Developing an Agent-based Model for Evaluating the Effectiveness of Malaria Interventions in Nanyumbu and Masasi Districts, Tanzania

Abstract

Objective : Agent-based models and simulation (ABMS) can be utilized to understand the dynamism of transmission and the effect of interventions. We evaluated using ABMS, the efficacy of insecticide-treated bednets (ITNs) at different coverage levels and quality of houses for control of malaria in Masasi and Nanyumbu districts, Tanzania. Methods: The model was developed and simulated in Anylogic software with mosquitoes, humans, and the environment along with their attributes as agents. Using field data, buildings of different qualities were created to be human environment, and ITN use was assigned to respective human agents. Shapefiles were imported into the built-in global imaging system map in Anylogic for better placement of buildings using their coordinates, and coordinates of streams extracted from the study area map were used to allocate the aquatic environment of the mosquito agents. ITNs coverage scenarios of 16%, 40%, 64%, and 80% were simulated. The model was simulated for 90-day period and a model time-step was set to a day. The primary outcome was the prevalence of human agents with malaria infection at the end of the 90-day simulation period. Results: At the end of the 90-day simulation period and initial ITNs coverage of 16% (257/1607), the prevalence of malaria infection was 15.4% (248/1607). When the coverage was increased to 40%, 64%, and 80% malaria prevalence declined to 15.1% (242/1607), 14.1% (227/1607), and 13.9% (223/1607), respectively. ABMS clearly indicated that an increase in ITNs coverage was associated with a decline in the prevalence of infected humans and mosquito population in consistency with the field data. Novelty: This work is unique in a sense that it incorporated the data on house quality which has direct impact in malaria transmission.