“The expediency of local modelling to aid national responses to SARS-CoV-2.”

  1. Bernard M. Groen
  2. Paul Turner
  3. Peter Lacey

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Abstract

Background

With the SARS-CoV-2 pandemic gripping most of the globe, healthcare and economic recovery strategies are being explored currently as a matter of urgency. The underpinning rationale of this paper is that we believe that health and care services are provided locally, therefore, local implications of national policy need to be reflected when informing national responses to the SARS-CoV-2 pandemic.

Methods

We adopted the assumptions underlying the United Kingdom government’s national epidemiological model which influences the national policy response to the SARS-CoV-2 pandemic. We used these in a local context and show projections in terms of presentations of symptomatic patients differ in a variety of settings. Setting: North of England, United Kingdom, population modelled at four local constituent levels which aggregated gives a total population of 3.2m .

Results

We clearly demonstrate that there is significant difference in the way the national modelling outputs are replicated at local levels. Specifically, in terms of projected increased levels of demand for services on the local health and care systems.

Conclusions

We present significant evidence of differing timelines specifically in terms of subsequent projected peak demands. Additionally, it clearly indicates varying levels of such demand throughout the four modelled localities. These idiosyncrasies are ‘masked’ by both regional and national approaches to modelling. We urge readers to ensure that any national policy is appropriately adopted through the use of complementary bottom up approach, to suit local health and care systems. Finally, we share our methodology to ensure other professionals could replicate this study elsewhere.

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    SciScore for 10.1101/2020.05.27.20107656: (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: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.05.27.20107656 on medRxiv