Strengthening the resilience of societies to extreme weather events is an urgent and critical priority around the world. Extreme weather often causes population displacement that compromises human security. Environment-induced displacement is multifaceted because climate extremes, population, and socio-economic conditions, among other factors, converge to influence individuals’ decisions to move. When large-scale, catastrophic floods occur, people tend to move both suddenly and rapidly for survival. Quantifying the patterns and mechanisms of such displacement at global scale is essential to support areas at high risk for climate-induced displacement. Here we present the global distribution of vulnerability to floods by mapping potential flood exposure and observed flood-induced displacement. We found that countries in Africa might be highly vulnerable to floods because they have high flood-induced displacement even at low- to mid-level flood exposure. Our results show that income levels (Gross National Income) substantial impact flood-induced displacement. Moreover, the relationship between income levels and displacement is nonlinear, and this nonlinearity indicates large gaps in flood-induced displacement between high- and low-income countries. We suggest that low-income countries, particularly in Africa, face a high likelihood of flood-induced displacement and need to develop adaptation measures to mitigate the potential for displacement and the associated risks.

As of mid-August 2020, Brazil was the country with the second-highest number of cases and deaths by the COVID-19 pandemic, but with large regional and social differences. In this study, using data from the Brazilian Ministry of Health, we analyze the spatial patterns of infection and mortality from Covid-19 across small areas of Brazil. We apply spatial autoregressive Bayesian models and estimate the risks of infection and mortality, taking into account age, sex composition of the population and other variables that describe the health situation of the spatial units. We also perform a decomposition analysis to study how age composition impacts the differences in mortality and infection rates across regions. Our results indicate that death and infections are spatially distributed, forming clusters and hotspots, especially in the Northern Amazon, Northeast coast and Southeast of the country. The high mortality risk in the Southeast part of the country, where the major cities are located, can be explained by the high proportion of the elderly in the population. In the less developed areas of the North and Northeast, there are high rates of infection among young adults, people of lower socioeconomic status, and people without access to health care, resulting in more deaths.

Background: Cardiovascular disease (CVD) is one of the most serious health issues and the leading cause of death worldwide in both developed and developing countries. The risk factors for CVD include demographic, socioeconomic, behavioral, environmental, and physiological factors. However, the spatial distribution of these risk factors, as well as CVD mortality, are not uniformly distributed across countries. Therefore, the goal of this study is to compare and evaluate some models commonly used in mortality and health studies to investigate whether the CVD mortality rates in the adult population (over 30 years of age) of a country are associated with the characteristics of surrounding countries from 2013 to 2017. Methods: We present the spatial distribution of the age-standardized crude mortality rate from cardiovascular disease, as well as conduct an exploratory data analysis (EDA) to obtain a basic understanding of the behavior of the variables of interest. Then, we apply the ordinary least squares (OLS) to the country level dataset. As OLS does not take into account the spatial dependence of the data, we apply two spatial modelling techniques, that is, spatial lag and spatial error models. Results: Our empirical findings show that the relationship between CVD and income, as well as other socioeconomic variables, are important. In addition, we highlight the importance of understanding how changes in individual behavior across different countries might affect future trends in CVD mortality, especially related to smoking and dietary behaviors. Conclusions: We argue that this study provides useful clues for policymakers establishing effective public health planning and measures for the prevention of deaths from cardiovascular disease. The reduction of CVD mortality can positively impact GDP growth because increasing life expectancy enables people to contribute to the economy of the country and its regions for longer.

Background: Chronic Respiratory Diseases (CRDs) in Asian countries are a growing concern in terms of morbidity and mortality. However, a systematic understanding of the increasing age-adjusted mortality rate of chronic respiratory disease (CRD) and its associated factors is not readily available for many Asian countries. We aimed to determine country-level factors affecting CRD mortality using a panel error correction model. Methods: Based on data from the Global Burden of Disease Study 2017, we estimated the trends and distribution of CRD mortality for selected Asian countries from 2010 to 2017. Furthermore, we evaluated the relationship between CRD mortality and Gross Domestic Product (GDP) per capita, average years of schooling, urbanization, and pollutant emission (PM2.5 concentration) using a fixed-effect model. We corrected the estimates for heteroscedasticity and autocorrelation through Prais-Winsten adjustment along with robust standard error. Results: Between 2010 and 2017, approximately 21.4 million people died from chronic respiratory diseases in the countries studied. Age-standardized crude mortality rate from CRDs in the period had minimum and maximum values of 8.19 (Singapore in 2016) and 155.42 (North Korea in 2010) per 100,000 population, respectively. The coefficients corrected for autocorrelation and heteroskedasticity based on the final model of our study (Prais-Winsten), showed that all explanatory variables were statistically significant (p < 0.001). The model shows that the 1% increase in GDP per capita results in a 20% increase (0.203) in the CRD mortality rate and that a higher concentration of air pollution is also positively associated with the CRD deaths (0.00869). However, an extra year of schooling reduces the mortality rate by 4.79% (− 0.0479). Further, rate of urbanization is negatively associated with the CRD death rate (− 0.0252). Conclusions: Our results indicate that both socioeconomic and environmental factors impact CRD mortality rates. Mortality due to CRD increases with rising GDP per capita and decreases with the percentage of the total population residing in urban areas. Further, mortality increases with greater exposure to PM2.5. Also, higher years of schooling mitigate rising CRD mortality rates, showing that education can act as a safety net against CRD mortality. These results are an outcome of sequential adjustments in the final model specification to correct for heteroscedasticity and autocorrelation.

Objectives The study explores the awareness and e-cigarette use by demographic and socio-economic characteristics of selected 14 Global Adult Tobacco Survey (GATS) countries. Design Cross-sectional. Setting 14 countries. Participants Surveyed population ≥15 years selected through multi-stage cluster sampling. Primary and secondary outcome measures We selected 14 countries from 6 different WHO regions where GATS was conducted in different years during 2011–2017. Results Awareness and usage of e-cigarette were highest in Greece and lowest in India. Females were less aware of e-cigarette across ages. The gender gap in awareness is wide in Greece post 50 years of age, while the gap is distinct in early ages in Kazakhstan and Qatar. The gender difference in use of e-cigarette was negligible in most of the countries except among the younger cohorts of Russia, Philippines Malaysia and Indonesia. Relatively higher prevalence of e-cigarette smoking among females in the older adult age was observed in some of the Asian countries like India. Multivariate analysis indicates that those who were younger, male, residing in urban areas, current tobacco smokers were more likely to use e-cigarette than their counterparts. Though prevalence of e-cigarette use increased with wealth and education, such pattern is not strong and consistent. Promotional advertisement plays important role in higher use of e-cigaratte. The predicted national prevalence of e-ciragette use was highest in Malaysia . Conclusions E-cigarette use is more among urban adults, current smokers, males and in countries with promotional advertisement of e-cigarette. Area specific interventions are needed to understand the nature of e-cigarette use. Russia, Ukraine, Costa Rica and Mexico need better understanding to explore whether e-cigaratte use is an indulgence to new mode of addiction, as youth being highly likely to adopt this practice.