One of the challenges for eradication of infectious diseases is corruption. This may result in an increase in the number of infectious disease cases. In this article, the effect of corruption on the transmission dynamics of malaria is analyzed using a mathematical model. A deterministic model in the form of a system of differential equations is formulated and analyzed. Sensitivity analysis and numerical simulations are also conducted to determine the effect of parameters on the basic reproductive number. The results show that corruption has negative effects on the efforts for reducing the number of malaria cases.

A mathematical model has been widely used to understand complex phenomena in biology, social, and politics. A number of mathematical model has been formulated to understand infectious diseases or corruption phenomena. However, to the best of our knowledge, none of the work has has been conducted to investigate the relation of corruption and transmission dynamics of infectious diseases. In this work, a structured model in the form of system of differential equations has been formulated to investigate the relation between corruption and transmission dynamics of infectious diseases. In this work, a novel mathematical model has been formulated to investigate the relation between corruption and the transmission dynamics of infectious diseases. The results showed that in the presence of corruption the number of infections is higher compared to that in the absence of corruption. Although the implementation of public health intervention can reduce the number of infections, the presence of corruption can increase the disease incidence. This implies that corruption potentially hinder the effort for disease elimination. Numerical simulations showed that in the absence of corruption, the level of efficacy of public health intervention can reduce the number of infections. It showed that 80% efficacy level can eliminate the disease cases, which cannot be achieved in the presence of corruption. The results suggest that the corruption should be minimized in order to achieve disease elimination. When data becomes available, the model would be validated against the data.