	15	(7–30)
	Drug pick-up	13	(5–26)	21	(3–39)	0.935	13	(6–26)	21	(3–39)	13	(6–26)
	Follow-up	1	(0–21)	0	(0–0)	0.301	1	(0–21)	0	(0–0)	0	(0–0)

* Significant difference (0.01 ≤ p < 0.05).

** Significant difference (0.001 ≤ p < 0.01).

IQR: Interquartile range, DS-TB: drug-susceptible TB, DR-TB: drug-resistant TB.

Table 4

Estimated median total costs incurred by TB-affected households in Lao PDR, 2018–2019, assessed by output approach (in US$).

TB patient costs			Nationally representative sample						With additional sample
			DS-TB		DR-TB		All		All DR-TB		All TB-HIV
			median (IQR)		median (IQR)		median (IQR)		median (IQR)		median (IQR)
			n = 717		n = 8		n = 725		n = 30		n = 123
Pre-TB diagnosis	Direct medical	Total	40	(6–177)	71	(24–73)	41	(6–177)	71	(24–106)	138	(35–353)
		Hospitalization	4	(0–31)	6	(1–17)	4	(0–29)	2	(0–11)	99	(8–353)
		Outpatient services	38	(7–174)	71	(13–186)	38	(7–174)	71	(21–212)	87	(12–239)
	Direct non-medical	Total	11	(4–39)	40	(24–52)	11	(4–39)	15	(9–52)	17	(8–79)
		Travel	4	(1–12)	7	(4–24)	4	(1–12)	9	(2–13)	5	(1–12)
		Food	1	(0–8)	8	(0–26)	1	(0–8)	1	(0–5)	2	(0–6)
		Accommodation	0	(0–0)	0	(0–0)	0	(0–0)	0	(0–0)	0	(0–0)
Post-TB diagnosis	Direct medical	Total	27	(13–30)	210	(145–479)	29	(13–30)	0	(0–83)	261	(15–282)
		Hospitalization	13	(13–30)	208	(111–381)	13	(13–30)	0	(0–15)	261	(15–261)
		Directly observed therapy	0	(0–0)	0	(0–0)	0	(0–0)	0	(0–0)	0	(0–0)
		Drug pick-up	0	(0–31)	132	(69–195)	0	(0–31)	69	(0–195)	27	(8–54)
		Follow-up	0	(0–3)	0	(0–2)	0	(0–3)	0	(0–0)	0	(0–0)
	Direct non-medical	Total	327	(169–702)	266	(209–791)	327	(173–703)	863	(410–1,276)	680	(474–991)
		Travel	33	(18–62)	85	(78–201)	33	(18–64)	50	(50–64)	64	(33–125)
		Food	0	(0–31)	25	(18–154)	1	(0–31)	11	(9–58)	23	(12–55)
		Accommodation	0	(0–0)	0	(0–0)	0	(0–0)	0	(0–0)	0	(0–0)
		Nutritional Supplement	229	(104–581)	161	(115–210)	223	(104–566)	275	(183–1,009)	367	(229–612)
		Other	0	(0–15)	10	(0–46)	0	(0–15)	0	(0–14)	0	(0–15)
	Indirect costs (output approach)		32	(0–565)	1,324	(318–1,881)	57	(0–565)	795	(0–1,589)	512	(0–1,059)
Total direct medical costs			53	(53–88)	280	(167–526)	53	(53–88)	71	(21–129)	261	(60–440)
Total direct non-medical costs			338	(185–735)	298	(226–816)	338	(186–736)	868	(464–1,276)	696	(481–1,065)
Total indirect costs			32	(0–565)	1,324	(318–1,881)	57	(0–565)	795	(0–1,589)	512	(0–1,059)
Total TB patient costs			748	(350–1,432)	2,205	(1,081–3,273)	755	(351–1,454)	2,243	(1,231–2,986)	1,633	(1,007–2,653)

IQR: Interquartile range, DS-TB: drug-susceptible TB, DR-TB: drug-resistant TB.

Table 5

Reported coping mechanisms and social consequences in participants of the national TB patients cost survey by drug resistance and HIV status, Lao PDR, 2018–2019.

Coping mechanism and social consequences		Nationally representative sample							With additional sample
		DS-TB		DR-TB		P-value	All		All DR-TB		All TB-HIV
		n = 717		n = 8			n = 725		n = 30		n = 123
Coping strategy	Dissaving	152	(21.2%)	3	(37.5%)	0.706	155	(21.4%)	14	(46.7%)	59	(48.0%)
	Loan	189	(26.4%)	2	(25.0%)	0.610	191	(26.3%)	7	(23.3%)	43	(35.0%)
	Sale of assets	127	(17.7%)	1	(12.5%)	1.000	128	(17.7%)	3	(10.0%)	22	(17.9%)
	Any of above	358	(49.9%)	4	(50.0%)	0.088	362	(49.9%)	17	(56.7%)	80	(65.0%)
Social effect	Food insecurity	146	(20.4%)	1	(12.5%)	0.582	147	(20.3%)	3	(10.0%)	13	(10.6%)
	Divorce/separation	15	(2.1%)	1	(12.5%)	0.046*	16	(2.2%)	3	(10.0%)	2	(1.6%)
	Job loss	212	(29.6%)	2	(25.0%)	0.778	214	(29.5%)	12	(40.0%)	58	(47.2%)
	Interrupted schooling	10	(1.4%)	1	(12.5%)	0.011*	11	(1.5%)	1	(3.3%)	5	(4.1%)
	Social exclusion	73	(10.2%)	2	(25.0%)	0.171	75	(10.3%)	5	(16.7%)	10	(8.1%)
	Any of above	419	(58.4%)	6	(75.0%)	0.344	425	(58.6%)	19	(63.3%)	76	(61.8%)

* Significant difference (0.01 ≤ p < 0.05).

DS-TB: drug-susceptible TB, DR-TB: drug-resistant TB.

Table 6

Perceived financial impact and impoverishment in participants of the national TB patients cost survey by drug resistance and HIV status, Lao PDR, 2018–2019.

Perceived financial impact and impoverishment		Nationally representative sample							With additional sample
		DS-TB		DR-TB		P-value	All		All DR-TB		All TB-HIV
		n = 717		n = 8			n = 725		n = 30		n = 123
Self-reported financial impact	No impact	79	(11.0%)	1	(12.5%)	0.002**	80	(11.0%)	4	(13.3%)	12	(9.8%)
	Little impact	250	(34.9%)				250	(34.5%)	4	(13.3%)	30	(24.4%)
	Moderate impact	222	(31.0%)	1	(12.5%)		223	(30.8%)	9	(30.0%)	30	(24.4%)
	Serious impact	144	(20.1%)	4	(50.0%)		148	(20.4%)	10	(33.3%)	41	(33.3%)
	Very serious impact	22	(3.1%)	2	(25.0%)		24	(3.3%)	3	(10.0%)	9	(7.3%)
Self-reported impoverishment	Richer	0	(0.0%)	0	(0.0%)	0.026*	0	(0.0%)	0	(0.0%)	0	(0.0%)
	Unchanged	316	(44.1%)	1	(12.5%)		317	(43.7%)	11	(36.7%)	56	(45.5%)
	Poorer	369	(51.5%)	5	(62.5%)		374	(51.6%)	13	(43.3%)	52	(42.3%)
	Much poorer	32	(4.5%)	2	(25.0%)		34	(4.7%)	6	(20.0%)	14	(11.4%)

* Significant difference (0.01 ≤ p < 0.05).

** Significant difference (0.001 ≤ p < 0.01).

DS-TB: drug-susceptible TB, DR-TB: drug-resistant TB

Table 7

Factors associated with catastrophic costs faced by TB-affected households, Lao PDR, 2018–2019.

Risk factors		Total	Facing catastrophic costs		Univariate			Multivariate
			N	%	Crude OR	95% CI	p-value	Adjusted OR	95% CI	p-value
Age	in years	-	-	-	0.99	(0.99–1.00)	0.184	-	-	-
Sex	Female	292	187	(64.0%)	Ref	-	-	-	-	-
	Male	433	266	(61.4%)	0.91	(0.64–1.29)	0.573	-	-	-
Insurance	Any insurance	175	105	(60.0%)	Ref	-	-	-	-	-
	No insurance	550	348	(63.3%)	1.14	(0.82–1.59)	0.415	-	-	-
Education	Secondary or higher	281	162	(57.7%)	Ref	-	-	Ref	-	-
	Primary school	177	118	(66.7%)	1.42	(0.87–2.31)	0.153	0.80	(0.40–1.62)	0.527
	No education	267	173	(64.8%)	1.38	(0.95–1.99)	0.088	0.93	(0.55–1.56)	0.765
Occupation	Employed (formal)	78	36	(46.2%)	Ref	-	-	Ref	-	-
	Unemployed	122	72	(59.0%)	1.71	(0.91–3.23)	0.091	0.95	(0.49–1.85)	0.870
	Employed (informal)	449	316	(70.4%)	2.73	(1.70–4.39)	<0.001***	1.66	(0.96–2.87)	0.066
	Other (housework, student etc)	76	29	(38.2%)	0.74	(0.41–1.34)	0.307	0.60	(0.31–1.16)	0.122
Household income quintile	Highest	91	25	(27.5%)	Ref	-	-	Ref	-	-
	Second highest	149	79	(53.0%)	3.06	(1.78–5.26)	<0.001***	2.66	(1.56–4.52)	0.001**
	Middle	195	111	(56.9%)	3.47	(1.94–6.18)	<0.001***	2.98	(1.72–5.17)	<0.001***
	Second lowest	141	103	(73.0%)	7.03	(3.37–14.65)	<0.001***	5.99	(2.84–12.61)	<0.001***
	Lowest	149	135	(90.6%)	29.28	(13.37–64.13)	<0.001***	28.79	(11.57–71.64)	<0.001***
Household size		-	-	-	0.95	(0.89–1.01)	0.084	0.96	(0.89–1.04)	0.273
Treatment phase	Intensive phase	270	179	(66.3%)	Ref	-	-	-	-	-
	Continuation phase	455	274	(60.2%)	0.76	(0.51–1.14)	0.175	-	-	-
Drug susceptibility	Drug susceptible TB	717	446	(62.2%)	Ref	-	-	Ref	-	-
	Drug resistant TB	8	7	(87.5%)	4.02	(0.47–34.56)	0.194	3.89	(0.57–26.29)	0.156
Treatment category	New	710	444	(62.5%)	Ref	-	-	-	-	-
	Relapse	12	8	(66.7%)	1.34	(0.32–5.59)	0.680	-	-	-
	Loss to follow-up or Treatment after failure	2	1	(50.0%)	0.53	(0.03–10.28)	0.665	-	-	-
Delay in TB diagnosis	1 month or less	627	391	(62.4%)	Ref	-	-	-	-	-
	More than 1 month	98	62	(63.3%)	1.05	(0.62–1.77)	0.859	-	-	-
HIV status	Negative/unknown	706	440	(62.3%)	Ref	-	-	-	-	-
	Positive	19	13	(68.4%)	1.38	(0.47–4.07)	0.546	-	-	-
Self reported financial impact	No or little impact	330	163	(49.4%)	Ref	-	-	-	-	-
	Moderate, serious, very serious impact	395	290	(73.4%)	2.89	(1.96–4.28)	<0.001***	-	-	-
Self reported impoverishment	Richer/unchanged	317	145	(45.7%)	Ref	-	-	-	-	-
	Poorer/much poorer	408	308	(75.5%)	3.66	(2.48–5.41)	<0.001***	-	-	-

* Significant difference (0.01 ≤ p < 0.05)

** Significant difference (0.001 ≤ p < 0.01)

*** Significant difference (p < 0.001)

95% CI: 95% confidence interval, OR: Odds Ratio

Crude ORs are adjusted for clustering effects associated with sampling method

Adjusted ORs are adjusted for all variables in the final model as well as for clustering effects associated with sampling method