# An agent-based model for household COVID-19 transmission in Gauteng, South Africa

## TL;DR

This paper creates a model to study how government policies affect household and community spread of COVID-19 in South Africa's Gauteng province.

## Contribution

The study introduces an agent-based model revealing a new movement activation threshold impacting infection rates.

## Key findings

- Higher within-household infections occur in low-density communities, while high-density areas see more community infections.
- A movement activation threshold was identified where outside household infections surpass within-household ones.
- The model successfully simulated two epidemic peaks in Gauteng by adjusting quarantine and movement parameters.

## Abstract

Since the discovery of COVID-19 in Wuhan, China in 2019, close to seven million people have died from the infection. At the onset of the pandemic, many countries enacted stringent measures such as school and event closings in a bid to control and curtail the spread of the virus, leading to many within-household infections as people spent more time at home. This study develops an agent-based model (ABM) to gain insight into the impact of government COVID-19 mitigation guidelines and policy options on within-household and community COVID-19 infections in Gauteng, South Africa. Gauteng is the province in South Africa having the smallest land area, but it accounts for 25.8% of the country’s population. Agents are randomly assigned to cells on a 1000×1000 square grid varying according to Gauteng’s population density and household size distribution. We found that the percentage of within-household infections is higher in communities with smaller population densities, with the reverse being true for communities with larger population densities. Furthermore, as the agents’ movement activation rate increases, community-related infections increase, especially in communities with small population densities. Our study found an interesting phenomenon, observed for the first time: the existence of a movement activation threshold where the percentage and number of outside household infections overtake the percentage and number of within household infections when the activation rate increases. Lastly, our simulation results captured the two epidemic peaks experienced in Gauteng from March 30, 2020 to June 22, 2021 while varying quarantine violation and movement activation rates. Thus, the developed ABM can be used to exploit the implications of COVID-19 mitigation guidelines and policy options on household transmission to provide interesting insights.