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Targeting malaria hotspots in Myanmar: An individual-based modeling approach (360G-Wellcome-205240_Z_16_Z)

<p>The epidemiology of malaria in Myanmar has been changing with its decreasing incidence in Myanmar, while there is also an urgent need to address emerging resistance to artemisinin. Current malaria control strategies are no longer enough to achieve elimination. New strategies, like targeting of malaria hotspots where transmission intensity exceeds the average, have been suggested both by studies and the WHO.</p> <p>Such targeted strategies has been implemented in Kayin, Myanmar. However, detection of hotspots using qPCR has been limited to randomly selected villages because of the financial and operational constraints. This could be optimized by a simulation model.</p> <p>The proposed project will develop an individual-based mathematical model to:</p> <p>- Understand/model the changing epidemiology of malaria as its incidence declines in Myanmar</p> <p>- Derive cost-effective strategy to identify and treat malaria hotspots&nbsp;in Kayin, Myanmar</p> <p>As inputs, the model will have census data, population movement, and malaria data from relevant sources to create a dynamic, synthetic population. Simulated individuals will have their own risk of infection, health behaviour and response to treatment which will influence the overall disease transmission dynamics. A corresponding mosquito model will drive the force of infection for humans. Several detection methods and treatment strategies will be simulated.</p>


22 Nov 2016

Grant details
Amount Awarded 128087
Applicant Surname Tun
Approval Committee International Interview Committee
Award Date 2016-11-22T00:00:00+00:00
Financial Year 2016/17
Grant Programme: Title International Masters Fellowship
Internal ID 205240/Z/16/Z
Lead Applicant Dr Sai Thein Than Tun
Planned Dates: End Date 2020-09-01T00:00:00+00:00
Planned Dates: Start Date 2017-09-01T00:00:00+00:00
Recipient Org: Country United Kingdom
Region South East
Sponsor(s) Prof Lisa White
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