The number of COVID-19 cases in Spain amounted to around 13.9 million as of June 28, 2023. As of that date, the Spanish authorities had confirmed approximately 121,760 deaths as a result of complications stemming from the disease, most of them reported in Madrid and Catalonia, with 21,361 deaths and 21,241 casualties related to COVID-19, respectively.Find the most up-to-date information about the coronavirus pandemic in the world under Statista’s COVID-19 facts and figures site.

The state of alarm decreed by the Spanish government to deal with the pandemic caused by SARS-Cov-2 ended on *************. This allowed citizens to regain freedom of movement, establishing the new normal. Since then, more than *** of the new outbreaks detected in the national territory are still active as of ***************. The Region of Valencia is the Spanish autonomous community most affected at the moment, with more than *** cases.

This repository contains COVID-19 data for Spain, including daily cases at the level of autonomous communities as well as provinces, and higher spatial resolution for several autonomous communities (eight out of the nineteen autonomous communities publish reports with local daily COVID-19 cases at the level of municipalities or Basic Health Areas).

Each record has an identifier, the associated date, the corresponding identifier of the layer and code of the region and a set of COVID-19 related fields, which include the number of new cases (daily incidence) and total cases.

• Autonomous Communities: ES.covid_cca

• Provinces: ES.covid_cpro

• Higher spatial resolution:

  • Principado de Asturias: 03.covid_cumun

  • Cantabria: 06.covid_cumun

  • Castilla y Leon: 07.covid_abs

  • Cataluña/Catalunya: 09.covid_abs

  • Comunitat Valenciana: 10.covid_cumun

  • Comunidad de Madrid: 13.covid_abs

  • Comunidad Foral de Navarra: 15.covid_abs

  • País Vasco/Euskadi: 16.covid_abs

For information about data sources, visit: https://flowmaps.life.bsc.es/flowboard/data

Raw data belonged to the study: "The sharing of research data facing the COVID-19 pandemic"

This data-set contains daily aggregations of the hourly data provided by MITMA, aggregated at different levels of spatial resolution.

Maestra 1: Origin-Destination matrix for the mobility layer, with hourly resolution Each entry has a date and time period (the range between two consecutive hours), the origin and destination zones and the number of trips from origin to destination. Origin and destination zones correspond to geometries from the MITMA mobility layer and internal trips (same layer of origin and destination) are also reported.

Maestra 2: Trips per person matrix on each mobility area on a daily basis. This indicator reports population-based daily mobility behavior. For each date and zone from the MITMA mobility layer, the indicator reports how many persons have performed 0, 1, 2 or more than 2 trips. While the indicator does not provide the destination of the trips, it accounts for the fractions of people performing at least one trip or none, as well as the estimated total population in that zone for the given date (considering as population those persons who stay overnight in the zone on that date).

Original data records come from a study conducted by the MITMA, which analyses the mobility and distribution of the population in Spain from February 14th 2020 to May 9th 2021. The study is based on a sample of more than 13 million anonymised mobile phone lines provided by a single mobile operator whose subscribers are evenly distributed.

For more information visit: https://flowmaps.life.bsc.es/flowboard/data and https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data.

We analysed whole blood and nasopharyngeal swabs from COVID-19 patients in two different cohorts collected at hospitals in Germany (Bochum) and Spain (Valencia) by epigenetic immune cell quantification using qPCR assays (demethyl-specific). The aim was to investigate the prognostic potential of this approach to identify patients with higher risk for a poor outcome. Also, we compared epigenetic data of patients with those of healthy donors.

Dataset includes Cp (crossing-point) values, cell specific plasmid units (PU) per qPCR reaction resulting from epigenetic qPCR analyses (calculated based on a quantification standard), as well as coefficient of variation (C.V.). PUs were translated into immune cell counts relative to the housekeeping gene GAPDH (glyceraldehyde 3-phosphate dehydrogenase) for each sample (peripheral whole blood, dried blood spots and swabs). GAPDH is also targeted by an epigenetic qPCR assay to quantify all GAPDH PUs.

All samples were lysed to extract genomic DNA. Afterwards, DNA was incubated with ammonium-bisulfite to convert all unmethylated CpGs (cytosin-guanine-dinucleotide) to uracil residues by deamination and desulphonation reaction without alteration of methylated CpGs. Within the subsequent epigenetic qPCR generated uracils are changed to thymine by proof-reading capability of the used DNA-Polymerase.

The epigenetic qPCR assays consist of demethyl-specific primer pairs and probes to detect cell type-specific demethylation within genes of interest.

Due to the coronavirus (COVID-19) outbreak, the attributable profit of six of the largest Spanish banks presented a negative year-on-year variation in 2020. Sabadell, with headquarters in the Spanish autonomous community of Region of Valencia, reported the second largest profit loss as its attributable profit fell nearly 73 percent compared to 2019. BBVA recorded the third largest variation, -62.9 percent. This is one of the countless impacts of the coronavirus pandemic in Spain.