Predictive Models on COVID 19: What Africans Should Do?

Abstract

BackgroundCOVID 19 is becoming a global health problem, where strong intervention is needed. Thus, this paper addresses predictive models on COVID 19 in Africa, from which the government and others put a strong intervention in optimizing resources and necessary healthcare demand.MethodsPredictive models (Cubic polynomial and quadratic regression models) are considered based on the daily report of WHO, 2020 rampant data. The data were analyzed using R and STATA packages.ResultsThe result of the study has shown that the spatial and temporal pattern of this novel virus is varying, spreading and covering the entire world within a brief time. The result has shown that the fitting effect of cubic model is best outperforming compared to the other six families of exponentials ( {R}^{2}=0.996, F=538.334, {D}_{{F}_{1}}=3,{D}_{{F}_{1}}=7, {b}_{1}=13691.949, {b}_{2}=-824.701, {b}_{1}=12.956). The cubic algorithm is more robust in predicting the deaths and confirmed cases of COVID 19. There are also evidences that the source of the outbreak of the epidemic is related to Huanan Seafood from the whole market, fever (78%), cough (59%), fatigue (75%), headache (76%), and others are identified as the major symptoms of COVID 19. Moreover, the result of our study has shown the corona virus infection epidemic is increasing, which seeks a long-term plan to take an action in disease prevention and intervention programs.ConclusionThe trend of COVID 19 is increasing with an alarm rate, thus strong intervention is needed to mitigate the spread of this novel virus. This also can be done through reducing the spread of COVID 19 as persistent and strict self-isolation. The results acquired from this study also recommend that COVID-19 mortality and more cases might be engulfing in Africa due to lack of preparedness and giving strong awareness for the public.This pandemic will sustain to grow up, and peak to the highest for which a strong care and public health interventions practically implemented. Africans must go beyond theory preparations, strong awareness for the public and practical implementation is highly recommended. Highly recommended more sophisticated equipment to tackle the spread of the virus and safe the loss of the infected from deaths.

Modeling and Forecasting of COVID-19 New Cases in Top 10 Infected African Countries 

“…The result of the study had shown that the spatial and temporal pattern of this novel virus was varying, spreading and covering the entire world within a brief time. In the study, the fitting effect of the cubic model (R 2 =99.6%) was the best outperforming compared to the other six families of exponentials [21].…”

“…And based on recovered patients, Ghana had the highest recovered rate (97.6% with 43,693 recovered). The next 9 countries were Cameroon (94.1% with 18,448), Cote dʹIvoire (93.8% with 17,323), South Africa (88.1% with 561,204), Nigeria (78% with 42,922), Egypt (77.4% with 77,208), Morocco (76.9% with 53,929), Algeria (70.5% with 32,481), Kenya (60.4% with 21,158), and Ethiopia had the lowest recovered rate (36.2% with 20,776). These highest rates may indicate that the countries have well protected and have taken strong measures against the virus but still needs more efforts to control the pandemic in the next long and short times.…”

Modeling and Forecasting of COVID-19 New Cases in the Top 10 Infected African Countries Using Regression and Time Series Models

“…The result of the study had shown that the spatial and temporal pattern of this novel virus was varying, spreading and covering the entire world within a brief time. In the study, the fitting effect of cubic model (R 2 =99.6%) was a best outperforming compared to the other six families of exponentials [21].…”

“…And based on recovered patients, Ghana had the highest recovered rate (97.6% with 43,693 recovered). The next 9 countries were Cameroon (94.1% with 18,448), Cote d Ivoire (93.8% with 17,323), South Africa (88.1% with 561,204), Nigeria (78% with 42,922), Egypt (77.4% with 77,208), Morocco (76.9% with 53,929), Algeria (70.5% with 32,481), Kenya (60.4% with 21,158), and Ethiopia had the lowest recovered rate (36.2% with 20,776). These highest rates may indicate that the countries have well protected and have taken strong measures on the virus, but still needs more efforts to control the pandemic in the next long and short times.…”