Impact evaluation of patient/pharmacy incentives for malaria care in Kenyan pharmacies
Lia Fernald, Professor
Public Health
Closed. This professor is continuing with Spring 2024 apprentices on this project; no new apprentices needed for Fall 2024.
In Kenya, over 70% of the population is at risk of malaria, with the areas around Lake Victoria and on the coast presenting the highest risk, and children under age 5 and pregnant women being most vulnerable to infection. Over half of malaria patients access treatment via pharmacies, which are often the preferred access point for primary care. Availability of malaria treatment in these sites is largely due to ACT subsidies via an initiative to provide manufacturer incentives to lower prices for patients to less than $1/treatment. This subsidy has had a large positive impact but has also led to high levels of overuse. High quality diagnostic tests for malaria are available, but most cases are not diagnosed prior to being treated. Given that pharmacies play a crucial role in providing access to malaria treatment in Kenya, it is essential that they provide appropriate diagnostic testing and low-cost, effective and appropriate medicines for treatment.
Role: This project uses data from two sources: 1) health care product purchase data from pharmacies, and 2) survey data from pharmacy staff surveys and patient surveys.
Students working on this project will receive training in econometric and epidemiologic data analysis, use of administrative and survey data, and develop an understanding of clinical guidelines for infectious diseases.
Tasks:
- Clean and analyze data
- Produce data visualizations and reproducible tables and figures
- Review medical, epidemiological, and health economics literature related to malaria care, performance incentives, and subsidies for health care
Qualifications: experience with statistical software required (R and Stata preferred, Python accepted, experience in SQL is a plus), desire to pursue graduate school in public health, economics, public policy or data science a plus.
Day-to-day supervisor for this project: Maria Deici, Ph.D. candidate
Hours: to be negotiated
Off-Campus Research Site: Remote work can be considered
Social Sciences Biological & Health Sciences