| Literature DB >> 29599974 |
Buddha Basnyat1,2,3, Maxine Caws4,5, Zarir Udwadia6.
Abstract
BACKGROUND: Tuberculosis (TB) remains the most common cause of infectious disease deaths worldwide. What is perhaps less appreciated is that the caseload of tuberculosis patients in South Asia is staggering.South Asia has almost 40% of the global TB burden with 4,028,165 cases in 2015. This region also has a disproportionate share of TB deaths (681,975 deaths, 38% of the global burden). Worldwide just 12.5% of TB cases are in HIV positive individuals, but much research and investment has focused on HIV-associated TB. Only 3.5% of patients with tuberculosis in South Asia have HIV co-infection. Not surprisingly with such a huge burden of disease, this region has an estimated 184,336 multi drug resistant (MDR) cases among notified TB cases which accounts for a third of global MDR burden. Crucially, at least 70% of the estimated MDR cases remain untreated in this region and MDR treatment success ranged from only 46% for India to 88% for Sri Lanka in the 2012 cohort that received treatment. This region represents many of the drivers of the modern TB epidemic: rapid urbanization and high density populations with dramatically rising incidence of diabetes, a burgeoning and largely unregulated private sector with escalating drug resistance and high air pollution both outdoor and household.Entities:
Keywords: Equity; Infectious disease; LMICs; Research priorities; Tuberculosis
Year: 2018 PMID: 29599974 PMCID: PMC5868053 DOI: 10.1186/s40248-018-0122-y
Source DB: PubMed Journal: Multidiscip Respir Med ISSN: 1828-695X
Tuberculosis in South Asia in 2015
| Country | TB Incidence (per 100,000 population) | Absolute number of new TB cases 2015 (N %) | HIV prevalence general populationa | Absolute number of TB cases in HIV infected individuals 2015 | Absolute number of MDR TB cases 2015 | Absolute number of deaths from TB 2015 |
|---|---|---|---|---|---|---|
| Afghanistan | 189 | 61,000 (1.5) | < 0.1 | 460 (0.3) | 3000 (1.63) | 12,170 (1.8) |
| Bangladesh | 225 | 362,000 (9.0) | < 0.1 | 630 (0.4) | 9700 (5.3) | 73,230 (10.7) |
| Bhutan | 155 | 975 (0.02) | No estimate | 6 (0.004) | 37 (2.0) | 144 (0.02) |
| India | 217 | 2,840,000 (70.5) | 0.3 | 113,000 (79.7) | 130,000 (70.5) | 517,000 (75.8) |
| Nepal | 156 | 44,000 (1.1) | 0.2 | 1900 (1.3) | 1500 (0.8) | 1900 (0.3) |
| Maldives | 53 | 190 (0.004) | No estimate | 0 (0) | 10 (0.005) | 20 (0.003) |
| Myanmar | 365 | 197,000 (4.9) | 0.8 | 17,000 (12.0) | 14,000 (7.6) | 27,000 (4.0) |
| Pakistan | 270 | 510,000 (12.7) | 0.1 | 8800 (6.2) | 26,000 (14.1) | 45,600 (6.7) |
| Sri Lanka | 65 | 13,000 (0.3) | < 0.1 | 43 (0.03) | 89 (0.05) | 1211 (0.2) |
| South Asia Total | 4,028,165 (100) | 141,839 (100) | 184,336 (100) | 681,975 (100) |
aAdults aged 15–49. Source UNAIDS data. Available at: http://aidsinfo.unaids.org/
Fig. 1Tuberculosis in South Asia
GeneXpert availability in countries of South Asia as of 31st December 2016(http://apps.who.int/tb/laboratory/xpertmap/)
| Country | No of Xpert modules procured | Total population (thousands, 2016)a | Modules per 100, 000 population | No. of Xpert cartridges procured |
|---|---|---|---|---|
| Afghanistan | 42 | 34,656.03 | 0.12 | 10,770 |
| Bangladesh | 424 | 162,951.56 | 0.26 | 381,210 |
| Bhutan | 12 | 797.76 | 1.23 | 2600 |
| India | 3000 | 1,324,171.35 | 0.23 | 2,134,760 |
| Maldives | 4 | 417.49 | 0.96 | 500 |
| Myanmar | 416 | 52,885.22 | 0.79 | 340,370 |
| Nepal | 143 | 28,982.77 | 0.49 | 136,170 |
| Pakistan | 1012 | 193,203.48 | 0.52 | 525,500 |
| Sri Lanka | 62 | 21,203.00 | 0.29 | 13,100 |
| Total | 5115 | 1,819,268.66 | 0.28 | n/a |
aSource: UN population division: https://esa.un.org/unpd/wpp/
Research priorities for TB in South Asia
| Theme | Priority Research areas | AIMS |
|---|---|---|
| Diagnosis | ||
| Engaging the public sector to capture notifications and ensure treatment quality | Understanding components of successful Public Private Mix(PPM) models and resources needed for national scale-up | |
| Optimal algorithms and implementation behaviour | Improving application of optimal diagnostic algorithms. | |
| Facilitators and barriers to diagnostic access | Removing access barriers for TB diagnosis in underserved populations | |
| Childhood TB | Access to TB diagnosis for all children at risk | |
| Targeting Active Case Finding (ACF) | Understanding how to target ACF activities to maximise yield for minimal resources. | |
| Mobile health applications for TB | Minimising loss to follow up in diagnostic pathway and maximising outreach of novel diagnostics. Eg. Remote Chest Xray reading. | |
| Scale up of Drug Susceptibility Testing(DST) availability | Increasing access to full drug susceptibility testing through molecular scale-up and improving culture facilities in underserved populations. | |
| Integrating TB and diabetes | Understanding risk factors for TB among diabetic patients and optimal implementation of TB screening. | |
| Treatment | ||
| Increasing Randomized Controlled Trial (RCT) capacity | Develop regional network and ability to systematically evaluate multiple regimens in adequately powered trials. | |
| Treatment of drug resistant TB, including INH mono-resistance, Multidrug Resistance(MDR) and Extensively Drug Resistance (XDR) TB. | Programme of trials to systematically answer locally relevant questions, including both alternative regimens and treatment delivery strategies | |
| Theoretical and practical studies to understand consequences of different approaches to novel drug roll-out | Optimising novel drug implementation in terms of negative outcomes averted and preventing emergence of resistance. | |
| Increasing drug resistance surveillance | Evaluating strategies applying molecular technology to increase monitoring of drug resistance prevalence and emergence | |
| Systematic evaluation of variation in pharmacokinetics and pharmacodynamics | Dose optimisation for existing drugs in adults and children to maximise efficacy, minimise adverse events and prevent resistance. | |
| Adverse drug events | Understanding susceptibility risk, improved detection and management of Adverse Events (AEs) and development of personalised regimens to avoid AEs. | |
| Retreatment regimen in non-MDR cases | Retreatment regimens that are economically feasible and effective allowing abolition of the currently failing ‘category 2’ retreatment regimen. | |
| Mobile health for Video Directly Observed Therapy (V-DOTS) and adherence | Alternative strategies for treatment monitoring to increase compliance while minimising costs and disruption to the patient. | |
| Optimal treatment of TB in diabetic patients. | Evidence base for optimal treatment and case management of TB in diabetic patients. | |
| Prevention | ||
| Correlates of immunity | Understanding of components of a protective immune response for vaccine development. | |
| Standardising implementation of basic infection control in health care facilities regionwide | Development of evidence- based recommendations for minimal infection control standards in regional health care facilities. | |
| Targeted prophylactic therapy | Evidence base for risk:benefit of scale-up of prophylactic treatment in different population groups. | |
| Strengthening health systems resilience | Contingency measures for natural or political upheavals leading to person displacement or infrastructure loss | |
| Heterogeneity of risk in populations | Understanding molecular epidemiology of TB susceptibility and transmission in both dispersed rural and high density urban populations. Optimal targeting of TB control activities to appropriate risk groups. | |
| Risk of active TB in latently infected individuals | Biomarkers and social factors influencing risk for latently infected individuals developing active TB to optimise targeted prophylaxis. | |
| Host:pathogen interaction in susceptibility and transmission | Integrated analysis of host and pathogen genomes to understand complex interplay of host susceptibility and pathogen virulence. | |