Background: Understanding the trend of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) is becoming crucial. Previous studies focused on predicting COVID-19 trends, but few papers have considered models for disease estimation and progression based on large real-world data.
Methods: We used de-identified data from 60,938 employees of a major financial institution in Italy with daily COVID-19 status information between 31 March 2020 and 31 August 2021.
Surface heat fluxes of the Adriatic Sea are estimated for the period 1998-2001 through bulk formulae with the goal to assess the uncertainties related to their estimations and to describe their interannual variability. In addition a comparison to observations is conducted. We computed the components of the sea surface heat budget by using two different operational meteorological data sets as inputs: the ECMWF operational analysis and the regional limited area model LAMBO operational forecast.
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