Examining Approaches to Estimate the Prevalence of Catastrophic Costs Due to Tuberculosis from Small-Scale Studies in South Africa

Sedona Sweeney (), Anna Vassall, Lorna Guinness, Mariana Siapka, Natsayi Chimbindi, Don Mudzengi and Gabriela B. Gomez
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Sedona Sweeney: London School of Hygiene & Tropical Medicine
Anna Vassall: London School of Hygiene & Tropical Medicine
Lorna Guinness: London School of Hygiene & Tropical Medicine
Mariana Siapka: London School of Hygiene & Tropical Medicine
Natsayi Chimbindi: Africa Health Research Institute
Don Mudzengi: The Aurum Institute
Gabriela B. Gomez: London School of Hygiene & Tropical Medicine

PharmacoEconomics, 2020, vol. 38, issue 6, No 7, 619-631

Abstract: Abstract Background and Objective In context of the End TB goal of zero tuberculosis (TB)-affected households encountering catastrophic costs due to TB by 2020, the estimation of national prevalence of catastrophic costs due to TB is a priority to inform programme design. We explore approaches to estimate the national prevalence of catastrophic costs due to TB from existing datasets as an alternative to nationally representative surveys. Methods We obtained, standardized and merged three patient-level datasets from existing studies on patient-incurred costs due to TB in South Africa. A deterministic cohort model was developed with the aim of estimating the national prevalence of catastrophic costs, using national data on the prevalence of TB and likelihood of loss to follow-up by income quintile and HIV status. Two approaches were tested to parameterize the model with existing cost data. First, a meta-analysis summarized study-level data by HIV status and income quintile. Second, a regression analysis of patient-level data also included employment status, education level and urbanicity. We summarized findings by type of cost and examined uncertainty around resulting estimates. Results Overall, the median prevalence of catastrophic costs for the meta-analysis and regression approaches were 11% (interquartile range [IQR] 9–13%) and 6% (IQR 5–8%), respectively. Both approaches indicated that the main burden of catastrophic costs falls on the poorest households. An individual-level regression analysis produced lower uncertainty around estimates than a study-level meta-analysis. Conclusions This paper presents a novel application of existing data to estimate the national prevalence of catastrophic costs due to TB. This type of model could be useful for researchers and policy makers looking to inform certain policy decisions; however, some uncertainties remain due to limitations in data availability. There is an urgent need for standardized reporting of cost data and improved guidance on methods to collect income data to improve these estimates going forward.

Date: 2020
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DOI: 10.1007/s40273-020-00898-3

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