On the 5th of March 2020, South Africa reported its first cases of COVID-19. This signalled the onset of the first COVID-19 epidemic wave in South Africa. The response by the Government of South Africa to the COVID-19 epidemic in South Africa was the use of non-pharmaceutical interventions (NPIs). In this study, a semi-reactive COVID-19 model, the ARI COVID-19 SEIR model, was used to investigate the impact of NPIs in South Africa to understand their effectiveness in the reduction of COVID-19 transmission in the South African population. This study also investigated the COVID-19 testing, reporting, hospitalised cases and excess deaths in the first COVID-19 epidemic wave in South Africa.

Background Emerging SARS-CoV-2 variants have been attributed to the occurrence of secondary, tertiary, quaternary, and quinary COVID-19 epidemic waves threatening vaccine efforts owing to their immune invasiveness. Since the importation of SARS-CoV-2 in South Africa, with the first reported COVID-19 case on March 5, 2020, South Africa has observed 5 consecutive COVID-19 epidemic waves. The evolution of SARS-CoV-2 has played a major role in the resurgence of COVID-19 epidemic waves in South Africa and across the globe. Objective We aimed to conduct descriptive and inferential statistical analysis on South African COVID-19 epidemiological data to investigate the impact of SARS-CoV-2 lineages and COVID-19 vaccinations in South African COVID-19 epidemiology. Methods The general methodology involved the collation and stratification, covariance, regression analysis, normalization, and comparative inferential statistical analysis through null hypothesis testing (paired 2-tailed t tests) of South African COVID-19 epidemiological data. Results The mean daily positive COVID-19 tests in South Africa’s first, second, third, fourth, and fifth COVID-19 epidemic wave periods were 11.5% (SD 8.58%), 11.5% (SD 8.45%), 13.3% (SD 9.72%), 13.1% (SD 9.91%), and 14.3% (SD 8.49%), respectively. The COVID-19 transmission rate in the first and second COVID-19 epidemic waves in South Africa was similar, while the COVID-19 transmission rate was higher in the third, fourth, and fifth COVID-19 epidemic waves than in the aforementioned waves. Most COVID-19 hospitalized cases in South Africa were in the general ward (60%-79.1%). Patients with COVID-19 on oxygen were the second-largest admission status (11.2%-16.8%), followed by patients with COVID-19 in the intensive care unit (8.07%-16.7%). Most patients hospitalized owing to COVID-19 in South Africa’s first, second, third, and fourth COVID-19 epidemic waves were aged between 40 and 49 years (16.8%-20.4%) and 50 and 59 years (19.8%-25.3%). Patients admitted to the hospital owing to COVID-19 in the age groups of 0 to 19 years were relatively low (1.98%-4.59%). In general, COVID-19 hospital admissions in South Africa for the age groups between 0 and 29 years increased after each consecutive COVID-19 epidemic wave, while for age groups between 30 and 79 years, hospital admissions decreased. Most COVID-19 hospitalization deaths in South Africa in the first, second, third, fourth, and fifth COVID-19 epidemic waves were in the ages of 50 to 59 years (15.8%-24.8%), 60 to 69 years (15.9%-29.5%), and 70 to 79 years (16.6%-20.7%). Conclusions The relaxation of COVID-19 nonpharmaceutical intervention health policies in South Africa and the evolution of SARS-CoV-2 were associated with increased COVID-19 transmission and severity in the South African population. COVID-19 vaccination in South Africa was strongly associated with a decrease in COVID-19 hospitalization and severity in South Africa.

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ObjectiveIn this study, we investigated the impact of COVID-19 NPIs in South Africa to understand their effectiveness in the reduction of transmission of COVID-19 in the South African population. This study also investigated the COVID-19 testing, reporting, hospitalised cases and excess deaths in the first wave of the COVID-19 epidemic in South Africa. MethodsA semi-reactive stochastic COVID-19 model, the ARI COVID-19 SEIR model, was used to investigate the impact of NPIs in South Africa to understand their effectiveness in the reduction of COVID-19 transmission in the South African population. COVID-19 testing, reporting, hospitalised cases and excess deaths in the first COVID-19 epidemic wave in South Africa were investigated using descriptive statistics.FindingsThe general trend in population movement in South African locations shows that the COVID-19 NPIs (National Lockdown Alert Levels 5,4,3,2) were approximately 30% more effective in reducing population movement concerning each increase by 1 Alert Level. The translated reduction in the effective SARS-CoV-2 daily contact number (β) was only 4.13 % to 14.6 % concerning increasing Alert Levels. Due to implemented NPIs, the effective SARS-CoV-2 daily contact number in the first COVID-19 epidemic wave in South Africa was reduced by 58.1-71.1 % while the peak was delayed by 84 days. The estimated COVID-19 reproductive number was between 1.98 to 0.40. During South Africa’s first COVID-19 epidemic wave, the estimated mean for the COVID-19 general ward, intensive care unit, on oxygen, high care, on ventilator, in isolation ward admission status in South African hospital was 58.5 %, 95% CI [58.1,59.0], 13.4 %, 95% CI [13.1,13.7], 13.3 %, 95% CI [12.6,14.0], 6.37 %, 95% CI [6.23,6.51], 6.29 %, 95% CI [6.02,6.55], 2.13 %, 95% CI [1.87,2.43] respectively. The estimated mean South African COVID-19 patient discharge rate was 11.9 days per patient. While the estimated mean of the South African COVID-19 patient case fatality rate (CFR) in hospital and outside the hospital was 2.06 %, 95% CI [1.86,2.25] (deaths per admitted patients) and 2.30 %, 95% CI [1.12,3.83](deaths per severe and critical cases) respectively.ConclusionThe results from this study show that the COVID-19 NPI policies implemented by the Government of South Africa played a significant role in the reduction of COVID-19 active, hospitalised cases and deaths in South Africa’s first COVID-19 epidemic wave.

ObjectiveWe compared reported COVID-19 case, fatality, and peak date data for Africa Union (AU) member states with estimates and projections produced by various mathematical models to assess their accuracy in the context of an ongoing pandemic and identify key gaps to improve the utility of models in the future.MethodsWe conducted a systematic literature review to identify studies published in any language between January and December 2020 that reported results of COVID-19 modeling analyses for any AU member state. Reported COVID-19 case, fatality, peak date, and testing rate data were obtained. Descriptive, bivariate, and meta-analyses were conducted to compare reported data to model-generated estimates. FindingsFor included countries in the respective model simulation periods, model-predicted cumulative cases ranged from 2 to 76,213,155 while model-predicted cumulative deaths ranged from 8 to 700,000. The difference between reported and predicted cumulative COVID-19 cases was between -99.3 % to 1.44×106 % with most values being above 24.7%, and the difference between reported and predicted cumulative COVID-19 deaths for models reviewed was between -2.0 % to 2.73×105 % with most values being above 50.0%. The difference in the predicted and reported dates for the first epidemic wave peak was between -242 Days to 249 Days.ConclusionFor the first COVID-19 epidemic wave, epidemiological model results were observed to have high precision but low accuracy when compared to reported peak case date and cumulative cases and deaths indicating that these data were either under-reported or model-overestimated.