Virus-2 (SARS-CoV-2). [1] The outbreak started in Wuhan, China, in December 2019. [2, 3] It was declared a Public Health Emergency of International Concern by the World Health Organization (WHO) in January 30, 2020 and a pandemic in March 11, 2020 . [4, 5] The primary mode of spread of SARS-CoV-2 is via close contact of persons, through small droplets generated by sneezing, coughing, and talking. [5] [6] [7] The incubation period is about five (5) days with a range of two (2) to fourteen (14) days. Common symptoms include fever, cough, fatigue, shortness of breath, anosmia, and can be complicated by pneumonia and acute respiratory distress syndrome. [7] [8] [9] [10] J o u r n a l P r e -p r o o f Recommended measures to prevent spread include hand hygiene, physical distancing, wearing a face mask in the public, and isolation of suspects. Other measures include travel restrictions, lockdowns, and facility closures. [9] [10] [11] In the early period of COVID-19 pandemic when China, then Italy, Spain, and the United States were terribly hit by fatalities, it was widely speculated that Africa will be worst hit when the virus eventually crosses her shores. This prediction is of course, logical owing to the fact that most of Africa is underdeveloped, constantly struggling with inadequate healthcare facilities with gloomy health indices.
Alas! the virus found its way into Africa, though there are some fatalities already recorded but the silently awaited Armageddon never came even though the pandemic has reached its peak, plateaued or sliding downwards. It is presently slowly rising again in some countries though not as rapidly as before.
This paradox is the basis for this study in order to objectively look at the possible factors affecting COVID-19 mortality rate. This will enable us to attempt to explain why Africa's COVID-19 mortality rate is ironically lower than that of more advanced countries with better health systems. This will also enable heads of governments of advanced and underdeveloped countries to prioritize preventive measures that best suit their overall risk and pattern of COVID-19 fatalities, thereby ensuring a healthy balance between lockdown/ restrictive measures and socio-economic policies.
This is an analytic review that used population data and current COVID-19 mortality figures to attempt to answer why COVID-19 mortality in Africa is ironically lower than in more advanced countries.
Considering the cumbersome nature of attempting to analyze data from all countries in the world, sample countries used for the analysis were selected to represent certain criteria in order to have ample J o u r n a l P r e -p r o o f representation of socio-demographic and mortality pattern (pre-COVID-19 and COVID-19) of the different world regions. These criteria include differences in population pyramids, median age, life expectancy, socioeconomic/ technological advancement, pre-COVID-19 era mortality rates, and COVID-19 mortality rates. Additionally, countries selected have reached their peaks of infection rates and/ or case fatality rates (CFR), in plateau or downslide phase.
Current population data like population mean age, mean life expectancy, pre-COVID-19 era mortality rates for the general population and age group > 65 years were collated for selected countries.
Additionally, data on diabetes prevalence and cardiovascular disease (CVD) mortality were obtained.
Subsequently, the most current COVID-19 morbidity and mortality data were compiled and tabulated. Furthermore, stepwise multiple regression analysis was used to determine significant predictors of COVID-19 mortality rates. COVID-19 mortality rate (deaths per million population) was used as a dependent variable in the regression analysis because it was more reliable than case fatality rate (CFR) since the latter heavily depends on the COVID-19 testing capability which is highly variable and resource-based.
Pre-COVID-19 era population/ mortality data and current COVID-19 mortality data from twenty-three (23) countries were used for the analysis. [12] [13] [14] [15] [16] [17] . Likewise, the 65yr+ mortality% is lowest among these countries. (Table 1 ) [12] [13] [14] [15] [16] [17] COVID-19 deaths per million population (mortality rate) was significantly directly correlated with population mean age (r=0.66, p<0.001), life expectancy (r=0.58, p=0.003), pre-COVID era 65yr+ mortality% (r=0.66, p<0.001), but inversely correlated with pre-COVID-era CVD death (r=-0.59, p=0.002).
COVID-19 CFR was also directly correlated with mean age, life expectancy, pre-COVID era 65yr+ mortality%, though with lower strength than COVID-19 mortality rate. CFR was also inversely correlated with pre-COVID CVD deaths. (Table 2) Significant positive predictors of COVID-19 mortality rate included pre-COVID era 65yr+ mortality% (R square=0.574, B=2.86, p<0.001), population mean age (R square=0.570, B=4.77, p=0.001), and life expectancy (R square=0.524, B=1.67, p=0.008). Pre-COVID era CVD deaths was a negative predictor of COVID-19 mortality rate (R square=0.524, B=-0.584, p=0.012). (Table 3) DISCUSSION J o u r n a l P r e -p r o o f 8 The aim of this study is to attempt to explain the seemingly low COVID-19 mortality rate in low income, less developed African countries. This can only be possible if we look into possible determinants of COVID-19 mortality rate. Population data showed that the median ages and life expectancy of most African countries are lower than those of countries in Europe, North America, Asia, South America, etc.
( Table 1 ). This has given rise to a population pyramid consisting of predominantly young population in Africa while the Western and other developed nations have a predominantly older population. This disparity may be explained by the high birth rates in less developed African countries, and the more advanced healthcare system in the developed nations making their citizens live longer. On the other hand, Africa with less advanced healthcare system, continue to be bedeviled with communicable and even non-communicable diseases causing the lower life expectancy.
In the same vein, mortality data showed that the '65yr+ mortality%' is clearly higher in the West and other developed nation than in Africa. This is obviously due to the fact that a much higher proportion of the citizens of the West and other industrialized nations tend to live beyond 65yrs of age compared to a much lower proportion of the population in Africa. (Table 1 ) This high '65yr+ mortality%' in Italy, Spain, Britain, USA, China, Japan, etc. may also have reflected in the COVID-19 mortality rate since the elderly persons are most susceptible to COVID-19 death. (Table 1) On further analysis, there was a significant positive correlation between COVID-19 mortality rate and population mean age, life expectancy, and pre-COVID-19 '65yr+ mortality%'. This further strengthens the fact that a predominantly older population is more susceptible to COVID-19 deaths. Ironically, a significant negative correlation was noted between COVID-19 mortality and pre-COVID era cardiovascular disease (CVD) deaths. This may be explained by the fact that advanced countries like US, Italy, Spain, Japan, China, etc. with better healthcare facilities were able to slow down CVD deaths prior to COVID-19, as such maintained a larger pool of persons surviving and living with moderate and even severe CVDs. These persons with CVD are highly susceptible to COVID-19 deaths. On the other hand, less J o u r n a l P r e -p r o o f advanced nations like Nigeria, Chad, Benin Republic, Niger, Ivory Coast, etc. with less advanced healthcare systems will most likely have had their pool of persons with CVD trimmed by pre-COVID era CVD deaths.
Even though diabetes mellitus (DM) have generally been identified as a risk factor for COVID-19 death, no significant correlation was found between COVID-19 mortality rate and DM prevalence. This may be explained by effects of confounders like poor glycemic control, age of the persons with DM, duration of DM, prevalence of complications of DM, level of DM care, pre-COVID era mortality due to DM, etc.
Similarly, COVID-19 case fatality rate (CFR) was positively correlated with population mean age, life expectancy, pre-COVID era '65yr+ mortality%', and negatively correlated to pre-COVID era CVD mortality rate. However COVID-19 mortality rate showed stronger correlations with these variables than COVID-19 CFR. This may be due to the fact that COVID-19 mortality rate with the population as denominator is a more reliable index of mortality than COVID-19 CFR whose denominator is total confirmed cases of COVID-19. Needless to say that the total cases recorded is dependent on the testing capacity and resources of a facility/ country. Finally, multiple stepwise regression analysis identified pre-COVID era '65yr+ mortality%' as the strongest predictor of COVID-19 death. This further strengthens the fact of the vulnerability of the elderly to COVID-19 death. Other significant predictors identified were population mean age and life expectancy. These of course, are factors that contribute to pre-COVID era '65yr+ mortality%' as well as swelling the proportion of elderly persons susceptible to COVID-19 death. Pre-COVID era CVD deaths was identified as a negative or inverse predictor of COVID-19 mortality rate. This also strengthens the above argument that advanced healthcare is associated with lower pre-COVID era CVD mortality rate leaving a larger pool of persons surviving and living with CVD who eventually became susceptible to COVID-19 death. 