A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Mathematical modelling of malaria control interventions to support strategic planning in Tanzania
Strategic planning of malaria control interventions is the selection and geographical targeting of interventions in a country to meet defined control or elimination targets. Due to epidemiological, environmental, and financial factors, progress in reducing malaria stagnated, and heterogeneity in transmission increased, hence the strategic planning process has become more challenging. In this context, mathematical modelling of malaria transmission and disease dynamics is a potentially valuable tool as it allows to make predictions on likely intervention impact across a range of different settings. This PhD aimed to contribute to a stronger basis for the rational development of malaria strategies for maximum progress towards control and elimination targets in Tanzania. The research outcomes provide a comprehensive description of malaria risk at the council level in Tanzania using School Malaria Parasitaemia Survey data, and a model calibration and parameterisation workflow for council-specific intervention impact predictions. The research was conducted in close collaboration with the National Malaria Control Program in Tanzania and the application of mathematical modelling in addition to interactive discussions on intervention impact and stratification, contributed to a new national malaria control strategy. This PhD further demonstrated the use of mathematical modelling for in-depth questions on intervention deployment by assessing different deployment strategies for larviciding, an intervention to target mosquito larvae not yet implemented on a large scale. The work provides a framework as well as lessons learned for the use of mathematical modelling to support NMCPs in the planning of national malaria strategies in high malaria burden countries in Sub-Saharan Africa.
Mathematical modelling of malaria control interventions to support strategic planning in Tanzania
Strategic planning of malaria control interventions is the selection and geographical targeting of interventions in a country to meet defined control or elimination targets. Due to epidemiological, environmental, and financial factors, progress in reducing malaria stagnated, and heterogeneity in transmission increased, hence the strategic planning process has become more challenging. In this context, mathematical modelling of malaria transmission and disease dynamics is a potentially valuable tool as it allows to make predictions on likely intervention impact across a range of different settings. This PhD aimed to contribute to a stronger basis for the rational development of malaria strategies for maximum progress towards control and elimination targets in Tanzania. The research outcomes provide a comprehensive description of malaria risk at the council level in Tanzania using School Malaria Parasitaemia Survey data, and a model calibration and parameterisation workflow for council-specific intervention impact predictions. The research was conducted in close collaboration with the National Malaria Control Program in Tanzania and the application of mathematical modelling in addition to interactive discussions on intervention impact and stratification, contributed to a new national malaria control strategy. This PhD further demonstrated the use of mathematical modelling for in-depth questions on intervention deployment by assessing different deployment strategies for larviciding, an intervention to target mosquito larvae not yet implemented on a large scale. The work provides a framework as well as lessons learned for the use of mathematical modelling to support NMCPs in the planning of national malaria strategies in high malaria burden countries in Sub-Saharan Africa.
Mathematical modelling of malaria control interventions to support strategic planning in Tanzania
Runge, Manuela (author) / Pothin, Emilie / Lengeler, Christian / Smith, Thomas A. / Cohen, Justin
2021-01-01
Theses
Electronic Resource
English
DDC:
710
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