| Autor: |
Jiang, Ai‐Ling, Lee, Ming‐Chieh, Selvaraj, Prashanth, Degefa, Teshome, Getachew, Hallelujah, Merga, Hailu, Yewhalaw, Delenasaw, Yan, Guiyun, Hsu, Kuolin |
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| Zdroj: |
Geohealth; Dec2023, Vol. 7 Issue 12, p1-19, 19p |
| Abstrakt: |
A combination of accelerated population growth and severe droughts has created pressure on food security and driven the development of irrigation schemes across sub‐Saharan Africa. Irrigation has been associated with increased malaria risk, but risk prediction remains difficult due to the heterogeneity of irrigation and the environment. While investigating transmission dynamics is helpful, malaria models cannot be applied directly in irrigated regions as they typically rely only on rainfall as a source of water to quantify larval habitats. By coupling a hydrologic model with an agent‐based malaria model for a sugarcane plantation site in Arjo, Ethiopia, we demonstrated how incorporating hydrologic processes to estimate larval habitats can affect malaria transmission. Using the coupled model, we then examined the impact of an existing irrigation scheme on malaria transmission dynamics. The inclusion of hydrologic processes increased the variability of larval habitat area by around two‐fold and resulted in reduction in malaria transmission by 60%. In addition, irrigation increased all habitat types in the dry season by up to 7.4 times. It converted temporary and semi‐permanent habitats to permanent habitats during the rainy season, which grew by about 24%. Consequently, malaria transmission was sustained all‐year round and intensified during the main transmission season, with the peak shifted forward by around 1 month. Lastly, we evaluated the spatiotemporal distribution of adult vectors under the effect of irrigation by resolving habitat heterogeneity. These findings could help larval source management by identifying transmission hotspots and prioritizing resources for malaria elimination planning. Plain Language Summary: Population growth and severe droughts have driven the development of irrigation schemes across sub‐Saharan Africa, which can increase malaria risk. Risk prediction remains difficult due to the heterogeneity of irrigation and the environment. Malaria models are seldom used to investigate the effect of irrigation as they typically rely only on rainfall to quantify larval habitats. By coupling a hydrologic model with a malaria model for a sugarcane plantation site in Arjo, Ethiopia, we demonstrated how incorporating hydrologic processes to estimate larval habitats can affect malaria transmission. Using the coupled model, we then examined the impact of the local irrigation on malaria transmission. The inclusion of hydrologic processes increased the variability of larval habitat area and resulted in a significant reduction in malaria transmission. In addition, irrigation increased all habitat types in the dry season and prolonged habitat stability during the rainy season. Consequently, malaria transmission was sustained year‐round and intensified during the main transmission season, with the peak shifted forward by around 1 month. Lastly, we demonstrated how irrigation could affect the spatiotemporal distribution of larval habitats and adult mosquitoes. These findings could help identify mosquito breeding hotspots and prioritize resources for malaria elimination planning. Key Points: An agent‐based malaria model was coupled with a hydrologic model to spatially simulate transmission by resolving habitat heterogeneityThe coupling framework enhanced larval habitat area variability which resulted in a lower malaria transmission predictionIrrigation sustained transmission year‐round, intensifying and shifting the peak forward by 1 month from the original period [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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