A structured model for COVID-19 spread: modelling age and healthcare inequities

  1. A James
  2. M J Plank
  3. R N Binny
  4. A Lustig
  5. K Hannah
  6. S C Hendy
  7. N Steyn

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Abstract

We use a stochastic branching process model, structured by age and level of healthcare access, to look at the heterogeneous spread of COVID-19 within a population. We examine the effect of control scenarios targeted at particular groups, such as school closures or social distancing by older people. Although we currently lack detailed empirical data about contact and infection rates between age groups and groups with different levels of healthcare access within New Zealand, these scenarios illustrate how such evidence could be used to inform specific interventions. We find that an increase in the transmission rates among children from reopening schools is unlikely to significantly increase the number of cases, unless this is accompanied by a change in adult behaviour. We also find that there is a risk of undetected outbreaks occurring in communities that have low access to healthcare and that are socially isolated from more privileged communities. The greater the degree of inequity and extent of social segregation, the longer it will take before any outbreaks are detected. A well-established evidence for health inequities, particularly in accessing primary healthcare and testing, indicates that Māori and Pacific peoples are at a higher risk of undetected outbreaks in Aotearoa New Zealand. This highlights the importance of ensuring that community needs for access to healthcare, including early proactive testing, rapid contact tracing and the ability to isolate, are being met equitably. Finally, these scenarios illustrate how information concerning contact and infection rates across different demographic groups may be useful in informing specific policy interventions.

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  1. Version published to 10.1093/imammb/dqab006
  2. Version published to 10.1101/2020.05.17.20104976v3 on medRxiv
  3. Version published to 10.1101/2020.05.17.20104976v2 on medRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.05.17.20104976: (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:
    There are some important caveats to this work. While we have endeavoured to consider scenarios that are consistent with existing evidence, for the most part the current evidence base is currently too thin to draw firm conclusions, particularly around school closures. Nonetheless, it is anticipated that better information on contact rates for various groups in New Zealand will be available soon. This study illustrates how such information will allow us to better understand the risk factors for specific communities in New Zealand and how specific control measures might reduce the impact on these communities. The age-structured model used very coarse age classes. This allows investigation of school closures or other policy interventions that differentially affect transmission in different age groups. However, these coarse age classes are likely to contain significant heterogeneity in variables such as occupation, as well as masking finer-scale contact structures. The model framework allows finer age classes once sufficient data is available to parameterise contact rates under different control interventions and epidemiological parameters (e.g. proportion of subclinical cases) for these groups. We examined age structure and inequities in access to healthcare as two separate scenarios. These could be combined by stratifying the population by age and level of healthcare access simultaneously. Again this would require more detailed data to parameterise the contact structure for the ...

    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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  5. Version published to 10.1101/2020.05.17.20104976v1 on medRxiv