Updated
12 October 2020
| Dataset date: September 12, 2020-September 12, 2020
This dataset updates: As needed
The INFORM COVID-19 Risk Index is a composite index that identifies: “countries at risk from health and humanitarian impacts of COVID-19 that could overwhelm current national response capacity, and therefore lead to a need for additional international assistance”.
The INFORM COVID-19 Risk Index is primarily concerned with structural risk factors, i.e. those that existed before the outbreak. It can be used to support prioritization of preparedness and early response actions for the primary impacts of the pandemic, and identify countries where secondary impacts are likely to have the most critical humanitarian consequences.
The main scope of the INFORM COVID-19 Risk Index is global and regional risk-informed resource allocation, i.e. where comparable understanding of countries’ risk is important. It cannot predict the impacts of the pandemic in individual countries. It does not consider the mechanisms behind secondary impacts - for example how a COVID-19 outbreak could increase conflict risk.
Updated
4 March 2021
| Dataset date: July 29, 2020-September 27, 2020
This dataset updates: As needed
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.
Updated
Live
| Dataset date: January 01, 2020-December 05, 2021
This dataset updates: Live
Aid funding related to the global COVID-19 pandemic, as published via the International Aid Transparency Initiative. This data is a result of a collaboration between the Centre for Humanitarian Data and USAID, and is the basis for the IATI COVID-19 Funding Dashboard and related data story.
For more information about data licensing, see https://data.humdata.org/viz-iati-c19-dashboard/about#licensing
Updated
11 March 2021
| Dataset date: February 03, 2021-February 03, 2021
This dataset updates: Never
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.
Updated
7 November 2021
| Dataset date: June 01, 2020-July 16, 2020
This dataset updates: Never
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.
Updated
2 November 2021
| Dataset date: March 12, 2021-March 31, 2021
This dataset updates: Every six months
The dataset contains IDPs, Returnees and Refugees at sub national level with information on IDPs in camps and host communities.
IOM set up and rolled out the first round of the DTM in November 2015 with the objective of providing regular, accurate and updated information on displaced populations within the Far North region of Cameroon to better support the response of the Government of Cameroon and the humanitarian community.
Updated
1 December 2021
| Dataset date: September 01, 2021-December 05, 2021
This dataset updates: Every day
This dataset contains World Bank COVID-19 Vaccine financing support, the Gavi COVID-19 Delivery Support (early access), and the GAVI CDS (early access) Disbursed for selected countries.
Updated
4 March 2021
| Dataset date: July 29, 2020-November 30, 2020
This dataset updates: As needed
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.
Updated
5 November 2021
| Dataset date: June 01, 2019-December 05, 2021
This dataset updates: Every month
Raw Global 3W national data visualized in the Global Humanitarian Operational Presence Who, What, Where (3W) Portal as of 05 November 2021
Fields:
'country code' -- example 'UKR' for Ukraine
'sector' -- example 'CCCM' = Camp Coordination / Management
'organization' -- Organization name provided in the field inputs
'type' -- INGO (International NGO), NNGO (National NGO), UN (United Nations), 'Undefined', or 'Other'
'COVID 19' -- 'yes' / 'no' (pertaining to the context): Field DISCONTINUED as of November 2021!!!!
'3W date' -- date of data applicability
'Display Name' -- Organization name - standardized as much as possible
Note these intended to be cleaned and standardized, though language variations (such as "Acción Contra el Hambre" / "Action Against Hunger" / "Action Contre La Faim"), and national offices of international organizations (such as "Caritas Internationalis - Nigeria" / "Caritas Internationalis - Switzerland") are preserved.
Note also that the names of some organizations working in Protection have been suppressed.
Users with questions are encouraged to use the 'Contact the contributor' button below.
Updated
5 February 2021
| Dataset date: November 20, 2020-December 14, 2020
This dataset updates: As needed
Democratic Republic of the Congo Coronavirus(COVID-19) Subnational Cases per province. The dataset has been made available on the Food security cluster website. It is made available via a collaboration between multiple agencies including: DR Congo Ministry of Health, World Health Organisation, UNICEF, JICA, CDC, PATH and IOM
Updated
22 February 2021
| Dataset date: March 01, 2020-February 04, 2021
This dataset updates: Every day
Region-level data collected from the official website of Russian Federal Agency Rospotrebnadzor (https://стопкоронавирус.рф/). Dataset exists attributes: data, infected, recovered, died. The dataset contains information of 85 Russian regions.
Updated
18 November 2021
| Dataset date: March 09, 2020-November 14, 2021
This dataset updates: Every week
Subnational data about Covid19 in Burkina Faso - Infected (new cases, gender), Deceased, Recovered.
NEW (!) : VACCINATION DATA PER REGION (1st & 2nd dose)
Type of vaccine : AstraZeneca ; Johnson&Johnson
Updated
19 November 2021
| Dataset date: May 06, 2020-October 08, 2021
This dataset updates: Every day
This dataset contains the number of suspected cases, confirmed cases, and deaths by Département due to the Coronavirus pandemic in Haiti. Released by the Ministry of Public Health and Population of Haiti.
Updated
2 September 2020
| Dataset date: August 31, 2020-August 31, 2020
This dataset updates: Every two weeks
This dataset contains scores for humanitarian access constraints into country, constraints within country, impacts the constraints have led to as well as the mitigation strategies in place to limit the impact.
The scores have the following interpretations:
0 = NA,
1 = No or open,
2 = partially open/closed,
3 = Yes or closed
