COVID-19 Pandemic

See multiple data sources across 56 humanitarian operations in the COVID-19 Data Explorer

Datasets [133] | Archived Datasets[0] [?]
  • Updated 20 April 2021 | Dataset date: October 04, 2020-October 04, 2020
    Community perceptions and feedback
    100+ Downloads
    This dataset updates: Every month
  • Updated 8 September 2021 | Dataset date: January 01, 2017-July 31, 2021
    These datasets contain information on violent and threatening incidents affecting aid operations, civilians, education, health care, refugees and IDPs to ensure staff safety and better response outcomes.
    80+ Downloads
    This dataset updates: As needed
  • Updated Live | Dataset date: August 20, 2020-August 20, 2020
    CERF and CBPF pooled funds have allocated a combined total of US$222 million to COVID-19 pandemic responses.
    70+ Downloads
    This dataset updates: Live
  • Updated 29 May 2020 | Dataset date: May 25, 2020-May 25, 2020
    COVID-19 cases high risk population arrivals by state_25 May 2020
    70+ Downloads
    This dataset updates: As needed
  • Updated 11 March 2021 | Dataset date: February 03, 2021-February 03, 2021
    This dataset contains a forecast on early availability of doses of the Pfizer-BioNTech vaccine and the AstraZeneca/Oxford vaccine to COVAX Facility participants. The forecast is as at 3 February 2021. This dataset contains figures on indicative distribution of 240 million doses of the AstraZeneca/Oxford vaccine, licensed to Serum Institute of India (SII) and 96 million doses of the AstraZeneca/Oxford vaccine, under the advance purchase agreement between Gavi, the Vaccine Alliance and AstraZeneca for Q1 & Q2 2021. It also contains an overview of exceptional first round allocation of 1.2 million doses of the WHO Emergency Use Listing (EUL)-approved Pfizer-BioNTech vaccine for Q1 2021. The data was manually extracted from the The COVAX Facility Interim Distribution Forecast which was announced by COVAX on 3 February 2021.
    70+ Downloads
    This dataset updates: Never
  • Updated 16 July 2020 | Dataset date: April 29, 2020-July 16, 2020
    This dataset contains the number of confirmed cases, recoveries and deaths by admin 1 due to the Coronavirus pandemic in Ethiopia.
    300+ Downloads
    This dataset updates: As needed
  • Updated 9 December 2020 | Dataset date: December 30, 2020-December 30, 2020
    This data is a zipped shapefile of the COVID-19 risk index based on the INFORM index framework.
    40+ Downloads
    This dataset updates: Never
  • Updated 6 March 2021 | Dataset date: January 01, 2020-December 31, 2020
    UNICEF Eastern and Southern Africa Risks and Hazards- situation and response
    100+ Downloads
    This dataset updates: Never
  • Updated 26 May 2021 | Dataset date: July 16, 2020-September 18, 2020
    The participants of this phone interview were identified using mixed methods. Stratified random sampling were adopted for PoCs based in Kakuma, Kalobeyei, Dadaab and Urban areas. While a census were used for all PoCs who were 18+ years amongst the Shona community; this cohort forms 48.6% of the enumerated population of the Shona people. The survey was conducted at two levels; household and individual. For the second wave, 4390 individuals were included belonging to 1735 households.
    This dataset updates: Never
  • This dataset contains information from five waves of the COVID-19 RRPS, which is a bi-monthly panel survey that targets Kenyan nationals and refugees and started in May 2020. The same households are interviewed every two months, with interviews conducted using Computer Assisted Telephone Interviewing (CATI) techniques. Sampled households that were not reached in earlier waves were also contacted along with households that were interviewed before. The “wave” variable represents in which wave the households were interviewed in. All waves of this survey include information on household background, service access, employment, food security, income loss, transfers, health, and COVID-19 knowledge. The data set contains three files. The first is the hh file, which contains household level information. The ‘hhid’, uniquely identifies all household. The second is the adult level file, which contains data at the level of adult household members. Each adult in a household is uniquely identified by the ‘adult_ID’. The third file is child level file, which contain information for every child in the household. Each child in a household is uniquely identified by the ‘child_id’. The duration of data collection for each wave was: Wave 1: May 14 to July 7, 2020 Wave 2: July 16 to September 18, 2020 Wave 3: September 18 to November 28, 2020 Wave 4: January 15 to March 25, 2021 Wave 5: March 29 to June 13, 2021 The participants of this phone interview were identified using mixed methods. Stratified random sampling were adopted for Persons of Concern (POC) to UNHCR based in Kakuma, Kalobeyei, Dadaab and Urban areas. While a census were used for all PoCs who were 18+ years amongst the Shona community; this cohort forms 48.6% of the enumerated population of the Shona people. The survey was conducted at two levels; household and individual.
    This dataset updates: Never
  • Updated 7 April 2021 | Dataset date: March 12, 2021-March 12, 2021
    Compilation of international financial institution and economic data
    100+ Downloads
    This dataset updates: As needed
  • Further the emergence of COVID-19 and the perceived socioeconomic hardship imposed by the measures put in place to curtail the spread of the virus, the United High Commissioner for Refugees (UNHCR) in conjunction with several partners in Nigeria carried out a study to understand the socioeconomic impact of COVID-19 among Persons of Concern to UNHCR including refugees, internally displaced persons, returnees, asylum-seekers, stateless persons and community members hosting displaced populations. The study examines several dimensions including the impact of the pandemic on economic, social, cultural, civil, and political rights.
    10+ Downloads
    This dataset updates: Never
  • Updated 4 December 2020 | Dataset date: April 26, 2020-May 15, 2020
    In April and May, as a service to responders and authorities, Ground Truth Solutions (GTS) – in partnership with the Iraq Information Centre (IIC) – conducted phone interviews in Arabic with 556 returnees, refugees, and IDPs across Anbar, Dahuk, Erbil, Ninewa, Salah al-Din, and Sulaymaniyah to gauge their perspectives on information needs and channels, behaviours, trust, and the economic impact of the virus.
    This data is by request only
  • Updated 7 February 2021 | Dataset date: July 16, 2020-September 18, 2020
    The participants of this phone interview were identified using mixed methods. Stratified random sampling were adopted for PoCs based in Kakuma, Kalobeyei, Dadaab and Urban areas. While a census were used for all PoCs who were 18+ years amongst the Shona community; this cohort forms 48.6% of the enumerated population of the Shona people. The survey was conducted at two levels; household and individual. For the second wave, 4390 individuals were included belonging to 1735 households.
    This dataset updates: Never
  • Updated 28 February 2021 | Dataset date: May 14, 2020-July 07, 2020
    The participants of this phone interview were identified using mixed methods. Stratified random sampling were adopted for PoCs based in Kakuma, Kalobeyei, Dadaab and Urban areas. While a census were used for all PoCs who were 18+ years amongst the Shona community; this cohort forms 48.6% of the enumerated population of the Shona people. The survey was conducted at two levels; household and individual.
    20+ Downloads
    This dataset updates: Never
  • Updated 4 March 2021 | Dataset date: July 29, 2020-November 30, 2020
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
    30+ Downloads
    This dataset updates: As needed
  • The COVID- 19 pandemic is having an unprecedented impact on people's lives. The pandemic is no doubt evolving into an economic and labor market downturn affecting all communities. In Zambia, daily status updates by the Ministry of Health indicate that, the cumulative number of cases are nearing 2,000 (as of 10th July 2020). The pandemic has further compounded the already distressed macroeconomic outlook. Cognisant of the resultant effect on economic systems, including trade restrictions, limited mobility of people and goods, and restricted movement in and out of the refugee settlements, a multi- stakeholder rapid assessment was conducted (2,796 respondents) during the period 8th to 19th June to quantify /determine measurable impact on refugees and hosting community livelihoods. The rapid survey was conducted in Lusaka and in the three refugee settlements and hosting villages of Zambia based on stratified random sampling.
    This dataset updates: Never
  • Updated 1 February 2021 | Dataset date: July 29, 2020-November 30, 2020
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
    100+ Downloads
    This dataset updates: As needed
  • Updated 16 August 2021 | Dataset date: January 01, 2018-December 31, 2020
    Information calls to the ECU 911 with symptomatology related to the coronavirus COVID-19 by month.
    10+ Downloads
    This dataset updates: Every year
  • Updated 16 August 2021 | Dataset date: January 01, 2018-December 31, 2020
    Information calls to the ECU 911 with symptomatology related to the coronavirus COVID-19 by year.
    10+ Downloads
    This dataset updates: Every year
  • Updated 1 January 2021 | Dataset date: July 29, 2020-September 27, 2020
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
    100+ Downloads
    This dataset updates: As needed
  • Updated 4 December 2020 | Dataset date: June 07, 2020-June 14, 2020
    In June, Ground Truth Solutions in partnership with the Iraq Information Centre (IIC) conducted its second round of phone interviews with in Arabic with 545 returnees, refugees and IDPs across Anbar, Dahuk, Erbil, Ninewa, Salah al-Din, and Sulaymaniyah to understand their perspectives of the COVID-19 response.
    This data is by request only
  • The participants of this phone interview were identified using mixed methods. Stratified random sampling were adopted for PoCs based in Kakuma, Kalobeyei, Dadaab and Urban areas. While a census were used for all PoCs who were 18+ years amongst the Shona community; this cohort forms 48.6% of the enumerated population of the Shona people. The survey was conducted at two levels; household and individual. 1,332 households were reached. The survey consent rate was 51 percent. From these households, 3,529 individuals were selected and interviewed.
    This dataset updates: Never
  • The COVID- 19 pandemic is having an unprecedented impact on people's lives. The pandemic is no doubt evolving into an economic and labor market downturn affecting all communities. In Zambia, daily status updates by the Ministry of Health indicate that, the cumulative number of cases are nearing 2,000 (as of 10th July 2020). The pandemic has further compounded the already distressed macroeconomic outlook. Cognisant of the resultant effect on economic systems, including trade restrictions, limited mobility of people and goods, and restricted movement in and out of the refugee settlements, a multi- stakeholder rapid assessment was conducted (2,796 respondents) during the period 8th to 19th June to quantify /determine measurable impact on refugees and hosting community livelihoods. The rapid survey was conducted in Lusaka and in the three refugee settlements and hosting villages of Zambia based on stratified random sampling.
    This dataset updates: Never
  • Updated 26 May 2021 | Dataset date: January 15, 2021-March 25, 2021
    The participants of this phone interview were identified using mixed methods. Stratified random sampling were adopted for Persons of Concern (POC) to UNHCR based in Kakuma, Kalobeyei, Dadaab and Urban areas. While a census were used for all PoCs who were 18+ years amongst the Shona community; this cohort forms 48.6% of the enumerated population of the Shona people. The survey was conducted at two levels; household and individual.
    This dataset updates: Never
  • Updated 26 May 2021 | Dataset date: September 28, 2020-November 30, 2020
    The participants of this phone interview were identified using mixed methods. Stratified random sampling were adopted for PoCs based in Kakuma, Kalobeyei, Dadaab and Urban areas. While a census were used for all PoCs who were 18+ years amongst the Shona community; this cohort forms 48.6% of the enumerated population of the Shona people. The survey was conducted at two levels; household and individual.
    This dataset updates: Never
  • Updated 6 May 2020 | Dataset date: March 26, 2020-March 26, 2020
    Data on unmitigated(no intervention) COVID-19 scenarios for OCHA HRP countries. Simulation done by Imperial College London.
    1000+ Downloads
    This dataset updates: As needed
  • The dataset contains number of displaced persons by gender and age dis-aggregated. Dataset contains data on Covid-19, WASH, Shelter and other needs.
    200+ Downloads
    This dataset updates: Every six months
  • Updated 13 April 2020 | Dataset date: April 13, 2020-April 13, 2020
    This dataset contains information about COVID-19 health facilities and testing capacity per province in Afghanistan.
    60+ Downloads
    This dataset updates: As needed
  • Updated 4 March 2021 | Dataset date: July 29, 2020-November 30, 2020
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
    100+ Downloads
    This dataset updates: As needed
  • Updated 26 May 2020 | Dataset date: May 26, 2020-May 26, 2020
    The COVID-19 Humanitarian Exemptions to Government Measures Dataset puts together all the measures implemented by governments worldwide in response to the Coronavirus pandemic.
    100+ Downloads
    This dataset updates: As needed
  • Updated 11 September 2020 | Dataset date: July 27, 2020-August 09, 2020
    DTM relies on its network of key informants and on secondary sources to provide a weekly assessment of mobility and COVID-19 preparedness at priority locations in South Sudan. On 24 March 2020, movement restrictions have been put in place by South Sudanese (SSD) Government and its neighbours. Some border points like Renk and Kaya are reported to be near completely blocked, whilst refugees have been allowed back into SSD through places like Nimule (neighbouring Uganda [UGA]), Pagak (Ethiopia [ETH]) and Jekow (ETH). Cargo has also been largely allowed to enter South Sudan with a maximum of three passengers in trucks.
    500+ Downloads
    This dataset updates: Every two weeks
  • Updated 19 February 2021 | Dataset date: June 30, 2020-September 28, 2021
    Registry of Russian social-oriented non profit organizations recognized by the government as affected by COVID-19 and that receive government support. The Ministry of Economic Development of Russia published the register of non profit non government organizations (NGOs) that will be provided with additional measures of support. Dataset columns: name of organization, OGRN, INN, Responsible government agency, Status, Orgform. The dataset contains information about 11 208 NGOs of 85 Russian regions.
    80+ Downloads
    This dataset updates: Every year