Abstract
Modelling the small-area spatio-temporal dynamics of the Covid-19 pandemic is of major public health importance, because it allows health agencies to better understand how and why the virus spreads. However, in Scotland during the first wave of the pandemic testing capacity was severely limited, meaning that large numbers of infected people were not formally diagnosed as having the virus. As a result, data on confirmed cases are unlikely to represent the true infection rates, and due to the small numbers of positive tests these data are not available at the small-area level for confidentiality reasons. Therefore to estimate the small-area dynamics in Covid-19 incidence this paper analyses the spatio-temporal trends in telehealth data relating to Covid-19, because during the first wave of the pandemic the public were advised to call the national telehealth provider NHS 24 if they experienced symptoms of the virus. Specifically, we propose a multivariate spatio-temporal correlation model for modelling the proportions of calls classified as either relating to Covid-19 directly or having related symptoms, and provide software for fitting the model in a Bayesian setting using Markov chain Monte Carlo simulation. The model was developed in partnership with the national health agency Public Health Scotland, and here we use it to analyse the spatio-temporal dynamics of the first wave of the Covid-19 pandemic in Scotland between March and July 2020, specifically focusing on the spatial variation in the peak and the end of the first wave.
Highlights
Jou repro of virus spreads more in certain areas.The focus of this study is Covid-19 surveillance in Scotland, which is currently in its second wave of infection since September 2020
This paper has developed a multivariate spatio-temporal model for quantifying the spread of Covid-19 in Scotland during the first wave of the pandemic, which was a period with limited testing capacity resulting in large numbers of infected people whose disease status was not confirmed by a diagnostic test
As a result we quantified the spatio-temporal dynamics of Covid-19 spread using proxy data from the national telehealth service NHS 24, who members of the public were advised to call if they experienced symptoms
Summary
The focus of this study is Covid-19 surveillance in Scotland, which is currently in its second wave of infection since September 2020 During this second wave the spatio-temporal spread of the pandemic can be measured using data on positive tests at the small-area scale, which is due to Scotland having a wide-spread testing programme during this period. Covid-19 cases will not provide a detailed picture of the spatio-temporal spread of the virus during this first wave, because only a very small fraction of the actual cases were confirmed by a positive test Due to this massive under-reporting the aim of this paper is to use proxy indicators of disease incidence to quantify the small-area spatio-temporal dynamics of the Covid-19 pandemic in Scotland during its first wave of infections. It jointly models the spatio-temporal variation in the numbers of calls to NHS 24 directly categorised as Covid-19, as well as those rna
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