Climate finance and conflict: adaptation amid instability.

Conflict and climate change might be present in the same areas and expose communities that struggle with these dual risks, but they do not co-occur in consistent or predictable ways. We question how to effectively adapt to climate change in areas experiencing violence. Conflict can make adaptation to climate change more difficult, but when local conflict patterns are better understood it is possible to introduce climate adaptation measures that are effective and responsive to the needs of the population. Further, we argue that conflict mitigation is not a climate adaptation. Even in conflict zones, the most effective climate adaptations focus on climate-centred technical solutions and poverty reduction, local governance legitimacy, and community-led efforts to cooperate in periods of climate stress. We outline some of these possibilities.

Dry growing seasons predicted Central American migration to the US from 2012 to 2018.

Controlling for factors such as criminal violence and poverty, we tested if drier than usual growing season weather was a predictor of emigration from El Salvador, Guatemala, and Honduras to the US between 2012 and 2018. We focus on growing season weather because agriculture is a primary transmission pathway from the effects of climate change upon migration. We secured the migration apprehensions data for our analysis through a FOIA request to US Customs and Border Protection. Border Patrol intake interviews recorded the original home location of families that arrived at the southern US border. We used this geographic information to measure recent weather patterns and social circumstances in the area that each family departed. We found 70.7% more emigration to the US when local growing seasons in Central America were recently drier than the historical average since 1901.

How indiscriminate violence fuels conflicts between groups: Evidence from Kenya.

Armed conflicts frequently fuel tensions between groups. The "cognitive perspective" of group identification offers a possible explanation, but is tacit on exact causal pathways. We predict that indiscriminate violence by armed actors induces fear of future attacks which in turn leads to prejudice, enhanced in-group cohesion, and calls for segregation. Selective violence does not have these effects. Relying on panel surveys conducted in Nairobi and Mombasa during the violent Kenyan elections in the Summer of 2017, we find evidence for the predicted effects among Christians in 2-way Fixed Effects estimation and an endorsement experiment.

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

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.

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.

BACKGROUND: Malaria 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. METHODS: By 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. RESULTS: Of 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). CONCLUSIONS: This 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.