Health and Fitness

Predicting effectiveness of countermeasures during the COVID-19 outbreak in South Africa using agent-based simulation

M. Kersting, A. Bossert, et al.

This study investigates the impact of COVID-19 countermeasures in Nelson Mandela Bay Municipality through agent-based epidemic simulations. The findings reveal that premature relaxation of measures risks intense infection surges, threatening healthcare capacity. The research emphasizes maintaining strict measures to effectively contain the virus, demonstrating crucial insights by Moritz Kersting, Andreas Bossert, Leif Sörensen, Benjamin Wacker, and Jan Chr. Schlüter.

00:00

Playback language: English

Index

Abstract

This study uses agent-based epidemic simulations to assess the effectiveness of COVID-19 countermeasures in South Africa's Nelson Mandela Bay Municipality. The simulations indicate that prematurely lifting or relaxing measures leads to continued exponential infection growth or a second major infection peak, potentially overwhelming healthcare capacity. Strict measures, conversely, effectively contain the virus. The initial lockdown is deemed sufficient, but relaxing countermeasures risks a severe second outbreak.

Publisher

Humanities & Social Sciences Communications

Published On

Jul 16, 2021

Authors

Moritz Kersting, Andreas Bossert, Leif Sörensen, Benjamin Wacker, Jan Chr. Schlüter

Related Publications

Explore these studies to deepen your understanding of the subject.

Medicine and Health

Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

J. Almagor and S. Picascia

Psychology

The Emotional Landscape of Pregnancy and Postpartum during the COVID-19 Pandemic in Italy: A Mixed-Method Analysis Using Artificial Intelligence

Ravald, Mosconi, et al.

Chemistry

Using physiologically-based pharmacokinetic modeling to assess the efficacy of glove materials in reducing internal doses and potential hazards of N-methylpyrrolidone during paint stripping

C. R. Kirman

Social Work

Online public opinion during the first epidemic wave of COVID-19 in China based on Weibo data

W. Shi, F. Zeng, et al.

Listen, Learn & Level Up

Over 10,000 hours of research content in 25+ fields, available in 12+ languages.

No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.

listen to research audio papers with researchbunny