The Effectiveness of Non Pharmaceutical Interventions in Reducing the Outcomes of the COVID-19 Epidemic in the UK, an Observational and Modelling Study [post]

Giorgos Galanis, Corrado Di Guilmi, David Bennett, Georgios Baskozos
2021 unpublished
Background: the context and purpose of the studyEpidemiological models used to inform government policies aimed to contain the contagion of COVID-19, assume that the reproduction rate is reduced through Non-Pharmaceutical Interventions (NPIs) leading to physical distancing. Available data in the UK show an increase in physical distancing before the NPIs were implemented and a fall soon after implementation. We aimed to estimate the effect of people's behaviour on the epidemic curve and the
more » ... t of NPIs taking into account this behavioural component. Methods: how the study was performed and statistical tests usedWe have estimated the effects of confirmed daily cases on physical distancing and we used this insight to design a bevavioural SEIR model (BeSEIR), simulated different scenaria regarding NPIs and compared the results to the standard SEIR. Results: the main findingsTaking into account behavioural insights improves the description of the contagion dynamics of the epidemic significantly. The BeSEIR predictions regarding the number of infections without NPIs were several orders of magnitude less than the SEIR. However, the BeSEIR prediction showed that early measures would still have an important influence in the reduction of infections. The BeSEIR model shows that even with no intervention the percentage of the cumulative infections within a year will not be enough for the epidemic to resolve due to a herd immunity effect. On the other hand, a standard SEIR model significantly overestimates the effectiveness of measures. Conclusions:Without taking into account the behavioural component, the epidemic is predicted to be resolved much sooner than when taking it into account and the effectiveness of measures are significantly overestimated.
doi:10.21203/ fatcat:cmdqfygnkvcuta3vik4oygl7qq