Explore the vast range of titles available.

Most severe disasters cause large population movements. These movements make it difficult for relief organizations to efficiently reach people in need. Understanding and predicting the locations of affected people during disasters is key to effective humanitarian relief operations and to long-term societal reconstruction. We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, to 341 d after the devastating Haiti earthquake of January 12, 2010. Nineteen days after the earthquake, population movements had caused the population of the capital Port-au-Prince to decrease by an estimated 23%. Both the travel distances and size of people’s movement trajectories grew after the earthquake. These findings, in combination with the disorder that was present after the disaster, suggest that people’s movements would have become less predictable. Instead, the predictability of people’s trajectories remained high and even increased slightly during the three-month period after the earthquake. Moreover, the destinations of people who left the capital during the first three weeks after the earthquake was highly correlated with their mobility patterns during normal times, and specifically with the locations in which people had significant social bonds. For the people who left Port-au-Prince, the duration of their stay outside the city, as well as the time for their return, all followed a skewed, fat-tailed distribution. The findings suggest that population movements during disasters may be significantly more predictable than previously thought.

Recognition of projected increases in exposure to large-scale hazard events over the coming decades has identified a need to develop how disaster risk reduction and recovery are conceptualized and enacted. This paper discusses some strategies for pursing this goal in both disaster recovery and preparedness settings. The approaches discussed include understanding how communities learn from their hazardous experiences and transform these lessons into beliefs, relationships and capabilities that build future adaptive capacity. The paper draws on examples of transformative learning that illustrate how people can make fundamental shifts in how they think about, prepare for and respond to environmental challenge and change. Regarding transformation in pre-event settings, the paper first discusses why the addition of transformative strategies to disaster risk reduction programs is required. These include a need for rethinking socio-environmental relationships, increasing risk acceptance in the context of evolving hazardscapes, and countering beliefs regarding not preparing. The paper then offers strategies for motivating transformation and consolidating the outcomes of transformation in pre-event disaster risk reduction (DRR) strategies. A preliminary model that could inform the development of research questions on the development of transformative outcomes and their consolidation in enduring adaptive processes is presented.

Analyses of the effects of extreme weather disasters on global crop production over the past five decades show that drought and extreme heat reduced national cereal production by 9–10%, whereas no discernible effect at the national level was seen for floods and extreme cold; droughts affect yields and the harvested area, whereas extreme heat mainly affects yields. Effects of extreme weather on crop yields This statistical analyses of the effects of extreme weather disasters on global crop yields — derived from country-level agricultural statistics — shows that drought and extreme heat reduced national cereal yields by about 10% over the past five decades. No discernible effect was seen for floods and extreme cold at the national level; droughts affect yields and the harvested area, whereas extreme heat mainly affects yields. In recent years, several extreme weather disasters have partially or completely damaged regional crop production 1 , 2 , 3 , 4 , 5 . While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964–2007. We show that droughts and extreme heat significantly reduced national cereal production by 9–10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8–11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.

Much of the literature on recovery focuses on the economy, the physical environment and infrastructure at a macro level, which may ignore the personal experiences of affected individuals during recovery. This paper combines internal factors at a micro level and external factors at a macro level to model for understanding perception of recovery (PoR). This study focuses on areas devastated by the 2008 Wenchuan earthquake in China. With respect to three recovery-related aspects (house recovery condition (HRC), family recovery power (FRP) and reconstruction investment (RI)), structural equation modeling (SEM) was applied. It was found that the three aspects (FRP, HRC and RI) effectively explain how earthquake affected households perceive recovery. Internal factors associated with FRP contributed the most to favourable PoR, followed by external factors associated with HRC. Findings identified that for PoR the importance of active recovery within households outweighed an advantageous house recovery condition. At the same time, households trapped in unfavourable external conditions would invest more in housing recovery, which result in wealth accumulation and improved quality of life leading to a high level of PoR. In addition, schooling in households showed a negative effect on improving PoR. This research contributes to current debates around post-disaster permanent housing policy. It is implied that a one-size-fits-all policy in disaster recovery may not be effective and more specific assistance should be provided to those people in need.

Iran's health system has developed a Farsi edition of the Hospital Safety Index (HSI) and has integrated the related assessment program into the health information system. This article presents the results of the 2015 estimation of hospital safety from disasters in I.R.Iran using HSI. We analyzed data from 421 hospitals that had submitted a complete HSI assessment form on the Ministry of Health and Medical Education Portal System. Data collection was based on the self-assessments of the hospital disaster committees. HSI includes 145 items categorized in three components including, structural, non-structural and functional capacity. For each item, safety status was categorized into three levels: not safe (0), average safety (1) and high safety (2). A normalized scoring scheme on a 100-point scale was developed. Hospitals were classified to three safety classes according to their normalized total score: low (≤34.0), average (34.01-66.0) and high (>66.0). The average score of all safety components were 43.0 out of 100 (± 11.0). Eighty-two hospitals (19.4%) were classified as not safe, and 339 hospitals (80.6%) were classified in the average safety category. No hospital was placed in the high safety category. Average safety scores were 41.0, 47.0, and 42.0 for functional capacity, non-structural safety, and structural safety respectively. The average safety score increased between 2012 and 2015, from 34.0 to 43.0. Hospital safety in the event of disasters has improved in Iran in recent years and more hospitals have joined the HSI program. This is a result of continuous efforts invested in capacity building programs and promotion of the 2012 HSI estimation. The HSI should be maintained to monitor the progress of Iran's health system in regards to hospital safety in the case of disasters. It is recommended that WHO continue advocacy of HSI, establish a HSI monitoring system, and add it to country profiles on WHO website.

The objective of this study was to explore the burden of disasters and adverse health outcomes during and following disasters in Bangladesh. We analyzed 6 788 947 respondents' data from a cross-sectional and nationally representative 2021 Bangladesh Disaster-related Statistics (BDRS). The key explanatory variables were the types of disasters respondents faced, while the outcome variables were the disease burden during and following disasters. Descriptive statistics were used to determine disease burden. A multilevel mixed-effects logistic regression model assessed the association between disease burden and disaster types, along with socio-demographic characteristics of respondents. Nearly 50% of respondents experienced diseases during disasters, rising to 53.4% afterward. Fever, cough and diarrhea were prevalent during and after disasters, with increases in skin diseases, malnutrition, and asthma post-disaster. Vulnerable groups, such as children aged 0-4, hijra individuals, those with lower education, people with disabilities, and rural residents, especially in Chattogram, Rangpur, and Sylhet divisions, were most affected. Floods, cyclones, thunderstorms, and hailstorms significantly increased disease likelihood during and after disasters. The study underscores the complex relationship between disasters and health outcomes in Bangladesh, stressing the need for targeted public health interventions, improved health care infrastructure, and evidence-based policies to mitigate disaster-related health risks.

Huge landslides, mobilizing hundreds to thousands of km3 of sediment and rock are ubiquitous in submarine settings ranging from the steepest volcanic island slopes to the gentlest muddy slopes of submarine deltas. Here, we summarize current knowledge of such landslides and the problems of assessing their hazard potential. The major hazards related to submarine landslides include destruction of seabed infrastructure, collapse of coastal areas into the sea and landslide-generated tsunamis. Most submarine slopes are inherently stable. Elevated pore pressures (leading to decreased frictional resistance to sliding) and specific weak layers within stratified sequences appear to be the key factors influencing landslide occurrence. Elevated pore pressures can result from normal depositional processes or from transient processes such as earthquake shaking; historical evidence suggests that the majority of large submarine landslides are triggered by earthquakes. Because of their tsunamigenic potential, ocean-island flank collapses and rockslides in fjords have been identified as the most dangerous of all landslide related hazards. Published models of ocean-island landslides mainly examine 'worst-case scenarios' that have a low probability of occurrence. Areas prone to submarine landsliding are relatively easy to identify, but we are still some way from being able to forecast individual events with precision. Monitoring of critical areas where landslides might be imminent and modelling landslide consequences so that appropriate mitigation strategies can be developed would appear to be areas where advances on current practice are possible.

Three trends will combine to hasten it, warn Yangyang Xu, Veerabhadran Ramanathan and David G. Victor. Global warming will happen faster than we think Three trends will combine to hasten it, warn Yangyang Xu, Veerabhadran Ramanathan and David G. Victor.

Monitoring levels and trends in premature mortality is crucial to understanding how societies can address prominent sources of early death. The Global Burden of Disease 2016 Study (GBD 2016) provides a comprehensive assessment of cause-specific mortality for 264 causes in 195 locations from 1980 to 2016. This assessment includes evaluation of the expected epidemiological transition with changes in development and where local patterns deviate from these trends. We estimated cause-specific deaths and years of life lost (YLLs) by age, sex, geography, and year. YLLs were calculated from the sum of each death multiplied by the standard life expectancy at each age. We used the GBD cause of death database composed of: vital registration (VR) data corrected for under-registration and garbage coding; national and subnational verbal autopsy (VA) studies corrected for garbage coding; and other sources including surveys and surveillance systems for specific causes such as maternal mortality. To facilitate assessment of quality, we reported on the fraction of deaths assigned to GBD Level 1 or Level 2 causes that cannot be underlying causes of death (major garbage codes) by location and year. Based on completeness, garbage coding, cause list detail, and time periods covered, we provided an overall data quality rating for each location with scores ranging from 0 stars (worst) to 5 stars (best). We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to generate estimates for each location, year, age, and sex. We assessed observed and expected levels and trends of cause-specific deaths in relation to the Socio-demographic Index (SDI), a summary indicator derived from measures of average income per capita, educational attainment, and total fertility, with locations grouped into quintiles by SDI. Relative to GBD 2015, we expanded the GBD cause hierarchy by 18 causes of death for GBD 2016. The quality of available data varied by location. Data quality in 25 countries rated in the highest category (5 stars), while 48, 30, 21, and 44 countries were rated at each of the succeeding data quality levels. Vital registration or verbal autopsy data were not available in 27 countries, resulting in the assignment of a zero value for data quality. Deaths from non-communicable diseases (NCDs) represented 72·3% (95% uncertainty interval [UI] 71·2–73·2) of deaths in 2016 with 19·3% (18·5–20·4) of deaths in that year occurring from communicable, maternal, neonatal, and nutritional (CMNN) diseases and a further 8·43% (8·00–8·67) from injuries. Although age-standardised rates of death from NCDs decreased globally between 2006 and 2016, total numbers of these deaths increased; both numbers and age-standardised rates of death from CMNN causes decreased in the decade 2006–16—age-standardised rates of deaths from injuries decreased but total numbers varied little. In 2016, the three leading global causes of death in children under-5 were lower respiratory infections, neonatal preterm birth complications, and neonatal encephalopathy due to birth asphyxia and trauma, combined resulting in 1·80 million deaths (95% UI 1·59 million to 1·89 million). Between 1990 and 2016, a profound shift toward deaths at older ages occurred with a 178% (95% UI 176–181) increase in deaths in ages 90–94 years and a 210% (208–212) increase in deaths older than age 95 years. The ten leading causes by rates of age-standardised YLL significantly decreased from 2006 to 2016 (median annualised rate of change was a decrease of 2·89%); the median annualised rate of change for all other causes was lower (a decrease of 1·59%) during the same interval. Globally, the five leading causes of total YLLs in 2016 were cardiovascular diseases; diarrhoea, lower respiratory infections, and other common infectious diseases; neoplasms; neonatal disorders; and HIV/AIDS and tuberculosis. At a finer level of disaggregation within cause groupings, the ten leading causes of total YLLs in 2016 were ischaemic heart disease, cerebrovascular disease, lower respiratory infections, diarrhoeal diseases, road injuries, malaria, neonatal preterm birth complications, HIV/AIDS, chronic obstructive pulmonary disease, and neonatal encephalopathy due to birth asphyxia and trauma. Ischaemic heart disease was the leading cause of total YLLs in 113 countries for men and 97 countries for women. Comparisons of observed levels of YLLs by countries, relative to the level of YLLs expected on the basis of SDI alone, highlighted distinct regional patterns including the greater than expected level of YLLs from malaria and from HIV/AIDS across sub-Saharan Africa; diabetes mellitus, especially in Oceania; interpersonal violence, notably within Latin America and the Caribbean; and cardiomyopathy and myocarditis, particularly in eastern and central Europe. The level of YLLs from ischaemic heart disease was less than expected in 117 of 195 locations. Other leading causes of YLLs for which YLLs were notably lower than expected included neonatal preterm birth complications in many locations in both south Asia and southeast Asia, and cerebrovascular disease in western Europe. The past 37 years have featured declining rates of communicable, maternal, neonatal, and nutritional diseases across all quintiles of SDI, with faster than expected gains for many locations relative to their SDI. A global shift towards deaths at older ages suggests success in reducing many causes of early death. YLLs have increased globally for causes such as diabetes mellitus or some neoplasms, and in some locations for causes such as drug use disorders, and conflict and terrorism. Increasing levels of YLLs might reflect outcomes from conditions that required high levels of care but for which effective treatments remain elusive, potentially increasing costs to health systems. Bill & Melinda Gates Foundation.

This household survey gave an estimate of 4645 excess deaths after the 2017 hurricane as compared with the same period in 2016. One third of the deaths were attributed to delayed or interrupted health care.