Maps

Somalia - Baseline Mobility Assessment: Accessibility of Settlement - Round 1 (June 2020) public:///thumbs/637357754060080711.png Sep 15 2020 /node/9687 https://displacement.iom.int/system/tdf/maps/SOM_MT_B2_R1_Accessibility_Settlement.pdf?file=1&type=node&id=9687 9687

Somalia - Baseline Mobility Assessment: Summary of Number Of Absentees - Round 1 (June 2020) public:///thumbs/637358048847904470.png Sep 15 2020 /node/9686 https://displacement.iom.int/system/tdf/maps/SOM_MT_B2_R1_Absentees_Summary.pdf?file=1&type=node&id=9686 9686

Somalia - Baseline Mobility Assessment: Number of Absentees - Round 1 (June 2020) public:///thumbs/637357749363617608.png Sep 15 2020 /maps/somalia-baseline-mobility-assessment-number-absentees-round-1-june-2020 https://displacement.iom.int/system/tdf/maps/SOM_MT_B2_R1_Absentees..pdf?file=1&type=node&id=9685 9685

Lebanon — Foreign Nationals MSNA Analysis: Type of Assistance Received by Foreign Nationals (September 2020) On 4th August 2020, a large explosion occurred at the port of Beirut, Lebanon that left more than 6,500 individuals injured and caused at least 180 deaths. To assess the impact of the explosion and the arising needs and vulnerabilities, the Lebanese Red Cross (LRC), in coordination with the Office for the Coordination of Humanitarian Affairs (OCHA), have conducted large multi-sectoral needs assessments (MSNA) across 11,008 households. To support these efforts as well as draw attention to the gap on the needs and vulnerabilities of foreign nationals that were affected by the explosion, IOM has undertaken a secondary data review of LRC’s data. This map uses the data of 1,896 foreign national households with migrant workers in Beirut to provide an overview on the type of assistance received by foreign nationals. For information on the Foreign Nationals Multi-Sector Needs Assessment Analysis Report, please visit: https://migration.iom.int/node/9637 public:///thumbs/637356880167250856.png Sep 14 2020 /node/9677 https://displacement.iom.int/system/tdf/maps/MSNA_ForeignNationals_TypeofAssistanceReceived_11092020.pdf?file=1&type=node&id=9677 9677

Lebanon —Foreign Nationals MSNA Analysis: Priority Needs Reported by Foreign Nationals (September 2020) On 4th August 2020, a large explosion occurred at the port of Beirut, Lebanon that left more than 6,500 individuals injured and caused at least 180 deaths. To assess the impact of the explosion and the arising needs and vulnerabilities, the Lebanese Red Cross (LRC), in coordination with the Office for the Coordination of Humanitarian Affairs (OCHA), have conducted large multi-sectoral needs assessments (MSNA) across 11,008 households. To support these efforts as well as draw attention to the gap on the needs and vulnerabilities of foreign nationals that were affected by the explosion, IOM has undertaken a secondary data review of LRC’s data.  This map uses the data of 1,896 foreign national households with migrant workers in Beirut to provide an overview on the priority needs.For information on the Foreign Nationals Multi-Sector Needs Assessment Analysis Report, please visit: https://migration.iom.int/node/9637 public:///thumbs/637356880315377184.png Sep 14 2020 /maps/lebanon-%E2%80%94-multi-sectoral-needs-assessment-msna-analysis-priority-needs-reported-foreign https://displacement.iom.int/system/tdf/maps/MSNA_ForeignNationals_TopPriorityNeeds_11092020.pdf?file=1&type=node&id=9676 9676

Lebanon — Foreign Nationals MSNA Analysis: Population Overview (September 2020) On 4th August 2020, a large explosion occurred at the port of Beirut, Lebanon that left more than 6,500 individuals injured and caused at least 180 deaths. To assess the impact of the explosion and the arising needs and vulnerabilities, the Lebanese Red Cross (LRC), in coordination with the Office for the Coordination of Humanitarian Affairs (OCHA), have conducted large multi-sectoral needs assessments (MSNA) across 11,008 households. To support these efforts as well as draw attention to the gap on the needs and vulnerabilities of foreign nationals that were affected by the explosion, IOM has undertaken a secondary data review of LRC’s data. This map uses the data of 1,896 foreign national households with migrant workers in Beirut to provide an overview on the nationalities of foreign nationals.For information on the Foreign Nationals Multi-Sector Needs Assessment Analysis Report, please visit: https://migration.iom.int/node/9637 public:///thumbs/637356880034437149.png Sep 14 2020 /maps/lebanon-%E2%80%94-foreign-nationals-msna-population-overview-september-2020 https://displacement.iom.int/system/tdf/maps/Population_nationalities_11_09.pdf?file=1&type=node&id=9671 9671

Lebanon — Foreign Nationals MSNA Analysis: Post-Incident Household Assistance (September 2020) On 4th August 2020, a large explosion occurred at the port of Beirut, Lebanon that left more than 6,500 individuals injured and caused at least 180 deaths. To assess the impact of the explosion and the arising needs and vulnerabilities, the Lebanese Red Cross (LRC), in coordination with the Office for the Coordination of Humanitarian Affairs (OCHA), have conducted large multi-sectoral needs assessments (MSNA) across 11,008 households. To support these efforts as well as draw attention to the gap on the needs and vulnerabilities of foreign nationals that were affected by the explosion, IOM has undertaken a secondary data review of LRC’s data. This map uses the data of 1,896 foreign national households with migrant workers in Beirut to provide an overview on the post-incident household assistance. For information on the Foreign Nationals Multi-Sector Needs Assessment Analysis Report, please visit: https://migration.iom.int/node/9637 public:///thumbs/637356879891935952.png Sep 14 2020 /maps/lebanon-%E2%80%94-foreign-nationals-msna-post-incident-household-assistance-september-2020 https://displacement.iom.int/system/tdf/maps/FN_Received_aid_11_09.pdf?file=1&type=node&id=9669 9669

DTM COVID-19 Regional Atlas Point Operational Status As Of 28 August 2020 The current outbreak of COVID-19 has affected global mobility in complex and unprecedented ways in the form of various travel restrictions, suspension of air travel, and border closures. To better understand this, the International Organization for Migration (IOM) has developed a global mobility database to map these impacts on human mobility, across global, regional, and country levels. Furthermore, COVID-19 has had a disproportionate impact on vulnerable populations in camps and camp-like settings as well as exacerbated the vulnerabilities of mobile populations who may now be stranded owing to COVID-19 related mobility restrictions. This data is particularly important when addressing specific needs faced by migrants and mobile populations.IOM has developed a global mobility database mapping the status of different Points of Entry (PoE) and Key Locations of Internal Mobility, globally. These include airports, land border crossing points (could be rail or road), blue border crossing points (sea, river or lake), internal transit points, and areas of interest. For each point of entry, data is collected on the type of restriction, measured applied, and the timeframe, as well as the population category that may be affected by the restrictive measures. This workstream uses direct input from IOM missions and this dashboard displays regularly updated mobility restrictions at the location level. public:///thumbs/637352647660196892.png Sep 09 2020 /maps/dtm-covid-19-regional-atlas-point-operational-status-28-august-2020 https://displacement.iom.int/system/tdf/maps/DTM_COVID19_20200828_MRM_Regional_Atlas_Point_Operational_Status.pdf?file=1&type=node&id=9647 9647

South Sudan - Wau County_Village Assessment Survey_Facilities Infrastructure and Services Since the beginning of the exercise in the last quarter of 2019, IOM’s Displacement Tracking Matrix (DTM) conducted Village Assessment Survey (VAS) across 7 counties covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties. Additional 9 focus group discussions were conducted, due to varying perspectives on boma boundaries. To supplement the findings from the boma questionnaire, key informant interviews were conducted at 560 educational facilities and 150 health facilities. In addition to this, Facility, Infrastructure and Service mapping component geo referenced 3,227 facilities including administrative buildings, education facilities, healthcare facilities, markets, religious buildings, transport points and water points. public:///thumbs/637348095802182754.png Sep 03 2020 /maps/south-sudan-wau-countyvillage-assessment-surveyfacilities-infrastructure-and-services https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Wau%20County%20Village%20Assessment%20Survey_Facilities%20Infrastructure%20and%20Services.pdf?file=1&type=node&id=9580 9580

South Sudan - Torit County_Village Assessment Survey_Facilities Infrastructure and Services Since the beginning of the exercise in the last quarter of 2019, IOM’s Displacement Tracking Matrix (DTM) conducted Village Assessment Survey (VAS) across 7 counties covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties. Additional 9 focus group discussions were conducted, due to varying perspectives on boma boundaries. To supplement the findings from the boma questionnaire, key informant interviews were conducted at 560 educational facilities and 150 health facilities. In addition to this, Facility, Infrastructure and Service mapping component geo referenced 3,227 facilities including administrative buildings, education facilities, healthcare facilities, markets, religious buildings, transport points and water points. public:///thumbs/637347637431417291.png Sep 03 2020 /maps/south-sudan-torit-countyvillage-assessment-surveyfacilities-infrastructure-and-services https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Torit%20County%20Village%20Assessment%20Survey_Facilities%20Infrastructure%20and%20Services.pdf?file=1&type=node&id=9579 9579

South Sudan - Rubkona County_Village Assessment Survey_Facilities Infrastructure and Services Since the beginning of the exercise in the last quarter of 2019, IOM’s Displacement Tracking Matrix (DTM) conducted Village Assessment Survey (VAS) across 7 counties covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties. Additional 9 focus group discussions were conducted, due to varying perspectives on boma boundaries. To supplement the findings from the boma questionnaire, key informant interviews were conducted at 560 educational facilities and 150 health facilities. In addition to this, Facility, Infrastructure and Service mapping component geo referenced 3,227 facilities including administrative buildings, education facilities, healthcare facilities, markets, religious buildings, transport points and water points. public:///thumbs/637347636479533633.png Sep 03 2020 /maps/south-sudan-rubkona-countyvillage-assessment-surveyfacilities-infrastructure-and-services https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Rubkona%20County%20Village%20Assessment%20Survey_Facilities%20Infrastructure%20and%20Services.pdf?file=1&type=node&id=9578 9578

South Sudan - Malakal County_Village Assessment Survey_Facilities Infrastructure and Services Since the beginning of the exercise in the last quarter of 2019, IOM’s Displacement Tracking Matrix (DTM) conducted Village Assessment Survey (VAS) across 7 counties covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties. Additional 9 focus group discussions were conducted, due to varying perspectives on boma boundaries. To supplement the findings from the boma questionnaire, key informant interviews were conducted at 560 educational facilities and 150 health facilities. In addition to this, Facility, Infrastructure and Service mapping component geo referenced 3,227 facilities including administrative buildings, education facilities, healthcare facilities, markets, religious buildings, transport points and water points. public:///thumbs/637347634815650710.png Sep 03 2020 /maps/south-sudan-malakal-countyvillage-assessment-surveyfacilities-infrastructure-and-services https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Malakal%20County%20Village%20Assessment%20Survey_Facilities%20Infrastructure%20and%20Services.pdf?file=1&type=node&id=9577 9577

South Sudan - Magwi County_Village Assessment Survey_Facilities Infrastructure and Services Since the beginning of the exercise in the last quarter of 2019, IOM’s Displacement Tracking Matrix (DTM) conducted Village Assessment Survey (VAS) across 7 counties covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties. Additional 9 focus group discussions were conducted, due to varying perspectives on boma boundaries. To supplement the findings from the boma questionnaire, key informant interviews were conducted at 560 educational facilities and 150 health facilities. In addition to this, Facility, Infrastructure and Service mapping component geo referenced 3,227 facilities including administrative buildings, education facilities, healthcare facilities, markets, religious buildings, transport points and water points. public:///thumbs/637347634105800567.png Sep 03 2020 /maps/south-sudan-magwi-countyvillage-assessment-surveyfacilities-infrastructure-and-services https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Magwi%20County%20Village%20Assessment%20Survey_Facilities%20Infrastructure%20and%20Services.pdf?file=1&type=node&id=9576 9576

South Sudan - Bor South County_Village Assessment Survey_Facilities Infrastructure and Services Since the beginning of the exercise in the last quarter of 2019, IOM’s Displacement Tracking Matrix (DTM) conducted Village Assessment Survey (VAS) across 7 counties covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties. Additional 9 focus group discussions were conducted, due to varying perspectives on boma boundaries. To supplement the findings from the boma questionnaire, key informant interviews were conducted at 560 educational facilities and 150 health facilities. In addition to this, Facility, Infrastructure and Service mapping component geo referenced 3,227 facilities including administrative buildings, education facilities, healthcare facilities, markets, religious buildings, transport points and water points. public:///thumbs/637347633233131966.png Sep 03 2020 /maps/south-sudan-bor-south-countyvillage-assessment-surveyfacilities-infrastructure-and-services https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Bor%20South%20County%20Village%20Assessment%20Survey_Facilities%20Infrastructure%20and%20Services.pdf?file=1&type=node&id=9575 9575

South Sudan - Aweil Centre County_Village Assessment Survey_Facilities Infrastructure and Services Since the beginning of the exercise in the last quarter of 2019, IOM’s Displacement Tracking Matrix (DTM) conducted Village Assessment Survey (VAS) across 7 counties covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties. Additional 9 focus group discussions were conducted, due to varying perspectives on boma boundaries. To supplement the findings from the boma questionnaire, key informant interviews were conducted at 560 educational facilities and 150 health facilities. In addition to this, Facility, Infrastructure and Service mapping component geo referenced 3,227 facilities including administrative buildings, education facilities, healthcare facilities, markets, religious buildings, transport points and water points. public:///thumbs/637347632321385712.png Sep 03 2020 /maps/south-sudan-aweil-centre-countyvillage-assessment-surveyfacilities-infrastructure-and-services https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Aweil%20Centre%20County%20Village%20Assessment%20Survey_Facilities%20Infrastructure%20and%20Services.pdf?file=1&type=node&id=9574 9574

South Sudan — Unity State Flooding (August 2020) Seasonal Floods Analysis in Unity State for 5, 11 and 12 August 2020 public:///thumbs/637357705234106012.png Sep 03 2020 /maps/south-sudan-%E2%80%94-unity-state-flooding-august-2020 https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Floods%20Unity.pdf?file=1&type=node&id=9572 9572

South Sudan — Jonglei State Flooding (August 2020) Seasonal Floods Analysis in Jonglei State for12, 14 and 19 August 2020 public:///thumbs/637347393422024163.png Sep 03 2020 /maps/south-sudan-%E2%80%94-jonglei-state-flooding-august-2020 https://displacement.iom.int/system/tdf/maps/20200903%20IOM%20DTM%20SSD%20Floods%20Jonglei.pdf?file=1&type=node&id=9571 9571

DTM COVID-19 Regional Atlas Point Operational Status As Of 20 August 2020 The current outbreak of COVID-19 has affected global mobility in complex and unprecedented ways in the form of various travel restrictions, suspension of air travel, and border closures. To better understand this, the International Organization for Migration (IOM) has developed a global mobility database to map these impacts on human mobility, across global, regional, and country levels. Furthermore, COVID-19 has had a disproportionate impact on vulnerable populations in camps and camp-like settings as well as exacerbated the vulnerabilities of mobile populations who may now be stranded owing to COVID-19 related mobility restrictions. This data is particularly important when addressing specific needs faced by migrants and mobile populations.IOM has developed a global mobility database mapping the status of different Points of Entry (PoE) and Key Locations of Internal Mobility, globally. These include airports, land border crossing points (could be rail or road), blue border crossing points (sea, river or lake), internal transit points, and areas of interest. For each point of entry, data is collected on the type of restriction, measured applied, and the timeframe, as well as the population category that may be affected by the restrictive measures. This workstream uses direct input from IOM missions and this dashboard displays regularly updated mobility restrictions at the location level. public:///thumbs/637341221628281650.png Aug 27 2020 /maps/dtm-covid-19-regional-atlas-point-operational-status-20-august-2020 https://displacement.iom.int/system/tdf/maps/DTM_COVID19_20200806_MRM_Regional_Atlas_Point_Operational_Status_0.pdf?file=1&type=node&id=9490 9490

DTM COVID19 Regional Atlas Point Operational Status As Of 6 August 2020 The current outbreak of COVID-19 has affected global mobility in complex and unprecedented ways in the form of various travel restrictions, suspension of air travel, and border closures. To better understand this, the International Organization for Migration (IOM) has developed a global mobility database to map these impacts on human mobility, across global, regional, and country levels. Furthermore, COVID-19 has had a disproportionate impact on vulnerable populations in camps and camp-like settings as well as exacerbated the vulnerabilities of mobile populations who may now be stranded owing to COVID-19 related mobility restrictions. This data is particularly important when addressing specific needs faced by migrants and mobile populations.IOM has developed a global mobility database mapping the status of different Points of Entry (PoE) and Key Locations of Internal Mobility, globally. These include airports, land border crossing points (could be rail or road), blue border crossing points (sea, river or lake), internal transit points, and areas of interest. For each point of entry, data is collected on the type of restriction, measured applied, and the timeframe, as well as the population category that may be affected by the restrictive measures. This workstream uses direct input from IOM missions and this dashboard displays regularly updated mobility restrictions at the location level. public:///thumbs/637329143587729158.png Aug 13 2020 /maps/dtm-covid19-regional-atlas-point-operational-status-6-august-2020 https://displacement.iom.int/system/tdf/maps/DTM_COVID19_20200806_MRM_Regional_Atlas_Point_Operational_Status.pdf?file=1&type=node&id=9390 9390

South Sudan — COVID-19 — Inflows from neighbouring countries (May 2020) IOM DTM, UNHCR and REACH combined their flow monitoring data for South Sudan with geographically disaggregated data about COVID-19 cases in South Sudan and neighbouring countries compiled by UNICEF, with the aim of mapping population inflows at risk of COVID-19 transmission. This map shows the total number of incoming individual movements recorded across all flow monitoring points.Data reflects the situation as of 31 May.  public:///thumbs/637329056806433323.png Aug 13 2020 /maps/south-sudan-%E2%80%94-covid-19-%E2%80%94-inflows-neighbouring-countries-may-2020 https://displacement.iom.int/system/tdf/maps/SSD_FLOW_COVID_COUNTRIES_MAY.pdf?file=1&type=node&id=9389 9389

South Sudan — COVID-19 — Flows From Affected Areas (May 2020) IOM DTM, UNHCR and REACH combined their flow monitoring data for South Sudan with geographically disaggreagated data about COVID-19 cases in South Sudan and neighbouring countries compiled by UNICEF, with the aim of mapping population flows that may be vulnerable to COVID-19 transmission. Data on individuals travelling from areas with COVID-19 cases includes both those entering from neighbouring countries as well as internal movements within South Sudan.The data reflects the situation as of 31 May public:///thumbs/637329038807840216.png Aug 13 2020 /maps/south-sudan-%E2%80%94-covid-19-%E2%80%94-flows-affected-areas-may-2020 https://displacement.iom.int/system/tdf/maps/SSD_FLOW_COVID_AREAS_MAY.pdf?file=1&type=node&id=9388 9388

DTM COVID19 Regional Atlas Point Operational Status As Of 23 July 2020 The current outbreak of COVID-19 has affected global mobility in complex and unprecedented ways in the form of various travel restrictions, suspension of air travel, and border closures. To better understand this, the International Organization for Migration (IOM) has developed a global mobility database to map these impacts on human mobility, across global, regional, and country levels. Furthermore, COVID-19 has had a disproportionate impact on vulnerable populations in camps and camp-like settings as well as exacerbated the vulnerabilities of mobile populations who may now be stranded owing to COVID-19 related mobility restrictions. This data is particularly important when addressing specific needs faced by migrants and mobile populations.IOM has developed a global mobility database mapping the status of different Points of Entry (PoE) and Key Locations of Internal Mobility, globally. These include airports, land border crossing points (could be rail or road), blue border crossing points (sea, river or lake), internal transit points, and areas of interest. For each point of entry, data is collected on the type of restriction, measured applied, and the timeframe, as well as the population category that may be affected by the restrictive measures. This workstream uses direct input from IOM missions and this dashboard displays regularly updated mobility restrictions at the location level.   public:///thumbs/637316270756276745.png Jul 29 2020 /maps/dtm-covid19-regional-atlas-point-operational-status-23-july-2020 https://displacement.iom.int/system/tdf/maps/DTM_COVID19_20200723_MRM_Regional_Atlas_Point_Operational_Status.pdf?file=1&type=node&id=9301 9301

DTM COVID19 Regional Atlas Point Operational Status As Of 9 July 2020 The current outbreak of COVID-19 has affected global mobility in complex and unprecedented ways in the form of various travel restrictions, suspension of air travel, and border closures. To better understand this, the International Organization for Migration (IOM) has developed a global mobility database to map these impacts on human mobility, across global, regional, and country levels. Furthermore, COVID-19 has had a disproportionate impact on vulnerable populations in camps and camp-like settings as well as exacerbated the vulnerabilities of mobile populations who may now be stranded owing to COVID-19 related mobility restrictions. This data is particularly important when addressing specific needs faced by migrants and mobile populations.IOM has developed a global mobility database mapping the status of different Points of Entry (PoE) and Key Locations of Internal Mobility, globally. These include airports, land border crossing points (could be rail or road), blue border crossing points (sea, river or lake), internal transit points, and areas of interest. For each point of entry, data is collected on the type of restriction, measured applied, and the timeframe, as well as the population category that may be affected by the restrictive measures. This workstream uses direct input from IOM missions and this dashboard displays regularly updated mobility restrictions at the location level. public:///thumbs/637305281368044143.png Jul 15 2020 /maps/dtm-covid19-regional-atlas-point-operational-status-9-july-2020 https://displacement.iom.int/system/tdf/maps/DTM_COVID19_20200709_MRM_Regional_Atlas_Point_Operational_Status_0.pdf?file=1&type=node&id=9201 9201

Afghanistan — Overview Map — Total Inflows (IDPs + Returnees) — December 2019 This map provides information on Total inflow (Returnees from Abroad + Arrival IDPs) during the period from 2012 through December 2019. public:///thumbs/637299048677591084.png Jul 09 2020 /maps/afghanistan-%E2%80%94-overview-map-%E2%80%94-total-inflows-idps-returnees-%E2%80%94-december-2019 https://displacement.iom.int/system/tdf/maps/AFG_DTM_December2019_District_Total_Inflow_Overview_By_District%26Villages.pdf?file=1&type=node&id=9148 9148