Exponential growth models on COVID-19 in Uganda: A case study of daily cumulative cases

Abstract

Background: The COVID-19 pandemic is argued to have originated from a sea food market in Wuhan City, Hubei Province of China. Due to the contagious nature of the COVID-19, people had to social distance to contain the spread of this novel virus. The spread of COVID-19 has been modelled and predicted using data that begins with first reported cases and the forces of infection in mathematical transmission models typically estimated using time series data that describes epidemic growth as a function of time so as to determine whether daily COVID-19 cases, recoveries and deaths cause inflation. Results: At 5% level of significance, the daily COVID-19 cases, recoveries and deaths were revealed to be insignificant determinants of inflation in Uganda during the COVID-19 pandemic. Conclusion: The analysis on co-integration revealed that there is co-integration of daily COVID-19 cases, recoveries, deaths and inflation. This could be attributed to the impact the impact the COVID-19 pandemic has had on the economy whereby a big proportion of the labour force was laid off their work and production put to a standstill during the COVID-19 pandemic. So I recommend that there should be efforts to allow workers work in shifts and even work from theirif possible so as to reduce crowding at workplaces which in turn reduces on the number of COVID-19 cases and deaths, increasing recoveries and increases production which in turn controls inflation.