Evidence map›Paper›PMID 32239479›Full record

ArticlePharmacoEconomics2020

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, Gabriela B Gomez

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Article in PharmacoEconomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Sedona SweeneyDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, Room 327, 15-17 Tavistock Place, London, WC1H 9SH, UK. sedona.sweeney@lshtm.ac.uk.ORCID 0000-0003-4233-9080
Anna VassallDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, Room 327, 15-17 Tavistock Place, London, WC1H 9SH, UK.
Lorna GuinnessDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, Room 327, 15-17 Tavistock Place, London, WC1H 9SH, UK.
Mariana SiapkaDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, Room 327, 15-17 Tavistock Place, London, WC1H 9SH, UK.
Natsayi ChimbindiAfrica Health Research Institute, Durban, South Africa.
Don MudzengiThe Aurum Institute, Johannesburg, South Africa.
Gabriela B GomezDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, Room 327, 15-17 Tavistock Place, London, WC1H 9SH, UK.

Funding

Bill & Melinda Gates Foundation OPP1109722Wellcome Trust 201433
6 · The paper itself

Abstract

BACKGROUND AND

objectiveIn 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.

methodsWe 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.

resultsOverall, 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.

conclusionsThis 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.

Indexed as

Models, EconomicAdultCatastrophic IllnessCohort StudiesCost of IllnessDatasets as TopicFemaleHealth Care CostsHumansIncomeMaleMiddle AgedPolicy MakingPrevalenceSouth AfricaTuberculosis

Identifiers

PMID32239479
PMCPMC7307451

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