An improved method to estimate the effective reproduction number of the COVID-19 pandemic: lessons from its application in Greece
Abstract
Introduction
Monitoring the time-varying effective reproduction number R t is crucial for assessing the evolution of the COVID-19 pandemic. We present an improved method to estimate R t and its application to routine surveillance data from Greece.
Methods
Our method extends that of Cori et al (2013), adding Bayesian imputation of missing symptom onset dates, imputation of infection times using an external estimate of the incubation period, and an adjustment for reporting delay. To facilitate its use, we provide an R software package named “bayEStim”. We applied the method to COVID-19 surveillance data from Greece, and examined the resulting R t estimates in relation to control measures applied, in order to assess their effectiveness. We also associated R t , as a measure of transmissibility, to population mobility as recorded in Google data and to ambient temperature. We used a serial interval between 4 and 7.5 days, and a median incubation period of 5.1 days.
Results
In Greece R t fell rapidly as the first control measures were introduced, dropping below 1 at least a week before a full lockdown came into effect. In mid-July R t started increasing again, as increased mobility associated with tourism activity was observed. Each 10% of increase in relative mobility increased R t by 8.1% (95% CrI 6.1–10.2%), whereas each unit celsius of temperature increase decreased R t by 4.6% (95% CrI 5.4–13.7%).
Conclusions
Mobility patterns significantly affect R t . Most of the reduction in COVID-19 transmissibility in Greece occurred already before the lockdown, likely as a result of decreased population mobility. Lower viral transmissibility in summer does not appear sufficient to counterbalance the increased mobility due to tourism. Monitoring R t is an essential component of COVID-19 surveillance, and it is crucial for correctly assessing the effect of control measures.
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