[Analysis and future scenarios of the SARS-CoV-2 epidemic in Tuscany Region (Central Italy)]

Abstract

Objectives: about two months after the end of the lockdown imposed for the containment of the SARS-CoV-2 epidemic, the contagion dynamics in the Tuscany Region (Central Italy) have been assessed from the beginning of the emergency to the end of June through a compartmental model, and future medium-long term projections have been produced.

Data and methods: this study used a SIRD model in which the infection reproduction number R0 varied over time, according to a piecewise constant function. The fatality parameter and the time from contagion to infection resolution (death or recovery) were fixed to ensure parameter identifiability, and the model was calibrated on the Covid-19 deaths notified from March 9th to June 30th 2020. The uncertainty around the estimates was quantified through parametric bootstrap. Finally, the resulting model was used to produce medium-long term projections of the epidemic dynamics.

Results: the date of the first infection in Tuscany was estimated as February 21st 2020. The value of R0(t) ranged from 7.78 (95%CI 7.55-7.89), at the beginning of the outbreak, to a value very close to 0 between April 27th and May 17th. Finally, R0(t) rose, reaching an average of 0.66 (0.32, 0.88) between May 18th and June 30th. At the epidemic peak, estimated at the beginning of April, the notified infected people circulating in the region were just 22% of those predicted by the model. According to the estimated SIRD, under the hypothetical scenario that R0(t) slightly exceeds 1 from the beginning of October 2020, a new wave of contagion could arise by next spring.

Conclusions: the estimated trend of R0(t) is suggestive of a strong effect of the lockdown in Tuscany and of a mild increase of the contagion potentially attributable to the easing of the containment measures. Medium-long term projections unequivocally indicate that the danger of a new epidemic wave has not been averted.

Keywords: SIRD; basic reproduction number; compartmental models; projections SARS-CoV-2..