covid19census: U.S. and Italy COVID-19 epidemiological data and demographic and health related metrics
Claudio Zanettini,Mohamed Omar,Wikum Dinalankara,Eddie Luidy Imada,Elizabeth Colantuoni,Giovanni Parmigiani,Luigi Marchionni Department of Pathology and Laboratory Medicinel, Weill Cornell Medicine, New York, NY
Abstract
Since the beginning of the COVID-19 pandemic in 2020, there has been a tremendous accumulation of data capturing different statistics including the number of tests, confirmed cases and deaths. This data wealth offers a great opportunity for researchers to model the effect of certain variables on COVID-19 morbidity and mortality and to get a better understanding of the disease at the epidemiological level. However, in order to draw any reliable and unbiased estimate, models need to take into account also other variables and metrics available from a plurality of official and unofficial heterogenous resources. In this study, we introduce covid19census, an R package that extracts from many different repositories, and combines together COVID-19 metrics as well as other demographic, environmental, and health-related variables of United States and Italy at the county and regional-level, respectively. The package is equipped with a number of user-friendly functions that dynamically extract the data over different timepoints and contains a detailed description of the included variables. To demonstrate the utility of this tool, we used it to extract and combine different county-level data from the US which we subsequently used to model the effect of diabetes on COVID-19 mortality at the county-level taking into account other variables that may influence such effect. In conclusion, the covid19census package allows to easily extract area-level data from both the USA and Italy using few functions. This comprehensive data can be used to provide reliable estimates of the effect of certain variables on COVID-19 outcomes.
Keywords: R,COVID19,mortality,cases,Italy,US