Mathematical modelling of COVID-19 transmission and control strategies in the population of Bauchi State, Nigeria

  • Yusuf Abdu Misau | Department of Community Medicine, College of Medical Sciences Abubakar Tafawa Balewa University, Bauchi State, Nigeria; Department of Epidemiology and Biostatistics, School of Public Health Mount Kenya University, Thika, Kenya.
  • Nanshin Nansak Zonal Advance Space Applications Laboratory Kashere, Gombe State, Nigeria.
  • Aliyu Maigoro Ministry of Health, Bauchi State, Nigeria.
  • Sani Malami Department of Histopathology, College of Medical Sciences, Abubakar Tafawa Balewa University Teaching Hospital, Bauchi State, Nigeria.
  • Dominic Mogere Department of Epidemiology and Biostatistics, School of Public Health Mount Kenya University, Thika, Kenya.
  • Suleiman Mbaruk Department of Epidemiology and Biostatistics, School of Public Health Mount Kenya University, Thika, Kenya.
  • Rilwanu Mohammed Ministry of Health, Bauchi State, Nigeria.
  • Suleiman Lawal Depatment of Medicine, Abubakar Tafawa Balewa University Teaching Hospital, Bauchi State, Nigeria.
  • Sunusi Usman Usman Department of Public Health, Bauchi State University, Gadau, Bauchi State, Nigeria.


The novel SARS-COV-2 has since been declared a pandemic by the World Health Organization (WHO). The virus has spread from Wuhan city in China in December 2019 to no fewer than 200 countries as at June 2020 and still counting. Nigeria is currently experiencing a rapid spread of the virus amidst weak health system and more than 80% of population leaving on less than 1USD per day. To help understand the behavior of the virus in resource limited settings, we modelled the outbreak of COVID-19 and effects of control strategies in Bauchi state at north-eastern Nigeria. Using the real data of Bauchi state COVID-19 project, this research work extends the epidemic SEIR model by introducing new parameters based on the transmission dynamics of the novel COVID-19 pandemic and preventive measures. The total population of Bauchi State at the time of the study, given by is compartmentalized into five (5) different compartments as follows: Susceptible (S), Exposed (E), Infectious (I), Quarantined (Q) and Recovered (R). The new model is SEIQR. N = S → E → I → Q → R Data was collected by accessing Bauchi state electronic database of COVID-19 project to derive all the model parameters, while analysis and model building was done using Maple software. At the time of this study, it was found that the reproduction number R, for COVID-19 in Bauchi state, is 2.6 × 10-5. The reproduction number R decreased due to the application of control measures. The compartmental SEIRQ model in this study, which is a deterministic system of linear differential equations, has a continuum of disease-free equilibria, which is rigorously shown to be locallyasymptotically stable as the epidemiological threshold, known as the control reproduction number R= 0.0000026 is less than unity. The implication of this study is that the COVID-19 pandemic can be effectively controlled in Bauchi, since is R<1. Contact tracing and isolation must be increased as the models shows, the rise in infected class is a sign of high vulnerability of the population. Unless control measures are stepped up, despite high rate of recovery as shown by this study, infection rate will keep increasing as currently there is a no vaccine for COVID-19.



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COVID-19, Modelling, Bauchi, Nigeria
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How to Cite
Abdu Misau, Yusuf, Nanshin Nansak, Aliyu Maigoro, Sani Malami, Dominic Mogere, Suleiman Mbaruk, Rilwanu Mohammed, Suleiman Lawal, and Sunusi Usman Usman. 2020. “Mathematical Modelling of COVID-19 Transmission and Control Strategies in the Population of Bauchi State, Nigeria”. Annals of African Medical Research 3 (1).