COVID-19 Data Explorer

This dataset contains data obtained from a variety of sources and transformed into a form suitable for driving the Covid-19 Data Explorer. The visual itself is driven by a JSON file which contains the same data as the resources in this dataset which point to published csvs from a Google spreadsheet.

Immunization campaigns impacted due to COVID-19

This dataset contains Countries, Commodities and Markets data, sourced from the World Food Programme Price Database. The volume of data means that the actual Food Prices data is in country level datasets. The World Food Programme Price Database covers foods such as maize, rice, beans, fish, and sugar for 98 countries and some 3000 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "People Displaced" refers to the number of people living in displacement as of the end of each year. Contains data from IDMC's Global Internal Displacement Database.

The Cadre Harmonisé (CH) and Integrated Food Security Phase Classification (IPC) are analytical frameworks which synthesize indicators of food and nutrition security outcomes and the inference of contributing factors into scales and figures representing the nature and severity of crisis and implications for strategic response in food security and nutrition. (Refer to the documents linked as showcases for more information).

The number of children, youth and adults not attending schools or universities because of COVID-19 is soaring. Governments all around the world have closed educational institutions in an attempt to contain the global pandemic. According to UNESCO monitoring, over 100 countries have implemented nationwide closures, impacting over half of world’s student population. Several other countries have implemented localized school closures and, should these closures become nationwide, millions of additional learners will experience education disruption.

This dataset shows the number of people in need(PiN), funds required and funds received by country and over the years, from 2010 to 2021. PIN figures for 2022 are available in this dataset: Interagency Response Plans in 2022

CERF and CBPF pooled funds have allocated a combined total of US$222 million to COVID-19 pandemic responses.

Compilation of international financial institution and economic data

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.

Global Humanitarian Response Plan COVID-19 administrative level 1 boundaries, gazetteer and population tables for countries covered by the May update of the Global Humanitarian Response Plan COVID-19. 13 OCTOBER 2020 UPDATE: The Ethiopia - Subnational Administrative Boundaries dataset has been updated with changes at administrative level 1 and below. However, as the Ethiopia - Subnational Population Statistics dataset has not been updated and no longer matches, this global dataset has not yet been updated. 30 SEPTEMBER 2020 UPDATE: The dataset has been updated to reflect official Brazil P-codes. Users should note that the Brazil P-codes in earlier versions no longer correspond to the current CODs. 17 SEPTEMBER 2020 UPDATE: The dataset has been updated to reflect the new (2020) Paraguay COD-PS projections and the adjusted Paraguay P-codes. Users should note that the Paraguay P-codes in earlier versions no longer correspond to the current CODs. 26 AUGUST 2020 UPDATE: administrative level 1 total population statistics have been added for the following 11 countries: Benin , Djibouti, Liberia, Pakistan, Panama, Philippines, Paraguay, Sierra Leone, Togo, Uruguay, Zimbabwe. Population statistics are now available for 48 of the 63 countries or territories. Data fields: ADM1_PCODE: Administrative level 1 (various types) P-code ADM0_PCODE: Administrative level 0 (country or territory) P-code alpha_3: ISO 3166-1 Alpha 3 country or territory identifier ADM0_REF: Administrative level 0 (country or territory) reference name (Latin script without special characters) ADM1_REF: Administrative level 1 (various types) reference name (Latin script without special characters) Population: Most recent available total population. PLEASE SEE CAVEATS

Percentage of children under 5 years of age falling below -3standard deviations (severe) from the median weight-for-height of the reference population

Country's economic exposure due to COVID-19. Composite indicator based on World Bank's datasets on remittances, food import dependence, primary commodity export dependence, tourism dependence, government indebtedness and foreign currency reserves.

The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.

Data on unmitigated(no intervention) COVID-19 scenarios for OCHA HRP countries. Simulation done by Imperial College London.

This dataset contains simulation ­based estimates for COVID­-19 epidemic scenarios in OCHA HRP countries. Simulation is done by London School of Hygiene & Tropical Medicine(LSHTM).

Coronavirus COVID-19 daily new and cumulative cases and deaths by country.

This data has been collected from various sources and is displayed in this online dashboard: https://geonode.wfp.org/travel Mobile version: https://geonode.wfp.org/travel_mobile The data is divided in two datasets: COVID-19 restrictions by country: This dataset shows current travel restrictions. Information is collected from various sources: IATA, media, national sources, WFP internal or any other. COVID-19 airline restrictions information: This dataset shows restrictions taken by individual airlines or country. Information is collected again from various sources including WFP internal and public sources. The data displayed is a collaborative effort and anybody with more accurate/updated information is highly encouraged to contact WFP GIS unit for Emergencies at the following email address: hq.gis@wfp.org