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Estimating the Impact of Tuberculosis Case Detection in Constrained Health Systems: An Example of Case-Finding in South Africa.
Sumner, Thomas; Bozzani, Fiammetta; Mudzengi, Don; Hippner, Piotr; Houben, Rein M; Cardenas, Vicky; Vassall, Anna; White, Richard G.
Afiliação
  • Sumner T; TB Modelling Group, TB Centre, Centre for the Mathematical Modelling of Infectious Disease, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Bozzani F; Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Mudzengi D; Aurum Institute, Johannesburg, South Africa.
  • Hippner P; Aurum Institute, Johannesburg, South Africa.
  • Houben RM; TB Modelling Group, TB Centre, Centre for the Mathematical Modelling of Infectious Disease, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Cardenas V; Aurum Institute, Johannesburg, South Africa.
  • Vassall A; Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • White RG; TB Modelling Group, TB Centre, Centre for the Mathematical Modelling of Infectious Disease, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Am J Epidemiol ; 188(6): 1155-1164, 2019 06 01.
Article em En | MEDLINE | ID: mdl-30824911
ABSTRACT
Mathematical models are increasingly being used to compare strategies for tuberculosis (TB) control and inform policy decisions. Models often do not consider financial and other constraints on implementation and may overestimate the impact that can be achieved. We developed a pragmatic approach for incorporating resource constraints into mathematical models of TB. Using a TB transmission model calibrated for South Africa, we estimated the epidemiologic impact and resource requirements (financial, human resource (HR), and diagnostic) of 9 case-finding interventions. We compared the model-estimated resources with scenarios of future resource availability and estimated the impact of interventions under these constraints. Without constraints, symptom screening in public health clinics and among persons receiving care for human immunodeficiency virus infection was predicted to lead to larger reductions in TB incidence (9.5% (2.5th-97.5th percentile range (PR), 8.6-12.2) and 14.5% (2.5th-97.5th PR, 12.2-16.3), respectively) than improved adherence to diagnostic guidelines (2.7%; 2.5th-97.5th PR, 1.6-4.1). However, symptom screening required large increases in resources, exceeding future HR capacity. Even under our most optimistic HR scenario, the reduction in TB incidence from clinic symptom screening was 0.2%-0.9%-less than that of improved adherence to diagnostic guidelines. Ignoring resource constraints may result in incorrect conclusions about an intervention's impact and may lead to suboptimal policy decisions. Models used for decision-making should consider resource constraints.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Busca de Comunicante Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Busca de Comunicante Idioma: En Ano de publicação: 2019 Tipo de documento: Article