La méthodologie utilisée pour l’estimation des mouvements de populations a été élaborée collectivement en avril 2015 par l’ensemble des acteurs humanitaires et services étatiques.
The International Federation of Red Cross and Red Crescent Societies (IFRC) is the world’s largest humanitarian network. Our secretariat supports local Red Cross and Red Crescent action in more than 192 countries, bringing together almost 15 million volunteers for the good of humanity.
We launch Emergency Appeals for big and complex disasters affecting lots of people who will need long-term support to recover. We also support Red Cross and Red Crescent Societies to respond to lots of small and medium-sized disasters worldwide—through our Disaster Response Emergency Fund (DREF) and in other ways.
There is also a global dataset.
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This dataset updates: Every week
This dataset is part of the data series [?]: IFRC - Appeals
The Oceanic Niño Index (ONI) has become the de facto standard that the National
Oceanic and Atmospheric Administration (NOAA) uses to identify El Niño (warm) and
La Niña (cool) events in the tropical Pacific. It is the three month mean SST
anomaly for the El Niño 3.4 region (i.e., 5°N-5°S, 120°-170°W). Events are defined as five
consecutive overlapping three month periods at or above the +0.5°C anomaly for warm (El
Niño), events and at or below the -0.5 anomaly for cold (La Niña) events. The threshold
is further broken down into Weak (with a 0.5 to 0.9 SST anomaly), Moderate (1.0 to 1.4)
and Strong (≥ 1.5) events. For an event to be categorized as weak, moderate or strong. it
must have equalled or exceeded the threshold for at least three consecutive overlapping
three month periods.
This collection of datasets is related to the Lake Chad Basin crisis visualization. The collection includes key crisis figures, Number of IDPs and refugees; number of incidents by location; Accessible territories; and data on funding.
This dataset contains the change in the cost of a food basket in relation to a previous period (Periods of 3 months). The change of the cost of basic food basket is calculated by comparing the seasonally adjusted cost of the food basket with the cost in the reference period (previous quarter or baseline), as percentage change. The change is considered normal when the percentage change is between 0 and 3%, moderate when it is between 3 and 10%, high when it is between 10 and 25%, and severe above 25%. Note that the countries included here only include those monitored by WFP.
Papua New Guinea administrative level 0-3 2011 population statistics.
(Please see caveats.)
REFERENCE YEAR: 2011
See caveats
These population statistics .csv tables are suitable for database or GIS linkage to the shapefiles available in the Papua New Guinea - Subnational Administrative Boundaries HDX dataset.
Source: National Statistics Office 2011 Census results
Resource has no data rows! No conflict and disaster population movement (flows) data recorded for Samoa in the last 180 days.
Internally displaced persons are defined according to the 1998 Guiding Principles (https://www.internal-displacement.org/publications/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.
The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD), accessible at https://www.internal-displacement.org/database/displacement-data. The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.
Guinea administrative level 0-3 edge-matched gazetteer, shapefiles, geodatabase, and geoservice.
COD-EM datasets do not replace the authoritative COD-AB available here; however COD-EM datasets may be preferred for cartographic purposes. See caveats.
These layers are suitable for database or GIS linkage to the Guinea - Subnational Population Statistics tables using the ADM0, ADM1, ADM2, and ADM3_PCODE fields.
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
Armenia administrative level 0-1 edge-matched gazetteer, shapefiles, geodatabase, and geoservice.
These boundaries are suitable for database or GIS linkage to the Armenia - Subnational Population Statistics tables using the ADM0, ADM1, and ADM2_PCODE fields.
COD-EM datasets do not replace the authoritative COD-AB available here; however COD-EM datasets may be preferred for cartographic purposes. See caveats.
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
This dataset contains dekadal rainfall indicators computed from Climate Hazards Group InfraRed Precipitation satellite imagery with insitu Station data (CHIRPS) version 2, aggregated by subnational administrative units.
Included indicators are (for each dekad):
10 day rainfall [mm] (rfh)
rainfall 1-month rolling aggregation [mm] (r1h)
rainfall 3-month rolling aggregation [mm] (r3h)
rainfall long term average [mm] (rfh_avg)
rainfall 1-month rolling aggregation long term average [mm] (r1h_avg)
rainfall 3-month rolling aggregation long term average [mm] (r3h_avg)
rainfall anomaly [%] (rfq)
rainfall 1-month anomaly [%] (r1q)
rainfall 3-month anomaly [%] (r3q)
The administrative units used for aggregation are based on WFP data and contain a Pcode reference attributed to each unit. The number of input pixels used to create the aggregates, is provided in the n_pixelscolumn.
DTM’s Displacement Tracking tool collects and reports on displaced numbers of households on a daily basis, allowing for regular reporting of new displacements in terms of numbers, geography and needs. More than 3.6 million people are displaced as per August 2018 assessment.
This dataset contains dekadal rainfall indicators computed from Climate Hazards Group InfraRed Precipitation satellite imagery with insitu Station data (CHIRPS) version 2, aggregated by subnational administrative units.
Included indicators are (for each dekad):
10 day rainfall [mm] (rfh)
rainfall 1-month rolling aggregation [mm] (r1h)
rainfall 3-month rolling aggregation [mm] (r3h)
rainfall long term average [mm] (rfh_avg)
rainfall 1-month rolling aggregation long term average [mm] (r1h_avg)
rainfall 3-month rolling aggregation long term average [mm] (r3h_avg)
rainfall anomaly [%] (rfq)
rainfall 1-month anomaly [%] (r1q)
rainfall 3-month anomaly [%] (r3q)
The administrative units used for aggregation are based on WFP data and contain a Pcode reference attributed to each unit. The number of input pixels used to create the aggregates, is provided in the n_pixelscolumn.
These datasets contain information on reported incidents of violence and threats affecting aid operations and workers, education, health care services and refugee and IDP camps in Sudan.They also provide information on incidents of conflict related sexual violence (CRSV) and explosive weapons use affecting aid access, education and health care services. Also included are datasets cited in the Safeguarding Health in Conflict Coalition (SHCC)'s annual reports. Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
This dataset contains agency- and open source events published in the Attacks on Health Care News Brief. Categorized by country.
Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
See here for data supporting the Safeguarding Health in Conflict Coalition (SHCC).
This dataset contains dekadal rainfall indicators computed from Climate Hazards Group InfraRed Precipitation satellite imagery with insitu Station data (CHIRPS) version 2, aggregated by subnational administrative units.
Included indicators are (for each dekad):
10 day rainfall [mm] (rfh)
rainfall 1-month rolling aggregation [mm] (r1h)
rainfall 3-month rolling aggregation [mm] (r3h)
rainfall long term average [mm] (rfh_avg)
rainfall 1-month rolling aggregation long term average [mm] (r1h_avg)
rainfall 3-month rolling aggregation long term average [mm] (r3h_avg)
rainfall anomaly [%] (rfq)
rainfall 1-month anomaly [%] (r1q)
rainfall 3-month anomaly [%] (r3q)
The administrative units used for aggregation are based on WFP data and contain a Pcode reference attributed to each unit. The number of input pixels used to create the aggregates, is provided in the n_pixelscolumn.
These datasets contain information on reported incidents of violence and threats affecting aid operations and workers, education, health care services and refugee and IDP camps in Myanmar. They also provide information on incidents of explosive weapons use affecting aid access, education and health care services. Also included are datasets cited in the Safeguarding Health in Conflict Coalition (SHCC)'s annual reports. Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
The Who does What Where is a core humanitarian dataset for coordination. This data contains operational presence of humanitarian partners in South Sudan at admin 2 level.
This dataset shows the current IPC AMN period (October 2022–May 2023) analysis. The acute malnutrition situation has deteriorated further in GoY-controlled areas when compared to the same period in 2022. This is due to a combination of factors; severe food insecurity, low immunization coverage, poor access to health and WASH services and increased disease incidences.