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.

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.social instability | standard precipitation index | generalized additive modeling | negative binomial modeling | disaggregated spatial analysis

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 one's 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.

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. SubSaharan 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 crosssectional dataset for disaggregated analyses.climate variability | multilevel modeling | disaggregated spatial analysis | regional contexts | types of violence indicators C ontinued public and academic interest in the topic of global climate change consequences for political instability and the risk of conflict has generated a growing but inconclusive literature, especially about the effects in sub-Saharan Africa. Claims that climate change contributes to conflict have been plentiful since Miguel et al. (1) found that negative deviations of annual precipitation in sub-Saharan African countries reduce national economic growth, and thus indirectly lead to higher risk of civil war. The recent fifth assessment of the Intergovernmental Panel on Climate Change highlights the severely damaging effects of predicted climatic disturbances for vulnerable societies around the world (2). Multiple recent analyses provide support for the general position that climate change has "strong causal" influences on conflict (3, 4), although the authors do not elaborate on nor test the causal mechanisms (also refs. 5 and 6).Many existing statistical studies are based on data aggregated to large geographic units such as countries, using crude climate indicators and generalized high-level conflict measures. Some studies indicate positive relationships between climate extremes and violence at the large scale (7-9), whereas contrasting work reports a lack of significant effects (10-12). Using fine-resolution spatial scales, other researchers find weak or no climate-conflict association; they conclude that the relationship is complex and depends on the social characteristics of the regional settings (13-15), or that the relationship is nonlinear across multiple regions and livelihood zones (16). In direct contrast to the scarcity narrative, some research suggests that an abundance of wa...

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