Dataset Information

COVID-19 prediction in South Africa: Understanding the unascertained cases -- the hidden part of the epidemiological iceberg.

ABSTRACT:

Background

Understanding the impact of non-pharmaceutical interventions remains a critical epidemiological problem in South Africa that reported the largest number of confirmed COVID-19 cases and deaths from the African continent.

Methods

In this study, we applied two existing epidemiological models, an extension of the Susceptible-Infected-Removed model (eSIR) and SAPHIRE, to fit the daily ascertained infected (and removed) cases from March 15 to July 31 in South Africa. To combine the desirable features from the two models, we further extended the eSIR model to an eSEIRD model.

Results

Using the eSEIRD model, the COVID-19 transmission dynamics in South Africa was characterized by the estimated basic reproduction number (R0) at 2.10 (95%CI: [2.09,2.10]). The decrease of effective reproduction number with time implied the effectiveness of interventions. The low estimated ascertained rate was found to be 2.17% (95%CI: [2.15%, 2.19%]) in the eSEIRD model. The overall infection fatality ratio (IFR) was estimated as 0.04% (95%CI: [0.02%, 0.06%]) while the reported case fatality ratio was 4.40% (95% CI: [<0.01%, 11.81%]). As of December 31, 2020, the cumulative number of ascertained cases and total infected would reach roughly 801 thousand and 36.9 million according to the long-term forecasting.

Conclusions

The dynamics based on our models suggested a decline of COVID-19 infection and that the severity of the epidemic might be largely mitigated through strict interventions. Besides providing insights on the COVID-19 dynamics in South Africa, we develop powerful forecasting tools that allow incorporating ascertained rate and IFR estimation and inquiring into the effect of intervention measures on COVID-19 spread.

SUBMITTER: Gu X

PROVIDER: S-EPMC7743090 | biostudies-literature |

REPOSITORIES: biostudies-literature

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