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How does the community COVID-19 level of risk impact on that of a care home?

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  • Glenna Nightingale
  • Megan Laxton
  • Janine B Illian

Abstract

Objectives: To model the risk of COVID-19 mortality in British care homes conditional on the community level risk. Methods: A two stage modeling process (“doubly latent”) which includes a Besag York Mollie model (BYM) and a Log Gaussian Cox Process. The BYM is adopted so as to estimate the community level risks. These are incorporated in the Log Gaussian Cox Process to estimate the impact of these risks on that in care homes. Results: For an increase in the risk at the community level, the number of COVID-19 related deaths in the associated care home would be increased by exp (0.833), 2. This is based on a simulated dataset. In the context of COVID-19 related deaths, this study has illustrated the estimation of the risk to care homes in the presence of background community risk. This approach will be useful in facilitating the identification of the most vulnerable care homes and in predicting risk to new care homes. Conclusions: The modeling of two latent processes have been shown to be successfully facilitated by the use of the BYM and Log Gaussian Cox Process Models. Community COVID-19 risks impact on that of the care homes embedded in these communities.

Suggested Citation

  • Glenna Nightingale & Megan Laxton & Janine B Illian, 2021. "How does the community COVID-19 level of risk impact on that of a care home?," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-8, December.
    • Handle: RePEc:plo:pone00:0260051
    DOI: 10.1371/journal.pone.0260051
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    References listed on IDEAS

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    1. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
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