This map shows a picture of return and relocation flows tracked by DTM's Flow Monitoring Registry in South Sudan and between South Sudan and neighbouring countries, based on interviews carried out at 34 Flow Monitoring Points between October and December 2020. Figures are only indicative of existing trends among respondents at the active FMPs since DTM does not have full coverage of cross-border or internal flows. Participation in the survey is voluntary and anonymous.Flows are mapped at the second administrative level for neighbouring countries and at the county or payam level for South Sudan. Flows to and from camps are mapped using UNHCR or IOM camp coordinates where available.The map is best visualized in Adobe Acrobat or Chrome, other PDF readers may result in graphic distortions.

This map shows a picture of long / medium term migration flows tracked by DTM's Flow Monitoring Registry in South Sudan and between South Sudan and neighbouring countries, based on interviews carried out at 34 Flow Monitoring Points between October and December 2020. Figures are only indicative of existing trends among respondents at the active FMPs since DTM does not have full coverage of cross-border or internal flows. Participation in the survey is voluntary and anonymous.Flows are mapped at the second administrative level for neighbouring countries and at the county or payam level for South Sudan. Flows to and from camps are mapped using UNHCR or IOM camp coordinates where available.The map is best visualized in Adobe Acrobat or Chrome, other PDF readers may result in graphic distortions.

This map shows a picture of the human mobility network tracked by DTM's Flow Monitoring Registry in South Sudan and between South Sudan and neighbouring countries, based on interviews carried out at 34 Flow Monitoring Points between October and December 2020. Figures are only indicative of existing trends among respondents at the active FMPs since DTM does not have full coverage of cross-border or internal flows. Participation in the survey is voluntary and anonymous.Flows are mapped at the second administrative level for neighbouring countries and at the county or payam level for South Sudan. Flows to and from camps are mapped using UNHCR or IOM camp coordinates where available.The map is best visualized in Adobe Acrobat or Chrome, other PDF readers may result in graphic distortions.

Seasonal Flood Analysis for Koch County in Unity State as of 28 and 29 December 2020.

Seasonal Flood Analysis for Panyijar County in Unity State as of 29 September 2020.

Seasonal Flood Analysis for Ayod County in Jonglei State as of 29 September 2020.

Seasonal Flood Analysis for Twic East County in Jonglei State as of 28 December 2020.

Seasonal Flood Analysis for Tonj East County in Warrap State as of 29 October 2020.

Seasonal Flood Analysis for Twic East County in Jonglei State as of 29 October 2020.

Seasonal Flood Analysis for Terekeka County in Central Equatoria State as of 29 October 2020.

This document contains country-level overview of location types assessed during Mobility Tracking Round 9 conducted between July and September 2020.

This document contains payam/sub-area level overview of assessed locations with confirmed presence of IDPs and returnees (Mobility Tracking Round 9, September 2020). 

This document contains state-level maps with indicated location types (IDP, returnee) as per Mobility Tracking Round 9 assessment (September 2020).

This map displays assessed locations with confirmed presence of IDPs and Returnees (Mobility Tracking Round 9, September 2020).

This map displays the number of returnees by county as of September 2020, Round 9 of Mobility Tracking. 

This map displays the number of IDPs by county as of September 2020, Round 9 of Mobility Tracking. 

Seasonal Flood Analysis for Duk County in Jonglei State as of 29 September 2020. 

Seasonal Flood Analysis for Bor South County in Jonglei State and Awerial County in Lakes State as of 29 September 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. This indicative map of population inflows aims to inform public health measures to reduce the risk of COVID-19 transmission and enable safe mobility. The map shows the total number of incoming individual movements recorded across all flow monitoring points.Data reflects the situation as of 31 July. 

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. This indicative map of population inflows aims to inform public health measures to reduce the risk of COVID-19 transmission and enable safe mobility. The map shows the total number of incoming individual movements recorded across all flow monitoring points.Data reflects the situation as of 30 June. 

IOM DTM has ben collaborating with South Sudan's National Bureau of Statistics to develop updated enumeration areas for Juba Town and map shelter density using remote sensing data. The aim of this work is to inform the COVID-19 response and enable the roll-out of representative household surveys in collaboration with humanitarian and development partners.

Seasonal Floods Analysis for Twic East and Duk, Jonglei State, with imagery as of 11 September 2020.

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.

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.