‘Dark matter’, second waves and epidemiological modelling

Bibliographic Data

ID21880763
AuthorsKarl J Friston (0000-0001-7984-8909, Queen Mary University of London, corresponding author), Anthony Costello (0000-0002-0460-4245, University College London), Deenan Pillay (0000-0003-3640-2573, Faculty (United Kingdom))
Year2020
Volume5
Issue12
Pagese003978
Publication date2020-12-01
Open AccessYes
TypeARTICLE
VenueBMJ Global Health (JOURNAL)
Journal identifiersISSN: 2059-7908 • E-ISSN: 2059-7908
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2020-003978
PMID33328201
OpenAlexW3110669826
LanguageEN
Citations received3
References cited48

Recent reports using conventional Susceptible, Exposed, Infected and Removed models suggest that the next wave of the COVID-19 pandemic in the UK could overwhelm health services, with fatalities exceeding the first wave. We used Bayesian model comparison to revisit these conclusions, allowing for heterogeneity of exposure, susceptibility and transmission. We used dynamic causal modelling to estimate the evidence for alternative models of daily cases and deaths from the USA, the UK, Brazil, Italy, France, Spain, Mexico, Belgium, Germany and Canada over the period 25 January 2020 to 15 June 2020. These data were used to estimate the proportions of people (i) not exposed to the virus, (ii) not susceptible to infection when exposed and (iii) not infectious when susceptible to infection. Bayesian model comparison furnished overwhelming evidence for heterogeneity of exposure, susceptibility and transmission. Furthermore, both lockdown and the build-up of population immunity contributed to viral transmission in all but one country. Small variations in heterogeneity were sufficient to explain large differences in mortality rates. The best model of UK data predicts a second surge of fatalities will be much less than the first peak. The size of the second wave depends sensitively on the loss of immunity and the efficacy of Find-Test-Trace-Isolate-Support programmes. In summary, accounting for heterogeneity of exposure, susceptibility and transmission suggests that the next wave of the SARS-CoV-2 pandemic will be much smaller than conventional models predict, with less economic and health disruption. This heterogeneity means that seroprevalence underestimates effective herd immunity and, crucially, the potential of public health programmes

Biology · Disease · Environmental health · Geography · Herd immunity · Pandemic · Population · Seroprevalence · COVID-19 and healthcare impacts · COVID-19 epidemiological studies · COVID-19 Pandemic Impacts · Demography · Medicine · Epidemiology · Immunology

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