A modelling study across the Italian regions: Lockdown, testing strategy, colored zones, and skew-normal distributions. How a numerical index of pandemic criticality could be useful in tackling the CoViD-19.

Stefano De Leo (1) , Manoel P. Araújo (2)
(1) Department of Applied Mathematics, Campinas State University, Brazil , Brazil
(2) Department of Applied Mathematics, Campinas State University, Brazil , Brazil

Abstract

Background: As Europe is  facing the  second wave of the CoViD-19 pandemic, each country should carefully review how it  dealt with  the first wave of outbreak. Lessons from the first experience should be useful  to avoid  indiscriminate closures and, above all, to determine  universal (understandable)  parameters to guide the  introduction of containment measures to reduce the spreading of the virus.


Objective: The use of  few (effective) parameters is indeed of extreme importance to create a link between authorities and population, allowing the latter to understand the reason for some restrictions and, consequently, to allow an active participation in the fight against the pandemic.


Methods: Testing strategies, fitting skew parameters (as mean, mode, standard deviation, and skewness), mortality rates,  and  weekly CoViD-19 spreading data, as more people are getting infected,  were used to compare the first wave of the outbreak  in the Italian regions and to determine which parameters have to be checked before introducing  restrictive containment measures.


Results: We propose few universal parameters that, once appropriately  weighed, could  be useful to correctly differentiate the pandemic situation in the national territory  and to rapidly assign the properly pandemic risk to each region.


 

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Authors

Stefano De Leo
Manoel P. Araújo
Leo, S. D. ., & Araújo, M. P. . (2021). A modelling study across the Italian regions: Lockdown, testing strategy, colored zones, and skew-normal distributions. How a numerical index of pandemic criticality could be useful in tackling the CoViD-19. Jour Med Resh and Health Sci, 4(7), 1356–1376. https://doi.org/10.15520/jmrhs.v4i7.382
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