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Modelling space-time HIV/AIDS dynamics: Applications to disease control

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  • Thomas, Richard

Abstract

This paper applies the outputs of a family of HIV/AIDS models to problems in disease control. The epidemic models comprising this suite include single and multiregion representations each adopting either a one or two risk population format. Here, risk is expressed in terms of activity rates and those at low risk are characterized by a reproduction rate of less than unity which defines a simulated epidemic that cannot start. These models are applied to the following problems in prevention and control: first, estimating the impact of national variations in population growth rates on the predicted size of the epidemic, second, constructing control charts to assess the impact of intended interventions, third, evaluating the consequences of targeting preventative action at those at high risk; and last, evaluating the implications for international control of differences between the serological and simulated pandemic pathways. The discussion sets these findings within the context of forming health policy.

Suggested Citation

  • Thomas, Richard, 1996. "Modelling space-time HIV/AIDS dynamics: Applications to disease control," Social Science & Medicine, Elsevier, vol. 43(3), pages 353-366, August.
    • Handle: RePEc:eee:socmed:v:43:y:1996:i:3:p:353-366
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    Cited by:

    1. Banerjee, Ritwik & Bhattacharya, Joydeep & Majumdar, Priyama, 2021. "Exponential-growth prediction bias and compliance with safety measures related to COVID-19," Social Science & Medicine, Elsevier, vol. 268(C).
    2. Banerjee, Ritwik & Bhattacharya, Joydeep & Majumdar, Priyama, 2020. "Exponential-Growth Prediction Bias and Compliance with Safety Measures in the Times of COVID-19," IZA Discussion Papers 13257, Institute of Labor Economics (IZA).

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