Modelling the Spread of Tuberculosis in South African Informal Settlements

Chrystal Bianca Udall () and Christa Searle ()
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Chrystal Bianca Udall: Stellenbosch University
Christa Searle: Stellenbosch University

SN Operations Research Forum, 2023, vol. 4, issue 1, 1-17

Abstract: Abstract Due to the high population density of informal settlements, the spread of communicable diseases is highly effective in this environment. South Africa has been on the World Health Organization’s list of 30 top tuberculosis-burdened countries in the world for the last two decades. The rate of individuals diseased with tuberculosis in informal settlements, however, is reported to be double that of the country. In order to succeed in reducing the number of tuberculosis cases, policy decision makers have a growing need to understand the risk factors surrounding tuberculosis and data which may inform their decision in a quantifiable manner. In this paper, agent-based simulation is employed in order to facilitate the understanding of the spread of tuberculosis in these environments. The simulation model developed models the personal characteristics, daily movements and interactions between informal settlement residents. This model is able, within a certain range of accuracy, to indicate the spread of tuberculosis given certain input parameters, such as population size, probability of treatment termination and percentage initially infected, amongst others. This may assist policy makers in making informed decisions based on quantitative targets. It is evident that population density has a great impact on the spread rate of the disease. This is supportive of the fact that 90% of residents in informal settlements have latent tuberculosis. Given that only 68% of people with the disease seek treatment, by increasing this likelihood through incentives, it is possible to drastically decrease the rate of death and unsuccessful treatment.

Keywords: Agent-based simulation modelling; Disease modelling; Tuberculosis; South African informal settlements (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s43069-022-00181-5

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