The coronavirus (COVID-19) has spread through Germany between 2020 and 2024. As of April 2024, there were over 38.8 million cases recorded in the country. . Click here for more statistical data and facts on the coronavirus.

This dataset contains data regarding COVID-19 cases in Germany by Landkreise (district). It was originally published by the Robert Koch-Institut (RKI).For each Landkreis, data is available about: number of cases (cumulative), number of cases per 100 000 persons (cumulative or only the last seven days), percentage of cases (cumulative number of cases among the Landkreis population), number of deaths (cumulative) and death rate (percentage of deaths among the cases).The dataset also contains various geo-administrative information, such as populations, geographical shapes and administrative codes.Enrichment:Dates given in German format have been converted to ISO datetime.

The coronavirus (COVID-19) has led to over 183,000 deaths in Germany, as of 2024. When looking at the distribution of deaths by age, based on the figures currently available, most death occurred in the age group 80 years and older at approximately 118,938 deaths.

The coronavirus (COVID-19) epidemic in Germany began in March 2020, with high new daily case numbers still being recorded during 2023. The pandemic is ongoing.

Staying home

The coronavirus (COVID-19) outbreak was declared a pandemic by the World Health Organisation on March 11, 2020. This declaration immediately impacted life in Germany on all levels. Rising coronavirus (COVID-19) case numbers in March-April led to the swift implementation of nationwide distancing and crowd control measures to stop further spread of the virus, which primarily transferred most easily from person to person. From a large-scale economic shutdown, venue, school, daycare and university closures, to social distancing and the contact ban officially implemented by the German government, seemingly in the space of days life as the population knew it came to a standstill in the whole country.

Unlockdown

Later in April 2020, Germany began easing some of the restrictions related to the coronavirus (COVID-19) outbreak as case numbers began to drop. Elements of uncertainty remain and touch on various aspects, for example, regarding national mental and physical health, both among adults and children, the possibility of long-term effects from the virus, immunity. A rising worry among European nations was economic recovery.

As of April 2023, the coronavirus (COVID-19) tracing app was downloaded almost 21.56 million times from the Apple App Store, while the Google Play Store recorded around 27.07 million downloads. This is an official coronavirus tracing app, developed by the German government and available since June 2020. The app is voluntary.

The Coronavirus (SARS-CoV-2) outbreak, dubbed COVID-19, is first and foremost a human tragedy, affecting millions of people globally. The contagious Coronavirus, which broke out at the close of 2019, has led to a medical emergency across the world, with the World Health Organization officially declaring the novel Coronavirus a pandemic on March 11, 2020. Read More

In 2023, the coronavirus (COVID-19) is still present in Germany, affecting all of its federal states. Case numbers vary across age groups and genders. Based on current figures, among men, the most affected age group was 35-59 years. The same was true for women. These figures confirm that the virus can also affect younger age groups.

In 2020, thinking of work after the pandemic, 48 percent of German employees stated that they wanted to work from home as often as they did during the COVID-19 crisis. In contrast to this, 13 percent did not want to work from home at all. The figures are based on an online survey conducted in Germany in 2020.

The datasets included in this repository represent a pandemic severity indicator for the COVID-19 pandemic in Germany based on a composite indicator for the years 2020 and 2021. The pandemic severity index consists of three indicators: the incidence of patients tested positive for COVID-19, the incidence of patients with COVID-19 in intensive care, and the incidence of registered deaths due to COVID-19. The datasets have been developed within the CODIFF project (Socio-Spatial Diffusion of COVID-19 in Germany) at Leibniz Insitute for Research on Society and Space. The project received funding by Deutsche Forschungsgemeinschaft (DFG, project number 492338717). The datasets have been used in the following publications, in which further methodological details on the indicator can be found:

• Stabler, M., & Kuebart, A. (2023). Tempo-spatial dynamics of COVID-19 in Germany: A phase model based on a pandemic severity indicator. medRxiv, 2023-02.
• Kuebart, A., & Stabler, M. (2023). Waves in time, but not in space – An analysis of pandemic severity of COVID-19 in Germany. Spatial and Spatio-temporal Epidemiology, 2023.

This repository consists of two files:

pandemic_severity_germany

This table contains the composite indicator for daily pandemic severity for Germany on the national scale as well as the three sub-indicators for each day between 2020-03-01 and 2021-12-31. The sub-indicators were sourced from the Robert Koch Institute, the German government agency responsible for disease control and prevention.

pandemic_severity_counties

This table contains the composite indicator for daily pandemic severity for Germany on the level of the 400 individual counties, as well as the three sub-indicators for each day between 2020-03-01 and 2021-12-31. The sub-indicators were sourced from the Robert Koch Institute, the German government agency responsible for disease control and prevention. The counties can be identified by name (kreis) or by county identification number (ags5)

The Austrian ski resort of Ischgl is commonly claimed to be ground zero for the diffusion of the SARS-CoV-2 virus in the first wave of infections experienced by Germany. Drawing on data for 401 German counties, we find that conditional on geographical latitude and testing behavior by health authorities, road distance to Ischgl is indeed an important predictor of infection cases, but — in line with expectations — not of fatality rates. Were all German counties located as far from Ischgl as the most distant county of Vorpommern-Rügen, Germany would have seen about 45% fewer COVID-19 cases. A simple diffusion model predicts that the absolute value of the distance-to-Ischgl elasticity should fall over time when inter- and intra-county mobility are unrestricted. We test this hypothesis and conclude that the German lockdown measures have halted the spread of the virus.

Germany COVID-2019: Number of Deaths: To Date: CC: Hamburg data was reported at 3,706.000 Person in 21 Apr 2023. This records an increase from the previous number of 3,705.000 Person for 20 Apr 2023. Germany COVID-2019: Number of Deaths: To Date: CC: Hamburg data is updated daily, averaging 1,589.000 Person from Mar 2020 (Median) to 21 Apr 2023, with 933 observations. The data reached an all-time high of 3,706.000 Person in 21 Apr 2023 and a record low of 0.000 Person in 26 Mar 2020. Germany COVID-2019: Number of Deaths: To Date: CC: Hamburg data remains active status in CEIC and is reported by Robert Koch Institute. The data is categorized under High Frequency Database’s Disease Outbreaks – Table DE.D001: Robert Koch Institute: Coronavirus Disease 2019 (COVID-2019) (Discontinued).

Germany COVID-2019: Number of Deaths: To Date: CC: Brandenburg data was reported at 6,619.000 Person in 21 Apr 2023. This records an increase from the previous number of 6,615.000 Person for 20 Apr 2023. Germany COVID-2019: Number of Deaths: To Date: CC: Brandenburg data is updated daily, averaging 3,792.000 Person from Mar 2020 (Median) to 21 Apr 2023, with 933 observations. The data reached an all-time high of 6,619.000 Person in 21 Apr 2023 and a record low of 0.000 Person in 24 Mar 2020. Germany COVID-2019: Number of Deaths: To Date: CC: Brandenburg data remains active status in CEIC and is reported by Robert Koch Institute. The data is categorized under High Frequency Database’s Disease Outbreaks – Table DE.D001: Robert Koch Institute: Coronavirus Disease 2019 (COVID-2019) (Discontinued).

Germany COVID-2019: Number of Deaths: To Date: CC: Bavaria data was reported at 29,293.000 Person in 21 Apr 2023. This records an increase from the previous number of 29,262.000 Person for 20 Apr 2023. Germany COVID-2019: Number of Deaths: To Date: CC: Bavaria data is updated daily, averaging 15,233.000 Person from Mar 2020 (Median) to 21 Apr 2023, with 933 observations. The data reached an all-time high of 29,293.000 Person in 21 Apr 2023 and a record low of 0.000 Person in 11 Mar 2020. Germany COVID-2019: Number of Deaths: To Date: CC: Bavaria data remains active status in CEIC and is reported by Robert Koch Institute. The data is categorized under High Frequency Database’s Disease Outbreaks – Table DE.D001: Robert Koch Institute: Coronavirus Disease 2019 (COVID-2019) (Discontinued).

Germany COVID-2019: Number of Cases: To Date: CC: Thuringen data was reported at 887,661.000 Person in 21 Apr 2023. This records an increase from the previous number of 887,619.000 Person for 20 Apr 2023. Germany COVID-2019: Number of Cases: To Date: CC: Thuringen data is updated daily, averaging 128,658.000 Person from Mar 2020 (Median) to 21 Apr 2023, with 940 observations. The data reached an all-time high of 887,661.000 Person in 21 Apr 2023 and a record low of 1.000 Person in 06 Mar 2020. Germany COVID-2019: Number of Cases: To Date: CC: Thuringen data remains active status in CEIC and is reported by Robert Koch Institute. The data is categorized under High Frequency Database’s Disease Outbreaks – Table DE.D001: Robert Koch Institute: Coronavirus Disease 2019 (COVID-2019) (Discontinued).

The crisis barometer on the COVID-19 pandemic in Germany was conducted by USUMA on behalf of the Konrad Adenauer Foundation. During the survey period from 30.03.2020 to 04.07.2020, 4228 respondents aged 18 and over living in private households in Germany were interviewed by telephone (CATI) on the following topics: pessimism/optimism; trust in institutions, crisis competence of political parties, effects of the Corona crisis, reception of news about Corona, Corona disease, Sunday question. Respondents were selected through multi-stage random sampling from an ADM selection frame including landline and mobile numbers (dual-frame sampling). The study was conducted week-by-week as a rolling cross-section survey. Pessimism or optimism about the future in general and for Germany; party preference (Sunday question); confidence in institutions (state government of the federal state, federal government, European Union, federal armed forces, police, health authorities, authorities, courts, German Bundestag); most competent party to deal with the crisis; assessment of measures as appropriate, going too far, or not going far enough; expected extent of the impact of the Corona crisis for the respondent; reception frequency of news about the Corona crisis; respondent has contracted the Corona virus COVID 19 himself; number of people in his circle of acquaintances who have tested positive for the Corona virus. Demography: sex; age; education; employment status; federal state; number of people 18 years and older who also regularly use the cell phone used; number of cell phone numbers used to reach the respondent by phone; number of landline phone numbers; household size. Additionally coded were: respondent ID; day of interview; weighting factor. Das Krisenbarometer zur COVID-19-Pandemie in Deutschland wurde von USUMA im Auftrag der Konrad-Adenauer-Stiftung durchgeführt. Im Erhebungszeitraum vom 30.03.2020 bis 04.07.2020 wurden 4228 in Privathaushalten in Deutschland lebende Prsonen ab 18 Jahren in telefonischen Interviews (CATI) zu folgenden Themen befragt: Pessimismus/Optimismus; Institutionenvertrauen, Krisenkompetenz der Parteien, Auswirkungen der Corona-Krise, Rezeption von Nachrichten über Corona, Corona-Erkrankung, Sonntagsfrage. Die Auswahl der Befragten erfolgte durch eine mehrstufige Zufallsauswahl aus einem ADM-Auswahlrahmen unter Einschluss von Festnetz- und Mobilfunknummern (Dual-Frame Stichprobe). Die Studie wurde wochenweise als Rolling-Cross-Section Survey durchgeführt. Pessimismus oder Optimismus im Hinblick auf die Zukunft allgemein und für Deutschland; Parteipräferenz (Sonntagsfrage); Institutionenvertrauen (Landesregierung des Bundeslandes, Bundesregierung, Europäische Union, Bundeswehr, Polizei, Gesundheitsamt, Behörden, Gerichte, Deutscher Bundestag); kompetenteste Partei zur Bewältigung der Krise; Bewertung der Maßnahmen als angemessen, gehen zu weit oder gehen nicht weit genug; erwartetes Ausmaß der Auswirkungen der Corona-Krise für den Befragten; Rezeptionshäufigkeit von Nachrichten über die Corona-Krise; Befragter ist selbst am Corona-Virus COVID 19 erkrankt; Anzahl der positiv auf das Corona-Virus getesteten Menschen im Bekanntenkreis. Demographie: Geschlecht; Alter; Bildung; Erwerbsstatus; Bundesland; Anzahl Personen ab 18 Jahren, die das genutzte Handy ebenfalls regelmäßig nutzen; Anzahl der Handynummern, über die der Befragte telefonisch erreichbar ist; Anzahl der Festnetz-Rufnummern; Haushaltsgröße. Zusätzlich verkodet wurde: Befragten-ID; Befragungstag; Gewichtungsfaktor.

Feature service with the current Covid-19 infections per 100,000 inhabitants on the German federal states. The service is updated daily with the current case numbers of the Robert Koch Institute.

Data source: Robert Koch Institute Terms of Use: Robert Koch Institute; German Federal Agency for Cartography and Geodesy Source note: Robert Koch-Institute (RKI), dl-en/by-2-0 Disclaimer: "The content made available on the Internet pages of the Robert Koch-Institute is intended solely for the general information of the public, primarily the specialist public". Data protection declaration: "The use of the RKI website is generally possible without disclosing personal data".

Case data from 02-29-2020 to 08-16-2020, this data repository stores COVID-19 virus case data for Germany, including the daily case, summary data, and base map. Each zip file contains weekly case data from Monday to Sunday.

The Corona crisis (COVID-19) affects a large proportion of companies and freelancers in Germany. Against this background, the study examines the personal situation and working conditions of employees in Germany in times of corona. The analysis mainly refers to the situation in May 2020 and can only make limited statements about the further situation of the employed persons in the course of the corona pandemic.
1. Personal situation: change in working times during the corona crisis; current work situation (local focus of one´s own work); preference for home office; preference for future home office; financial losses due to the corona crisis; concerns about the financial and economic consequences of the corona crisis in Germany; concerns about the corona crisis in personal areas (job security, current working conditions, financial situation, career opportunities, family situation, health, psychological well-being, housing situation); support from the employer in the corona crisis.

1. Economy and welfare state: political interest; assessment of the economic situation in Germany; preferred form of government (strong vs. liberal state); agreement on various statements on the weighing of values in the Corona crisis (the restrictions on public life to protect the population from Corona are not in proportion to the economic crisis caused by it, the money now being made available for economic aid will later be lacking in other important areas such as education, infrastructure or climate protection, for politicians, the health of the population is the top priority, the interests of the economy influence them less strongly with regard to the corona crisis, the worst part of the crisis is now behind us, as a result of the economic effects of the corona crisis the contrast between rich and poor in Germany will become even more pronounced, the corona crisis affects the low earners more than the middle class, the corona crisis significantly advances the digitalisation of the world of work); perception of state action in the corona crisis on the basis of pairs of opposites (e.g. bureaucratic - unbureaucratic, passive - active, etc.); responsibility of the state to provide financial support to companies in the corona crisis; responsibility of the state to provide financial support to private individuals in the corona crisis over and above basic provision; recipients of state financial aid in the corona crisis (companies, directly to needy private individuals, companies and private individuals alike); assessment of the bureaucracy involved in state financial aid (speed vs. exact examination).

2. Measures: awareness of current measures to support business and individuals in the corona crisis; assessment of current measures to support business and individuals in the corona crisis; reliance on assistance in the corona crisis; nature of assistance used in the corona crisis; barriers to use of assistance in the corona crisis; assessment of the effectiveness of the state measures to cope with the corona crisis; appropriate additional measures to mitigate the economic consequences; concerns about the consequences of the planned state measures (increasing tax burden, rising social contributions, rising inflation, stagnating pension levels, rising retirement age, reduction of other state transfers, safeguarding savings).

3. Information: active search for information on financial assistance offers by the Federal Government in the corona crisis; self-assessment of the level of information on measures to support business and private individuals in the corona crisis; request for detailed information on state assistance measures in the corona crisis (e.g. application process, sources of funding, conditions for receiving assistance, etc.) sources of information used about state aid measures in the Corona crisis; contact with institutions offering economic and financial aid during the Corona crisis (development bank/ municipal development agency, employment agency, tax office, none of them); experience with institutions offering economic and financial aid during the Corona crisis (appropriate treatment).

4. Outlook: assessment of the future economic situation in Germany; assessment of Germany´s future as a strong business location; assessment of its own future economic situation; assessment of the duration of the economic impairment caused by the Corona crisis.

Demography: age; sex; education; employment; self-localization social class; net household income; current household income; household income before the crisis; occupational activity; belonging to systemically important occupations; number of persons in the household; number of children under 18 in the household; size of town; party sympathy; migration background.

Additionally coded: current number; federal state; education (low, medium, high); weighting factor.

Im Datensatz '7-Tage-Inzidenz von COVID-19 in Deutschland' werden die aktuellen 7-Tage-Inzidenzen der nach den Vorgaben des Infektionsschutzgesetzes - IfSG - an das RKI übermittelten COVID-19-Fälle veröffentlicht. Datengrundlage zur Berechnung der 7-Tage-Inzidenzen sind die an das RKI übermittelten COVID-19-Fälle. Eine detaillierte Dokumentation zur Erhebung der Daten zum Infektionsgeschehen ist im Datensatz 'SARS-CoV-2-Infektionen in Deutschland' enthalten. Die für die Berechnung der 7-Tage-Inzidenz notwendigen Bevölkerungsdaten bezieht das RKI durch das Statistisches Bundesamt (Destatis), Referat F24 | Bevölkerungsfortschreibung, Ausländer- und Integrationsstatistiken.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.