Pan African Journal of Life Sciences(PAJOLS)

A publication of Faculty of Basic Medical Sciences and Faculty of Basic Clinical Sciences,
Ladoke Akintola University of Technology, Ogbomoso

e-ISSN: 2672-5924
Volume 6, No. 2, August 2022
Pages 486-494

DOI: 10.36108/pajols/2202/60.0270

Impact of Temperature and Population Size on the Spread of COVID-19 in Nigeria: A Robust Regression Approach
Abiola T. Owolabi*, Olasunkanmi J. Oladapo, Janet I. Idowu and Wakeel A. Kasali
Department of Statistics, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria.


Background: COVID-19, a global pandemic ravaging many countries, shares some semblances with influenza, whose transmission can be affected by many factors. Atmospheric temperature and population density have been identified as two key factors influencing the spread of viruses. Nigerian states with different weather patterns and varying populations across her states have recorded about 173,908 COVID-19 cumulative confirmed cases between March 2020 and July 2021.
Methods: Data sets of confirmed Covid-19 cases, average monthly temperature and population of each State, and Nigeria’s Federal Capital Territory were obtained. A test of assumptions of linear regression was carried out and there is the presence of outliers in the dataset. M-estimator as an alternative to Ordinary Least Square (O.L.S.) estimator for regression analysis was used to investigate the impacts of each State’s population size and atmospheric temperature on the rate of COVID-19 cases confirmed. The spearman rank correlation coefficient was also used to investigate the strength of the relationship be-tween the confirmed cases, the population and temperature.
Results: Results show no multicollinearity (VIF=1.041) between the independent variables, and there is no autocorrelation as the Durbin-Watson test value gives 2.113 (approximately 2). There is a weak positive correlation between cumulative confirmed cases and population (r = 0.281), but a weak negative correlation exists between COVID-19 cumulative confirmed cases and atmospheric temperature (r = -0.341). For OLS estimation method, only population is significant (β1= 0.002, p < 0.002) but the population (β1= 0.0006, p < 0.05) and the atmospheric temperature ( β2= -683, p < 0.05) are both significant when M-estimation method was applied.
Conclusion: The findings in this study show that population size and temperature are important factors in the spread of Covid-19. The spread of the pandemic may be partially suppressed with higher temperatures but increases with an increased population.
Keywords: Covid-19, Temperature, Population size, O.L.S., M-Estimation, Nigeria.


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