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Supporting malaria control with interfaced applications of mathematical models that enables investigating effectiveness of various interventions as well as their cost implications could be useful. Through their usage for planning, these applications may improve the prospects of attaining various set targets such as those of the National Strategic Plan policies for malaria control in Ghana. A malaria model was adapted and used for simulating the incidence of malaria in various regions of Ghana. The model and its application were developed by the Modelling and Simulation Hub Africa and calibrated using district level data in Ghana from 2012 to 2018. Average monthly rainfall at the zonal level was fitted to trigonometric functions for each ecological zone using least squares approach. These zonal functions were then used as forcing functions. Subsequently, various intervention packages were investigated to observe their impact on averting malaria incidence by 2030. Increased usage of bednets but not only coverage levels, predicted a significant proportion of cases of malaria averted in all regions. Whereas, improvements in the health system by way of health seeking, testing and treatment predicted a decline in incidence largely in all regions. With an increased coverage of SMC, to include higher age groups, a modest proportion of cases could be averted in populations of the Guinea savannah. Indoor residual spraying could also benefit populations of the Transitional forest and Coastal savannah as its impact is significant in averting incidence. Enhancing bednet usage to at least a doubling of the current usage levels and deployed in combination with various interventions across regions predicted significant reductions, in malaria incidence. Regions of the Transitional forest and Coastal savannah could also benefit from a drastic decline in incidence following a gradual introduction of indoor residual spraying on a sustained basis.

Original publication

DOI

10.1371/journal.pgph.0000474

Type

Journal

PLOS global public health

Publication Date

01/2022

Volume

2

Addresses

Modelling and Simulation Hub, Africa, Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa.