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This summary is machine-generated.

This study introduces a web app to optimize COVID-19 testing schedules in retirement homes, balancing resident safety and staff workload. The tool creates tailored testing strategies to detect infections efficiently.

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Area of Science:

  • Infectious disease epidemiology
  • Public health interventions
  • Operations research

Background:

  • COVID-19 significantly impacted long-term care facilities, with older residents facing higher mortality risks.
  • Regular resident testing is crucial for proactive infection detection in retirement homes (RHs).
  • Balancing staff time between testing and essential care presents a significant challenge.

Purpose of the Study:

  • To develop a web application, the Retirement Home Testing Optimizer, to aid RH managers in creating effective resident testing schedules.
  • To optimize testing strategies by grouping residents and testing no more than one group daily.

Main Methods:

  • Developed a web application incorporating resident/staff numbers, contact rates, testing time, and constraints on test intervals and group sizes.
  • Utilized mixed integer nonlinear programming to balance staff workload and minimize infection detection time.
  • Employed a fast, efficient local search method leveraging problem symmetries for optimal solutions.

Main Results:

  • The application computes optimal trade-off testing strategies, suggesting resident groupings and schedules tailored to facility constraints.
  • The tool is accessible online, open-source, and available in English and German with comprehensive guidelines.
  • Launched in July 2022, the application is currently undergoing testing in German retirement homes.

Conclusions:

  • Testing strategies are customized for each RH, aligning with manager-defined goals.
  • The model focuses on expected infection risks and does not guarantee prevention of worst-case scenarios.
  • The application provides a practical approach to managing testing logistics in long-term care settings.