Author: Livio Fenga
Title: CoViD--19: An Automatic, Semiparametric Estimation Method for the Population Infected in Italy Document date: 2020_3_18
ID: hhj7zte1_45
Snippet: In order to give the reader the opportunity to gain a better insight, in Figure 2 -5 the time series of the variable C (see Eqn. 2) is reported for each region. Note that sudden variations (i.e. Bolzano in Figure 5 , Valle D'Aosta in Figure 4 and Molise and CAmpania in Figure 3 ) are due to the little number of test administrated (denominator of the variable C T (2)) That said, the main result of the paper is summarized by Table 2 , where three e.....
Document: In order to give the reader the opportunity to gain a better insight, in Figure 2 -5 the time series of the variable C (see Eqn. 2) is reported for each region. Note that sudden variations (i.e. Bolzano in Figure 5 , Valle D'Aosta in Figure 4 and Molise and CAmpania in Figure 3 ) are due to the little number of test administrated (denominator of the variable C T (2)) That said, the main result of the paper is summarized by Table 2 , where three estimates of the number of infected people are reported by region. The regions belonging to the set Ω • (i.e. no deaths) are in Italics (all the others belong to the set Ω • ). In the column "Mean" and Lower (Upper) Bounds the bootstrap estimates computed according to Eqn 5 and 6 and the Lower (Upper) Bounds the lower (upper) bootstrap CIs are respectively reported. The column denominated "Official Cases" accounts for the number of official cases released by the Italian Authorities whereas the column "Morbidity" expresses the percentage ratio between µ • (5) or µ • (6) and the actual population of each region.
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