Project Title: Using novel technologies for real-time monitoring of the risk of mosquito-borne diseases in the context of climate and land-use changes
Project Description: Transmission of mosquito-borne diseases can be affected by climate and land-use patterns in different ways. Increased temperatures can shorten the latency of malaria parasites thereby enabling transmission in previously-temperate zones. Yet extended droughts could crash populations of vectors such as Anopheles gambiae, which breed in small, open and drought-sensitive habitats. In contrast, flooding can increase populations of container-breeding dengue vectors, Aedes aegypti. Most investigations of climate and vector-borne diseases are too expansive to be computationally-practical;... Transmission of mosquito-borne diseases can be affected by climate and land-use patterns in different ways. Increased temperatures can shorten the latency of malaria parasites thereby enabling transmission in previously-temperate zones. Yet extended droughts could crash populations of vectors such as Anopheles gambiae, which breed in small, open and drought-sensitive habitats. In contrast, flooding can increase populations of container-breeding dengue vectors, Aedes aegypti. Most investigations of climate and vector-borne diseases are too expansive to be computationally-practical; and often overlook local data on entomological, anthropological or land-use characteristics. Fortunately, advanced cloud-based data processing, sensor design and on-board computing now enable highly-sensitive multi-modal systems with real-time data acquisition and integration. Microsoft Premonition offers a surveillance platform that autonomously lures, identifies and selectively captures arthropods for downstream studies, including metagenomics. With Gates-Foundation support, we are deploying this system in Tanzania to enhance malaria vector surveillance. Here, we propose extending the Premonition platform to investigate local associations between climate, landuse and mosquito-borne diseases. By combining capabilities in vector-biology, spatial analytics, machine learning and mathematical modeling, we will: i) integrate environmental and entomological data-streams to predict transmission risk, ii) investigate climate-dependent survival strategies of medically-important mosquitoes and iii) evaluate entomological data for monitoring climate and land-use.
Principal Investigator : Emanuel Kaindoa
Department Name :
Time frame: (2023-02-06) - (2026-01-06)
Wellcome Trust (Normal)
External Collaborating Partners
None added yet.