Abstract
AbstractThe impact of specific risk factors for SARS-CoV-2 infection spread was investigated among the 215 municipalities in north-eastern Italy. SARS-CoV-2 incidence was gathered fortnightly since April 1, 2020 (21 consecutive periods) to depict three indicators of virus spreading from hierarchical Bayesian maps. Eight explanatory features of the municipalities were obtained from official databases (urbanicity, population density, active population on total, hosting schools or nursing homes, proportion of commuting workers or students, and percent of > 75 years population on total). Multivariate Odds Ratios (ORs), and corresponding 95% Confidence Intervals (CIs), quantified the associations between municipality features and virus spreading. The municipalities hosting nursing homes showed an excess of positive tested cases (OR = 2.61, ever versus never, 95% CI 1.37;4.98), and displayed repeated significant excesses: OR = 5.43, 3–4 times versus 0 (95% CI 1.98;14.87) and OR = 6.10, > 5 times versus 0 (95% CI 1.60;23.30). Municipalities with an active population > 50% were linked to a unique statistical excess of cases (OR = 3.06, 1 time versus 0, 95% CI 1.43;6.57) and were inversely related to repeated statistically significant excesses (OR = 0.25, > 5 times versus 0; 95% CI 0.06;0.98). We highlighted specific municipality features that give clues about SARS-CoV-2 prevention.
Publisher
Springer Science and Business Media LLC
Cited by
3 articles.
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