Chikungunya is one of the Aedes aegypti diseases that mosquito transmits to humans and that are common in tropical countries like Yemen. In this work, we formulated a novel dynamic mathematical model framework, which integrates COVID-19 and Chikungunya outbreaks. The proposed model is governed by a system of dynamic ordinary differential equations (ODEs). Particle swarm optimization was employed to solve the parameters estimation problem of the outbreaks of COVID-19 and Chikungunya in Yemen (March 1, 2020, to May 30, 2020). Besides, a bi-objective optimal control model was formulated, which minimizes the number of affected individuals and minimizes the total cost associated with the intervention strategies. The bi-objective optimal control was also solved using PSO. Five preventive measures were considered to curb the environmental and social factors that trigger the emergence of these viruses. Several strategies were simulated to evaluate the best possible strategy under the conditions and available resources in Yemen. The results obtained confirm that the strategy, which provides resources to prevent the transmission of Chikungunya and provides sufficient resources for testing, applying average social distancing, and quarrying the affected individuals, has a significant effect on flattening the epidemic curves and is the most suitable strategy in Yemen.
Keywords: COVID-19; Chikungunya; Optimal control; Particle swarm optimization; Prediction.
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.