The goal of this paper was to assess the COVID-19 spread and attendant deaths in Nigeria and selected countries during the first 120 days of outbreaks. First, our analysis showed the spread of the pandemic increased following the relaxation of lockdowns. Both spread and mortality patterns in Nigeria compared closely with other African countries (Ghana, Cameroun and Egypt). Lastly, the findings suggested that different predictive models fitted the data for different countries.
In this study, the COVID-19 data in Nigeria showed an increasing trend. The epidemic curve for Nigeria differed from the typical propagated epidemic curve that would have been expected for COVID-19 and other infectious diseases with person-to-person mode of transmission. COVID-19 reproduction number appears to gain traction with time as estimated to be from 1.4 to 2.5, 3.6 to 4.0, and 2.24 to 3.58 from earlier studies [3, 5–7]. This indicates that the infection rate continues to increase. Therefore, the observed pattern found in our study agrees with the known pattern of spread of the disease. We also found that a higher number of cases was reported after the relaxation of lockdown than was reported during the lockdown period. The increased spread of the disease after the relaxation of lockdown could be due to poor adherence to the recommended preventive measures in Nigeria. This may be expected because when restrictive measures are lifted, exposures to disease risks become higher. Consequently, an increased number of infections is likely to follow. This is in tandem with evidence from developed countries where the transmission dynamics and effectiveness of control measures have been rigorously studied [8,9]. However, another plausible explanation for the increase in the number of confirmed cases could be the improved testing capacity in the country which coincided with the lockdown relaxation. Compared with Ghana and South Africa, the testing capacity in Nigeria was generally low. While Nigeria had only 2,755 persons tested for COVID-19 per 1,000,000 people, the estimate was 16,206 and 76,067 for Ghana and South Africa respectively .
We found a similar pattern in the number of cumulative cases of COVID-19 in Nigeria, Ghana and Cameroon possibly due to similarity in the capacity for testing in the first 120 days of the disease outbreak. 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 day 120in these four countries, the total COVID-19 tests per 1 million population was strikingly higher than that of Nigeria over the same period [1, 10]. Only Indonesia had a population size that was similar to that of Nigeria while the other countries had a considerably lower population than that of Nigeria. Mexico, Bangladesh, South Africa and Indonesia had environmental factors such as temperature and humidity that were comparable to that of Nigeria [11, 12]. Thus, the reasons that could explain the differences in disease spread pattern between these countries and Nigeria is not immediately clear except for the differences in COVID-19 testing rate. The implication is that community testing has not commenced fully in Nigeria as it is done in South Africa. The disease currently exhibited a sporadic cluster of local transmission in Nigeria.
We further found that the distribution of COVID-19-associated deaths observed for Nigeria was comparable to six of the seven countries investigated and aligned perfectly with the Cameroun and Ghana patterns. COVID-19-related death trajectory in Mexico may be explained by the higher number of observed COVID-19 cases recorded within the study period compared to other countries. The similarity in COVID-19 deaths between Nigeria, Ghana and Cameroon may be attributed to other factors different from the COVID-19 testing capacity and case management capabilities.
Cubic Polynomial Model (CPM) was identified as the best fit model 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 some previous studies as the best predictive models for some infectious diseases including Ebola and COVID-19 [13, 14]. None of the country data was suited for the exponential model except South Africa, which was suitable for the first 70 days of the outbreak. A similar observation was reported previously on the suitability of the exponential model for fitting the epidemic curve of infectious diseases . Nonetheless, differences in the levels and modes of testing across countries could be responsible for South Africa’s exemption. In South Africa, a community testing approach was instituted early unlike in other African countries such as Nigeria, Ghana and Cameroon. In addition, the marked differences in atmospheric and environmental conditions between countries may constitute potential explanatory variables [11,12].
In our study, the predicted COVID-19 cumulative case for 30 September 2020 using QM and CPM was 93,988 and 155,467 respectively. This is premised on the assumption that the present COVID-19 testing capacity and the level of compliance with the preventive measures to mitigate the spread is sustained. The wide gap between the two estimates could be linked to differences in the equations governing the use of QM and CPM, which implied that different parameters were used for the estimation. In this study, the model with the best fit differed across countries indicating variations in the epidemiological contexts, transmission dynamics and control efforts. Although some of these countries shared similarities in demographic and developmental profile, there were potential differences in other factors such as testing capacity, risk profile, enforcement of containment measures and the level of exposure to infected individuals.
The public health implication of our study is that there is a need for adequate emergency preparedness. The identified trajectory of COVID-19 infection in Nigeria is an impetus for increased surveillance, enhanced testing capacity and proactive planning for clinical management of cases as well as psychosocial management of discharged cases. Also, the preventive measures may have to be strengthened for containment of disease spread in Nigeria and the other countries.
The Nigeria data was premised on testing suspected cases who reported at the testing centres or symptomatic individuals who called the NCDC response team lines at their various homes for help. The differences in the scale of testing and the environmental conditions in different countries should be considered in interpreting our findings. This is because evidence suggests a relationship between weather conditions and transmission risks of COVID-19 [11,12]. Inaccessibility to data on socio-demographic profile and health history of the COVID-19 patients and survivors limited the opportunity to perform further statistical and mathematical modelling.