Reconstructing the first COVID-19 pandemic wave with minimal data in the UK

Accurate measurement of exposure to SARS-CoV-2 in the population is crucial for understanding the dynamics of disease transmission and evaluating the impacts of interventions. However, it is particularly challenging to achieve this in the early phase of a pandemic because of the sparsity of epidemiological data. In our previous publication[[1][1]], we developed an early pandemic diagnostic tool that can link minimum datasets: seroprevalence, mortality and infection testing data to estimate the true exposure in different regions of England and found levels of SARS-CoV-2 population exposure are considerably higher than suggested by seroprevalence surveys. Here, we re-examined and evaluated the model in the context of reconstructing the first COVID-19 epidemic wave in England from three perspectives: validation from ONS Coronavirus Infection Survey, relationship between model performance and data abundance and time-varying case detection rate. We found that our model can recover the first but unobserved epidemic wave of COVID-19 in England from March 2020 to June 2020 as long as two or three serological measurements are given as model inputs additionally, with the second wave during winter of 2020 validated by the estimates from ONS Coronavirus Infection Survey. Moreover, the model estimated that by the end of October in 2020 the UK government’s official COVID-9 online dashboard reported COVID-19 cases only accounted for 9.1% (95%CrI (8.7%,9.8%)) of cumulative exposure, dramatically varying across two epidemic waves in England in 2020 (4.3% (95%CrI (4.1%, 4.6%)) vs 43.7% (95%CrI (40.7%, 47.3%))). ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Not applicable. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: No new data is used in this manuscript. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript [1]: #ref-1