Modeling the dynamics and control of rabies in dog population within and around Lagos, Nigeria
Department of Mathematics, University of Lagos, Lagos, Nigeria
2 Department of Mathematics, University of Ilorin, Ilorin, Nigeria
Accepted: 12 April 2023
Published online: 9 May 2023
Rabies appeared in Nigeria in 1912 and the disease is endemic in many states of the country including Lagos. The government of Lagos state, in its efforts to end rabies in the state, embarked on a free mass vaccination campaign for 1.5 million dogs against rabies in 2021. For the purpose of assessing the effort of the government and to study various factors that can inhibit or escalate rabies in Lagos to properly guide the government in its efforts to end the disease, we formulate a mathematical model as a system of ODEs. To investigate the dynamics of the disease in the state, the theory of reproductive ratio is applied. As this ratio increases beyond one, rabies invades the state and vice-versa. We show that if , the disease-free equilibrium is globally asymptotically stable in the feasible region . We also show that if , an endemic equilibrium exists and it is locally and globally stable in . Further, we show that if , the model may exhibit backward bifurcation. We performed sensitivity analysis to determine the strength of the model parameters to rabies spread and eradication and also computed herd immunity to assess the strength of the vaccination program embarked upon by the government which targeted 60% dog population. To validate the analytical findings and gain more insight into the dynamics of rabies in Lagos state, simulations are run. The results indicate that vaccine efficacy and recruitment rate for dogs have serious effects on rabies transmission in Lagos state. It was also discovered that the detection of the exposed dogs through screening had to be integrated into the vaccination program of the government if the vaccination campaign of 1.5 million dogs by the government was to champion rabies transmission in Lagos state.
© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.