Testing for the SARS-CoV-2 infection is critical for tracking the spread of the virus and controlling the transmission dynamics. In the early phase of the pandemic in Italy, the decentralized healthcare system allowed regions to adopt different testing strategies. The objective of this paper is to assess the impact of the extensive testing of symptomatic individuals and their contacts on the number of hospitalizations against a more stringent testing strategy limited to suspected cases with severe respiratory illness and an epidemiological link to a COVID-19 case. A Poisson regression modelling approach was adopted. In the first model developed, the cumulative daily number of positive cases and a temporal trend were considered as explanatory variables. In the second, the cumulative daily number of swabs was further added. The explanatory variable, given by the number of swabs over time, explained most of the observed differences in the number of hospitalizations between the two strategies. The percentage of the expected error dropped from 70% of the first, simpler model to 15%. Increasing testing to detect and isolate infected individuals in the early phase of an outbreak improves the capability to reduce the spread of serious infections, lessening the burden of hospitals.
To swab or not to swab? The lesson learned in italy in the early stage of the COVID-19 pandemic
Lorenzoni G.;Sciannameo V.;Urru S.;Prosepe I.;Lanera C.;Azzolina D.;Gregori D.
2021
Abstract
Testing for the SARS-CoV-2 infection is critical for tracking the spread of the virus and controlling the transmission dynamics. In the early phase of the pandemic in Italy, the decentralized healthcare system allowed regions to adopt different testing strategies. The objective of this paper is to assess the impact of the extensive testing of symptomatic individuals and their contacts on the number of hospitalizations against a more stringent testing strategy limited to suspected cases with severe respiratory illness and an epidemiological link to a COVID-19 case. A Poisson regression modelling approach was adopted. In the first model developed, the cumulative daily number of positive cases and a temporal trend were considered as explanatory variables. In the second, the cumulative daily number of swabs was further added. The explanatory variable, given by the number of swabs over time, explained most of the observed differences in the number of hospitalizations between the two strategies. The percentage of the expected error dropped from 70% of the first, simpler model to 15%. Increasing testing to detect and isolate infected individuals in the early phase of an outbreak improves the capability to reduce the spread of serious infections, lessening the burden of hospitals.Pubblicazioni consigliate
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