Effectiveness of a multifaceted prevention programme for melioidosis in diabetics (PREMEL): A stepped-wedge cluster-randomised controlled trial.

BACKGROUND: Melioidosis, an often-fatal infectious disease caused by the environmental Gram-negative bacillus Burkholderia pseudomallei, is endemic in tropical countries. Diabetes mellitus and environmental exposure are important risk factors for melioidosis acquisition. We aim to evaluate the effectiveness of a multifaceted prevention programme for melioidosis in diabetics in northeast Thailand. METHODOLOGY/PRINCIPAL
FINDINGS: From April 2014 to December 2018, we conducted a stepped-wedge cluster-randomized controlled behaviour change trial in 116 primary care units (PCUs) in Ubon Ratchathani province, northeast Thailand. The intervention was a behavioural support group session to help diabetic patients adopt recommended behaviours, including wearing rubber boots and drinking boiled water. We randomly allocated the PCUs to receive the intervention starting in March 2016, 2017 and 2018. All diabetic patients were contacted by phone yearly, and the final follow-up was December 2018. Two primary outcomes were hospital admissions involving infectious diseases and culture-confirmed melioidosis. Of 9,056 diabetics enrolled, 6,544 (72%) received a behavioural support group session. During 38,457 person-years of follow-up, we observed 2,195 (24%) patients having 3,335 hospital admissions involved infectious diseases, 80 (0.8%) melioidosis, and 485 (5%) deaths. In the intention-to-treat analysis, implementation of the intervention was not associated with primary outcomes. In the per-protocol analysis, patients who received a behavioural support group session had lower incidence rates of hospital admissions involving infectious diseases (incidence rate ratio [IRR] 0.89; 95%CI 0.80-0.99, p = 0.03) and of all-cause mortality (IRR 0.54; 95%CI 0.43-0.68, p<0.001). However, the incidence rate of culture-confirmed melioidosis was not significantly lower (IRR 0.96, 95%CI 0.46-1.99, p = 0.66).
CONCLUSIONS/SIGNIFICANCE: Clear benefits of this multifaceted prevention programme for melioidosis were not observed. More compelling invitations for the intervention, modification of or addition to the behaviour change techniques used, and more frequent intervention may be needed. TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov, number NCT02089152.

RCT Entities:   Population Interventions Outcomes

Introduction

Melioidosis is an often-fatal infection caused by the environmental Gram-negative bacillus Burkholderia pseudomallei, found in soil and water. The disease is considered highly endemic [1-3] and an increasing number of melioidosis cases are increasingly reported in other tropical regions including South Asia, Africa and Central and South America [4-7]. A recent modelling study estimated that there were 165,000 melioidosis cases per year worldwide, of which 54% die [8]. Diabetes mellitus is the most important risk factor for melioidosis [1-3]. About half of melioidosis patients have underlying diabetes, and diabetic patients have a 12-fold higher risk of melioidosis after adjusting for age, sex and other risk factors [9,10]. Skin inoculation, ingestion and inhalation are all important routes of infection from environmental B. pseudomallei [1]. Patients commonly present with sepsis and septic shock with or without localized or disseminated organ involvement such as pneumonia, urinary tract infection, and central nervous system infection [1-3]. Culture positive for B. pseudomallei from any clinical specimens is the gold standard for diagnosis [1].

There is a strong need for interventions to prevent melioidosis with proven effectiveness, particularly for high-risk populations such as diabetic patients in tropical countries [1]. No melioidosis vaccine is currently available, and effectiveness of the recommendations for melioidosis prevention has not been evaluated to date [1]. In Thailand, evidence-based guidelines recommend that residents, rice farmers and visitors should wear protective gear such as rubber boots when in direct contact with soil and environmental water, and consume only boiled or bottled water [11]. Only a small proportion of people follow such recommendations, even though the Ministry of Public Health (MoPH) Thailand has consistently recommended them [11]. In a previous focus group study, we identified barriers to adopting recommended preventive behaviours [11]. The main barriers are categorized into five domains: (i) knowledge, (ii) beliefs about consequences, (iii) intention and goals, (iv) environmental context and resources, and (v) social influence [11]. People have little knowledge of melioidosis, believe that there is little or no harm in not adopting the recommended preventive behaviours, and are not inclined to use boots while working in muddy rice fields [11]. Using the Theoretical Domains Framework [12,13] and the Behaviour Change Wheel [14,15], we previously identified intervention options and modes of delivery, and developed a multifaceted prevention programme aimed at changing behaviour to prevent melioidosis, based on the local context in Thailand [16]. We also reported the protocol and feasibility of the programme in a pilot group of diabetics in northeast Thailand [17].

Here, we reported the outcomes of the PREMEL study, aiming to evaluate whether a multifaceted prevention programme in diabetics would reduce hospital admissions involving infectious diseases and culture-confirmed melioidosis infections. A cluster-randomized design was selected because the intervention was the behavioural support group session. A step-wedge design was selected because of the recommendation of the ethical committees to provide the intervention to all participants, and inability to achieve the target power and follow the recommendation of the ethical committees in a parallel design.

Methods

Ethics statement

All participants provided individual written consent before enrollment. The trial was approved by the Institute for the Development of Human Research Protections, Ministry of Public Health, Thailand (ref 189/2557) and Oxford Tropical Research Ethics Committee, University of Oxford, United Kingdom (ref 06–14). This trial is registered with ClinicalTrials.gov, number NCT02089152.

Trial design and participants

From April 2014 to December 2018, we conducted a stepped-wedge cluster-randomized controlled behaviour change trial in Ubon Ratchathani province, northeast Thailand, where there was one provincial public hospital (Sunpasitthiprasong Hospital), three general public hospitals, 22 district hospitals and 317 Tambon Health Promoting Hospitals (THPHs). All hospitals also acted as primary care units (PCUs) that provide health promotion, prevention and medical treatment, including diabetic clinics, for communities. Clusters consisted of 116 PCUs in the province.

Diabetic patients aged from 18 to 65 years old presenting at diabetic clinics were invited to participate. Diabetes was defined as having fasting plasma glucose ≥126 mg/dl, HbA1c ≥6.5%, 2-hour plasma glucose (PG) ≥200 mg/dl during an oral glucose tolerance test, or classic symptoms of hyperglycaemia with a random PG ≥200 mg/dl. Patients who had been diagnosed with melioidosis and had not completed oral-eradicative treatment for melioidosis were excluded.

Randomisation

Diabetic patients were approached individually. Those consenting to enrollment in the study were asked for blood samples to test for HbA1c. We informed them that they would be randomly assigned to a group intervention lasting about 50–60 minutes once during the study period and that the aim was to prevent infectious diseases. Participants were not given the name of the target disease (melioidosis) or details of the intervention before the intervention. We completed the enrollment in November 2014, and allocated year 2015 as pre-intervention period. We randomly allocated the PCUs to receive the intervention starting in March 2016, 2017 and 2018 (defined as group 1, 2 and 3, respectively; Figs 1 and 2). After the completion of enrollment, an independent statistician generated the randomization code and assigned clusters to sequences.

Fig 1

Trial profile.

Fig 2

Schematic of the PREMEL stepped-wedge cluster-randomised controlled trial.

PREMEL = multifaceted PREvention programme of MELioidosis in diabetics. No group received the intervention at baseline. Period 1 was the enrollment period, and period 2 was the baseline period. Clusters were randomly assigned to three groups that crossover to receive the intervention in March 2016, 2017 and 2018. Participants (diabetic patients enrolled) in each cluster group received a multi-faceted prevention programme once from March to July 2016, 2017 and 2018, respectively.

Procedures

The intervention was a multifaceted prevention programme for melioidosis developed using two behavioral frameworks: Theoretical Domains Framework [12,13] and the Behaviour Change Wheel [14,15]. Details of the intervention have been published [17]. The programme was a small-group intervention, in which 6 to 20 diabetic patients at a time attended a behavioural support group session conducted by the study team. Each session lasted about 50 to 60 minutes. The aim was to deliver the intervention from March to May of each year, prior to the start of rainy season and rice farming in June in northeast Thailand. Each diabetic patient was contacted by a member of the study team who gave them the date and the venue of their behavioural support group session. As diabetic patients came early in the morning for fasting blood glucose (FBG) testing, we delivered the behavioural support group after patients had breakfast (after FBG testing) and while they were waiting to see the doctors. When necessary, we delivered the group session after patients saw the doctors.

The objective of the intervention was to increase the frequency of the two recommended preventive behaviours: wearing boots while working in rice fields and drinking boiled or bottled water. The multifaceted prevention programme included 13 behaviour change techniques identified by a focus group study conducted in 2012 [16,17]. The behaviour change techniques include information about health consequences (e.g. explaining that not wearing boots while working in rice fields and that drinking untreated water can lead to an often fatal infectious disease called melioidosis), credible source (e.g. a high status professional in the government giving a speech that emphasises the importance of melioidosis prevention), adding objects to the environment (e.g. providing baby powder and long socks to alleviate the problem of discomfort due to heat and humidity when wearing boots), reconstructing the physical environment, instruction on how to perform a behaviour, demonstration of the behaviour, commitment, prompts/cues, self-monitoring of behaviour, goal setting, feedback on behaviour, feedback on outcome(s) and social support.

The intervention package included six short videos, three pamphlets, and a calendar with a space for participants’ individual photographs and self-pledge. The materials are publicly available online (https://dx.doi.org/10.6084/m9.figshare.5734155) [17]. Each participant also received a pair of long socks and a bottle of baby powder (to reduce uncomfortable feelings while wearing boots) and a 2-litre plastic ice bucket (commonly used to store boiled water to drink while working in rice fields). In each behavioural support group, participants received an introduction by a moderator, watched a series of brief videos, and had short group discussions at the end of each video. Participants then had a session in which they tried out multiple kinds of boots to identify the ones which would be most comfortable for wearing. Next, the study team took a photograph of each participant while wearing their boots and holding a kettle and gave participants their printed photographs. Finally, participants made their own calendar to act as a reminder tool for the recommended preventive behaviours. We asked participants to attach their individual photograph to the calendar and write their own pledge on the calendar themselves. Participants were asked to hang their calendar in their house. The moderator also stimulated group discussion before and after as well as during the sessions. Additionally, we provided social support by giving information to nurses, doctors, participants’ relatives and village health volunteers in each participating PCU about the intervention and its potential benefits. We asked them to encourage participants to continue with the recommended behaviours.

Outcomes

Two primary outcomes were hospital admissions involving infectious diseases and culture-confirmed melioidosis. Hospital admissions involving infectious diseases were determined using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Thailand Modification (ICD-10-TM) [18] or final diagnoses made by attending physicians including the terms fever, febrile, infected, infection, abscess, pus, diarrhea, sepsis, pneumonia, cellulitis or diabetic foot. Secondary outcomes were all-cause mortality, and overall melioidosis (culture-confirmed melioidosis plus clinical melioidosis defined by attending physicians). We excluded continuing treatment from previous admissions, hospital-acquired infections and healthcare-associated infections by not including admissions occurring within 30 days of the discharge date of previous admissions. Culture-confirmed melioidosis was defined as the symptoms and signs of infection in association with at least one culture from any site positive for B. pseudomallei.

All diabetic patients were contacted by phone yearly. For diabetic patients who were admitted to hospitals, hospital admission data together with microbiology laboratory results were obtained from hospitals in the province. To determine outcomes of participants up to 31 December 2018, we conducted the last phone contact on every participant from 1 January to 30 June 2019. To investigate whether deaths were associated with infectious diseases, we used ICD-10-DM, microbiology laboratory results and final diagnoses made by attending physicians for admissions occurring within 30 days prior to death. We also used cause of death informed by relatives via phone contact.

Statistical analysis

The PREMEL study power calculation was performed with the assumption that, among diabetes, incidence rates of hospital admissions involving infectious diseases were 50 per 1,000 persons per year [19,20] and incidence rates of culture-confirmed melioidosis were 240 per 100,000 persons per year [10]. Using an alpha error of 0.05, a power of 0.8 and an intra-cluster correlation coefficient of 0.15, we calculated that we needed at least 9,000 diabetics from 30 diabetic clinics (300 diabetics per clinic). This design and sample size gave us 85% power to show a 30% reduction in incidence rates of hospital admissions involving infectious diseases and a 35% reduction in incidence rates of culture-confirmed melioidosis. During the enrollment period, we found that the number of diabetic patients we could enroll at each PCU was lower than we expected. Therefore, during the enrollment period, we adjusted and enrolled diabetic patients from 116 PCUs in the province.

We used both intention-to-treat (ITT) and per-protocol analyses. For the primary outcome of hospital admissions involving infectious diseases, we used multilevel mixed-effects negative binomial regression models adjusted for calendar time, and with a random effect for PCU and a random effect for repeated measures on the same diabetic patients [21,22]. This approach was recommended by Hemming et al [21,22] to allow for correlations between individuals in the same cluster and the dependence between individual measurements over the course of the study. In the ITT analysis, 1st March was set as the time of the intervention for the randomized clusters of those years. Patients were considered at risk from the enrollment until 31 Dec 2018. In the per-protocol analysis, participants who received a behavioural support group session for melioidosis prevention were defined as having received the intervention.

For the melioidosis and mortality outcomes we used multilevel mixed-effects Poisson regression models, adjusted for calendar time, with a random effect for PCU. This was because the multilevel mixed-effects negative binomial model did not converge [21,22]. In all models we performed interaction tests to evaluate whether treatment effects change over time [21,22].

We ran sensitivity analyses to evaluate whether the effectiveness of the intervention changed after adjusting for gender, age, diabetes duration and HbA1c level at enrollment using a multivariable regression model. We also evaluated whether the effectiveness would be observed when infections that are not plausibly related such as urinary tract infections were excluded. All analyses were performed using STATA version 14.2 (StataCorp, College Station, TX).

Patient and public involvement

No patients or members of the public were involved in the design or conduct of our research. However, Ubon Ratchathani Provincial Public Health Office contributed to the planning stages. Our research uptake strategy included widespread engagement with key stakeholder groups; including Diabetes Association of Thailand and other melioidosis-endemic countries.

Results

From April 2014 to November 2014, we enrolled 9,075 diabetic patients in 116 PCUs, representing the clusters, into the study (Fig 1).

Baseline characteristics of the 9,056 diabetic patients included in the study are summarised in Table 1, stratified by group. Their baseline characteristics were similar between groups. Overall, 73% were female, the median age was 55 years (IQR 49–60), 41% had known diabetes duration less than 5 years, 79% were taking only oral medication for their diabetes and 30% had poor diabetic control (HbA1c >9.0%) on enrollment. Fifty-three patients had history of culture-confirmed melioidosis and completed oral eradicative treatment prior to the enrollment.

Table 1

Baseline characteristics at enrollment.

Characteristics	Group 1	Group 2	Group 3	Total
Total no. of clusters	39	39	38	116
Total no. of participants	3169	2976	2911	9056
Sex, female	2285 (72%)	2194 (74%)	2158 (74%)	6637 (73%)
Age
18 - <50 years	872 (28%)	829 (28%)	778 (27%)	2479 (27%)
50 - <60 years	1453 (46%)	1308 (44%)	1311 (45%)	4072 (45%)
60–65 years	844 (27%)	839 (28%)	822 (28%)	2505 (28%)
Known diabetes duration
<5 years	1292 (41%)	1235 (41%)	1168 (40%)	3695 (41%)
5 - <10 years	956 (30%)	879 (30%)	844 (29%)	2679 (29%)
≥10 years	921 (29%)	862 (29%)	899 (31%)	2682 (30%)
Diabetic control
No medication	115 (4%)	115 (4%)	113 (4%)	343 (4%)
Only oral medication	2503 (79%)	2369 (80%)	2264 (78%)	7136 (79%)
Insulin therapy	551 (17%)	492 (17%)	534 (18%)	1577 (17%)
HbA1C level
<7.0%	706 (22%)	698 (23%)	664 (23%)	2068 (23%)
7.0–8.0%	898 (28%)	800 (27%)	819 (28%)	2517 (28%)
>8.0–9.0%	603 (19%)	565 (19%)	565 (19%)	1733 (19%)
>9.0%	962 (30%)	913 (31%)	863 (30%)	2738 (30%)
History of co-morbidities
Hypertension	1999 (63%)	1920 (65%)	1728 (59%)	5647 (62%)
Dyslipidemia	1800 (57%)	1665 (56%)	1702 (58%)	5167 (57%)
Kidney diseases	176 (6%)	152 (5%)	235 (8%)	563 (6%)

A total of 39, 39 and 38 PCUs were randomized to groups 1, 2 and 3, in which the intervention was given from March to July in 2016, 2017 and 2018, respectively (Fig 2). Of 9,056 diabetic patients, 6,544 (72%) received a behavioural support group session. The study team delivered a total of 522 sessions, of which 177 (34%) had fewer than six participants per session, 237 (45%) had 6 to 20 participants, and 108 (21%) had more than 20 participants. Of 522 sessions, 408 (78%) were conducted from March to May, 94 (18%) in June, and 20 (4%) in July. Participants who received a behavioural support group session were older and had a higher proportion of female, lower proportion of insulin therapy (16% vs 22%) and lower proportion of poor diabetic control (29% vs 33%) compared with those who did not receive a behavioural support group session (Table 2).

Table 2

Characteristics of participants who received a behavioural support group session for melioidosis prevention.

Characteristics	Received the intervention (n = 6544)	Did not receive the intervention (n = 2512)	P value
Groups
Group 1	2572 (39%)	597 (24%)	<0.001
Group 2	2020 (31%)	956 (38%)
Group 3	1952 (30%)	959 (38%)
Sex, female	4998 (76%)	1639 (65%)	<0.001
Age
18 - <40 years	1713 (26%)	766 (30%)	<0.001
40 - <55 years	2972 (45%)	1100 (44%)
55–65 years	1859 (28%)	646 (26%)
Diabetes duration
<5 years	2645 (40%)	1050 (42%)	0.14
5 - <10 years	1974 (30%)	705 (28%)
≥10 years	1925 (29%)	757 (30%)
Diabetic control
No medication	248 (4%)	95 (4%)	<0.001
Only oral medication	5263 (80%)	1873 (75%)
Insulin therapy	1033 (16%)	544 (22%)
HbA1c level
<7.0%	1523 (23%)	545 (22%)	<0.001
7.0–8.0%	1841 (28%)	676 (27%)
>8.0–9.0%	1283 (20%)	450 (18%)
>9.0%	1897 (29%)	841 (33%)
History of co-morbidities
Hypertension	4125 (63%)	1522 (61%)	0.03
Dyslipidemia	3767 (58%)	1400 (56%)	0.10
Kidney diseases	362 (6%)	201 (8%)	<0.001

Data are n (%) or median (interquartile range).

Of 2,512 diabetic patients who did not receive a behavioural support group session, 1,696 (68%) did not meet the study team, but received details of the behavioural support group by phone and received materials by delivery via village health volunteers. Another 386 (15%) diabetic patietns met the study team, received the materials and details of the behavioural support group personally, but declined to attend a behavioural support group session. The most frequent reasons for declining were that they did not want to wait for the session (while a session was already running), feared that they would miss their place in the queue for the doctor, wanted to go back home immediately (for cases that had already seen a doctor, and could attend a session after that), and unknown reasons. The other 250 (10%) diabetic patients died prior to the intervention period and 180 (17%) diabetic patients could not be contacted.

As of the end of December 2018, 8,495 (94%) patients survived, 485 (5%) died, and 76 (1%) could not be contacted. Of 76 patients who could not be contacted, six (0.1%) withdrew consent during the study period and data up to the last follow-up were used in the analyses. Total duration of follow-up period was 38,457 person-years.

For the primary outcome, 3,335 hospital admissions involving infectious diseases occurred in 2,195 patients. The most common diagnoses were acute gastroenteritis (582 admissions), pneumonia (367 admissions), post-traumatic wound infection (302 admissions), urinary tract infection (287 admissions), cellulitis (251 admissions) and unspecified fever (241 admissions; S1 Table). The rate of hospital admission involving infectious diseases was 87 (95%CI 84–90) admissions per 1,000 person-years. In the ITT analysis, the intervention was not associated with the incidence rate of hospital admissions involving infectious diseases (p = 0.79; Table 3). In the per-protocol analysis, diabetic patients who received a behavioural support group session had 11% lower incidence rate of hospital admissions involving infectious diseases (incidence rate ratio [IRR] 0.89; 95%CI 0.80–0.99, p = 0.03). The primary outcome of culture-confirmed melioidosis occurred in 58 patients. Fifty-seven patients admitted to hospitals and one patient had localized melioidosis infection of their hand with pus culture positive for B. pseudomallei. The patient was treated successfully as an outpatient case with cotrimoxazole-sulphamethoxazole as the oral eradicative treatment. In both ITT and per-protocol analyses, the intervention was not associated with the incidence of culture-confirmed melioidosis (p = 0.30 and p = 0.66, respectively).

Table 3

Outcomes of the study.

	Adjusted (for time) incidence rate ratio (95% CI)	Adjusted (for time and other risk factors*) incidence rate ratio (95% CI)
Intention-to-treat analysis
Primary outcomes
Hospital admissions involving infectious diseases	0.98 (0.87–1.11)	0.98 (0.87–1.10)
Culture-confirmed melioidosis	0.65 (0.29–1.47)	0.66 (0.29–1.50)
Secondary outcomes
Overall melioidosis	0.73 (0.37–1.44)	0.74 (0.38–1.45)
Mortality	0.97 (0.74–1.28)	0.98 (0.74–1.29)
Per-protocol analysis **
Primary outcomes
Hospital admissions involving infectious diseases	0.89 (0.80–0.99)	0.90 (0.81–1.00)
Culture-confirmed melioidosis	0.85 (0.41–1.76)	0.96 (0.46–1.99)
Secondary outcomes
Overall melioidosis	0.57 (0.31–1.08)	0.65 (0.35–1.22)
Mortality	0.54 (0.43–0.68)	0.56 (0.44–0.71)

CI = confidence interval

* Adjusted for age, sex, known diabetes duration and HbA1c level

** Participants who received a behavioural support group session for melioidosis prevention were defined as received the intervention per protocol.

The secondary outcome of all-cause mortality occurred in 485 patients. 15 of 58 (26%) patients with culture-confirmed melioidosis and none of 22 (0%) patients with clinical melioidosis died within 30 days of the hospital admissions of melioidosis. Of 485 deaths, 213 (44%) occurred within the hospitals, 198 (41%) occurred within 30 days after the last hospital admission and 74 (15%) occurred at home without hospital admission within 30 days prior to death. Of 198 who died within 30 days after the last hospital admission, 101 (51%) died on the hospital discharge date, 49 (25%) died within 1 to 7 calendar days after the hospital discharge, and 48 (24%) died within 8 to 30 calendar days after the hospital discharge. We found that 217 (45%) of 485 deaths were possibly related to infectious diseases, including septic shock recorded by attending physicians in 94 deaths (19%) (S2 Table). In the ITT analysis, implementation of the intervention was not associated with mortality (p = 0.85). In the per-protocol analysis, patients who received the multifaceted prevention programme had 46% lower rate of mortality (IRR 0.54; 95%CI 0.43–0.68, p<0.001). As we adjusted for calendar time, we observed that the rate of hospital admissions involving infectious diseases and mortality rose over time.

The secondary outcome of overall melioidosis occurred in 80 patients (58 culture-confirmed melioidosis and 22 clinical melioidosis). Of 53 patients who had history of culture-confirmed melioidosis and completed oral eradicative treatment prior to the enrollment, none had culture-confirmed melioidosis and three had clinical melioidosis during the study period. In both ITT and per-protocol analysis, implementation of the intervention was not significantly associated with the incidence rate of melioidosis (p = 0.37 and p = 0.09, respectively).

In a sensitivity analysis, using per-protocol analysis and multivariable regression models, we found that male gender, older age, longer known diabetes duration and higher HbA1c levels on enrollment were associated with incidence of hospital admissions involving infectious diseases (S3 Table) and mortality (S4 Table). Male gender, longer known diabetes duration and higher HbA1c level on enrollment were also associated with overall melioidosis (S5 Table). We also conducted a pre-specified analysis excluding hospital admissions involving infections that are not plausibly related to the intervention such as urinary tract infections, and similar results were observed (S6 Table).

Discussion

This is the first trial of a behavioural intervention to prevent melioidosis to the authors’ knowledge. Clear benefits of the multifaceted prevention programme for melioidosis could not be observed. It shows that diabetic patients who receive a behavioural support group session for melioidosis prevention have lower rates of hospital admissions related to infectious diseases and of all-cause mortality. Rates of culture-confirmed melioidosis were not statistically different. Our study also did not observe an intervention effect in the ITT analyses.

The absence of a clear intervention effect could be due to the type of the intervention and lack of statistical power. This is probably because a proportion of enrolled patients did not participate in a behavioural support group session, and only the patients who received a behavioural support group session adopted the recommended behaviours in significant numbers [16]. Providing information and materials without attending a behavioural supportive group probably only had a minimal effect on behaviour [14,15]. The study had a high proportion of female diabetic patients, while male diabetic patients are at a higher risk of melioidosis [1-3]. The reason for this could be that we met less male diabetic patients as males are more likely than females to miss appointments at diabetic clinics [23,24]. In addition, based on our experience, males are more likely to decline invitations to participate in studies than females. A high proportion of female diabetic patients in prospective studies (ranging from 58% to 75%) is also observed in other prospective studies in diabetics in Thailand [25]. Nonetheless, both male and female diabetic patients are primary targets for interventions directed at melioidosis prevention. It is also possible that a single behavioural support group session and component behavior change techniques used were not adequate. This suggest that the invitation for the intervention and prevention programme may need to be more proactive and persuasive for male diabetic patients. Modification or addition of the behaviour change techniques used, and more frequent intervention may also be needed.

Our findings suggest that wearing protective gear and drinking boiled water could have a wide impact on infectious diseases and overall health; however, the observed size of effect (e.g. IRR 0.54 for all-cause mortality) could also be attributed to other confounding factors. For example, diabetic patients may also improve their glycemic control and diabetes self-management [26], on top of wearing boots and drinking boiled water, after receiving a behavioural support group session. This may result from hearing information about the consequence of melioidosis and its association with diabetes and poor diabetic control from credible sources, and stories from relatives of fatal cases in the videos which were part of the behavioural support group session. It is also possible that diabetic patients who received a behavioural support group session might have better self-care behaviour or expose themselves less often to risky environments than those who did not receive the intervention.

We show that poor diabetic control (HbA1c >9.0%) and longer known diabetic duration at enrollment are significantly associated with hospital admissions related to infectious diseases, overall melioidosis and all-cause mortality. The association between poor diabetic control and all-cause mortality is consistent with previously published studies [27]. Infection-related deaths as a proportion of all-cause mortality estimated in our study (45%) was much higher than previous reports, ranging from 4 to 15% from the cohort in the U.S. [28] and 16% in the U.K. [29]. It is likely that the proportion of infection-related deaths in diabetes is higher in low and middle-income countries, where the burden of sepsis is estimated to be highest [30]. The difference could also be associated with the difference in training for International Statistical Classification of Diseases coders and limited data on cause of death in Thailand.

The proportion of diabetic patients with poor diabetic control in our study (30%) is relatively higher than the previous reports in Thailand [25,31] This could be because we tested HbA1c in 100% of the diabetic patients on enrollment. Previous studies in Thailand found that only 50% to 78% of diabetic patients had HbA1c tested and diabetic patients with repeatedly high fasting blood glucose may not be tested for HbA1c levels [24,25] The findings of increasing rate of hospital admission involving infectious diseases and mortality as the study period progressed (i.e. a rising tide phenomenon [21,22]) is consistent with our expectation that those events would occur more often as diabetic patients age and have a longer duration of living with diabetes.

This study has several strengths: the large sample size; the large number of PCUs; and the use of two behavioral frameworks: Theoretical Domains Framework [12,13] and the Behaviour Change Wheel [14,15] for the development of the intervention [16,17]. Strong support from PCUs and village healthcare volunteers, and the high rate of follow-up via phone contact, increased the reliability of hospital admissions and mortality endpoints over the study period. Limitations include the impossibility of blinding the intervention after unmasking, and the inability to record the data of non-responders to an invitation to the study, to repeat HbA1c, to have more than one behavioural support group session, to have more frequent follow-up, and to measure recommended behaviours. A high number of enrolled patients later declined to receive or wait around for the intervention. They were more likely to be male and have poor diabetic control. We also found that these participants were more likely to have hospital admissions involving infectious diseases, melioidosis and fatal outcome. Due to pragmatic reasons, we could not ensure the number of participants per session were always between six to 20. One of the major weakness is the lack of monitoring and reminder with only a yearly phone call. Lost opportunity to reinforce at regular clinic visits for diabetes which are more frequent than yearly may have improved the outcomes. Had we had more human resources, time and budget, we would have included more phone calls and reminder text messages including during the rainy season. The study team had eight research assistants, and the implementation of the intervention, conducting yearly phone calls, and following data on hospital admissions of 9,000 participants already required the full capacity of the study team. We also provided calendars as a reminder so that they could note their activities on a daily basis. ICD coding can also be diagnostically inaccurate because of the subjective nature of ICD certification practices and limited training. The association between receiving a behavioural support group session for melioidosis prevention and lower rates of hospital admissions related to infectious diseases was not strong, and the impact of the intervention on hospital admission related to infectious diseases should be considered carefully.

In conclusion, clear benefits of this multifaceted prevention programme for melioidosis were not observed. Successful and cost-effective interventions are still needed though challenging to design and implement. We propose that more compelling invitations for the intervention, modification of or addition to the behaviour change techniques used, and more frequent intervention may be needed. In addition, alternative interventions including targeted use of antimicrobial prophylaxis [32], and more general clinical and public health interventions such as better control of diabetes and improvement of water treatment [33] should also be considered.

ICD-10-TM codes and criteria used to determine that hospitals admissions were possibly related to infectious diseases.

(DOCX)

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ICD-10-TM codes and criteria used to determine that deaths were possibly related to infectious diseases.

(DOCX)

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Factors associated with hospital admissions involving infectious diseases.

(DOCX)

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Factors associated with mortality.

(DOCX)

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Factors associated with overall melioidosis.

(DOCX)

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Outcomes of the study excluding infections that are not plausibly related to the intervention.

(DOCX)

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16 Feb 2021

Dear Dr. Limmathurotsakul,

Thank you very much for submitting your manuscript "Effectiveness of a multifaceted prevention programme for melioidosis in diabetics (PREMEL): a stepped-wedge cluster-randomised controlled trial" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

The reviewers recommend substantial changes to the manuscript, including the conclusion, recommending caution in not over-stating the potential benefits of the intervention, and justification for inclusion of melioidosis cases that were not microbiologically confirmed. Despite the negative findings for the study, these are potentially important findings to share after addressing the reviewers’ comments. The authors could discuss why the interventions did not result in significant differences, with respect to study design or biological factors.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Yunn-Hwen Gan

Associate Editor

PLOS Neglected Tropical Diseases

Anna Ralph

Deputy Editor

PLOS Neglected Tropical Diseases

***********************

Note that reviewer 2 has consolidated his/her comments at a single section at the end instead of breaking into each manuscript section.

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: I am satisfied with the methods that have been employed.

The statistical analysis is very complicated and I lack the expertise to offer a sensible comment on the statistical methods that have been employed. I hope that one of the other reviewers have more expertise so that this might be critically assessed.

Reviewer #2: All good

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Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: The results are presented in a detailed manner and in general, I am happy with them.

Although I might suggest that the authors try not to duplicate results in the text and the tables/figures. For instance, lines 278-281 is repeated - almost word for word - in figure 1 and doesn't add much to the study's interpretation (0.2% of the cohort were excluded). There are several other examples where data are duplicated in text and in a table or figure like this.

Reviewer #2: Yes

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Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: This is my major concern with the paper.

I think the authors have performed an impressive study, but they have over-egged their - in my opinion - negative results. To me the studied intervention - if significant at all - appears to be a very low-value intervention.

The primary aim of the study was to evaluate the effectiveness of a prevention programme for melioidosis.

22/80 (27.5%) of the patients who were said to have melioidosis had a "clinical diagnosis".

As the authors themselves note in lines 94-95, a positive culture for B. pseudomallei is the gold standard for diagnosis.

So why then do they include the "clinical diagnosis" of melioidosis cases in their analysis? I would be quite confident that a significant proportion of the patients with "clinical melioidosis" did not actually have melioidosis. How then to explain that their case-fatality rate was 0 (compared to 26% among the culture-confirmed group). Even in the very well-resourced Australian health system the case-fatality rate of melioidosis is about 10% of those admitted. I would suggest that the reason that the case-fatality rate in the patients with "clinical melioidosis" is so low is that many did not actually have melioidosis. Indeed, the authors state that the reason that you would want to prevent melioidosis is that it is often fatal; in lines 86-88 they cite a modelling paper that suggests that 54% of cases of melioidosis die.

The patients with "clinical melioidosis" in this cohort actually did pretty well! If this is the case, perhaps there is less need to worry about preventing it?

Even including the clinically diagnosed cases in a per-protocol analysis in a sample of 9075 patients the IRR is 0.57 (95%CI 0.31-1.08), p=0.09. This is not, as the authors state, "borderline evidence of a lower incidence rate" it is statistically not significant. Even if the authors suggest that this "trend" is a type 2 error, the size of the sample that you would need to prove that the effect was statistically significant suggests that the actual impact of the intervention is quite limited. If you can’t show it in 38,457 person-years of follow-up, any putative benefit much be tiny. What is the number needed to treat (NNT)?

The two main interventions that the authors were keen to implement (drinking bottled/boiled water and wearing boots - lines 172-173) were said to reduce hospital admissions for infectious diseases (IRR 0.89 (95%CI 0.80-0.99, p=0.03), but how much was this simply determined by gastroenteritis admissions, (the most common cause for admission with infection) which could just be explained by getting the participants to drink boiled/bottled water. No need to fuss around with all the education about wearing boots. Additionally, how do the authors propose the wearing of boots and drinking bottled/boiled water reduce urinary tract infections?

The patients who did not receive the intervention were more likely to be male and more likely to have poorer glycaemic control (among other significant differences). Although the authors have used complicated statistical methods to control for the contribution of these factors, lacking the statistical knowledge to critically appraise this, I would want to be confident that the patients who declined to receive or wait around for the intervention are not just the patients who are going to make poorer health decisions anyway. Male gender is a recognised risk factor for poor health outcomes and poor glycaemic control may also be a proxy maker for poor access to care/adherence. Indeed, the authors do acknowledge this as a potential limitation in the study (lines 400-402). I think this discussion could be expanded.

Finally, I am not convinced by their health economic argument. The statistically non-significant benefit of the intervention would – the authors “estimate” – be cost-effective if policy makers were willing to pay $7000 per QALY. If this funding were directed elsewhere – to measures that improve glycaemic control for instance (lifestyle and pharmacological interventions) or prevent the development of diabetes, not only would this reduce the incidence of melioidosis but also the cardiovascular deaths and other complications of metabolic syndrome which have far more impact at a community level than melioidosis (56 confirmed cases in 38,457 years of patient follow up)

Reviewer #2: Yes

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Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: I would like to congratulate the authors on an ambitious and impressive piece of work.

However, I am not at all convinced by the article's conclusions as they presently stand.

Even with 38,457 person-years of follow-up, using a per-protocol analysis and included "clinical" cases of melioidosis they have not been able to show that the intervention significantly reduced the incidence of melioidosis.

There was a reduction in infections requiring hospitalisation, but what proportion of the reduction in infectious diseases admissions can be explained by the bottled water intervention alone on the most common infection, gastroenteritis?

Improving access to clean water may be a simpler and cost-effective intervention at a population level.

The paper certainly merits publication and the melioidosis research community will find the work very interesting. However, I think revision of their conclusions, downplaying the putative success of the intervention significantly would make the paper more credible.

Reviewer #2: The authors conducted a cluster randomised trial using step wedge design to study the impact of a behavioural intervention on hospitalisation due to infectious diseases and incidence of melioidosis among diabetic patients in Northern Thailand.

The authors acknowledged the imbalance in gender, and larger group size than predefined that may have influenced learning.

A few comments:

(1) Can the authors explain why recruitment ended in 2014 but randomisation only occurred in 2016?

(2) Did the authors exclude all diabetic patients with known melioidosis? Exclusion criteria stated that those yet to complete antibiotic were excluded. If they did not, what proportion with known previous melioidosis was enrolled? Even with completion of coytrimoxazole, there is still a 5% relapse rate, which may have affected the incidence of melioidosis.

(3) Can the authors clarify why they did not conduct the intervention year round which could lead to better recruitment and better power as even if rainy season has started, behaviour change could still reduce infections? In fact, it may be more effective as the potential outcomes may be more real.

(4) One of the major weakness is the lack of monitoring and reminder with only a yearly phone call. Lost opportunity to reinforce at regular clinic visits for diabetes which are more frequent than yearly may have improved the outcomes. Can the authors explain why they decided only on yearly phone call? Why did they not ask for diary; reminder text messages; more frequent phone calls e.g. 3 monthly; reminder during rainy season?

(5) Can the authors explain why they thought obtaining cause of death from relatives may contribute to reliable data on secondary outcome of mortality? What was the average educational background of the family members?

(6) Primary outcome included infections like urinary tract infections that are not plausibly related to wearing boots and drinking boiled or bottled water. These are also not in pre-defined primary outcome. Can the authors explain the basis of inclusion? Can they do sensitivity analysis by excluding infections that are not plausibly related?

(7) There is no effect on melioidosis. I think the authors should accept that and not claim borderline or trend to siginficance in any part of the manuscript including abstract.

--------------------

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Reviewer #1: No

Reviewer #2: No

Figure 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. 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 us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, PLOS recommends that you deposit laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see https://journals.plos.org/plosntds/s/submission-guidelines#loc-methods

9 Apr 2021

Submitted filename: response BCT 2021 04 03.docx

Click here for additional data file.

29 Apr 2021

Dear Dr. Limmathurotsakul,

Thank you very much for submitting your revised manuscript "Effectiveness of a multifaceted prevention programme for melioidosis in diabetics (PREMEL): a stepped-wedge cluster-randomised controlled trial" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

Dear authors, thank you for your major revision that has addressed the major issues pointed out by both reviewers. To further improve the clarity and message of the manuscript, please address the 3 points raised by reviewer 1, and if there is disagreement with the reviewer, please justify. The public message from this study remains clear: that successful, low-cost interventions are challenging in this community and the authors should spare a few more sentences to describe the socioeconomic challenges and perhaps new avenues of intervention, eg through better control of diabetes or targeted use of antimicrobial prophylaxis (e.g. see https://pubmed.ncbi.nlm.nih.gov/29340327/) or water treatment (e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741262/), that may be more effective.

Another minor point: Please delete the last sentence "Further study may be required" from the abstract as it adds no value.

Please revise carefully and to the points raised as this will be the last revision.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Yunn-Hwen Gan

Associate Editor

PLOS Neglected Tropical Diseases

Anna Ralph

Deputy Editor

PLOS Neglected Tropical Diseases

***********************

Dear authors, thank you for your major revision that has addressed the major issues pointed out by both reviewers. To further improve the clarity and message of the manuscript, please address the 3 points by reviewer 1, and if there is disagreement with the reviewer, please justify. The public message from this study remains clear: that intervention is not easy in this community and the authors should spare a few more sentences to describe the social economic challenges and perhaps new avenues of intervention, eg through better control of diabetes that may be more effective.

Another minor point: Please delete the last sentence "Further study may be required" from the abstract as it adds no value.

Please revise carefully and to the points raised as this will be the last revision.

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: See summary and general comments.

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: See summary and general comments.

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: See summary and general comments.

--------------------

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: Minor revision. See summary and general comments.

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: Thank you for the opportunity to review the revised manuscript by Limmathurotsakul et al. I appreciate the time that they have take to address the reviewers’ comments. I have only a few comments to make.

While they have pleasingly re-presented the study as a negative one, rather than a borderline positive one, I would suggest that they have not gone quite far enough, but I will leave it to the Editor to adjudicate!

1. In the abstract they say that in the per-protocol analysis the patients receiving the intervention had a lower incidence of hospital admissions involving infectious diseases (OR: 0.89, 95%CI 0.80-0.99, p=0.03).

In supplementary table 6, they present an OR of 0.89, (95%CI 0.80-1.0) and do not present a p value (that I can easily see).

They also say that they have “Excluded certain infectious and parasitic diseases (A15-A23, A25-A48, A50-A99, B00-B64, B85-B97), eye infection (ICD-10-TM H10, H16, H44.0), Infective otitis externa (ICD-10-TM H60, H65, H66), endocarditis (ICD-10-TM I01, I33, I38, I39), acute upper respiratory infections (ICD-10-TM J00-J06), influenza, viral pneumonia, pneumonia due to Streptococcus pneumoniae, Haemophilus influenzae and other specified infectious organisms (ICD-10-TM J09-J14, J16), acute bronchitis and acute bronchiolitis (ICD-10-TM J20-J21), (acute) cholecystitis (ICD-10-TM K80, K81), urinary tract infection (ICD-10-TM N13.6, N15.1, N30, N39.0) and infection and inflammatory reaction due to other internal prosthetic devices, implants and grafts (ICD-10-TM T85.7)” that are not plausibly related to the intervention (boots and bottled water)

However, I think I am right to say that they do not seem to have excluded a variety of infections that it would be quite a stretch to say are prevented by boots and bottled water. These would appear to include bone and joint infections and fever “unspecified”, among others.

It appears that they are just keen to show “some” effect of the intervention.

My strong advice would be to delete this from the abstract; if they are determined to link their intervention to a reduction in infectious diseases admissions, please list the infections that they are saying HAVE been prevented by the boots and bottled water (which I would argue might be limited to skin and soft tissue infections of the feet and their complications and gastroenteritis). Then present the odds ratio for the reduction in the incidence of these diseases.

2. I really think they should delete all references to “clinical melioidosis” in the paper. I am cognisant of the challenges of obtaining a microbiological diagnosis in regional Thailand, but to the melioidosis audience (who will be the main readers of the paper), this just reduces the paper's credibility. Especially as the case-fatality rate in these 25 patients was 0%. Even in Australia’s well resourced health system with access to ICU and ECMO the case fatality rate of hospitalised patients is about 10%. This suggests that many - if not most - of these patients with “clinical melioidosis” don’t have melioidosis at all. The CFR in the confirmed cases in this cohort was 26%, which is similar to relevant studies from the literature.

Alternatively, the authors could produce a very interesting case series on how they managed to reduce the CFR to 0% in these clinical melioidosis patients. We’d be interested to know!

3. The authors have had a really good go at providing an intervention that will reduce the incidence of melioidosis. They are to be commended for their efforts and the work is a valuable addition to the melioidosis literature.

However, fundamentally this is a negative study. If they cannot show a benefit of the intervention in the controlled study environment, how would prevention strategies fare in the Real-World setting?

About 30% of the patients in the cohort had poor glycaemic control, so they are struggling with their diabetes management. Meanwhile, 27% of enrolled patients did not have the time/understanding/interest to attend the education session.

Delivering interventions to this population is obviously going to be challenging, yet this does not seem to have been acknowledged, rather “Stronger invitations for the intervention, modification or addition of the behaviour change techniques used, and more frequent intervention may be needed”.

I do not want to seem nihilistic, but I think given that despite the dedicated work of the study team, they could not show a benefit. Therefore I would think at least a sentence or two about the cost-effectiveness of melioidosis prevention at a population level would be appropriate. My back of the envelope calculations suggest that culture-confirmed melioidosis occurred in this cohort at a rate of 151/100,000/year. Would finite health Dollars/Baht be better spent on other public health strategies that address the social determinants of health, health literacy and access to care that affect not only melioidosis but other communicable and non-communicable diseases?

--------------------

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Reviewer #1: No

Figure 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. 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 us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

References

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article's retracted status in the References list and also include a citation and full reference for the retraction notice.

16 May 2021

Submitted filename: response BCT 2021 05 03_ND.docx

Click here for additional data file.

4 Jun 2021

Dear Dr. Limmathurotsakul,

We are pleased to inform you that your manuscript 'Effectiveness of a multifaceted prevention programme for melioidosis in diabetics (PREMEL): a stepped-wedge cluster-randomised controlled trial' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Yunn-Hwen Gan

Associate Editor

PLOS Neglected Tropical Diseases

Anna Ralph

Deputy Editor

PLOS Neglected Tropical Diseases

***********************************************************

18 Jun 2021

Dear Dr. Limmathurotsakul,

We are delighted to inform you that your manuscript, "Effectiveness of a multifaceted prevention programme for melioidosis in diabetics (PREMEL): a stepped-wedge cluster-randomised controlled trial," has been formally accepted for publication in PLOS Neglected Tropical Diseases.

We have now passed your article onto the PLOS Production Department who will complete the rest of the publication process. All authors will receive a confirmation email upon publication.

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Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Shaden Kamhawi

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Paul Brindley

co-Editor-in-Chief

PLOS Neglected Tropical Diseases