Andrew M. Linke

Introducing ACLED: an armed conflict location and event dataset

This article presents ACLED, an Armed Conflict Location and Event Dataset. ACLED codes the actions of rebels, governments, and militias within unstable states, specifying the exact location and date of battle events, transfers of military control, headquarter establishment, civilian violence, and rioting. In the current version, the dataset covers 50 unstable countries from 1997 through 2010. ACLED’s disaggregation of civil war and transnational violent events allow for research on local level factors and the dynamics of civil and communal conflict. Findings from subnational conflict research challenges conclusions from larger national-level studies. In a brief descriptive analysis, the authors find that, on average, conflict covers 15% of a state’s territory, but almost half of a state can be directly affected by internal wars.

Climate variability and conflict risk in East Africa, 1990–2009

Recent studies concerning the possible relationship between climate trends and the risks of violent conflict have yielded contradictory results, partly because of choices of conflict measures and modeling design. In this study, we examine climate–conflict relationships using a geographically disaggregated approach. We consider the effects of climate change to be both local and national in character, and we use a conflict database that contains 16,359 individual geolocated violent events for East Africa from 1990 to 2009. Unlike previous studies that relied exclusively on political and economic controls, we analyze the many geographical factors that have been shown to be important in understanding the distribution and causes of violence while also considering yearly and country fixed effects. For our main climate indicators at gridded 1° resolution (∼100 km), wetter deviations from the precipitation norms decrease the risk of violence, whereas drier and normal periods show no effects. The relationship between temperature and conflict shows that much warmer than normal temperatures raise the risk of violence, whereas average and cooler temperatures have no effect. These precipitation and temperature effects are statistically significant but have modest influence in terms of predictive power in a model with political, economic, and physical geographic predictors. Large variations in the climate–conflict relationships are evident between the nine countries of the study region and across time periods.

Population, behavioural and environmental drivers of malaria prevalence in the Democratic Republic of Congo

BackgroundMalaria is highly endemic in the Democratic Republic of Congo (DRC), but the limits and intensity of transmission within the country are unknown. It is important to discern these patterns as well as the drivers which may underlie them in order for effective prevention measures to be carried out.MethodsBy applying high-throughput PCR analyses on leftover dried blood spots from the 2007 Demographic and Health Survey (DHS) for the DRC, prevalence estimates were generated and ecological drivers of malaria were explored using spatial statistical analyses and multilevel modelling.ResultsOf the 7,746 respondents, 2268 (29.3%) were parasitaemic; prevalence ranged from 0-82% within geographically-defined survey clusters. Regional variation in these rates was mapped using the inverse-distance weighting spatial interpolation technique. Males were more likely to be parasitaemic than older people or females (p < 0.0001), while wealthier people were at a lower risk (p < 0.001). Increased community use of bed nets (p = 0.001) and community wealth (p < 0.05) were protective against malaria at the community level but not at the individual level. Paradoxically, the number of battle events since 1994 surrounding ones community was negatively associated with malaria risk (p < 0.0001).ConclusionsThis research demonstrates the feasibility of using population-based behavioural and molecular surveillance in conjunction with DHS data and geographic methods to study endemic infectious diseases. This study provides the most accurate population-based estimates to date of where illness from malaria occurs in the DRC and what factors contribute to the estimated spatial patterns. This study suggests that spatial information and analyses can enable the DRC government to focus its control efforts against malaria.

The Afghanistan-Pakistan Wars, 2008-2009: Micro-geographies, Conflict Diffusion, and Clusters of Violence

A team of political geographers analyzes over 5,000 violent events collected from media reports for the Afghanistan and Pakistan conflicts during 2008 and 2009. The violent events are geocoded to precise locations and the authors employ an exploratory spatial data analysis approach to examine the recent dynamics of the wars. By mapping the violence and examining its temporal dimensions, the authors explain its diffusion from traditional foci along the border between the two countries. While violence is still overwhelmingly concentrated in the Pashtun regions in both countries, recent policy shifts by the American and Pakistani governments in the conduct of the war are reflected in a sizeable increase in overall violence and its geographic spread to key cities. The authors identify and map the clusters (hotspots) of conflict where the violence is significantly higher than expected and examine their shifts over the two-year period. Special attention is paid to the targeting strategy of drone missile strikes and the increase in their number and geographic extent by the Obama administration.

Effects of temperature and precipitation variability on the risk of violence in sub-Saharan Africa, 1980–2012

Significance A robust debate about the effects of climate change on conflict occurrences has attained wide public and policy attention, with sub-Saharan Africa generally viewed as most susceptible to increased conflict risk. Using a new disaggregated dataset of violence and climate anomaly measures (temperature and precipitation variations from normal) for sub-Saharan Africa 1980–2012, we consider political, economic, and geographic factors, not only climate metrics, in assessing the chances of increased violence. The location and timing of violence are influenced less by climate anomalies than by key political, economic, and geographic factors. Overall, the temperature effect is statistically significant, but important inconsistencies in the relationship between temperature extremes and conflict are evident in more nuanced relationships than have been previously identified. Ongoing debates in the academic community and in the public policy arena continue without clear resolution about the significance of global climate change for the risk of increased conflict. Sub-Saharan Africa is generally agreed to be the region most vulnerable to such climate impacts. Using a large database of conflict events and detailed climatological data covering the period 1980–2012, we apply a multilevel modeling technique that allows for a more nuanced understanding of a climate–conflict link than has been seen heretofore. In the aggregate, high temperature extremes are associated with more conflict; however, different types of conflict and different subregions do not show consistent relationship with temperature deviations. Precipitation deviations, both high and low, are generally not significant. The location and timing of violence are influenced less by climate anomalies (temperature or precipitation variations from normal) than by key political, economic, and geographic factors. We find important distinctions in the relationship between temperature extremes and conflict by using multiple methods of analysis and by exploiting our time-series cross-sectional dataset for disaggregated analyses.

Space-Time Granger Analysis of the War in Iraq: A Study of Coalition and Insurgent Action-Reaction

We investigate insurgent-coalition interaction using the WikiLeaks dataset of Iraq war logs 2004–2009. After a review of existing theoretical interventions on the dynamics of insurgency and presenting a baseline model of violent events, we test a conceptual model of reciprocity using an innovative space-time Granger causality technique. Our estimation procedure retains predicted probabilities of reaction in response to a previous opponents action across different temporal and spatial configurations in Iraq and in Baghdad. Our conclusions about conflict in Iraq are based on these profiles of risk—what we call space-time signatures. We find strong evidence of “tit-for-tat” associations between coalition/Iraq forces on one side and insurgents/militants on the other. Specifically, we find that the action-reaction association varies strongly by majority ethnic region across Iraq and in Baghdad, by urban and nonurban location, and within Sunni-dominated areas, by district income. While violence is strongly temporally dependent in the same location, the effect of distance varies significantly across the different subsets of the Iraq data.

Modeling and data choices sway conclusions about climate-conflict links

In an era of growing concern about the human impacts of climate change, the academic and policy communities are paying increasing attention to the possible link between weather anomalies and violent conflict. Early research papers on the topic by Burke et al. (1) and the reanalysis and extension of their work by Buhaug (2) claim contradictory findings, the first showing a link between increased temperatures and war, and the second—using an expanded dataset and different models—calling these results into question. Hsiang and Meng (3) reexamine the data and argue that the original Burke et al. (1) conclusions are robust and remain a “benchmark” for future studies of the climate–conflict relationship.

Subnational violent conflict forecasts for sub-Saharan Africa, 2015–65, using climate-sensitive models

How will local violent conflict patterns in sub-Saharan Africa evolve until the middle of the 21st century? Africa is recognized as a particularly vulnerable continent to environmental and climate change since a large portion of its population is poor and reliant on rain-fed agriculture. We use a climate-sensitive approach to model sub-Saharan African violence in the past (geolocated to the nearest settlements) and then forecast future violence using sociopolitical factors such as population size and political rights (governance), coupled with temperature anomalies. Our baseline model is calibrated using 1° gridded monthly data from 1980 to 2012 at a finer spatio-temporal resolution than existing conflict forecasts. We present multiple forecasts of violence under alternative climate change scenarios (optimistic and current global trajectories), of political rights scenarios (improvement and decline), and population projections (low and high fertility). We evaluate alternate shared socio-economic pathways (SSPs) by plotting violence forecasts over time and by detailed mapping of recent and future levels of violence by decade. The forecasts indicate that a growing population and rising temperatures will lead to higher levels of violence in sub-Saharan Africa if political rights do not improve. If political rights continue to improve at the same rate as observed over the last three decades, there is reason for optimism that overall levels of violence will hold steady or even decline in Africa, in spite of projected population increases and rising temperatures.

State and Stateless Violence in Somalia

Abstract Violent conflict has engulfed much of Somalia for decades. Marked most dramatically by the fall of Mohamed Siad Barres dictatorship early in 1991, southern Somalia remains in an untenable state of civil strife that amounts to a humanitarian disaster. In this article our goal is not to explain why violence occurs, but to investigate where and when it has occurred. To achieve this we employ precisely georeferenced conflict event data to analyze dynamics of Somalias violent political landscape from before the Ogaden wars of the late-1970s through Ethiopias intervention in Somalia beginning in December 2006. We utilize Geographic Information Systems (GIS) tools and spatial statistical methods to characterize the distribution of violence over time and across space within Somalia. We argue that Somalias conflict meets some expectations of civil war violence described in the conflict studies literature, but some unexpected trends also appear. Country-wide, for instance, we show that conflict intensity is characterized by a limited degree of spatial clustering during the period of centralized state-rule in Somalia, but also during stateless years. Despite this national trend, using sub-national analyses we present evidence that spatial patterns of conflict during state tenure vary from distributions conflict after state collapse. Finally, we elaborate upon how our methodological approach can contribute to the study of other conflict-prone African states.

Drought, Local Institutional Contexts, and Support for Violence in Kenya

We address two questions on the effects of climate change for social instability. First, do droughts and their associated environmental impacts affect support for the use of violence? Second, do local-level formal and informal institutions moderate support for violence when and where droughts worsen? To answer these questions, we conducted a national survey of 1,400 Kenyans in 2014. Respondents were asked about patterns of rainfall and the presence of rules regulating natural resource use and access. Survey data are joined to spatially disaggregated observed rainfall trends. The survey uses endorsement experiments to elicit honest responses about support for using violence. There is some evidence of a direct, though limited, link between observed drought and violent attitudes. Certain local-level natural resource use rules have moderating effects on support for violence where drought is reported and precipitation is less frequent. This conditional and contextual effect is an important modification of overly simplistic narratives of universal climate change effects.