The prevention of famine is once again a significant humanitarian and policy issue. The population at risk has risen and a number of policy initiatives have been initiated to address the threat of famine. While actual famines, as determined by the Integrated Food Security Phase Classification (IPC) thresholds are still relatively rare, nearfamine crises are increasingly frequent, suggesting the need for earlier prevention measures. Based on a 2020 observation of different trajectories into famine and recent insights from famine theory, this paper analyzes four recent cases of famine or near famine crises, and identifies five common categories of factors and 12-15 contextspecific indicators within those categories that describe famine trajectories. This paper develops two novel ways of analyzing and depicting them. The main finding is that the shape of the trajectory matters less than the observation of how and when a trajectory-in other words, a famine system-starts. The ability to demonstrate the onset of a famine trajectory (as opposed to simply warning of worsening food insecurity) should enable earlier interventions to prevent famine.

TRANSLATIONS:For the French, Spanish and Arabic translations of the abstract see Supplementary Materials section.

While climate change will impact all aspects of the food system, it is not clear how it will influence the risk of famine: situations of extreme starvation. Drawing on theory for how and why famines occur, we analyze the ways that changes in extreme weather might alter local agricultural yields. We present CMIP6 projections of the change in risk for specific climate changes that are relevant to agriculture: heat, frost, precipitation, and dry spells. Then, we analyze crop model projections that estimate crop yields under future climate projections. In crop models run with a future scenario in which people plant the same crops as today, we find that calorie production from attainable crop yields is projected to decrease in much of Central America, Eastern South America, much of Africa, the Eastern Mediterranean, South Asia, parts of Southeast and East Asia, and Australia. However, under a scenario in which people are allowed to switch crops, we find that there is global potential for adaptation to climate change, with certain crops in every region that are projected to increase attainable yield under climate change. There are also major yield gaps that could be closed with adaptation investments. Based on the theory and analysis, we conclude that climate change may act as a contributing, rather than determinative, factor to famine-related risk. Given that adaptation will ultimately influence whether climate change will increase the probability of famine, we recommend investments in adaptation, especially in conflict-affected regions.

High-quality data are a pre-requisite for the development of models—whether of famine or food and nutrition-related emergencies. We highlighted challenges, related to data in famines or near-famine emergencies, including data availability, quality, timeliness, and sharing; the misuse of data could be a real threat for applying new advanced data analytic tools, such as artificial intelligence and machine learning. We also explored promising opportunities, such as democratization of data related to famine. With growing demands for real-time assessment and modeling of famine and extreme emergencies, it is increasingly important to understand how predictive models and emerging data-integration technologies are affected by biased, incomplete, inconsistent, or outdated data. As we push for addressing data constraints, we call for ethical data democratization to minimize the risks of data misuse, weaponization, and politization and to enable famine modeling for collective efforts to enhance early warning, real-time analysis, and response.

Climate shocks are increasing, threatening global agricultural production and food security. But a more extreme climate allows for improved predictions and enables advisory services that allow farmers, ranchers and consumers to respond effectively. To date, there is limited uptake of forecasts. How can we make sure these predictions are valued by and valuable for users of agro‐climatic forecasts? Over the past two years, we held over 40 interviews with food system stakeholders to identify their needs and shortcomings of existing decision support. In this Commentary, we combine these findings and nascent modeling efforts with existing literature to characterize five lessons for improving the uptake and utilization of predictive tools for last mile users in the agrifood system. Given the explosion of machine learning prediction efforts across many applications, we believe our lessons are broadly applicable to forecasting models intended for decision support. Improved accuracy alone does not necessarily lead to improved decision support, and the trust required to motivate action.

Food security information systems (FSIS) face unprecedented threats from abrupt shifts in political and funding priorities, misinformation, and manipulation. We draw on 50 years of research in Food Policy and the broader FSIS literature to offer five resilience characteristics to guide development of a future-fit FSIS: (1) safeguard integrity and impartiality; (2) ensure independent and transparent governance; (3) optimize data and analysis value streams for decision-making; (4) break down sectoral barriers for holistic food security characterization; and (5) innovate responsibly while embedding accountability and learning. We suggest recommended actions based on these resilience characteristics to co-create a more resilient FSIS ecosystem to guide humanitarian responses, advance preventive action for acute crises, and efficiently deliver results.

Quantitative information plays an important role in humanitarian analysis. Indeed, humanitarian information systems have built substantive standards and procedures and have invested significantly in cultivating analyst skill in collecting, analysing and integrating quantitative data into acute food insecurity and other humanitarian analyses, while also developing robust measures to cross-check its validity, reliability and representativeness. However, qualitative information also plays an important role in the analyses that feed into humanitarian information systems. Collecting and considering such evidence can be at least as systematic as methods used for representative quantitative data. But guidance for gathering, analysing, cross-checking and integrating this broader range of evidence into analyses that support humanitarian decision-making continues to lag, hampering the effective functioning of an important facet of the humanitarian response infrastructure. This paper highlights the role of qualitative data, proposing approaches for addressing the real and perceived challenges of gathering and analysing data using qualitative methods with the objective of sparking demand for the development of a more structured and standardised means of integrating these methods into humanitarian analyses to support more holistic, accurate, effective and impactful humanitarian responses.

In recent years, the world has faced a rapid rise in humanitarian needs and an increasing risk of famine. Given the potential threats posed by conflict, climate change, economic shocks, and other issues, it is important to be prepared for the possibility of new crises in the future. Drawing on key informant interviews and a literature review, this paper assesses the state of the art in famine prevention, examining a range of technical and political approaches and analysing emerging lessons. Based on the findings, it identifies five levels of famine prevention: (i) averting famine; (ii) anticipating famine; (iii) reducing famine risks; (iv) altering famine risks; and (v) preventing famine risks. The paper argues that the current focus only partially addresses a relatively narrow set of levels. It concludes that a more comprehensive approach that engages all five levels simultaneously could contribute to a global famine prevention framework for the twenty-first century and beyond.

This commentary discusses new advances in the predictability of east African rains and highlights the potential for improved early warning systems (EWS), humanitarian relief efforts, and agricultural decision-making. Following an unprecedented sequence of five droughts, in 2022 23 million east Africans faced starvation, requiring >$2 billion in aid. Here, we update climate attribution studies showing that these droughts resulted from an interaction of climate change and La Niña. Then we describe, for the first time, how attribution-based insights can be combined with the latest dynamic models to predict droughts at eight-month lead-times. We then discuss behavioral and social barriers to forecast use, and review literature examining how EWS might (or might not) enhance agro-pastoral advisories and humanitarian interventions. Finally, in reference to the new World Meteorological Organization (WMO) “Early Warning for All” plan, we conclude with a set of recommendations supporting actionable and authoritative climate services. Trust, urgency, and accuracy can help overcome barriers created by limited funding, uncertain tradeoffs, and inertia. Understanding how climate change is producing predictable climate extremes now, investing in African-led EWS, and building better links between EWS and agricultural development efforts can support long-term adaptation, reducing chronic needs for billions of dollars in reactive assistance. The main messages of this commentary will be widely. Climate change is interacting with La Niña to produce extreme, but extremely predictable, Pacific sea surface temperature gradients. These gradients will affect the climate in many countries creating opportunities for prediction. Effective use of such predictions, however, will demand cross-silo collaboration.

The currently accepted means of categorizing household food insecurity and identifying famine or famine risk is through Integrated Food Security Phase Classification (IPC) analysis. IPC guidelines set criteria for the measurement and determination of famine, but recent analyses in famine-risk countries have faced several challenges. Commonly used indicators capture different aspects of food security and often produce very divergent estimates of the prevalence of food insecurity. This led to the usage of the Household Hunger Scale (HHS) as the presumed "anchor" indicator for IPC acute food insecurity analysis, with all other indicators of food consumption calibrated to the HHS. But because there was no gold standard, only an "anchor," this presumption had never been tested. Further, given that HHS was the only indicator that could specify the difference between the two most severe categories of IPC Phase Classification (Phase 4 "Emergency" and Phase 5 "Famine"), analysis of food insecurity at the extreme end of the IPC scale relies heavily on HHS, rather than the standard panoply of indicators used for acute food insecurity analysis at lesser levels of severity. This study sought to test how well HHS differentiates between IPC Phase 4 and Phase 5 and to investigate the validity of the usage of HHS as the "anchor" indicator across the spectrum of IPC analysis. Data was collected in seven different severely food-insecure areas of South Sudan, Kenya, and Somalia. The findings show that, overall, the HHS performs reasonably well as an "anchor indicator" across the IPC scale and is able to differentiate the majority of cases in Phases 4 and 5 but tends to over-classify (over-estimate the severity of food insecurity at the household level)—especially at the lower end of the IPC scale. At the high end of the scale, these results indicate that HHS is good at flagging highly food-insecure households but may require additional information to rigorously differentiate households in Phase 4 from those in Phase 5. The study identified ways to improve classification by HHS by some simple additional questions or observations to differentiate between Phase 4 and Phase 5. In an era of extreme scarcity of humanitarian funding, this has substantial implications for resource allocation and humanitarian prioritization.

As climate change increases the frequency and intensity of extreme weather events, governments and civil society organizations are making large investments in early warning systems (EWS) with the aim to avoid death and destruction from hydro-meteorological events. Early warning systems have four components: (1) risk knowledge, (2) monitoring and warning, (3) warning dissemination and communication, and (4) response capability. While there is room to improve all four of these components, we argue that the largest gaps in early warning systems fall in the latter two categories: warning dissemination/communication and response capability. We illustrate this by examining the four components of early warning systems for the deadliest and costliest meteorological disasters of this century, demonstrating that the lack of EWS protection is not a lack of forecasts or warnings, but rather a lack of adequate communication and lack of response capability. Improving the accuracy of weather forecasts is unlikely to offer major benefits without resolving these gaps in communication and response capability. To protect vulnerable groups around the world, we provide recommendations for investments that would close such gaps, such as improved communication channels, impact forecasts, early action policies and infrastructure. It is our hope that further investment to close these gaps can better deliver on the goal of reducing deaths and damages with EWS.

Abstract This chapter provides an overview of famine early warning systems (EWS) that have developed since the 1970s. With advances in the measurement and monitoring of malnutrition, augmented by new information and communication technologies, these systems have become increasingly sophisticated in the past decade, but they still tend to be based on the assumption that extreme food insecurity is an amplified version of regular seasonal stresses in agrarian societies, and is driven primarily by environmental and economic factors. Despite internationally agreed priorities about the links between armed conflict and extreme hunger, EWS can’t always deal directly with question of deliberately inflicted hunger. This is partly because they are either government-owned systems (and governments are frequently parties to the conflicts that cause contemporary famines) or they are managed by UN agencies that have to negotiate presence in and access to affected populations, and are therefore reluctant to anger parties to the conflict (be they government or non-state actors). Even attempting to track and analyse conflict can be difficult; tracking or analysing the use of hunger as a weapon of war is difficult for these formal, government- or UN-led systems. These arguments are exemplified in discussion of Somalia, South Sudan, Syria, and Yemen.

The explosion in data availability and new analytical tools combined with increasing humanitarian need and the imperative of anticipatory action compel us to rethink humanitarian information systems and humanitarian action for the future. Synthesizing interviews with humanitarian practitioners, donors, analysts, and researchers and analyses of early warning (EW) information systems and their linkages to Anticipatory Action (AA), we describe six information challenges within the current system: abundant but confusing information, the difficulty of predicting conflict, politicized information, limitations of new analytical tools, varying information needs, and limited data sharing. We then propose an approach to improve the timeliness and appropriateness of action for humanitarian crises and disasters. Rather than ask, “What can we do with the information (early warning and otherwise) that we have to inform action?” we propose asking, “What information do we need for anticipatory (and other) action?” In other words, we propose planning from known and likely hazards and actions back to information needs. Such an approach should help to mitigate shocks before they cause major humanitarian crises. While not all crises can be prevented, this approach could also support responsive action, which is equally important for protecting human life and dignity.

In 2017, the UN raised the alarm on famines in North-east Nigeria, Somalia, South Sudan and Yemen. Starvation has been used as a weapon of war in Syria, and the Democratic Republic of the Congo currently has among the largest numbers of severely food-insecure people of any country assessed by the Integrated Food Security Phase Classification (IPC) system. Each of these sites of mass starvation or famine can be understood as a ‘political marketplace’. They are characterised by the dominance of transactional politics over public institutions, and elite politics is conducted for factional or personal political advantage, on the basis of monetised patronage. This paper examines the relationship between these systems of transactional politics and famine and other forms of mass starvation, and outlines the implications of the political marketplace framework for humanitarian action. It argues that both transactional politics and mass starvation emerge from particular political-economic configurations characterised by economic precarity and mismanagement, violent forms of peripheral governance and war economies. Applying the political marketplace framework can help improve humanitarian information and early warning systems, as well as programme decision-making, while helping humanitarians think more carefully about the constant trade-offs they are forced to make.

In 2017, the UN raised the alarm on famines in North-east Nigeria, Somalia, South Sudan and Yemen. Starvation has been used as a weapon of war in Syria, and the Democratic Republic of the Congo currently has among the largest numbers of severely food-insecure people of any country assessed by the Integrated Food Security Phase Classification (IPC) system. Each of these sites of mass starvation or famine can be understood as a ‘political marketplace’. They are characterised by the dominance of transactional politics over public institutions, and elite politics is conducted for factional or personal political advantage, on the basis of monetised patronage. This paper examines the relationship between these systems of transactional politics and famine and other forms of mass starvation, and outlines the implications of the political marketplace framework for humanitarian action. It argues that both transactional politics and mass starvation emerge from particular political-economic configurations characterised by economic precarity and mismanagement, violent forms of peripheral governance and war economies. Applying the political marketplace framework can help improve humanitarian information and early warning systems, as well as programme decision-making, while helping humanitarians think more carefully about the constant trade-offs they are forced to make.

Famine means destitution, increased severe malnutrition, disease, excess death and the breakdown of institutions and social norms. Politically, it means a failure of governance – a failure to provide the most basic of protections. Because of both its human and political meanings, ‘famine’ can be a shocking term. This is turn makes the analysis – and especially declaration – of famine a very sensitive subject. This paper synthesises the findings from six case studies of the analysis of extreme food insecurity and famine to identify the political constraints to data collection and analysis, the ways in which these are manifested, and emergent good practice to manage these influences. The politics of information and analysis are the most fraught where technical capacity and data quality are the weakest. Politics will not be eradicated from analysis but can and must be better managed.

Background: Kwashiorkor is an often-fatal type of severe acute malnutrition affecting hundreds of thousands of children annually, but whose etiology is still unknown. Evidence suggests inadequate sulfur amino acid (SAA) status may explain many signs of the condition but studies evaluating dietary protein intake in relation to the genesis of kwashiorkor have been conflicting. We know of no studies of kwashiorkor that have measured dietary SAAs. Objectives: We aimed to determine whether children in a population previously determined to have high prevalence of kwashiorkor [high-prevalence population (HPP)] have lower dietary intakes of SAAs than children in a low-prevalence population (LPP). Methods: A cross-sectional census survey design of 358 children compared 2 previously identified adjacent populations of children 36-59 mo old in North Kivu Province of the Democratic Republic of the Congo. Data collected included urinary thiocyanate (SCN), cyanogens in cassava-based food products, recent history of illness, and a 24-h quantitative diet recall for the child. Results: The HPP and LPP bad kwashiorkor prevalence of 4.5% and 1.7%, respectively. A total of 170 children from 141 households in the LPP and 169 children from 138 households in the HPP completed the study. A higher proportion of HPP children had measurable urinary SCN (44.8% compared with 29.4%, P < 0.01). LPP children were less likely to have been ill recently (26.8% compared with 13.6%. P < 0.01). Median [IQR] intake of SAAs was 32.4 [22.9-49.3] mg/kg for the LPP and 29.6 [18.1-44.3] mg/kg for the HPP (P < 0.05). Methionine was the first limiting amino acid in both populations. with the highest risk of inadequate intake found among HPP children (35.1% compared with 23.6%. P < 0.05). Conclusions: Children in a population with a higher prevalence of kwashiorkor have lower dietary intake of SAAs than children in a population with a lower prevalence. Trial interventions to reduce incidence of kwashiorkor should consider increasing SAA intake, paying particular attention to methionine.

Famine was, until recently, largely a matter of historical or theoretical interest, but the “four famines” threat of 2017 demonstrated that Somalia in 2011 was not an aberration or outlier: famine is a contemporary reality and threat. Current methods of famine analysis however tend to emphasize the severity of current-status indicators as the sole dimension of analysis. This article argues that a more multi-dimensional view is required for a full understanding of famine, including not only severity but also the magnitude of the crisis, the temporal dimension or duration, and the spatial dimension or geographic specificity of the crisis. The article draws on recent experience of famine analysis in Nigeria, South Sudan, Somalia, and Yemen to demonstrate the way in which our current analytical perspective misses critical dimensions of famine, and the consequences of this for analysis, prevention, and response. A more multi-dimensional perspective sheds new light on famine dynamics, but also highlights the importance of causal analysis in addition to classification or determination.