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Inadequate water access is central to the experience of urban inequality across low- and middle-income countries and leads to adverse health and social outcomes. Previous literature on water inequality in Mumbai, India’s second largest city, offers diverse explanations for water disparities between and within slums.((1)) This study provides new insights on water disparities in Mumbai’s slums by evaluating the influence of legal status on water access. We analyzed data from 593 households in Mandala, a slum with legally recognized (notified) and unrecognized (non-notified) neighborhoods. Relative to households in a notified neighborhood, households in a non-notified neighborhood suffered disadvantages in water infrastructure, accessibility, reliability, and spending. Non-notified households used significantly fewer liters per capita per day of water, even after controlling for religion and socioeconomic status. Our findings suggest that legal exclusion may be a central driver of water inequality. Extending legal recognition to excluded slum settlements, neighborhoods, and households could be a powerful intervention for reducing urban water inequality.

BackgroundIndia has the highest burden of tuberculosis (TB), accounting for more than one-quarter of people with active TB and nearly one-third of TB deaths globally. Most people contracting active TB in India do not successfully navigate all stages of the care cascade to receive treatment and achieve TB recurrence-free survival. Understanding reasons for losses across the care cascade is critical to improve outcomes. In this paper, guided by a PECO (population/exposure/comparison/outcome) framework, we describe quantitative findings of a systematic review aimed at identifying factors contributing to unfavorable outcomes experienced by people with TB at each care cascade gap in India.Methods and findingsWe defined care cascade gaps as comprising people with confirmed or presumptive TB who did not: start the TB diagnostic workup (Gap 1), complete the diagnostic workup (Gap 2), start treatment (Gap 3), achieve treatment success (Gap 4), or achieve TB recurrence-free survival (Gap 5). Three systematic searches were conducted to identify 147 unique articles published from 2000 to 2021 that evaluated factors associated with unfavorable outcomes for each gap (reported as odds, relative risk, or hazard ratios) and, among people experiencing unfavorable outcomes, reasons reported for these outcomes (reported as proportions). Findings were organized into patient-, family-, society-, or health system-related factors, using a social-ecological framework.Some factors were common and associated with unfavorable outcomes across multiple care cascade stages. These included male sex, older age (variably defined across studies), a broad array of poverty-related factors, lower symptom severity or duration, undernutrition, alcohol use, smoking, and distrust of (or dissatisfaction with) local government health services. People who had been previously treated for TB were more likely to seek care and engage in the TB diagnostic workup (Gaps 1 and 2) but were also more likely to suffer pretreatment loss to follow-up (Gap 3) and unfavorable outcomes during TB treatment (Gap 4), especially those who had been lost to follow-up during their prior treatment episode.For individual care cascade gaps, multiple studies highlighted the importance of lack of TB knowledge and structural barriers to care (e.g., transport or financial challenges in reaching clinics) in contributing to lack of care-seeking for TB symptoms (Gap 1, 15 studies or analyses); lack of access to diagnostics (e.g., chest X-ray), non-identification of eligible patients for testing, and failure of providers to communicate concern for TB to patients in contributing to non-completion of the diagnostic workup (Gap 2, 20 studies or analyses); TB stigma, poor recording of patient contact information by providers, and early death due to diagnostic delays in contributing to pretreatment loss to follow-up (Gap 3, 25 studies); and medication adverse effects, TB stigma, and lack of TB knowledge in contributing to unfavorable treatment outcomes (Gap 4, 104 studies). Medication nonadherence contributed to unfavorable treatment outcomes (Gap 4) and post-treatment TB recurrence (Gap 5, 15 studies).ConclusionsThis extensive systematic review illuminates common patterns of risk that shape outcomes for people with TB in India, while also highlighting gaps in knowledge, particularly with regard to TB care for children or in the private sector, that can help to guide future research. These findings may help inform targeting of additional support services to people with TB who are at higher risk of poor outcomes and inform development of multi-component interventions to close gaps in India’s TB care cascade.Author SummaryWhy was this study done?India has the highest burden of tuberculosis (TB), accounting for more than one-quarter of people with active TB and nearly one-third of TB deaths globally.Of the nearly 3 million people contracting active TB every year in India, most do not successfully traverse all stages of the care needed to receive TB treatment and achieve an optimal long-term outcome, and serial losses of people with TB across these stages is often referred to as the “cascade of care.”Understanding risk factors among people with active or presumptive TB that contribute to losses from care, and why these losses occur, is crucial to inform the development of targeted interventions to prevent them from experiencing unfavorable outcomes.What did the researchers do and find?To understand reasons why people with TB are lost from care in India, we conducted three systematic searches of the medical literature to identify 147 unique and relevant articles published from 2000 to 2021.We extracted information from these studies on risk factors for unfavorable outcomes at each care cascade gap, as well as reasons reported by people with TB who experienced unfavorable outcomes and were surveyed by researchers.Some barriers to care or characteristics of people with TB contributed to losses at multiple stages of the care cascade, including male sex, older age, poverty-related factors, history of previous TB treatment, lower symptom severity or duration, undernutrition, alcohol use, smoking, and distrust of (or dissatisfaction with) local government health services.Other barriers contributed more substantially to individual care cascade gaps: lack of TB knowledge and structural barriers to care (e.g., transport barriers to clinics) contributed to lack of care-seeking for TB symptoms (Gap 1); poor accessibility of diagnostic testing, non-identification of eligible patients for testing, and failure of providers to communicate concern for TB to patients contributed to non-completion of the TB diagnostic workup (Gap 2); early death due to delays in diagnosis, TB stigma, and poor recording of patient contact information by healthcare providers contributed to losses of diagnosed patients before they started treatment (Gap 3); medication adverse effects, TB stigma, and lack of TB knowledge contributed to unfavorable TB treatment outcomes (Gap 4); and medication nonadherence contributed to unfavorable treatment outcomes and post-treatment TB recurrence (Gaps 4 and 5).What do these findings mean?The reasons for losses of people with TB across the care cascade are complex, vary by care cascade gap, and involve a mix of patient- and health system-related barriers.Given the complexity of the barriers contributing to unfavorable outcomes in India’s TB care cascade, future implementation interventions should consider involving multiple components that target different challenges faced by patients and the health system.In addition, India’s TB program and those in other high incidence settings should target additional services to people with TB who are at higher risk of experiencing poor outcomes.

Background Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures. Methods We enrolled adult Indians with drug-susceptible tuberculosis who were monitored using 99DOTS, a cellphone-based technology. During an unannounced home visit with each participant, we assessed adherence using a pill estimate, four-day dose recall, a last missed dose question, and urine isoniazid metabolite testing. We estimated the area under the receiver operating characteristic curve (AUC) for each alternate measure in comparison to urine testing. 99DOTS data were analyzed using patient-reported doses alone and patient- and provider-reported doses, the latter reflecting how 99DOTS is implemented in practice. We assessed each measure’s operating characteristics, with particular interest in specificity—i.e., the percentage of participants detected as being nonadherent by each alternate measure, among those who were nonadherent by urine testing. Results Compared to urine testing, alternate measures had the following characteristics: 99DOTS patient-reported doses alone (AUC 0.65, specificity 70%, 95%CI:58—81%), 99DOTS patient- and provider-reported doses (AUC 0.61, specificity 33%, 95%CI: 22—45%), pill estimate (AUC 0.55, specificity 21%, 95%CI:12—32%), four-day recall (AUC 0.60, specificity 23%, 95%CI: 14—34%), and last missed dose question (AUC 0.65, specificity 52%, 95%CI:40—63%). Conclusions Alternate measures missed detecting at least 30% of people who were nonadherent by urine testing. The last missed dose question performed similarly to 99DOTS using patient-reported doses alone. Tuberculosis programs should evaluate the feasibility of integrating more accurate, objective measures, such as urine testing, into routine care.

Background Poor adherence to tuberculosis (TB) treatment is associated with disease recurrence and death. Little research has been conducted in India to understand TB medication nonadherence. Methods We enrolled adult drug-susceptible TB patients, approximately half of whom were people with human immunodeficiency virus (PWH), in Chennai, Vellore, and Mumbai. We conducted a single unannounced home visit to administer a survey assessing reasons for nonadherence and collect a urine sample that was tested for isoniazid content. We described patient-reported reasons for nonadherence and identified factors associated with nonadherence (ie, negative urine test) using multivariable logistic regression. We also assessed the association between nonadherence and treatment outcomes. Results Of 650 participants in the cohort, 77 (11.8%) had a negative urine test. Nonadherence was independently associated with daily wage labor (adjusted odds ratio [aOR], 2.7; confidence interval [CI], 1.1–6.5; P = .03), the late continuation treatment phase (aOR, 2.0; CI, 1.1–3.9; P = .03), smear-positive pulmonary disease (aOR, 2.1; CI, 1.1–3.9; P = .03), alcohol use (aOR, 2.5; CI, 1.2–5.2; P = .01), and spending ≥30 minutes collecting medication refills (aOR, 6.6; CI, 1.5–29.5; P = .01). People with HIV reported greater barriers to collecting medications than non-PWH. Among 167 patients reporting missing doses, reported reasons included traveling from home, forgetting, feeling depressed, and running out of pills. The odds of unfavorable treatment outcomes were 4.0 (CI, 2.1–7.6) times higher among patients with nonadherence (P < .0001). Conclusion Addressing structural and psychosocial barriers will be critical to improve TB treatment adherence in India. Urine isoniazid testing may help identify nonadherent patients to facilitate early intervention during treatment., We evaluated adherence to tuberculosis medications in 650 Indian patients by conducting urine isoniazid tests collected during unannounced home visits. Structural barriers to collecting medication refills and psychosocial barriers emerged as the most important factors contributing to medication nonadherence.