Key Findings
• Main drivers and barriers to data collection and availability: Restrictions in humanitarian access are the primary barrier to data collection in Sudan. Violence, bureaucratic hurdles, logistical, and communication challenges force humanitarian partners to mostly depend on less reliable remote data collection methods. The challenges that government agencies face when engaging in data collection efforts due to political volatility and limited operational presence, along with constrained funding and economic instability, further detract from the country’s information landscape. Additionally, the accuracy and reliability of data are compromised by the safety concerns of assessed populations, leading often to the withholding of information.
• Limited quantitative and granular data: The data landscape that informed Sudan’s Humanitarian Needs and Response Plan (HNRP) 2024 starkly contrasts with previous exercises, which utilized a comprehensive Multi-Sector Needs Assessment (MSNA) covering over twenty thousand households. This year, the absence of such large-scale household assessments has forced the 2024 HNRP to rely on alternative sources, which tend to offer more qualitative than quantitative insights, leading to a gap in granular, quantified data. Current data collection efforts across various sectors, while extensive, lack the numerical specificity and severity scales that MSNA provided.
• Sudan’s operational environment: The conflict situation is extensively monitored through Armed Conflict and Event Data Project (ACLED) reports, covering political and violent events, and augmented by in-depth insights from sources like the International Crisis Group. International media such as Al Jazeera, Reuters, and Washington Post, along with regional and local Sudanese media, provide both broad and onthe-ground perspectives. However, the rapidly evolving conflict presents challenges in capturing detai
Sectoral overview
• Protection: Severe humanitarian access constraints hinder granular assessment of protection needs, particularly in regions like Greater Darfur, Greater Kordofan, and Khartoum. Unstable communication systems in conflict areas impede protection program implementation and disrupt communication between communities and humanitarian actors. • Food Security and Livelihoods: There is a notable gap in reliable data on non-agricultural livelihoods and income-generating activities, as well as comprehensive household economic data, partly due to the lack of extensive governmental surveys.
• Health: Significant gaps in epidemiological tracking and registration persist, despite presence of the Sudan Outbreaks Dashboard. These gaps are further exacerbated by a shortage of medical personnel and damaged infrastructure, hindering the regular retrieval of data and health monitoring in Sudan’s healthcare facilities.
• Water, Sanitation and Hygiene (WASH): Apart from baseline and localized assessments, data and analysis regarding the overall country situation and resident populations are lacking. This scarcity is particularly significant in assessing practices such as open defecation, which had high rates in Sudan before the conflict.
• Education: Data on education losses are missing age or district level, limiting the depth of nuanced analysis. A notable deficiency exists in data regarding educational access for over 3 million internally displaced children. The lack of data is compounded by the absence of regular and official reporting from the government, hindering a comprehensive understanding of the education system’s status. Lastly, inconsistencies in data regarding school closures and conversion of educational facilities continue to be a significant issue.
• Nutrition: The sector faces significant data gaps due to limited access in conflict areas, staffing shortages, and outdated nutrition information systems. Challenges include inadequate coordination across relevant sectors and bureaucratic hurdles that hinder comprehensive data collection. This results in a dependence on generalized estimates rather than detailed, location-specific analyses, contributing to substantial uncertainty regarding the actual extent of Severe Acute Malnutrition (SAM) and the effectiveness of nutrition services in the region.
• Shelter and Non-Food Items (NFI): Rapid displacement of people due to conflict, coupled with the absence of regular national household surveys, results in limited information on Non-Food Items and overall living conditions of non-displaced residents, who are underrepresented in the data landscape of the sector.
