A Multicenter Cost-of-Illness and Long-term Socioeconomic Follow-up Study in the Severe Typhoid Fever in Africa Program: Study Protocol. (30th October 2019)

• Record Type: Journal Article
• Authors: Ramani, Enusa; Park, Seeun; Toy, Trevor; Panzner, Ursula; Mogeni, Ondari D; Im, Justin; Cruz Espinoza, Ligia Maria; Jeon, Hyon Jin; Pak, Gi Deok; Seo, Hyeongwon; Chon, Yun; Rakotozandrindrainy, Raphaël; Owusu-Dabo, Ellis; Osei, Isaac; Soura, Abdramane Bassiahi; Teferi, Mekonnen; Marks, Florian; Mogasale, Vittal
• Is Part Of: Clinical infectious diseases. Volume 69(2019)Supplement 6
• Page Start: S459
• Page End: S465
• Publication Date: 2019-10-30
• Subjects: cost of illness -- socioeconomics -- enteric fever -- typhoid fever -- Africa; Communicable diseases -- Periodicals; 616.905
• DOI: 10.1093/cid/ciz608
• Languages: English
• ISSNs: 1058-4838

Abstract

Abstract: Background: There are limited data on typhoid fever cost of illness (COI) and economic impact from Africa. Health economic data are essential for measuring the cost-effectiveness of vaccination or other disease control interventions. Here, we describe the protocol and methods for conducting the health economic studies under the Severe Typhoid Fever in Africa (SETA) program. Methods: The SETA health economic studies will rely on the platform for SETA typhoid surveillance in 4 African countries—Burkina Faso, Ethiopia, Ghana, and Madagascar. A COI and long-term socioeconomic study (LT-SES) will be its components. The COI will be assessed among blood culture–positive typhoid fever cases, blood culture–negative clinically suspected cases (clinical cases), and typhoid fever cases with pathognomonic gastrointestinal perforations (special cases). Repeated surveys using pretested questionnaires will be used to measure out-of-pocket expenses, quality of life, and the long-term socioeconomic impact. The cost of resources consumed for diagnosis and treatment will be collected at health facilities. Results: Results from these studies will be published in peer-reviewed journals and presented at scientific conferences to make the data available to the wider health economics and public health research communities. Conclusions: The health economic data will be analyzed to estimate the average cost per case, the quality of life at different stages of illness, financial stress due to illness, and the burden on the family due to caregiving during illness. The data generated are expected to be used in economic analysis and policy making on typhoid control interventions in sub-Saharan Africa.