Geo-enabled surveillance system for antimalarial resistance in Africa

Project: PhD

Project Details

Description

Increasing global temperatures and climate change have yielded irreversible changes in weather patterns and increases in extreme weather events globally. This macro-level change and its impact on virtually all ecosystems has resulted in wide-scale losses in biodiversity and shifts in vegetation indices around the globe – thereby causing increased pressure on food systems, water resources, and human health -- including shifts in vector ecology that impact malaria, dengue, and other vector-borne disease transmission. Progress on malaria control and elimination has stagnated in recent years; and funding continues to dwindle in lieu of funding for other emerging threats such as global pandemics, that are likewise exacerbated by climate change. The need for increased efficient utilization of these dwindling malaria resources via 1) precise monitoring and strategic surveillance of transmission, as well as parasitological and entomological resistance to current drugs and tools, and 2) effective targeting of interventions will be the most important factor in maintaining the relevance of the current malaria toolkit. Well-designed, rapid and highly granular antimalarial surveillance systems are urgently needed to protect the efficacy of remaining antimalarial treatments, and inform discovery of new, effective drugs and vaccines. Molecular markers are effective tools for monitoring anti-malarial drug resistance, as samples collected on dried blood spots are sufficient to monitor known and validated molecular markers of resistance, and can help to detect the early emergence of resistance. This project will address the need for more powerful molecular surveillance through the integration and operationalisation of disparate public health data streams via the geospatial platform, Reveal. We will utilise the open-source Reveal platform to geo-enable the malaria genomic surveillance network in Ghana to link dried blood spot data captured at the household-level to an advanced next generation sequencing lab. Once sequenced, we will visualize and monitor molecular markers of antimalarial resistance at a granular geospatial level and utilize these geospatial characteristics to align these genomic data to other data streams including epidemiologic, programmatic, and sociodemographic data to inform intervention response. The linking and geo-enabling of the existing surveillance network to the Reveal platform will increase granular geospatial and temporal antimalarial resistance insights to guide responsive action and drive epidemiological understanding of antimalarial resistance emergence and spread
StatusActive
Effective start/end date15/01/25 → …

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