Folashada Agusto from the Department of Ecology and Evolutionary Biology Kansas University – Applied mathematician by training. And she actively applies this knowledge of her knowledge in the study of the spread of infectious diseases.

The subject of her recent study published in the journal PLOS Onebecame Covid-19. Armed with computer modeling and large data sets, The researcher decided to evaluate by the example of one of the communities in South Africa, whether restrictive measures were justified during the pandemic period.

Research methodology

“In the case of Covid, we were interested in how the politics (authorities) and the behavior of people affect the transfer of the virus,” she explained. “The community on which we concentrated in South Africa is Gauteng.”

Aguo built its computer model based on the data of the Census of the South African population about the population density and the size of households in the Gauteng province, epidemiological data from Covid studies and the chronology of government measures in the city aimed at restraining the spread of the disease.

“It was the period since March 2020, when the governments around the world introduced large -scale quarantines into different dates of March, as it was in the United States,” Agusto recalled. – The quarantine was introduced everywhere, but its conditions differed. We wanted to see what was the level of infection in households and beyond in those periods, given the various measures being implemented. ”

Instead of modeling each person separately-due to restrictions on computing power and time-the researchers divided the population into four groups in density.

“We had access to data both in terms of population and in size of households for these four groups. P1 represented a low density, then P2, P3 and P4, where P4 is the most densely populated areas. We also considered the size of the households: single people, families of two or three people, four to five and so on. The data set also included households with 0 people, to whom we attributed persons without a specific place of residence. Based on this, we were able to analyze how the density and size of the household influenced Covid transmission models. ”

Ago used computer modeling based on an agent approach – an alternative method compared to computer computer models, which use differential equations to study the populations as a whole, and then segment people according to the stages of infection.

“Unlike them, the agent model is focused on individual individuals. She uses the rules “if it is,” to simulate a person’s daily life and decisions made by him. These rules are more attached to probability. If someone performs a certain action, what will happen next? This is a more natural way of coding human behavior compared to differential equations, ”the researcher emphasized.

Some conclusions of the study:

• In areas with a greater population density, the probability that someone will bring Covid home and infect the family above;
• In areas with a low population density, the risk of virus penetration into the house is less, but if this happens, the chances of infection of the family are higher;
• Regardless of the conditions, the behavior of people – such as compliance with the mask regime and quarantine – had the greatest influence on the model of the transfer of the virus;
• The dynamics of the waves of infection differed depending on the density of the population.

An interesting threshold effect has been discovered: there is a certain level of mobility at which the number of infections outside the house begins to exceed the number of infections inside the house. This phenomenon is described for the first time.

The model reproduced two peaks of infectivity outside of households that coincided with the waves of incidence, in reality observed in Gauteng. This confirms the fidelity of calculations that will be useful for planning measures to combat future epidemics.

Bottom line: quarantine, elbow, mask regime and the like, and deprivation during pandemia Covid-19 were not in vain.

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on 2025-09-25 15:01:00.
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