The coronavirus SARS-CoV-2, otherwise known as COVID-19, is a worldwide pandemic of respiratory illness which has caused thousands of deaths across the globe . The morbidity rate has put huge pressure on the health sector of many nations where cases have been confirmed. The negative economic impact of the disease is enormous and unmatched in the history of disease outbreak worldwide . This contagious disease has no cure and its spread is sporadic. The first confirmed case of COVID-19 in sub-Saharan Africa was in Nigeria (27 February 2020) . Since the outbreak of the disease in Nigeria, the government has put in place preventive measures and policies including lockdown to mitigate the spread of the disease. Despite these instituted mechanisms and structures, the cumulative COVID-19 confirmed case continues to grow; as at the first 120 days of its outbreak confirmation it had risen to 22,614 . The figure attracts criticisms and divergence opinion from the experts in the field of epidemiology. Some opined that, drawing from the experience of countries like USA, Brazil, Russia, and Italy, the figure is low due to low testing capacity in Nigeria, while others likened the disease spread's pattern to what is obtainable in some Africa countries. The Nigeria Centre for Disease Control (NCDC), however, argued that the number may be underreported due to community spread but was of the view that the differential in protocol and guideline for testing could be responsible for the current disease trend in Nigeria compared to other countries . The huge population size of Nigeria, its population density and poor compliance with preventive measures are other possible reasons for the disagreement with the total reported cases of COVID-19 as at the 120th day of its outbreak in Nigeria. Unfortunately, little is known about the evidence to either support or refute these claims.
In this study, the COVID-19 data in Nigeria show an increasing trend. The curve for Nigeria is unlike a typical propagated epidemic curve that would have been expected in the case of COVID-19 being an infectious disease. The transmissibility interval of COVID-19, that is its reproductive number which signifies the number of people a single case can infect with the virus, was estimated to be from 1.4 to 2.5, 3.6 to 4.0, and 2.24 to 3.58 by earlier studies [3, 6–8]. An indication that the disease will continue to be on the increase. Therefore, the observed pattern found in our study agrees with the known pattern of spread of the disease. We also found a higher number of cases were reported after the relaxation of lockdown than during the lockdown period. There is no doubt that the spread of the disease will be more after the relaxation of lockdown due to poor adherence to the standard precautionary measures in Nigeria. However, an increase in capacity for testing may be the possible explanation for this finding.
We found a similarity possibly due to about the same capacity for testing in the trajectory pattern of cumulative confirmed cases of COVID-19 in Nigeria, Ghana and Cameroon in the first 120 days after the first outbreak in these countries. Conversely, a difference was observed in the pattern exhibited by Nigeria compared to four of the seven countries investigated (Mexico, Bangladesh, South Africa and Indonesia). As at the 120th day after first case confirmation in these four countries, the total COVID-19 test conducted and test per 1 million population were strikingly higher than that of Nigeria over the same period . Except Indonesia, which has comparable population size with Nigeria, the population figure for each of the other seven countries was extraordinarily lower. One would have expected the pattern of the disease spread in Nigeria to be similar to that of Mexico, Bangladesh, South Africa and Indonesia, all things being equal. Thus, it is tempting to conclude that low testing capacity in Nigeria is responsible for variability in the observed pattern of COVID-19 cases compared to the four countries. The implication is that community testing has not commenced fully in Nigeria as it is done in South Africa; the disease is presently having a sporadic cluster of local transmission in Nigeria.
We further found that the distribution of COVID-19 associated deaths in the course of the study period demonstrates that except Mexico, the pattern observed for Nigeria was comparable to 7 of the 8 countries investigated but aligns perfectly with the Cameroun and Ghana pattern. The prominent difference in COVID-19 related death trajectory found in Mexico compared to other countries may be explained by the higher number of observed COVID-19 cases within the study period. The compactness in the similarity in COVID-19 deaths between Nigeria, Ghana and Cameroon, countries from west Africa may be attributed to other factors aside the COVID-19 testing capacity and case management capabilities.
The cubic polynomial (CPM) was identified as the model of best fit among the four models used in this study. Next to the CPM is the quadratic model (QM). The CPM and QM have been identified in the previous studies as predictive models for some infectious diseases including COVID-19 [9, 10]. None of the data for the countries follow the exponential model except South Africa which aligns with the data within the first 70 days of the outbreak confirmation. A similar remark has been made in the past on the suitability of exponential model for fitting the spread curve of infectious disease . In our study, the predicted COVID-19 cumulative cases for 30 September 2020 using QM and CPM was 93,988 and 155,467 respectively, provided the present testing capacity for COVID-19 and the level of compliance with the preventive measures to mitigate the disease spread is sustained throughout the period.
The Nigeria data was based on testing suspected cases who either reported at the testing centres or symptomatic individuals at homes who call the NCDC response team lines for help. Differential in the scope of testing and atmospheric conditions in different countries should not be overruled while interpreting our findings. Inaccessibility to data on socio-demographic profile and health history of the COVID-19 patients and survivors limits the opportunity to do some statistical and mathematical modelling.