The following initiatives comprise the foundation of the proposed research agenda. We aim for research findings to be translated into policy recommendations with measurable outcomes for evaluation.
Measuring the impact of global health aid on child health
This initiative examines the causal relationship between child health aid and under-five child mortality rates globally. The research is conducted on the basis of a conceptual framework which combines child survival models in demography with health care production models in economics. It is funded by the National Institute of Child Health & Human Development.
Understanding the impact of community-based health financing approach on
achieving universal health care
We conduct a systematic and comprehensive investigation on the current practice of community-based health insurance program in developing countries, such as Rwanda. We evaluate its impact on medical care utilization and household catastrophic health spending. The initiative is partially funded by the Doris Duke Charitable Foundation.
Tracking health facility financing data effectively in resource-poor settings
High quality financing data is important for resource-poor settings where scarce resources must be allocated equitably and efficiently. This study explores an effective financing data tracking method that has been applied in two districts of Rwanda. Survey instruments and estimation protocols are developed. Effectiveness of data collection method is examined. The initiative is funded by the Doris Duke Charitable Foundation.
The effectiveness of community approach in improving child nutrition in Rwanda
We conduct a country case study in Rwanda on how to use community-health insurance, a program that has been adopted in many developing countries for achieving universal health coverage, to effectively address the financial sustainability of child nutrition programs. Evidence-based research will help policy makers to optimize the allocation of scarce resources and enhance cross-country learning. This is funded by the Charles Hood Foundation.
A longitudinal study about the effect of practicing Yan Xin Qigong on medical care cost with medical claims data
We use seven-year longitudinal medical claims data and statistical models to study the relationship between practicing Yan Xin Qigong (YXQG), a traditional advanced Chinese Qigong that has been integrated with modern science and technology, and practitioners’ medical care utilization and the associated costs. Measuring economic impact of traditional medicine adds value to ongoing scientific research in the area.
Effects of survey design and implementation on estimating universal financial risk protection using household surveys in developing countries
This study addresses a methodological issue in measuring universal financial risk protection when using household survey data in developing countries: the effect of survey design (non-sampling errors) and implementation (sampling errors) on estimates. This is funded by a Seed Grant from the Harvard Center for Population and Development Studies.
Assessing economic burden of disease and economic value of health care
We develop analytical frameworks to assess the economic burden of disease and economic benefits of health care. Our empirical work is currently focused on five local projects and one global study:
- mental disorders in China;
- HIV treatment and nutritional supplementation in Haiti;
- treatment of Buruli ulcer in Cameroon;
- comprehensive health system strengthening in Rwanda and Madagascar; and
- the burden of vector-borne and parasitic diseases on the distribution of income.
The projects are funded by the Fogarty International Center (NIH), the Doris Duke Charitable Foundation, the James S. McDonnell Foundation, and the Jim and Robin Herrnstein Foundation.
Generating new frameworks for modeling interactions between infectious diseases and economics
This work is based on the integration of a range of mathematical methods developed by epidemiologists, infectious disease ecologists, mathematicians, and economists. These models are applied to data from health care initiatives from the sites where we work. This work is funded by the Fogarty International Center (NIH), the James S. McDonnell Foundation, and the National Science Foundation.