Introduction to and spread of COVID-19-like illness in care homes in Norfolk, UK

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Abstract

Background

Residential care homes for the elderly are important settings for transmission of the SARS-CoV-2 virus that causes COVID-19 disease.

Methods

We undertook secondary analysis of 248 care homes in Norfolk, UK. The dataset counted nurses, care workers and non-care workers, their status (available, absent due to leave or sickness and extra staff needed to address the coronavirus pandemic) and residents (if any) with suspected COVID-19 in the period 6 April to 6 May 2020. Concurrent descriptions of access by the home to personal protection equipment (PPE: gloves, masks, eye protection, aprons and sanitizer) were in the data. PPE access was categorized as (most to least) green, amber or red. We undertook two-stage modelling, first for suspected COVID-19 cases amongst residents and second relating any increases in case counts after introduction to staffing or PPE levels.

Results

Counts of non-care workers had strongest relationships (P < 0.05) to introduction of suspected SARS-CoV-2 to the homes. Higher staff levels and more severe PPE shortages were linked to higher case counts (P < 0.05) during the monitoring period.

Conclusion

Managing aspects of staff interaction with residents and some working practices might reduce ingression to and spread of COVID-19-like illness within care homes.

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  1. SciScore for 10.1101/2020.06.17.20133629: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations: It is interesting that the data for infection were under-dispersed whilst those for spread were over-dispersed. The former outcome (whether or not a care home had any COVID-19) provides a good justification for using the Cox-proportional hazards model since infection was clearly not a straightforward binomial event; many more events should have occurred for this error structure to have been appropriate for the data. However, in reality, there is likely to have been a spatial component to the existence of disease in the wider community that would have meant that the binomial error model would have been inappropriate without consideration of spatial variation in community. Spatial and social network data interaction between homes were not available to us but would strengthen any future modelling efforts. Lack of ethnic diversity in Norfolk meant we could not consider whether minority ethnic composition was a factor in disease spread or severity; ethnic diversity seems to be important to disease outcomes among affected care homes in other localities [5]. Considerable efforts have been undertaken to increase supplies of PPE to UK care homes since these April 2020 data were collected [27]. Improvements in procurement processes and supply chains may have changed the balance of future risk factors from what we see in these April 2020 data.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

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