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A Simulation Model for Occupational Tuberculosis Transmission

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  • Mark Nicas
  • Edmund Seto

Abstract

A simulation model of tuberculosis (TB) transmission among hospital employees is described. A hypothetical cohort of 1000 workers was divided into low‐, medium‐, and high‐risk groups. The number of TB patients admitted daily was treated as a Poisson random variable. A patient imparted a daily infection risk that was identical for all workers within a risk group but that varied between risk groups. In some scenarios, infected employees were assigned a daily risk of developing TB disease. If disease developed, the individual remained on the job for 3 calendar weeks and imparted a substantial infection risk to 25 close contacts. Simulations were run over 5‐year intervals. Cumulative infection incidence increased over time and with more TB patients admitted. Given a scenario in which there were 600, 300, and 100 susceptibles in the low‐, medium‐, and high risk groups, respectively, 50 TB patients admitted annually and accounting for disease among infected employees, at 5 years there were approximately 100 primary infections (due to infection by patients), 40 secondary infections (due to infection by diseased coworkers), five primary disease cases, and two secondary disease cases. The input parameter values and simulation outcomes were reasonably consistent with the sparse information reported in the literature.

Suggested Citation

  • Mark Nicas & Edmund Seto, 1997. "A Simulation Model for Occupational Tuberculosis Transmission," Risk Analysis, John Wiley & Sons, vol. 17(5), pages 609-616, October.
  • Handle: RePEc:wly:riskan:v:17:y:1997:i:5:p:609-616
    DOI: 10.1111/j.1539-6924.1997.tb00901.x
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    References listed on IDEAS

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    1. Mark Nicas, 1996. "An Analytical Framework for Relating Dose, Risk, and Incidence: An Application to Occupational Tuberculosis Infection," Risk Analysis, John Wiley & Sons, vol. 16(4), pages 527-538, August.
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    Cited by:

    1. Ralf R. Küsel & Ian K. Craig & Anton C. Stoltz, 2019. "Modeling the Airborne Infection Risk of Tuberculosis for a Research Facility in eMalahleni, South Africa," Risk Analysis, John Wiley & Sons, vol. 39(3), pages 630-646, March.

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