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Modeling scenarios for mitigating outbreaks in congregate settings.

Seth Blumberg1,2,3, Phoebe Lu1,2, Ada T Kwan3

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Effective outbreak control in congregate settings like prisons requires strategic interventions. Reducing the susceptible population by 20% can decrease disease burden by 47%, demonstrating the power of proactive measures.

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • Congregate settings like prisons and nursing homes are highly vulnerable to explosive COVID-19 outbreaks.
  • Effective prevention and mitigation strategies are critical for these high-risk environments.

Purpose of the Study:

  • To analyze the impact of various control interventions on the expected number of symptomatic infections during outbreaks in congregate settings.
  • To provide a quantitative framework for evaluating infection control policies in outbreak settings.

Main Methods:

  • Modeled disease introduction as a stochastic point process coupled to a branching process.
  • Used a deterministic compartmental model for within-resident transmission, accounting for susceptible depletion.
  • Modeled control strategies as reductions in susceptible population, reproduction number, or symptomatic proportion.

Main Results:

  • Vaccination or depopulation can yield greater than linear reductions in expected cases.
  • A 20% preemptive reduction in susceptible population decreased disease burden by 47% (with R0=3.0 and density-dependent transmission).
  • Optimizing residential unit apportionment and implementing timely reactive controls can further mitigate outbreak risk and burden.

Conclusions:

  • Quantitative modeling offers a framework for understanding disease transmission and optimizing control in congregate settings.
  • Strategic interventions, including population reduction and optimized spatial organization, are key to managing outbreaks.
  • The findings provide a basis for policy decisions in infection control for vulnerable populations.