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The Importance of Long-Term Care Populations in COVID-19 Models

The spread of COVID-19 is substantially different in long-term care settings than in the general population. Mathematical models of COVID-19 should reflect that difference.

Long-term care settings provide ideal conditions for the rapid spread of COVID-19, but mathematical models that governments consult when making pandemic-related policies don’t account for residents of these settings separately from surrounding populations.

That’s a big mistake, according to 3 researchers writing in JAMA.

Current COVID models calculate the number of susceptible, exposed, infectious, and recovered individuals in an entire population and use that data to predict how protective strategies like school closure and physical distancing affect virus spread.

The authors offer 3 reasons why the spread of COVID-19 is substantially different in long-term care settings than in the general population:

  • Residents of long-term care settings are particularly susceptible to COVID-19 and have higher risks of mortality if they are infected.
  • Community-wide protective measures like physical distancing cannot be implemented in long-term care settings.
  • Staff who provide intimate personal care for multiple long-term care residents can contribute to virus transmission.

These factors make it necessary to re-evaluate the assumptions upon which most COVID-19 models are based, the authors maintain. Current models that combine data from long-term settings and the surrounding community may not be giving policy makers accurate analyses, either of an outbreak’s anticipated course in long-term care settings, or of the true effect that public health measures are having on community spread.

On the other hand, models that separate long-term care settings from surrounding populations could provide more accurate analyses, and could help policy makers tailor their pandemic responses to each setting.

“Both modelers and public health policy makers should recognize that COVID-19 is not a unitary epidemic,” the authors conclude. “Creating separate models that reflect how COVID-19 has affected these different populations could provide more accurate evidence to guide mitigation efforts in the community and in long-term care facilities, and could be helpful to better understand and reduce the morbidity and mortality this infection has caused among the most frail and vulnerable individuals.”

Read the full article.