covid: Covid incidences data

In estimateW: Estimation of Spatial Weight Matrices

Covid incidences data

Description

COVID-19 data set provided by Johns Hopkins University (Dong et al., 2020). The database contains information on (official) daily infections for a large panel of countries around the globe in the very beginning of the outbreak from 17 February to 20 April 2020.

Usage

covid

Format

A data.frame object.

Details

Data is provided for countries: Australia (AUS), Bahrain (BHR), Belgium (BEL), Canada (CAN), China (CHN), Finland (FIN), France (FRA), Germany (DEU), Iran (IRN), Iraq (IRQ), Israel (ISR), Italy (ITA), Japan (JPN), Kuwait (KWT), Lebanon (LBN), Malaysia (MYS), Oman (OMN), Republic of Korea (KOR), Russian Federation (RUS), Singapore (SGP), Spain (ESP), Sweden (SWE), Thailand (THA), United Arab Emirates (ARE), United Kingdom (GBR), United States of America (USA), and Viet Nam (VNM).

The dataset includes daily data on the country specific maximum measured temperature (Temperature) and precipitation levels (Precipitation) as additional covariates (source: Dark Sky API). The stringency index (Stringency) put forward by Hale et al. (2020), which summarizes country-specific governmental policy measures to contain the spread of the virus. We use the biweekly average of the reported stringency index.

References

Dong, E., Du, H., and Gardner, L. (2020). An interactive web-based dashboard to track COVID-19 in real time. The Lancet Infectious Diseases, 20(5), 533–534. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/S1473-3099(20)30120-1")}.

Hale, T., Petherick, A., Phillips, T., and Webster, S. (2020). Variation in government responses to COVID-19. Blavatnik School of Government Working Paper, 31, 2020–2011. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/s41562-021-01079-8")}.

Krisztin, T., and Piribauer, P. (2022). A Bayesian approach for the estimation of weight matrices in spatial autoregressive models, Spatial Economic Analysis, 1-20. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/17421772.2022.2095426")}.

Krisztin, T., Piribauer, P., and Wögerer, M. (2020). The spatial econometrics of the coronavirus pandemic. Letters in Spatial and Resource Sciences, 13 (3), 209-218. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s12076-020-00254-1")}.

Dong, E., Du, H., and Gardner, L. (2020). An interactive web-based dashboard to track COVID-19 in real time. The Lancet Infectious Diseases, 20(5), 533–534. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/S1473-3099(20)30120-1")}.

estimateW documentation built on June 8, 2025, 10:07 a.m.