CoViD-19: an automatic, semiparametric estimation method for the population infected in Italy

PeerJ. 2021 Mar 4:9:e10819. doi: 10.7717/peerj.10819. eCollection 2021.

Abstract

To date, official data on the number of people infected with the SARS-CoV-2-responsible for the Covid-19-have been released by the Italian Government just on the basis of a non-representative sample of population which tested positive for the swab. However a reliable estimation of the number of infected, including asymptomatic people, turns out to be crucial in the preparation of operational schemes and to estimate the future number of people, who will require, to different extents, medical attentions. In order to overcome the current data shortcoming, this article proposes a bootstrap-driven, estimation procedure for the number of people infected with the SARS-CoV-2. This method is designed to be robust, automatic and suitable to generate estimations at regional level. Obtained results show that, while official data at March the 12th report 12.839 cases in Italy, people infected with the SARS-CoV-2 could be as high as 105.789.

Keywords: Autoregressive metric; Covid-19; Maximum entropy bootstrap; Model uncertainty; Number of Italian people infected.

Grants and funding

The author received no funding for this work.