A framework for assessing the feasibility of malaria elimination

被引:0
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作者
Bruno Moonen
Justin M Cohen
Andy J Tatem
Jessica Cohen
Simon I Hay
Oliver Sabot
David L Smith
机构
[1] Clinton Health Access Initiative,Global Health Group
[2] University of California,Emerging Pathogens Institute
[3] University of Florida,Department of Geography
[4] University of Florida,Harvard School of Public Health
[5] Harvard University,Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology
[6] University of Oxford,Department of Biology
[7] University of Florida,undefined
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关键词
Malaria; Indoor Residual Spray; Parasite Rate; Malaria Elimination; Entomological Inoculation Rate;
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摘要
The recent scale-up of malaria interventions, the ensuing reductions in the malaria burden, and reinvigorated discussions about global eradication have led many countries to consider malaria elimination as an alternative to maintaining control measures indefinitely. Evidence-based guidance to help countries weigh their options is thus urgently needed. A quantitative feasibility assessment that balances the epidemiological situation in a region, the strength of the public health system, the resource constraints, and the status of malaria control in neighboring areas can serve as the basis for robust, long-term strategic planning. Such a malaria elimination feasibility assessment was recently prepared for the Minister of Health in Zanzibar. Based on the Zanzibar experience, a framework is proposed along three axes that assess the technical requirements to achieve and maintain elimination, the operational capacity of the malaria programme and the public health system to meet those requirements, and the feasibility of funding the necessary programmes over time. Key quantitative and qualitative metrics related to each component of the assessment are described here along with the process of collecting data and interpreting the results. Although further field testing, validation, and methodological improvements will be required to ensure applicability in different epidemiological settings, the result is a flexible, rational methodology for weighing different strategic options that can be applied in a variety of contexts to establish data-driven strategic plans.
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