Environmental Determinants of Malaria Transmission Around the Koka Reservoir in Ethiopia

Abstract

New dam construction is known to exacerbate malaria transmission in Africa as the vectors of malaria—Anopheles mosquitoes—use bodies of water as breeding sites. Precise environmental mechanisms of how reservoirs exacerbate malaria transmission are yet to be identified. Understanding of these mechanisms should lead to a better assessment of the impacts of dam construction and to new prevention strategies. Combining extensive multiyear field surveys around the Koka Reservoir in Ethiopia and rigorous model development and simulation studies, environmental mechanisms of malaria transmission around the reservoir were examined. Most comprehensive and detailed malaria transmission model, Hydrology, Entomology, and Malaria Transmission Simulator, was applied to a village adjacent to the reservoir. Significant contributions to the dynamics of malaria transmission are shaped by wind profile, marginal pools, temperature, and shoreline locations. Wind speed and wind direction influence Anopheles populations and malaria transmission during the major and secondary mosquito seasons. During the secondary mosquito season, a noticeable influence was also attributed to marginal pools. Temperature was found to play an important role, not so much in Anopheles population dynamics, but in malaria transmission dynamics. Change in shoreline locations drives malaria transmission dynamics, with closer shoreline locations to the village making malaria transmission more likely. Identified environmental mechanisms help in predicting malaria transmission seasons and in developing village relocation strategies upon dam construction to minimize the risk of malaria.

Impact of Insecticide Resistance on P. falciparum Vectors’ Biting, Feeding, and Resting Behaviour in Selected Clusters in Teso North and South Subcounties in Busia County, Western Kenya

“…SS mosquitoes were biting more during bed time while LS and LL vectors were seeking a human blood meal more during out of bed hours of the dusk to dawn period than during bed time. Temperature has been known to majorly alter mosquito and parasite life-history traits, a temperature sensitive combination which determine malaria transmission intensity [40,41]. Temperatures, humidity, and wind do vary from hour to hour throughout the night.…”

Increased risk of malaria transmission with warming temperature in the Ethiopian Highlands

“…Current and future R o were estimated using a detailed field-tested mechanistic model of malaria transmission at the village scale, Hydrology Entomology and Malaria Transmission Simulator (HYDRE-MATS) [25,26]. HYDREMATS was updated for the Highland conditions (supplementary figure 2) and calibrated extensively (supplementary figures 3-5) based on three years of monitoring campaigns at our field site in the Ethiopian Highlands, named Ejersa .…”

“…(Malaria Transmission Model) We use a mechanistic model of malaria transmission at the village scale, Hydrology Entomology and Malaria Transmission Simulator (HYDREMATS) [25,26]. HYDREMATS features one of the most detailed mechanistic structures, with coupled hydrology and entomology [25,26].…”

“…(Malaria Transmission Model) We use a mechanistic model of malaria transmission at the village scale, Hydrology Entomology and Malaria Transmission Simulator (HYDREMATS) [25,26]. HYDREMATS features one of the most detailed mechanistic structures, with coupled hydrology and entomology [25,26]. HYDREMATS was updated for the Highland conditions (supplementary figure 2) based on three years of extensive monitoring campaigns at our field site in the Ethiopian Highlands, Ejersa ( figure 1(b)) [26].…”

“…HYDREMATS features one of the most detailed mechanistic structures, with coupled hydrology and entomology [25,26]. HYDREMATS was updated for the Highland conditions (supplementary figure 2) based on three years of extensive monitoring campaigns at our field site in the Ethiopian Highlands, Ejersa ( figure 1(b)) [26]. The simulation results of HYDREMATS compare well with hydrological observation data (supplementary figures 3 and 4), sampled Anopheles mosquito population data (supplementary figure 5(a)), and the Approach and target of the study.…”