RESUMO
BACKGROUND: The association between nonoptimal temperatures and cardiovascular mortality risk is recognized. However, a comprehensive global assessment of this burden is lacking. OBJECTIVES: The goal of this study was to assess global cardiovascular mortality burden attributable to nonoptimal temperatures and investigate spatiotemporal trends. METHODS: Using daily cardiovascular deaths and temperature data from 32 countries, a 3-stage analytical approach was applied. First, location-specific temperature-mortality associations were estimated, considering nonlinearity and delayed effects. Second, a multivariate meta-regression model was developed between location-specific effect estimates and 5 meta-predictors. Third, cardiovascular deaths associated with nonoptimal, cold, and hot temperatures for each global grid (55 km × 55 km resolution) were estimated, and temporal trends from 2000 to 2019 were explored. RESULTS: Globally, 1,801,513 (95% empirical CI: 1,526,632-2,202,831) annual cardiovascular deaths were associated with nonoptimal temperatures, constituting 8.86% (95% empirical CI: 7.51%-12.32%) of total cardiovascular mortality corresponding to 26 deaths per 100,000 population. Cold-related deaths accounted for 8.20% (95% empirical CI: 6.74%-11.57%), whereas heat-related deaths accounted for 0.66% (95% empirical CI: 0.49%-0.98%). The mortality burden varied significantly across regions, with the highest excess mortality rates observed in Central Asia and Eastern Europe. From 2000 to 2019, cold-related excess death ratios decreased, while heat-related ratios increased, resulting in an overall decline in temperature-related deaths. Southeastern Asia, Sub-Saharan Africa, and Oceania observed the greatest reduction, while Southern Asia experienced an increase. The Americas and several regions in Asia and Europe displayed fluctuating temporal patterns. CONCLUSIONS: Nonoptimal temperatures substantially contribute to cardiovascular mortality, with heterogeneous spatiotemporal patterns. Effective mitigation and adaptation strategies are crucial, especially given the increasing heat-related cardiovascular deaths amid climate change.
Assuntos
Doenças Cardiovasculares , Saúde Global , Humanos , Doenças Cardiovasculares/mortalidade , Temperatura Baixa/efeitos adversosRESUMO
BACKGROUND: More intense tropical cyclones (TCs) are expected in the future under a warming climate scenario, but little is known about their mortality effect pattern across countries and over decades. We aim to evaluate the TC-specific mortality risks, periods of concern (POC) and characterize the spatiotemporal pattern and exposure-response (ER) relationships on a multicountry scale. METHODS AND FINDINGS: Daily all-cause, cardiovascular, and respiratory mortality among the general population were collected from 494 locations in 18 countries or territories during 1980 to 2019. Daily TC exposures were defined when the maximum sustained windspeed associated with a TC was ≥34 knots using a parametric wind field model at a 0.5° × 0.5° resolution. We first estimated the TC-specific mortality risks and POC using an advanced flexible statistical framework of mixed Poisson model, accounting for the population changes, natural variation, seasonal and day of the week effects. Then, a mixed meta-regression model was used to pool the TC-specific mortality risks to estimate the overall and country-specific ER relationships of TC characteristics (windspeed, rainfall, and year) with mortality. Overall, 47.7 million all-cause, 15.5 million cardiovascular, and 4.9 million respiratory deaths and 382 TCs were included in our analyses. An overall average POC of around 20 days was observed for TC-related all-cause and cardiopulmonary mortality, with relatively longer POC for the United States of America, Brazil, and Taiwan (>30 days). The TC-specific relative risks (RR) varied substantially, ranging from 1.04 to 1.42, 1.07 to 1.77, and 1.12 to 1.92 among the top 100 TCs with highest RRs for all-cause, cardiovascular, and respiratory mortality, respectively. At country level, relatively higher TC-related mortality risks were observed in Guatemala, Brazil, and New Zealand for all-cause, cardiovascular, and respiratory mortality, respectively. We found an overall monotonically increasing and approximately linear ER curve of TC-related maximum sustained windspeed and cumulative rainfall with mortality, with heterogeneous patterns across countries and regions. The TC-related mortality risks were generally decreasing from 1980 to 2019, especially for the Philippines, Taiwan, and the USA, whereas potentially increasing trends in TC-related all-cause and cardiovascular mortality risks were observed for Japan. CONCLUSIONS: The TC mortality risks and POC varied greatly across TC events, locations, and countries. To minimize the TC-related health burdens, targeted strategies are particularly needed for different countries and regions, integrating epidemiological evidence on region-specific POC and ER curves that consider across-TC variability.
Assuntos
Tempestades Ciclônicas , Doenças Respiratórias , Humanos , Estados Unidos , Clima , Brasil , JapãoRESUMO
BACKGROUND: Global climate change is likely to increase the geographic range and seasonality of malaria transmission. Areas suitable for distribution of malaria vectors are predicted to increase with climate change but evidence is limited on future distribution of malaria with climate in China. OBJECTIVE: Our aim was to assess a potential effect of climate change on Plasmodium vivax (P. vivax) and Plasmodium falciparum (P. falciparum) malaria under climate change scenarios. METHODS: National malaria surveillance data during 2005-2014 were integrated with corresponding climate data to model current weather-malaria relationship. We used the Generalized Additive Model (GAM) with a spatial component, assuming a quasi-Poisson distribution and including an offset for the population while accounting for potential non-linearity and long-term trend. The association was applied to future climate to project county-level malaria distribution using ensembles of Global Climate Models under two climate scenarios - Representative Concentration Pathways (RCP4.5 and RCP8.5). RESULTS: Climate change could substantially increase P. vivax and P. falciparum malaria, under both climate scenarios, but by larger amount under RCP8.5, compared to the baseline. P. falciparum is projected to increase more than P. vivax. The distributions of P. vivax and P. falciparum malaria are expected to increase in most regions regardless of the climate scenarios. A high percentage (>50%) increases are projected in some counties of the northwest, north, northeast, including northern tip of the northeast China, with a clearer spatial change for P. vivax than P. falciparum under both scenarios, highlighting potential changes in the latitudinal extent of the malaria. CONCLUSION: Our findings suggest that spatial and temporal distribution of P. vivax and P. falciparum malaria in China will change due to future climate change, if there is no policy to mitigate it. These findings are important to guide the malaria elimination goal for China.
Assuntos
Mudança Climática , Exposição Ambiental/estatística & dados numéricos , Malária Falciparum/epidemiologia , Malária Vivax/epidemiologia , China/epidemiologia , Humanos , Plasmodium vivaxRESUMO
BACKGROUND: The presence of landmines and explosive remnants of war (ERW) including unexploded ordnance (UXO) poses a serious public health risk for populations living in conflict-affected and contaminated areas. Current analysis, however, provides only a partial view of the burden. In this study, we examined the multivariable relationship between year of injury, activity at the time of the incident, case fatalities and casualty rates in order to provide decision-makers with a more fine-grained understanding of landmines and ERW injuries in the Lao PDR. METHODS: Using data from a retrospective, national household survey, frequency tables, logistic and Poisson regressions were performed using STATA 13 to predict the case fatality and population-standardized incidence rates for ERW casualties. RESULTS: The findings indicated that most casualties were male (86.75%), with the majority of incidents (74.7%) occurring during the conflict period (1964-1979). The odds of death for the conflict period was 1.5 times that of the post-conflict period (1980-2008). The highest odds of death during the conflict period was associated with big bombs (OR = 1.38, 95% CI: 1.243-1.522, p < 0.01), and landmine injuries were more common during conflict compared to the post-conflict period (IRR = 1.42, 95% CI: 1.368-1.477, p < 0.01). Post conflict, cluster munitions had the highest incidence rate for death or injury (IRR = 1.07, 95%CI: 1.006-1.143, p = 0.03). Scrap collection which is often the target of mine risk education and thought to be one of the main activities at time of injury had the second lowest incidence rate of the activities related to incident during post-conflict period. CONCLUSIONS: As the first study of this nature in Lao PDR, this research provides information essential for planning services and prevention. This study suggests more effort needs to be directed towards addressing the geographical regions and population subgroups experiencing increased casualty numbers and odds of death. Further research is required to improve the documentation and understanding of the health and socio-economic consequences of landmine and ERW injuries.
RESUMO
INTRODUCTION: The proportion of imported malaria cases in China has increased over recent years, and has presented challenges for the malaria elimination program in China. However, little is known about the geographic distribution and environmental suitability for malaria transmission under projected climate change scenarios. METHODS: Using the MaxEnt model based on malaria presence-only records, we produced environmental suitability maps and examined the relative contribution of topographic, demographic, and environmental risk factors for P. vivax and P. falciparum malaria in China. RESULTS: The MaxEnt model estimated that environmental suitability areas (ESAs) for malaria cover the central, south, southwest, east and northern regions, with a slightly wider range of ESAs extending to the northeast region for P. falciparum. There was spatial agreement between the location of imported cases and area environmentally suitable for malaria transmission. The ESAs of P. vivax and P. falciparum are projected to increase in some parts of southwest, south, central, north and northeast regions in the 2030s, 2050s, and 2080s, by a greater amount for P. falciparum under the RCP8.5 scenario. Temperature and NDVI values were the most influential in defining the ESAs for P. vivax, and temperature and precipitation the most influential for P. falciparum malaria. CONCLUSION: This study estimated that the ESA for malaria transmission in China will increase with climate change and highlights the potential establishment of further local transmission. This model should be used to support malaria control by targeting areas where interventions on malaria transmission need to be enhanced.
Assuntos
Mudança Climática , Malária Falciparum , Malária Vivax , Malária , China , Humanos , Malária/transmissão , Malária Falciparum/transmissão , Malária Vivax/transmissãoRESUMO
Background: Meteorological factors play a crucial role in malaria transmission, but limited evidence is available from China. This study aimed to estimate the weekly associations between meteorological factors and Plasmodium vivax and Plasmodium falciparum malaria in China. Methods: The Distributed Lag Non-Linear Model was used to examine non-linearity and delayed effects of average temperature, rainfall, relative humidity, sunshine hours, wind speed and atmospheric pressure on malaria. Results: Average temperature was associated with P. vivax and P. falciparum cases over long ranges of lags. The effect was more immediate on P. vivax (0-6 weeks) than on P. falciparum (1-9 weeks). Relative humidity was associated with P. vivax and P. falciparum over 8-10 weeks and 5-8 weeks lag, respectively. A significant effect of wind speed on P. vivax was observed at 0-2 weeks lag, but no association was found with P. falciparum. Rainfall had a decreasing effect on P. vivax, but no association was found with P. falciparum. Sunshine hours were negatively associated with P. falciparum, but the association was unclear for P. vixax. However, the effects of atmospheric pressure on both malaria types were not significant at any lag. Conclusions: Our study highlights a substantial effect of weekly climatic factors on P. vivax and P. falciparum malaria transmission in China, with different lags. This provides an evidence base for health authorities in developing a malaria early-warning system.
Assuntos
Pressão Atmosférica , Malária Falciparum/parasitologia , Malária Vivax/parasitologia , Plasmodium falciparum/crescimento & desenvolvimento , Plasmodium vivax/crescimento & desenvolvimento , Tempo (Meteorologia) , China , Clima , Feminino , Humanos , Umidade , Incidência , Conceitos Meteorológicos , Chuva , Luz Solar , Temperatura , VentoRESUMO
BACKGROUND: Despite the declining burden of malaria in China, the disease remains a significant public health problem with periodic outbreaks and spatial variation across the country. A better understanding of the spatial and temporal characteristics of malaria is essential for consolidating the disease control and elimination programme. This study aims to understand the spatial and spatiotemporal distribution of Plasmodium vivax and Plasmodium falciparum malaria in China during 2005-2009. METHODS: Global Moran's I statistics was used to detect a spatial distribution of local P. falciparum and P. vivax malaria at the county level. Spatial and space-time scan statistics were applied to detect spatial and spatiotemporal clusters, respectively. RESULTS: Both P. vivax and P. falciparum malaria showed spatial autocorrelation. The most likely spatial cluster of P. vivax was detected in northern Anhui province between 2005 and 2009, and western Yunnan province between 2010 and 2014. For P. falciparum, the clusters included several counties of western Yunnan province from 2005 to 2011, Guangxi from 2012 to 2013, and Anhui in 2014. The most likely space-time clusters of P. vivax malaria and P. falciparum malaria were detected in northern Anhui province and western Yunnan province, respectively, during 2005-2009. CONCLUSION: The spatial and space-time cluster analysis identified high-risk areas and periods for both P. vivax and P. falciparum malaria. Both malaria types showed significant spatial and spatiotemporal variations. Contrary to P. vivax, the high-risk areas for P. falciparum malaria shifted from the west to the east of China. Further studies are required to examine the spatial changes in risk of malaria transmission and identify the underlying causes of elevated risk in the high-risk areas.