Spatial Sampling Design to Improve the Efficiency of the Estimation of the Critical Parameters of the SARS-CoV-2 Epidemic

Given the urgent informational needs connected with the diffusion of infection with regard tothe COVID-19 pandemic, in this article, we propose a sampling design for building acontinuous-time surveillance system. Compared with other observational strategies, theproposed method has three important elements of strength and originality: (1) it aims toprovide a snapshot of the phenomenon at a single moment in time, and it is designed to be acontinuous survey that is repeated in several waves over time, taking different target variablesduring different stages of the development of the epidemic into account; (2) the statisticaloptimality properties of the proposed estimators are formally derived and tested with a MonteCarlo experiment; and (3) it is rapidly operational as this property is required by theemergency connected with the diffusion of the virus. The sampling design is thought to bedesigned with the diffusion of SAR-CoV-2 in Italy during the spring of 2020 in mind.However, it is very general, and we are confident that it can be easily extended to othergeographical areas and to possible future epidemic outbreaks. Formal proofs and a MonteCarlo exercise highlight that the estimators are unbiased and have higher efficiency than thesimple random sampling scheme