A preprint, an un-published non peer-reviewed study posted on the Harvard University website, looked at hospital traffic and search engine data in Wuhan in Autumn 2019 to infer possible outbreaks of COVID-19.
Prof Keith Neal, Emeritus Professor of the Epidemiology of Infectious Diseases, University of Nottingham, said:
“The comment that children’s hospitals were affected in the following section suggests this probably was not COVID-19:
“We obtained data on influenza-like illness from two sentinel hospitals in Wuhan: the Children’s Hospital of Wuhan and Wuhan No. 1 Hospital, from Kong et al. (2020)16. The authors state that ILI trends noted in these two hospitals represent the overall trend in the local population. The two hospitals are the largest pediatric hospital in Hubei and a major general hospital, respectively. Counts of confirmed COVID-19 cases in Wuhan were aggregated from an open access repository of global line-list disease data17.”
Professor Paul Digard, Chair of Virology, University of Edinburgh, said:
“This study is currently a preprint and so has not undergone peer-review. Using search engine data and satellite imagery of hospital traffic to detect disease outbreaks is an interesting idea with some validity. However, it’s important to remember that the data are only correlative and (as the authors admit) cannot identify the cause of the uptick. By focussing on hospitals in Wuhan, the acknowledged epicentre of the outbreak, the study forces the correlation. It would have been interesting (and possibly much more convincing) to have seen control analyses of other Chinese cities outside of the Hubei region.”
‘Analysis of hospital traffic and search engine data in Wuhan China indicates early disease activity in the Fall of 2019’ by Nsoesie et al is posted on the Harvard website. This is a preprint (not peer-reviewed work).
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