Since the late 1980s, a series of Plasmodium falciparum malaria epidemics have occurred in the highlands of African countries. The current pattern of malaria in the highlands exhibits the characteristics of an expanded geographic area, increased frequency, and increased fatality rates. What has caused the more frequent and more widespread malaria epidemics since the late 1980s in African highlands? Can we forecast when and where an epidemic will occur so that appropriate actions can be taken in advance to reduce morbidity and mortality? How can we maximize the efficacy and cost-effectiveness of vector control to reduce malaria transmission and incidence in the highlands? These questions are not only of scientific interest, but they are also of paramount importance for malaria control. The long-term objectives of this research are to determine the mechanisms of malaria epidemics in African highlands, and to develop efficient vector control methods for epidemic malaria control. In the previous period of support, we made significant progress elucidating the effects of land use and land cover on malaria transmission in African highlands. We proposed the climate- landscape hypothesis as a leading mechanism for the emergence of epidemic malaria in African highlands. This competing renewal application will test the climate-landscape hypothesis using epidemiological, entomological, and molecular population genetics data in western Kenya highlands. The project will use community-based longitudinal cohort studies as a central platform for the following three inter-related specific aims. First, we will develop models for malaria dynamics and epidemics forecasting in the highlands and determine the accuracy and sensitivity of the models using prospective climate and malaria incidence data. Second, we will determine the effects of landscape factors on the spread of malaria infections and identify transmission hotspots for targeted malaria vector control. Third, we will assess the impact of mosquito vector control targeted at transmission hotspots on rates of malaria transmission, infection incidence, and clinical malaria occurrence. This project will achieve the following goals: a) reveal critical parameters needed for the development of malaria early warning systems in African highlands, b) significantly enhance our understanding of the relationships between climate, landscape, and the transmission dynamics of malaria, and c) facilitate the development of cost-effective malaria vector control methods. We anticipate that our results will have broad applicability to malaria prevention and control in Africa.
In Africa highlands, malaria transmission is unstable, and epidemic malaria poses a serious public health problem. It was estimated that epidemic malaria kills about 110,000 people each year and 110 million people are at risk. Understanding the mechanisms leading to malaria epidemics in the highlands will facilitate the development of malaria early warning system so that timely preparedness and preventative measures can be implemented. We hypothesize that mosquito vector control by targeting the malaria transmission hotspots is a cost-effective approach for malaria control in the highlands. This application will combine epidemiological, molecular population genetic and modeling approaches with an interventional analysis to determine the mechanisms causing malaria epidemics and to develop cost-effective vector control methods in western Kenya highlands. Unique to this application is that we will collaborate with scientists at the National Center for Atmospheric Research to incorporate seasonal climate forecasting into our model, thus we can test the sensitivity and reliability of our model in a real-time manner. We will then determine the effects of targeted vector control on both mosquito larvae and adults in transmission hotspots on malaria incidences. This project will reveal critical parameters needed for the development of malaria early warning system, and will develop novel and cost-effective vector control methods for reducing malaria incidence and preventing malaria epidemics.
Showing the most recent 10 out of 99 publications
