Implementation Science to optimize malaria vector control and disease management
The central objective of this proposal is to improve malaria control outcomes through an implementation science approach that integrates health delivery experiments and decision support modeling to promote joint optimization of vector control and disease management strategies.
We propose three specific aims: (1) perform randomized experiments of vector control and disease management strategies in Tanzania to elucidate which intervention strategy combinations are most effective in real world settings, using an implementation science approach; (2) use analytical insights from the health delivery experiments to refine an existing decision support model that includes both vector control and disease management; and (3) develop approaches for replicating the decision support tool in other parts of Tanzania and other countries in sub-Saharan Africa.
Accomplishing these combined specific aims will provide a framework for designing and implementing multi-pronged malaria control strategies that have the best chances for sustained effectiveness in an operational setting. We will test the effectiveness of different combinations of vector and disease management interventions over time based on field experiments. We will then use the experimental results in conjunction with decision support modeling to improve a new tool that will allow decision-makers to jointly optimize vector and disease management strategies. The tool is flexible enough to incorporate new therapies and interventions as they are developed.
Malaria is one of the greatest health challenges facing the developing world. World Health Organization data indicate that malaria causes over 1 million deaths per year, with over 90% of those deaths occurring in sub-Saharan Africa. A number of strategies are available to prevent malaria, including the use of insecticide treated nets and indoor residual spraying for vector control and a variety of diagnostic strategies and drug therapies for both prophylaxis and treatment. However, it is often difficult for decision-makers to determine the best combination of interventions, given the constraints within local health care delivery systems, as well as in vector control infrastructure.
This proposal has been developed in a collaborative process with critical partners in Tanzania and, thus, leverages an active and vibrant set of professional relationships. Through these in-country partnerships, we have direct access to key decision-makers at both the local and national levels. In addition, our previous work across Africa provides a strong platform from which to launch future replication in areas beyond the primary study site.
This project will evaluate two malaria control interventions in Mvomero District, Tanzania: (1) a disease management strategy involving early detection and treatment by community health workers using rapid diagnostic technology; and (2) vector control through community-supported larviciding.
Six study villages were assigned to each of four groups (control, early detection and treatment, larviciding, and early detection and treatment plus larviciding). The primary endpoint of interest was change in malaria infection prevalence across the intervention groups measured during annual longitudinal cross-sectional surveys. Recurring entomological surveying, household surveying, and focus group discussions will provide additional valuable insights.