Mathematical modeling for analyzing mass drug administration operational factors for efficient malaria incidence reduction in southern Senegal

Mass drug administration (MDA) has emerged as a promising strategy for reducing malaria incidence in many African countries. A pilot study of MDA in the Tambacounda health district in southeastern Senegal had a significant impact on reducing the malaria burden. This led the Senegalese National Malaria Control Program (NMCP) to consider scaling up MDA to the district level. However, the infrequent use of MDA has resulted in limited knowledge of its use in the specific context of Senegal. In this work, we propose a mathematical model based on impulsive differential equations that integrates asymptomatic carriers to analyze the impact of MDA on malaria incidence in the region. To this end, we explore four different scenarios of MDA operational factors: 1) the number of MDA rounds, 2) the time interval between rounds, 3) the campaign coverage, and 4) the campaign start date. We find that MDA operational factors should not be oversimplified, as they play a critical role in the effectiveness of MDA campaigns. Our model predicts that successful MDA campaigns are obtained with high MDA coverage, multiple rounds within a year, an interval of five to six weeks between rounds, and an intervention that starts in the first month of the transmission period (mid-to-late July). In addition, we find that the starting campaign date and the interval between are highly correlated. These findings suggest that outcomes of MDA campaigns can be improved by optimizing operational factors for specific malaria-endemic settings. When implementing multiple MDA rounds, it is crucial to optimize these factors so that the intervention covers the entire period of high transmission and reaches most of the target population.