Joint Food Security Monitor
South Sudan, 78 areas, 2009-01-01 - 2026-07-01, version 2026-08-24
2009 - 2026
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SSD_2010-2025_JMR_v01_M
Joint Food Security Monitor
South Sudan, 78 areas, 2009-01-01 - 2026-07-01, version 2026-08-24
Joint Monitoring Report (JMR) data
Ongoing food security assessment in South Sudan
The Joint Food Security Monitor country pages provide live datasets compiled and updated monthly by the World Bank–led Joint Monitoring Report (JMR) team. These datasets draw on publicly available food-security-related data and statistical modeling techniques.
Each dataset provides a combination of raw data, transformed indicators, binary alerts, and population exposure estimates. The alerts are raised using the transformed indicator data at thresholds that best anticipate historical food insecurity escalations. The alert levels are categorized as Typical (no alert), Heightened, or Critical risks of escalation. The population estimates are generated using regression techniques.
The datasets are continually updated and refined as new data become available.
The following country pages are part of this series:
• World: https://microdata.worldbank.org/index.php/catalog/study/WLD_2010-2025_JMR_v01_M
• Afghanistan: https://microdata.worldbank.org/index.php/catalog/study/AFG_2010-2025_JMR_v01_M
• Burkina Faso: https://microdata.worldbank.org/index.php/catalog/study/BFA_2010-2025_JMR_v01_M
• Cameroon: https://microdata.worldbank.org/index.php/catalog/study/CMR_2010-2025_JMR_v01_M
• Democratic Republic of the Congo: https://microdata.worldbank.org/index.php/catalog/study/COD_2010-2025_JMR_v01_M
• Ethiopia: https://microdata.worldbank.org/index.php/catalog/study/ETH_2010-2025_JMR_v01_M
• Haiti: https://microdata.worldbank.org/index.php/catalog/study/HTI_2010-2025_JMR_v01_M
• Kenya: https://microdata.worldbank.org/index.php/catalog/study/KEN_2010-2025_JMR_v01_M
• Mali: https://microdata.worldbank.org/index.php/catalog/study/MLI_2010-2025_JMR_v01_M
• Mozambique: https://microdata.worldbank.org/index.php/catalog/study/MOZ_2010-2025_JMR_v01_M
• Malawi: https://microdata.worldbank.org/index.php/catalog/study/MWI_2010-2025_JMR_v01_M
• Niger: https://microdata.worldbank.org/index.php/catalog/study/NER_2010-2025_JMR_v01_M
• Nigeria: https://microdata.worldbank.org/index.php/catalog/study/NGA_2010-2025_JMR_v01_M
• Sudan: https://microdata.worldbank.org/index.php/catalog/study/SDN_2010-2025_JMR_v01_M
• Somalia: https://microdata.worldbank.org/index.php/catalog/study/SOM_2010-2025_JMR_v01_M
• South Sudan: https://microdata.worldbank.org/index.php/catalog/study/SSD_2010-2025_JMR_v01_M
• Chad: https://microdata.worldbank.org/index.php/catalog/study/TCD_2010-2025_JMR_v01_M
• Yemen: https://microdata.worldbank.org/index.php/catalog/study/YEM_2010-2025_JMR_v01_M
Generated using a data-driven approach, food security alerts are calibrated for accuracy and reliability, capturing granular trends often missed by traditional, infrequently updated assessments. The dataset aims to enhance the ability of policymakers, humanitarian organizations, and researchers to monitor and respond to food security risks promptly, supporting proactive interventions to mitigate impacts on vulnerable populations.
Alert levels for each indicator that drives food insecurity in South Sudan, where the level can be Typical (no alert raised), Heightened or Critical
Sub-national level, admin 2, monthly basis
Version
2026-08-24
Joint Monitoring Report (JMR) team
This version is based on the Joint Food Security Monitor of August 2026. Data cut-offs for the are set to August 24, 2026. The data do generally not reflect the impact of events up to the cut-off date as there is varying delay with which official data is published. Joint Food Security Monitor data are not directly comparable across different versions. Indicators are selected based on data availability and may be revised to improve the performance in predicting food security deteriorations using calibration methods outlined by Penson et al. (2024). Consequently, alert thresholds are also re-evaluated based on the updated data and may change over time. Historical versions of Joint Food Security Monitor data are preserved for transparency and research purposes.
Scope
Coverage
South Sudan, down to sub-national level, 10 admin 1 areas and 78 admin 2 areas
The sub-national levels follow the COD standard (https://knowledge.base.unocha.org/wiki/spaces/imtoolbox/pages/2557378679/Administrative+Boundaries+COD-AB)
Sub-national level, admin 2
Producers and sponsors
| Name | Affiliation |
|---|---|
| Lomme, Mathijs | World Bank, Development Data Group (DECDG) |
| Andrée, Bo Pieter Johannes | World Bank, Development Data Group (DECDG) |
| Name | Grant number | Role |
|---|---|---|
| World Bank's Food Systems 2030 | TF0C0728 | Support to methodological development. Support to data analytics. Data documentation and dissemination. Expansion of coverage and maintenance. |
| World Bank's Food Systems 2030 | TF0C0828 | Support to methodological development. Support to data analytics. Data documentation and dissemination. Expansion of coverage and maintenance. |
| Name | Affiliation | Role |
|---|---|---|
| IPC | iNGO | Multi-partner |
| FEWS NET | USAID | Source of FEWS NET IPC data |
| ACLED | iNGO | Source of conflict data |
| FAO | United Nations |
JMR drafting team Source of market prices Source of the Agricultural Stress Index |
| OCHA | United Nations | Source of administrative boundaries data |
| WFP | United Nations |
JMR drafting team Source of market prices Source of Rainfall data Source of NDVI data |
| WorldPop | School of Geography and Environmental Science, University of Southampton | Source of population data |
Survey instrument
The Joint Food Security Monitor datasets consist of four components: raw data, transformed indicators, binary alerts, and population exposure estimates. The transformation and alert framework is developed by Penson et al. (2024). For each indicator, multiple transformation methods and time windows are evaluated, and the best-performing ones are automatically selected. These transformations normalize time-varying risk into a stable range and include methods such as z-scores, moving average divergences, and the Relative Strength Index (RSI).
Alert levels (Heightened or Critical) are determined by applying thresholds to the normalized indicators so as to best reproduce historical food insecurity patterns. Thresholds are optimized by minimizing a loss function that balances the False Positive Rate (FPR) and the False Negative Rate (FNR). The loss formulations follow Andrée et al. (2020). The Heightened threshold minimizes the weighted loss with a two-thirds emphasis on false negatives, while the Critical threshold uses a more conservative calibration that places a two-thirds weight on false positives.
Binary alerts from different indicators are combined into a Generalized Linear Model (GLM) to produce population-at-risk estimates. The weights on the GLM are calibrated so that the sum of probability-weighted populations best matches each country's historical total of populations exceeding IPC cutoff phases.
References:
Andrée, B. P. J., Chamorro, A., Spencer, P., Kraay, A., & Wang, D. (2020). Predicting food crises (Policy Research Working Paper No. 9412). World Bank. https://hdl.handle.net/10986/34510
Gbadegesin, T. K., Andrée, B. P. J., & Braimoh, A. (2024). Climate shocks and their effects on food security, prices, and agricultural wages in Afghanistan (Policy Research Working Paper No. 10999). World Bank. https://hdl.handle.net/10986/42552
Penson, S., Lomme, M., Carmichael, Z., Manni, A., Shrestha, S., & Andrée, B. P. J. (2024). A data-driven approach for early detection of food insecurity in Yemen's humanitarian crisis (Policy Research Working Paper No. 10768). World Bank. https://hdl.handle.net/10986/41534
Data collection
| Start | End | Cycle |
|---|---|---|
| 2009-01-01 | 2026-07-01 | monthly |
time-series
monthly
| Start date | End date | Cycle |
|---|---|---|
| 2009-01-01 | 2026-07-01 | monthly |
Quality standards
World Bank Group. (2024). Development Data Quality Policy. https://ppfdocuments.azureedge.net/de65051a-a1ee-410e-aba8-9c302f59be2f.pdf
Access policy
World Bank Microdata Library, JMR Collection
2 per country page
Data Access
| Name | Affiliation | |
|---|---|---|
| Data Help Desk | World Bank, Development Data Group | https://datahelpdesk.worldbank.org/ |
Please cite this dataset as follows: Lomme, M. and Andrée, B. P. J. (2025). Joint Food Security Monitor - South Sudan (Version 2026-08-24). SSD_2010-2025_JMR_v01_M. Washington, DC: World Bank Microdata Library. DOI: TBC
The values presented in these datasets are all based on publicly-available data.
The datasets are published as open data.
Disclaimer and copyrights
The JMR data and metadata provided as is and as available, and every effort is made to ensure their timeliness, accuracy, and completeness. When errors are discovered, they are corrected as appropriate and feasible. For details on the terms and conditions for usage of the JMR database, please refer to the license details
For details on the terms and conditions for usage of the data, please refer to the Terms and Conditions when accessing the microdata.
Contacts
| Name | Affiliation | |
|---|---|---|
| Data Help Desk | World Bank, Development Data Group | https://datahelpdesk.worldbank.org/ |
Metadata production
SSD_2010-2025_JMR_v01_M
| Name | Affiliation | Role |
|---|---|---|
| Mathijs Lomme | World Bank, Development Data Group (DECDG) | Lead modeler |
| Bo Pieter Johannes Andrée | World Bank, Development Data Group (DECDG) | Technical lead |
| Zacharey Carmichael | World Bank, Agriculture and Food Global Practice | Technical coordinator |
| Steve Penson | World Bank, Agriculture and Food Global Practice | Co-investigator |
2026-08-24
Metadata version
2026-08-24
Joint Monitoring Report (JMR) team
This version is based on the Joint Food Security Monitor of August 2026. Data cut-offs for the are set to August 24, 2026. The data do generally not reflect the impact of events up to the cut-off date as there is varying delay with which official data is published. Joint Food Security Monitor data are not directly comparable across different versions. Indicators are selected based on data availability and may be revised to improve the performance in predicting food security deteriorations using calibration methods outlined by Penson et al. (2024). Consequently, alert thresholds are also re-evaluated based on the updated data and may change over time. Historical versions of Joint Food Security Monitor data are preserved for transparency and research purposes.