Modelling the impact of social protection on tuberculosis: the S-PROTECT project

Boccia, Delia; Rudgard, William E.; Shrestha, Sourya; Lönnroth, Knut; Eckhoff, Philip A.; Golub, Jonathan E.; Sanchez, Mauro Niskier; Maciel, Ethel Leonor Nóia; Rasella, Davide; Shete, Priya B.; Pedrazzoli, Debora; Houben, Rein M. G. J.; Chang, Stewart T.; Dowdy, David W.

doi:10.1186/s12889-018-5539-x

Cited by 21 publications

(21 citation statements)

References 34 publications

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“…The Social PROTection to Enhance the Control of Tuberculosis (S-PROTECT) group has developed a generalizable mathematical model to study the impact of social protection initiatives on national TB burden by improving nutrition. 53 The S-PROTECT model uses published data to look at the impact of cash transfers on intermediary factors such as socioeconomic situation, health service access, and food security, and in turn the impact of these factors on proximal determinants of health including undernutrition. Finally, it accounts for the impact of improved nutrition on TB progression, diagnosis, and treatment success.…”

Section: Catalyzing Policy Change and Improving Implementationmentioning

confidence: 99%

Food for thought: addressing undernutrition to end tuberculosis

Sinha

Lönnroth

Bhargava

et al. 2021

The Lancet Infectious Diseases

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Tuberculosis (TB) remains the leading infectious killer worldwide. The World Health Organization's (WHO) End-TB strategy is falling short of the 2020 mileposts in several domains. Undernutrition remains the leading population-level risk factor for TB. Studies have consistently found that undernutrition is associated with increased TB incidence, increased severity, worse treatment outcomes, and increased mortality. Modeling studies support implementing nutritional interventions for persons living with TB (PLWTB) and those at risk of TB disease to ensure the success of the End-TB strategy. In this Personal Views essay, we highlight nutrition-related immunocompromise, implications of undernutrition for TB treatment and prevention, the role of nutritional supplementation, pharmacokinetics and pharmacodynamics of antimycobacterial

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Section: Catalyzing Policy Change and Improving Implementationmentioning

confidence: 99%

Food for thought: addressing undernutrition to end tuberculosis

Sinha

Lönnroth

Bhargava

et al. 2021

The Lancet Infectious Diseases

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“…India’s recent National Strategic Plan underlines the potential importance of ACF in risk groups such as urban slums 16 , while recent work in Viet Nam has also demonstrated the potential value of screening close contacts of diagnosed TB cases, together with longitudinal followup of these contacts 35 . However, it is also possible for the patient delay to be impacted by measures to improve the demand for TB services; for example, social protection mechanisms 36 could have the secondary effects of encouraging TB symptomatics to come forward for care 37 . Such effects are currently hypothetical, and present an important evidence gap for future studies to address.…”

Section: Discussionmentioning

confidence: 99%

Modelling the impact of effective private provider engagement on tuberculosis control in urban India

Arinaminpathy

Deo

Singh

et al. 2019

Sci Rep

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In India, the country with the world’s largest burden of tuberculosis (TB), most patients first seek care in the private healthcare sector, which is fragmented and unregulated. Ongoing initiatives are demonstrating effective approaches for engaging with this sector, and form a central part of India’s recent National Strategic Plan: here we aimed to address their potential impact on TB transmission in urban settings, when taken to scale. We developed a mathematical model of TB transmission dynamics, calibrated to urban populations in Mumbai and Patna, two major cities in India where pilot interventions are currently ongoing. We found that, when taken to sufficient scale to capture 75% of patient-provider interactions, the intervention could reduce incidence by upto 21.3% (95% Bayesian credible interval (CrI) 13.0–32.5%) and 15.8% (95% CrI 7.8–28.2%) in Mumbai and Patna respectively, between 2018 and 2025. There is a stronger impact on TB mortality, with a reduction of up to 38.1% (95% CrI 20.0–55.1%) in the example of Mumbai. The incidence impact of this intervention alone may be limited by the amount of transmission that has already occurred by the time a patient first presents for care: model estimates suggest an initial patient delay of 4–5 months before first seeking care, followed by a diagnostic delay of 1–2 months before ultimately initiating TB treatment. Our results suggest that the transmission impact of such interventions could be maximised by additional measures to encourage early uptake of TB services.

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“…Наиболее распространенными моделями, в которых использовались социальноэкономические факторы риска, были сравнительные модели динамической передачи ТБ среди населения и нединамические аналитические модели. Большинство исследований включали концептуальную основу для иллюстрации механики моделей и гипотез, лежащих в основе их исследовательских вопросов, и отражали основную особенность туберкулеза по сравнению с острыми инфекционными заболеваниями -наличие длительного латентного периода [38][39][40].…”

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