Mathematical model analysis for maize yield under co-infection of maize streak virus and maize stripe virus diseases with control measures

Abstract

Maize is a staple food for billions of human globally. It is a very important food crop for sustaining global food security, livelihoods, and economic development. Despite the valuable advantages of maize, its optimal production is affected by several challenges, such as climate change, socio-economic factors, sustainable practices, pests, and diseases. A mathematical epidemiological model for maize yield that takes into account the major factors influencing maize yield, such as co-infection of maize streak virus and maize stripe virus, is developed. The essential dynamical features of the model, such as the basic reproduction number, disease-free and endemic equilibria, are determined and analysed. The model is used to investigate how to improve maize yield under several challenging factors, using Nigeria as a case study. By fitting the model to real data on maize yield in Nigeria, possible long-term model predictions on maize yield in Nigeria were obtained, and parameters of the model were also estimated. Numerical simulations using the estimated parameters illustrated how various control interventions, such as the use of modern technologies, controlling of insect vectors etc can improve maize yield significantly. The results of this study are expected to aid farmers and policy-makers to adopt best farming practices that will improve maize yield and consequently assist in achieving food security globally.