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

Temperature, Crime, and Violence: A Systematic Review and Meta-Analysis

BACKGROUND

Heat is known to affect many health outcomes, but more evidence is needed on the impact of rising temperatures on crime and/or violence.

OBJECTIVES

We conducted a systematic review with meta-analysis regarding the influence of hot temperatures on crime and/or violence.

METHODS

In this systematic review and meta-analysis, we evaluated the relationship between increase in temperature and crime and/or violence for studies across the world and generated overall estimates. We searched MEDLINE and Web of Science for articles from the available database start year (1946 and 1891, respectively) to 6 November 2023 and manually reviewed reference lists of identified articles. Two investigators independently reviewed the abstracts and full-text articles to identify and summarize studies that analyzed the relationship between increasing temperature and crime, violence, or both and met a priori eligibility criteria. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were used to extract information from included articles. Some study results were combined using a profile likelihood random-effects model for meta-analysis for a subset of outcomes: violent crime (assault, homicide), property crime (theft, burglary), and sexual crime (sexual assault, rape). This review is registered at PROSPERO, CRD42023417295.

RESULTS

We screened 16,634 studies with 83 meeting the inclusion criteria. Higher temperatures were significantly associated with crime, violence, or both. A 10°C (18°F) increase in short-term mean temperature exposure was associated with a 9% [95% confidence interval (CI): 7%, 12%] increase in the risk of violent crime (I 2 = 30.93 % ; eight studies). Studies had differing definitions of crime and/or violence, exposure assessment methods, and confounder assessments.

DISCUSSION

Our findings summarize the evidence supporting the association between elevated temperatures, crime, and violence, particularly for violent crimes. Associations for some categories of crime and/or violence, such as property crimes, were inconsistent. Future research should employ larger spatial/temporal scales, consistent crime and violence definitions, advanced modeling strategies, and different populations and locations. https://doi.org/10.1289/EHP14300.

Drivers of the dynamics of the spread of cholera in the Democratic Republic of the Congo, 2000-2018: An eco-epidemiological study

BACKGROUND

The dynamics of the spread of cholera epidemics in the Democratic Republic of the Congo (DRC), from east to west and within western DRC, have been extensively studied. However, the drivers of these spread processes remain unclear. We therefore sought to better understand the factors associated with these spread dynamics and their potential underlying mechanisms.

METHODS

In this eco-epidemiological study, we focused on the spread processes of cholera epidemics originating from the shores of Lake Kivu, involving the areas bordering Lake Kivu, the areas surrounding the lake areas, and the areas out of endemic eastern DRC (eastern and western non-endemic provinces). Over the period 2000-2018, we collected data on suspected cholera cases, and a set of several variables including types of conflicts, the number of internally displaced persons (IDPs), population density, transportation network density, and accessibility indicators. Using multivariate ordinal logistic regression models, we identified factors associated with the spread of cholera outside the endemic eastern DRC. We performed multivariate Vector Auto Regressive models to analyze potential underlying mechanisms involving the factors associated with these spread dynamics. Finally, we classified the affected health zones using hierarchical ascendant classification based on principal component analysis (PCA).

FINDINGS

The increase in the number of suspected cholera cases, the exacerbation of conflict events, and the number of IDPs in eastern endemic areas were associated with an increased risk of cholera spreading outside the endemic eastern provinces. We found that the increase in suspected cholera cases was influenced by the increase in battles at lag of 4 weeks, which were influenced by the violence against civilians with a 1-week lag. The violent conflict events influenced the increase in the number of IDPs 4 to 6 weeks later. Other influences and uni- or bidirectional causal links were observed between violent and non-violent conflicts, and between conflicts and IDPs. Hierarchical clustering on PCA identified three categories of affected health zones: densely populated urban areas with few but large and longer epidemics; moderately and accessible areas with more but small epidemics; less populated and less accessible areas with more and larger epidemics.

CONCLUSION

Our findings argue for monitoring conflict dynamics to predict the risk of geographic expansion of cholera in the DRC. They also suggest areas where interventions should be appropriately focused to build their resilience to the disease.

Exploring the worldwide impact of COVID-19 on conflict risk under climate change

Objectives

Understand whether and how the COVID-19 pandemic affects the risk of different types of conflict worldwide in the context of climate change.

Methodology

Based on the database of armed conflict, COVID-19, detailed climate, and non-climate data covering the period 2020-2021, we applied Structural Equation Modeling specifically to reorganize the links between climate, COVID-19, and conflict risk. Moreover, we used the Boosted Regression Tree method to simulate conflict risk under the influence of multiple factors.

Findings

The transmission risk of COVID-19 seems to decrease as the temperature rises. Additionally, COVID-19 has a substantial worldwide impact on conflict risk, albeit regional and conflict risk variations exist. Moreover, when testing a one-month lagged effect, we find consistency across regions, indicating a positive influence of COVID-19 on demonstrations (protests and riots) and a negative relationship with non-state and violent conflict risk.

Conclusion

COVID-19 has a complex effect on conflict risk worldwide under climate change.

Implications

Laying the theoretical foundation of how COVID-19 affects conflict risk and providing some inspiration for the implementation of relevant policies.

High ambient temperatures are associated with urban crime risk in Chicago

Urban crime (UC) seriously affects the security and stability of the communities and society. However, the effects of external temperatures on the risk of UC are still confusing. We quantitatively estimated the effects of high and low temperatures on UC in Chicago. After controlling for the confounding factors, we found that high temperature has a positive promoting effect on UC, for non-domestic crime, the effect occurs at lag day 0 with a maximum risk of 1.40 (95%CI, 1.34-1.46) compared to a risk of 1 at temperature of -12.3 °C, and decreased as the lag day increased. The effect of low temperature is not significant for UC. Heat waves above the 99th percentile with a duration of 4.5-5.5 days exert a significant positive impact on non-domestic crime of UC. Our findings confirm the adverse promotion effect of high temperature on UC risk, and effective individual behavior guidance and administrative intervention are of great significance for reducing the risk of UC under specific high temperature environment.

Exploring the direct and indirect impacts of climate variability on armed conflict in South Asia

Although numerous studies have examined the effects of climate variability on armed conflict, the complexity of these linkages requires deeper understanding to assess the causes and effects. Here, we assembled an extensive database of armed conflict, climate, and non-climate data for South Asia. We used structural equation modeling to quantify both the direct and indirect impacts of climate variability on armed conflict. We found that precipitation impacts armed conflict via direct and indirect effects which are contradictory in sign. Temperature affects armed conflict only through a direct path, while indirect effects were insignificant. Yet, an in-depth analysis of indirect effects showed that the net impact is weak due to two strong contradictory effects offsetting each other. Our findings illustrate the complex link between climate variability and armed conflict, highlighting the importance of a detailed analysis of South Asia's underlying mechanisms at the regional scale.

Environmental stress increases out-group aggression and intergroup conflict in humans

Peaceful coexistence and trade among human groups can be fragile and intergroup relations frequently transition to violent exchange and conflict. Here we specify how exogenous changes in groups' environment and ensuing carrying-capacity stress can increase individual participation in intergroup conflict, and out-group aggression in particular. In two intergroup contest experiments, individuals could contribute private resources to out-group aggression (versus in-group defense). Environmental unpredictability, induced by making non-invested resources subject to risk of destruction (versus not), created psychological stress and increased participation in and coordination of out-group attacks. Archival analyses of interstate conflicts showed, likewise, that sovereign states engage in revisionist warfare more when their pre-conflict economic and climatic environment were more volatile and unpredictable. Given that participation in conflict is wasteful, environmental unpredictability not only made groups more often victorious but also less wealthy. Macro-level changes in the natural and economic environment can be a root cause of out-group aggression and turn benign intergroup relations violent.

This article is part of the theme issue ‘Intergroup conflict across taxa’.

Modelling armed conflict risk under climate change with machine learning and time-series data

Understanding the risk of armed conflict is essential for promoting peace. Although the relationship between climate variability and armed conflict has been studied by the research community for decades with quantitative and qualitative methods at different spatial and temporal scales, causal linkages at a global scale remain poorly understood. Here we adopt a quantitative modelling framework based on machine learning to infer potential causal linkages from high-frequency time-series data and simulate the risk of armed conflict worldwide from 2000–2015. Our results reveal that the risk of armed conflict is primarily influenced by stable background contexts with complex patterns, followed by climate deviations related covariates. The inferred patterns show that positive temperature deviations or precipitation extremes are associated with increased risk of armed conflict worldwide. Our findings indicate that a better understanding of climate-conflict linkages at the global scale enhances the spatiotemporal modelling capacity for the risk of armed conflict.

Using machine learning, the authors reveal that stable background conditions explain most variation in armed conflict risk worldwide. Positive temperature deviations and precipitation extremes also increase the risk of conflict onset and incidence.

The association between weather and crime in a township setting in South Africa

The association between various meteorological parameters and crime is well-established in developed contexts. In contrast in this study, we investigated the association between three weather parameters (temperature, relative humidity and rainfall) and three categories of crime in the developing township of Khayelitsha, in the Western Cape Province of South Africa. Distributed lag non-linear modelling was used to identify temporal relationships between temperature, relative humidity and rainfall, and violent, property and sexual crime over a 10-year period (2006-2016). We found hot days (defined as [Formula: see text] 25 °C) increased the cumulative relative risk of violent crime by up to 32% but were also found to be associated with a lagged increase in violent crime for at least a week thereafter. On very cold days (defined as [Formula: see text]), the cumulative relative risk of property crime increased by up to 50% whereas on very rainy days (defined as [Formula: see text]) the risk of property crime surprisingly increased by 40%. These findings provide some additional evidence for the relationship between the atmospheric environment and human behaviour in a developing context.

A Monte Carlo analysis of false inference in spatial conflict event studies

Spatial event data is heavily used in contemporary research on political violence. Such data are oftentimes mapped onto grid-cells or administrative regions to draw inference about the determinants of conflict intensity. This setup can identify geographic determinants of violence, but is also prone to methodological issues. Problems resulting from spatial aggregation and dependence have been raised in methodological studies, but are rarely accounted for in applied research. As a consequence, we know little about the empirical relevance of these general problems and the trustworthiness of a popular research design. We address these questions by simulating conflict events based on spatial covariates from seven high-profile conflicts. We find that standard designs fail to deliver reliable inference even under ideal conditions at alarming rates. We also test a set of statistical remedies which strongly improve the results: Controlling for the geographic area of spatial units eliminates an important source of spurious correlation. In time-series analyses, the same result can be achieved with unit-level fixed effects. Under outcome diffusion, spatial lag models with area controls produce most reliable inference. When those are computationally intractable, geographically larger aggregations lead to similar improvements. Generally, all analyses should be performed at two separate levels of geographic aggregation. To facilitate future research into geographic methods, we release the Simple Conflict Event Generator (SCEG) developed for this analysis.

The Impact of Climate-Change-Related Disasters on Africa's Economic Growth, Agriculture, and Conflicts: Can Humanitarian Aid and Food Assistance Offset the Damage?

This study analyzed the impact of climate-related natural disasters (droughts, floods, storms/rainstorms) on economic and social variables. As the Africa-specific empirical literature is limited, this study used panel data from 1961–2011 on Africa. The study used a panel data regression model analysis. The results showed that climate change-related natural disasters affected Africa’s economic growth, agriculture, and poverty and caused armed conflicts. Among the disasters, droughts are the main cause of negative impact, severely affecting crops such as maize and coffee and resulting in increased urban poverty and armed conflicts. In contrast, international aid has a positive effect but the impact is insignificant compared to the negative consequences of climate-related natural disasters. Cereal food assistance has a negative crowding-out effect on cereal production. International donors should review their interventions to support Africa’s adaptative capacity to disasters. Government efficiency has reduced the number of deaths, and this is an area that supports Africa’s adaptative efforts.

Climate change-induced human conflicts and economic costs in Pakistani Punjab

Understanding causes of interpersonal conflicts, related costs, and the effects on investment in agriculture are important concerns of social sciences. The present study was designed to explore these aspects in relation to climate change, since rising temperature and precipitation are considered crucial causal factors in fueling interpersonal conflicts. The study used cross-sectional data collected from rural farm households from a large district of Pakistani Punjab. Cost of conflicts was estimated using standard economic methods whereas factors affecting interpersonal conflicts were estimated through employing logit model. The study found that interpersonal conflicts cost US$135 per month for following the proceedings of the conflicts filed in the court. Households involved in conflicts spent significantly very few resources in purchasing farm inputs which in turn declined productivity of maize (28%) and sugarcane (19%). Warm temperature, precipitation, and windstorm were perceived by households as causal factors for interpersonal conflicts. Socioeconomic characteristics namely, farm size, livestock, family size, and high monthly income of household, were significantly associated with interpersonal conflicts. The study concludes important policy implications.

Climate as a risk factor for armed conflict

Research findings on the relationship between climate and conflict are diverse and contested. Here we assess the current understanding of the relationship between climate and conflict, based on the structured judgments of experts from diverse disciplines. These experts agree that climate has affected organized armed conflict within countries. However, other drivers, such as low socioeconomic development and low capabilities of the state, are judged to be substantially more influential, and the mechanisms of climate-conflict linkages remain a key uncertainty. Intensifying climate change is estimated to increase future risks of conflict.

Climate as a risk factor for armed conflict

Research findings on the relationship between climate and conflict are diverse and contested. Here we assess the current understanding of the relationship between climate and conflict, based on the structured judgments of experts from diverse disciplines. These experts agree that climate has affected organized armed conflict within countries. However, other drivers, such as low socioeconomic development and low capabilities of the state, are judged to be substantially more influential, and the mechanisms of climate-conflict linkages remain a key uncertainty. Intensifying climate change is estimated to increase future risks of conflict.

Disaster risk reduction amidst armed conflict: informal institutions, rebel groups, and wartime political orders

Extant research has explored the effect of natural hazards on the risk of armed conflict, but very few studies have examined how conflict dynamics affect disaster risk reduction (DRR), including climate change adaptation. This is surprising given the empirical evidence that indicates how often disasters and armed conflicts collide. To understand better the impact of armed conflict on DRR, this paper develops a conceptual typology that is based on rebel groups' territorial control and on the strength of informal institutions. It documents three main political orders amid conflict: rebel stability; informal stability; and fragmented landscape. These wartime political orders will have different effects on DRR and other development programmes, revealing the importance of desegregating armed conflict to facilitate tailor-made and more efficient interventions. The paper provides empirical evidence from Mali and the Philippines that illustrates the influence of these wartime political orders on DRR programmes.

The Association of Ambient Temperature and Violent Crime

It is controversial if global warming will result into increased crime and conflict rate, and no causal neurobiological mechanisms have been proposed for the putative association between ambient temperature and aggressive behavior. This study shows that during 1996–2013, ambient temperature explained 10% of variance in the violent crime rate in Finland, corresponding to a 1.7% increase/degree centigrade. Ambient temperature also correlated with a one month delay in circannual changes in peripheral serotonin transporter density among both offenders and healthy control subjects, which itself correlated strongly with the monthly violent crime rate. This suggests that rise in temperature modulates serotonergic transmission which may increase impulsivity and general human activity level, resulting into increase in social interaction and risk of violent incidents. Together, these results suggest that the effect of ambient temperature on occurrence of violent crime is partly mediated through the serotonergic system, and that a 2 °C increase in average temperatures would increase violent crime rates by more than 3% in non-tropical and non-subtropical areas, if other contributing factors remained constant.

Climate Change and Collective Violence

Climate change is causing increases in temperature, changes in precipitation and extreme weather events, sea-level rise, and other environmental impacts. It is also causing or contributing to heat-related disorders, respiratory and allergic disorders, infectious diseases, malnutrition due to food insecurity, and mental health disorders. In addition, increasing evidence indicates that climate change is causally associated with collective violence, generally in combination with other causal factors. Increased temperatures and extremes of precipitation with their associated consequences, including resultant scarcity of cropland and other key environmental resources, are major pathways by which climate change leads to collective violence. Public health professionals can help prevent collective violence due to climate change (a) by supporting mitigation measures to reduce greenhouse gas emissions, (b) by promoting adaptation measures to address the consequences of climate change and to improve community resilience, and

Civil conflict sensitivity to growing-season drought

To date, the research community has failed to reach a consensus on the nature and significance of the relationship between climate variability and armed conflict. We argue that progress has been hampered by insufficient attention paid to the context in which droughts and other climatic extremes may increase the risk of violent mobilization. Addressing this shortcoming, this study presents an actor-oriented analysis of the drought-conflict relationship, focusing specifically on politically relevant ethnic groups and their sensitivity to growing-season drought under various political and socioeconomic contexts. To this end, we draw on new conflict event data that cover Asia and Africa, 1989-2014, updated spatial ethnic settlement data, and remote sensing data on agricultural land use. Our procedure allows quantifying, for each ethnic group, drought conditions during the growing season of the locally dominant crop. A comprehensive set of multilevel mixed effects models that account for the groups' livelihood, economic, and political vulnerabilities reveals that a drought under most conditions has little effect on the short-term risk that a group challenges the state by military means. However, for agriculturally dependent groups as well as politically excluded groups in very poor countries, a local drought is found to increase the likelihood of sustained violence. We interpret this as evidence of the reciprocal relationship between drought and conflict, whereby each phenomenon makes a group more vulnerable to the other.

A geostatistical analysis of the association between armed conflicts and Plasmodium falciparum malaria in Africa, 1997-2010

BACKGROUND

The absence of conflict in a country has been cited as a crucial factor affecting the operational feasibility of achieving malaria control and elimination, yet mixed evidence exists on the influence that conflicts have had on malaria transmission. Over the past two decades, Africa has seen substantial numbers of armed conflicts of varying length and scale, creating conditions that can disrupt control efforts and impact malaria transmission. However, very few studies have quantitatively assessed the associations between conflicts and malaria transmission, particularly in a consistent way across multiple countries.

METHODS

In this analysis an explicit geostatistical, autoregressive, mixed model is employed to quantitatively assess the association between conflicts and variations in Plasmodium falciparum parasite prevalence across a 13-year period in sub-Saharan Africa.

RESULTS

Analyses of geolocated, malaria prevalence survey variations against armed conflict data in general showed a wide, but short-lived impact of conflict events geographically. The number of countries with decreased P. falciparum parasite prevalence (17) is larger than the number of countries with increased transmission (12), and notably, some of the countries with the highest transmission pre-conflict were still found with lower transmission post-conflict. For four countries, there were no significant changes in parasite prevalence. Finally, distance from conflicts, duration of conflicts, violence of conflict, and number of conflicts were significant components in the model explaining the changes in P. falciparum parasite rate.

CONCLUSIONS

The results suggest that the maintenance of intervention coverage and provision of healthcare in conflict situations to protect vulnerable populations can maintain gains in even the most difficult of circumstances, and that conflict does not represent a substantial barrier to elimination goals.

Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network

Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.