Covid-19 Mortality Rates in Northamptonshire UK: Initial Sub-regional Comparisons and Provisional SEIR model of First Wave Disease Spread
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Abstract
We analysed mortality rates in a non-metropolitan UK subregion (Northamptonshire) using statistically-weighted data fitted to the start of the epidemic to quantify SARS-CoV-2 disease fatalities at sub 1,000,000 population levels. Using parameter estimates derived from the recorded mortality data, a numerical (SEIR) model was developed to predict the spread of Covid-19 sub regionally. Model outputs, including analysis of transmission rates and the basic reproduction number, suggest national lockdown flattened the curve and reduced potential deaths by up to 4000 locally. The modelled number of infected and recovered individuals is higher than official estimates, and a revised form of the theoretical critical population fraction requiring immunisation is derived. Combining published (sub-regional) mortality rate data with deterministic models on disease spread has the potential to help public health practitioners refine bespoke mitigation plans guided by local population demographics.
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SciScore for 10.1101/2020.07.30.20165399: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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: 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 …
SciScore for 10.1101/2020.07.30.20165399: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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: 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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