Newswise — ITHACA, N.Y. – Epidemiological models of COVID-19 that are used to guide policies on social distancing measures should take into account the special dynamics of the coronavirus’s spread in nursing homes and other long-term care facilities, according to researchers at Cornell University and Weill Cornell Medicine.
The researchers published a commentary in the Journal of the American Medical Association, noting that conditions in long-term care facilities tend to be highly conducive to the spread of SARS-CoV-2, the coronavirus that causes COVID-19.
These facilities have accounted for a vastly disproportionate number of COVID-19 cases, as well as COVID-19 deaths – more than 40% of deaths from the disease in the United States overall, while long-term care facilities house only a small percentage of the population – and more than 80% of COVID-19 deaths in some states.
Despite this, prominent epidemiological models that many national governments have used to guide their COVID-19 policy responses, including social distancing policies, have treated long-term care populations as if they are identical to surrounding populations – likely with adverse consequences for both, the researchers said.
“This is really a tale of two pandemics – a very intense one in long-term care facilities, and a much more varied on in the wider community – yet these influential models have failed to distinguish between the two,” said lead author Karl Pillemer, professor of human development at Cornell and professor of gerontology at Weill Cornell Medicine.
As the researchers note in their commentary, the most prominent and influential COVID-19 models work by estimating the numbers of susceptible, exposed, infectious and recovered people in a given population.
These models can take into account the way that major factors such as age alter the risks faced by virus-exposed people – for example, the risk of developing serious COVID-19 illness that requires hospitalization, or of dying from that illness. They may also break down a national population into different state or provincial populations to model the effects of local disease-control policies.
However, these models have not distinguished between the general population and the uniquely vulnerable population that resides in nursing homes and other long-term care facilities. The latter typically are older and relatively immobile, have age-related diseases such as dementia, and are the likeliest to perish when they get COVID-19, with case-fatality rates of 20% or more. Social distancing and isolation measures aren’t feasible for most of these individuals, due to their frailty and the density of their living arrangements – in which a single infected resident or caregiver may quickly infect everyone else. In this vulnerable, cloistered population, policies aimed at preventing COVID-19 spread in the wider community may have little or no effect, or even an adverse effect.
For more information, see this Cornell Chronicle story.
Please find other experts at Cornell available to discuss the coronavirus crisis from a science and public health perspective, for its impact on the economy and in the ways the pandemic is changing our daily lives and affecting countries around the world.
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Journal of the American Medical Association