{"doc_desc":{"title":"Joint Food Security Monitor","idno":"SSD_2010-2025_JMR_v01_M","producers":[{"name":"Mathijs Lomme","affiliation":"World Bank, Development Data Group (DECDG)","role":"Lead modeler"},{"name":"Bo Pieter Johannes Andr\u00e9e","affiliation":"World Bank, Development Data Group (DECDG)","role":"Technical lead"},{"name":"Zacharey Carmichael","affiliation":"World Bank, Agriculture and Food Global Practice","role":"Technical coordinator"},{"name":"Steve Penson","affiliation":"World Bank, Agriculture and Food Global Practice","role":"Co-investigator"}],"prod_date":"2026-08-24","version_statement":{"version_date":"2026-08-24","version_resp":"Joint Monitoring Report (JMR) team","version_notes":"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."}},"study_desc":{"title_statement":{"idno":"SSD_2010-2025_JMR_v01_M","title":"Joint Food Security Monitor","sub_title":"South Sudan, 78 areas, 2009-01-01 - 2026-07-01, version 2026-08-24","alternate_title":"Joint Monitoring Report (JMR) data"},"authoring_entity":[{"name":"Lomme, Mathijs","affiliation":"World Bank, Development Data Group (DECDG)"},{"name":"Andr\u00e9e, Bo Pieter Johannes","affiliation":"World Bank, Development Data Group (DECDG)"}],"oth_id":[{"name":"IPC","role":"Multi-partner","affiliation":"iNGO"},{"name":"FEWS NET","role":"Source of FEWS NET IPC data","affiliation":"USAID"},{"name":"ACLED","role":"Source of conflict data","affiliation":"iNGO"},{"name":"FAO","role":"JMR drafting team\nSource of market prices\nSource of the Agricultural Stress Index","affiliation":"United Nations"},{"name":"OCHA","role":"Source of administrative boundaries data","affiliation":"United Nations"},{"name":"WFP","role":"JMR drafting team\nSource of market prices\nSource of Rainfall data\nSource of NDVI data","affiliation":"United Nations"},{"name":"WorldPop","role":"Source of population data","affiliation":"School of Geography and Environmental Science, University of Southampton"}],"production_statement":{"copyright":"For details on the terms and conditions for usage of the data, please refer to the Terms and Conditions when accessing the microdata.","funding_agencies":[{"name":"World Bank's Food Systems 2030","grant":"TF0C0728","role":"Support to methodological development. Support to data analytics. Data documentation and dissemination. Expansion of coverage and maintenance."},{"name":"World Bank's Food Systems 2030","grant":"TF0C0828","role":"Support to methodological development. Support to data analytics. Data documentation and dissemination. Expansion of coverage and maintenance."}]},"distribution_statement":{"contact":[{"name":"Data Help Desk","affiliation":"World Bank, Development Data Group","email":"https:\/\/datahelpdesk.worldbank.org\/"}]},"series_statement":{"series_name":"Ongoing food security assessment in South Sudan","series_info":"The Joint Food Security Monitor country pages provide live datasets compiled and updated monthly by the World Bank\u2013led Joint Monitoring Report (JMR) team. These datasets draw on publicly available food-security-related data and statistical modeling techniques.\n\nEach 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.\n\nThe datasets are continually updated and refined as new data become available.\n\nThe following country pages are part of this series:\n\n\u2022\tWorld: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/WLD_2010-2025_JMR_v01_M\n\u2022\tAfghanistan: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/AFG_2010-2025_JMR_v01_M\n\u2022\tBurkina Faso: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/BFA_2010-2025_JMR_v01_M\n\u2022\tCameroon: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/CMR_2010-2025_JMR_v01_M\n\u2022\tDemocratic Republic of the Congo: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/COD_2010-2025_JMR_v01_M\n\u2022\tEthiopia: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/ETH_2010-2025_JMR_v01_M\n\u2022\tHaiti: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/HTI_2010-2025_JMR_v01_M\n\u2022\tKenya: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/KEN_2010-2025_JMR_v01_M\n\u2022\tMali: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/MLI_2010-2025_JMR_v01_M\n\u2022\tMozambique: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/MOZ_2010-2025_JMR_v01_M\n\u2022\tMalawi: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/MWI_2010-2025_JMR_v01_M\n\u2022\tNiger: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/NER_2010-2025_JMR_v01_M\n\u2022\tNigeria: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/NGA_2010-2025_JMR_v01_M\n\u2022\tSudan: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/SDN_2010-2025_JMR_v01_M\n\u2022\tSomalia: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/SOM_2010-2025_JMR_v01_M\n\u2022\tSouth Sudan: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/SSD_2010-2025_JMR_v01_M\n\u2022\tChad: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/TCD_2010-2025_JMR_v01_M\n\u2022\tYemen: https:\/\/microdata.worldbank.org\/index.php\/catalog\/study\/YEM_2010-2025_JMR_v01_M"},"version_statement":{"version_date":"2026-08-24","version_resp":"Joint Monitoring Report (JMR) team","version_notes":"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."},"study_notes":"Model is based on Penson, Steve; Lomme, Mathijs; Carmichael, Zacharey Austin; Manni, Alemu; Shrestha, Sudeep; Andree, Bo Pieter Johannes. A Data-Driven Approach for Early Detection of Food Insecurity in Yemen's Humanitarian Crisis (English). Policy Research working paper; no. WPS 10768. Washington, D.C.: World Bank Group. http:\/\/documents.worldbank.org\/curated\/en\/099709505092462162","study_info":{"keywords":[{"keyword":"South Sudan"},{"keyword":"Joint Monitoring Report"},{"keyword":"Integrated Food Security Phase Classification"},{"keyword":"Threshold modeling"},{"keyword":"FEWS NET"},{"keyword":"Exchange Rates"},{"keyword":"Exchange Rates - Volatility"},{"keyword":"Trade - Food"},{"keyword":"Fuel Prices"},{"keyword":"Conflict"},{"keyword":"Food Prices"},{"keyword":"Fuel Prices - Volatility"},{"keyword":"Food Prices - Volatility"},{"keyword":"Drought - NDVI"},{"keyword":"Trade - Fuel"},{"keyword":"Drought - Rainfall"}],"abstract":"This dataset provides high-frequency food security alerts and metrics of key indicators relevant to food security crises, offering critical insights into localized risks in areas prone to food insecurity. The dataset includes metrics such as economic, agricultural shock and conflict indicators, designed to support the identification of emerging food crises.\n\nGenerated 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.","time_periods":[{"start":"2009-01-01","end":"2026-07-01","cycle":"monthly"}],"coll_dates":[{"start":"2009-01-01","end":"2026-07-01","cycle":"monthly"}],"geog_coverage":"South Sudan, down to sub-national level, 10 admin 1 areas and 78 admin 2 areas","geog_coverage_notes":"The sub-national levels follow the COD standard (https:\/\/knowledge.base.unocha.org\/wiki\/spaces\/imtoolbox\/pages\/2557378679\/Administrative+Boundaries+COD-AB)","geog_unit":"Sub-national level, admin 2","analysis_unit":"Sub-national level, admin 2, monthly basis","data_kind":"Alert levels for each indicator that drives food insecurity in South Sudan, where the level can be Typical (no alert raised), Heightened or Critical","quality_statement":{"compliance_description":"World Bank Group. (2024). Development Data Quality Policy. https:\/\/ppfdocuments.azureedge.net\/de65051a-a1ee-410e-aba8-9c302f59be2f.pdf"}},"method":{"data_collection":{"time_method":"time-series","frequency":"monthly"},"method_notes":"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).\n\nAlert 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 Andr\u00e9e 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.\n\nBinary 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.\n\nReferences:\nAndr\u00e9e, 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\nGbadegesin, T. K., Andr\u00e9e, 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\nPenson, S., Lomme, M., Carmichael, Z., Manni, A., Shrestha, S., & Andr\u00e9e, 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_access":{"dataset_availability":{"access_place":"World Bank Microdata Library, JMR Collection","access_place_url":"https:\/\/microdatalib.worldbank.org","file_quantity":"2 per country page"},"dataset_use":{"restrictions":"The values presented in these datasets are all based on publicly-available data.\nThe datasets are published as open data.","contact":[{"name":"Data Help Desk","affiliation":"World Bank, Development Data Group","email":"https:\/\/datahelpdesk.worldbank.org\/"}],"cit_req":"Please cite this dataset as follows: Lomme, M. and Andr\u00e9e, 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","disclaimer":"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"}}},"schematype":"survey","tags":[{"tag":"DOI"}]}