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Background: We quantify the mortality burden and economic loss attributable to nonoptimal temperatures for cold and heat in the Central and South American countries in the Multi-City Multi-Country (MCC) Collaborative Research Network., Methods: We collected data for 66 locations from 13 countries in Central and South America to estimate location-specific temperature-mortality associations using time-series regression with distributed lag nonlinear models. We calculated the attributable deaths for cold and heat as the 2.5th and 97.5th temperature percentiles, above and below the minimum mortality temperature, and used the value of a life year to estimate the economic loss of delayed deaths., Results: The mortality impact of cold varied widely by country, from 9.64% in Uruguay to 0.22% in Costa Rica. The heat-attributable fraction for mortality ranged from 1.41% in Paraguay to 0.01% in Ecuador. Locations in arid and temperate climatic zones showed higher cold-related mortality (5.10% and 5.29%, respectively) than those in tropical climates (1.71%). Arid and temperate climatic zones saw lower heat-attributable fractions (0.69% and 0.58%) than arid climatic zones (0.92%). Exposure to cold led to an annual economic loss of $0.6 million in Costa Rica to $472.2 million in Argentina. In comparison, heat resulted in economic losses of $0.05 million in Ecuador to $90.6 million in Brazil., Conclusion: Most of the mortality burden for Central and South American countries is caused by cold compared to heat, generating annual economic losses of $2.1 billion and $290.7 million, respectively. Public health policies and adaptation measures in the region should account for the health effects associated with nonoptimal temperatures., Competing Interests: A.T. was supported by the JSPS KAKENHI Grant Number 24K13527. The other authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: The minimum mortality temperature (MMT) or MMT percentile (MMTP) is an indicator of population susceptibility to nonoptimum temperatures. MMT and MMTP change over time; however, the changing directions show region-wide heterogeneity. We examined the heterogeneity of temporal changes in MMT and MMTP across multiple communities and in multiple countries., Methods: Daily time-series data for mortality and ambient mean temperature for 699 communities in 34 countries spanning 1986-2015 were analyzed using a two-stage meta-analysis. First, a quasi-Poisson regression was employed to estimate MMT and MMTP for each community during the designated subperiods. Second, we pooled the community-specific temporally varying estimates using mixed-effects meta-regressions to examine temporal changes in MMT and MMTP in the entire study population, as well as by climate zone, geographical region, and country., Results: Temporal increases in MMT and MMTP from 19.5 °C (17.9, 21.1) to 20.3 °C (18.5, 22.0) and from the 74.5 (68.3, 80.6) to 75.0 (71.0, 78.9) percentiles in the entire population were found, respectively. Temporal change was significantly heterogeneous across geographical regions ( P < 0.001). Temporal increases in MMT were observed in East Asia (linear slope [LS] = 0.91, P = 0.02) and South-East Asia (LS = 0.62, P = 0.05), whereas a temporal decrease in MMT was observed in South Europe (LS = -0.46, P = 0.05). MMTP decreased temporally in North Europe (LS = -3.45, P = 0.02) and South Europe (LS = -2.86, P = 0.05)., Conclusions: The temporal change in MMT or MMTP was largely heterogeneous. Population susceptibility in terms of optimum temperature may have changed under a warming climate, albeit with large region-dependent variations., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: Heterogeneity in temperature-mortality relationships across locations may partly result from differences in the demographic structure of populations and their cause-specific vulnerabilities. Here we conduct the largest epidemiological study to date on the association between ambient temperature and mortality by age and cause using data from 532 cities in 33 countries., Methods: We collected daily temperature and mortality data from each country. Mortality data was provided as daily death counts within age groups from all, cardiovascular, respiratory, or noncardiorespiratory causes. We first fit quasi-Poisson regression models to estimate location-specific associations for each age-by-cause group. For each cause, we then pooled location-specific results in a dose-response multivariate meta-regression model that enabled us to estimate overall temperature-mortality curves at any age. The age analysis was limited to adults., Results: We observed high temperature effects on mortality from both cardiovascular and respiratory causes compared to noncardiorespiratory causes, with the highest cold-related risks from cardiovascular causes and the highest heat-related risks from respiratory causes. Risks generally increased with age, a pattern most consistent for cold and for nonrespiratory causes. For every cause group, risks at both temperature extremes were strongest at the oldest age (age 85 years). Excess mortality fractions were highest for cold at the oldest ages., Conclusions: There is a differential pattern of risk associated with heat and cold by cause and age; cardiorespiratory causes show stronger effects than noncardiorespiratory causes, and older adults have higher risks than younger adults., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: Precipitation could affect the transmission of diarrheal diseases. The diverse precipitation patterns across different climates might influence the degree of diarrheal risk from precipitation. This study determined the associations between precipitation and diarrheal mortality in tropical, temperate, and arid climate regions., Methods: Daily counts of diarrheal mortality and 28-day cumulative precipitation from 1997 to 2019 were analyzed across 29 locations in eight middle-income countries (Argentina, Brazil, Costa Rica, India, Peru, the Philippines, South Africa, and Thailand). A two-stage approach was employed: the first stage is conditional Poisson regression models for each location, and the second stage is meta-analysis for pooling location-specific coefficients by climate zone., Results: In tropical climates, higher precipitation increases the risk of diarrheal mortality. Under extremely wet conditions (95th percentile of 28-day cumulative precipitation), diarrheal mortality increased by 17.8% (95% confidence interval [CI] = 10.4%, 25.7%) compared with minimum-risk precipitation. For temperate and arid climates, diarrheal mortality increases in both dry and wet conditions. In extremely dry conditions (fifth percentile of 28-day cumulative precipitation), diarrheal mortality risk increases by 3.8% (95% CI = 1.2%, 6.5%) for temperate and 5.5% (95% CI = 1.0%, 10.2%) for arid climates. Similarly, under extremely wet conditions, diarrheal mortality risk increases by 2.5% (95% CI = -0.1%, 5.1%) for temperate and 4.1% (95% CI = 1.1%, 7.3%) for arid climates., Conclusions: Associations between precipitation and diarrheal mortality exhibit variations across different climate zones. It is crucial to consider climate-specific variations when generating global projections of future precipitation-related diarrheal mortality., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Objectives: This study aims to estimate the short-term preventable mortality and associated economic costs of complying with the World Health Organization (WHO) air quality guidelines (AQGs) limit values for PM 10 and PM 2.5 in nine major Latin American cities., Methods: We estimated city-specific PM-mortality associations using time-series regression models and calculated the attributable mortality fraction. Next, we used the value of statistical life to calculate the economic benefits of complying with the WHO AQGs limit values., Results: In most cities, PM concentrations exceeded the WHO AQGs limit values more than 90% of the days. PM 10 was found to be associated with an average excess mortality of 1.88% with concentrations above WHO AQGs limit values, while for PM 2.5 it was 1.05%. The associated annual economic costs varied widely, between US$ 19.5 million to 3,386.9 million for PM 10 , and US$ 196.3 million to 2,209.6 million for PM 2.5 ., Conclusion: Our findings suggest that there is an urgent need for policymakers to develop interventions to achieve sustainable air quality improvements in Latin America. Complying with the WHO AQGs limit values for PM 10 and PM 2.5 in Latin American cities would substantially benefits for urban populations., Competing Interests: The authors declare that they do not have any conflicts of interest., (Copyright © 2024 Madaniyazi, Alpízar, Cifuentes, Riojas-Rodríguez, Hurtado Díaz, de Sousa Zanotti Stagliorio Coelho, Abrutzky, Osorio, Carrasco Escobar, Valdés Ortega, Colistro, Roye and Tobías.)

Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects., Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality., Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates., Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV 0-7 (0.9 °C). An IQR increase in inter-day TV 0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV 0-7 and inter-day TV 0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type., Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Introduction. Health care strategies based on information and communication technologies (ICTs) may perpetuate health inequity, especially among vulnerable populations. In our setting, there are few validated tools to assess access to ICTs in pediatrics. Objectives. To develop and validate a questionnaire to assess ICT access among caregivers of pediatric patients. To describe the characteristics of ICT access and assess whether there is a correlation among the three levels of the digital divide. Population and methods. We developed and validated a questionnaire and then administered it to the caregivers of children aged 0-12 years. The outcome variables were the questions in the three levels of the digital divide. We also assessed sociodemographic variables. Results. We administered the questionnaire to 344 caregivers. Among them, 93% had their own cell phone and 98.3% had Internet access via a data network; 99.1% communicated via WhatsApp messages; 28% had had a teleconsultation. The correlation among the questions was null or low. Conclusion. The validated questionnaire allowed us to establish that the caregivers of pediatric patients aged 0-12 years mostly own a mobile phone, access the Internet via a data network, communicate mainly through WhatsApp, and obtain few benefits through ICTs. The correlation among the different components of ICT access was low., (Sociedad Argentina de Pediatría.)

Objective: To evaluate changes in RSV seasonality in the last 25 years and their correlation with the mean annual temperature., Methods: Cross-sectional study, based on RSV and temperature data from the City of Buenos Aires (1995-2019). For each year, we describe the beginning, end, and duration of the RSV season and the correlation with the mean annual temperature., Results: We identified 10,183 RSV infections. The duration of the RSV season decreased significantly (1995: 29 weeks vs. 2019: 18 weeks; R: 0.6 (p< 0.001)), due to an earlier ending (1995: week 45 vs. 2019: week 34; 0.6 (p<0.001)). No correlation was observed between mean annual temperature and the duration, start, or end of the RSV season., Conclusion: In the last 25 years, the duration of the RSV season has been significantly shortened due to an earlier ending, without correlation with temperature., (Universidad Nacional de Córdoba)

Introduction: Air pollution would increase the risk of severe infection repiratory in pediatrics. Research Sources: Environmental Protection Agency, National Meteorological. Service and Integral Health History of the Hospital Management System. Population: Patients under 2 years old who consulted for severe infection repiratory in effectors of Buenos Aires City Government and lived commune with continuous environmental monitoring during 2018. Predictors were daily levels of air pollutants (carbon monoxide, nitrous dioxide, particulate matter < 10 μ). Pollutants were measured at three monitoring stations. Temporal variables (media temperature), sex and effector were controlled. Result Variable: Total numbers of visits and total numbers of visits for severe infection respiratory. To select in the data base the visits to analyze an operative definition was made., Objective: Review impact of air pollution visits for severe infection repiratory in effectors of Buenos Aires City Government., Method: Ecologic research, time-series., Results: 80.287 visits were registered, 24.847 for severe infection respiratory (30%). The visits for severe infection respiratory had positive correlation in Cordoba station with N2O (RR: 1,13 [1,00-1,28]). The numbers of visits for severe infection respiratory was higher during cold months than warm months. (19,9% vs 11,9%; RR:1,67 [1,61-1,72])., Conclusion: average values of PM10 and N2O show correlation with the numbers of total visits and visits for severe infection respiratory. The visits increase during winter., (Universidad Nacional de Córdoba)

Background: Collective risk factors such as climate and pollution impact on the risk of acute cardiovascular events, including ST-elevation myocardial infarction (STEMI). There is limited data however on the precise temporal and independent association between these factors and STEMI, and the potentially interacting role of government policies against Coronavirus disease 2019 (COVID-19), especially for Latin America., Methods: We retrospectively collected aggregate data on daily STEMI admissions at 10 tertiary care centers in the Buenos Aires metropolitan area, Argentina, from January 1, 2017 to November 30, 2020. Daily measurements for temperature, humidity, atmospheric pressure, wind direction, wind speed, and rainfall, as well as carbon monoxide (CO), nitrogen dioxide, and particulate matter <10 µm (PM10), were retrieved. Exploratory analyses focused on key COVID-19-related periods (e.g. first case, first lockdown), and Stringency Index quantifying the intensity of government policy response against COVID-19., Results: A total of 1498 STEMI occurred over 1430 days, for an average of 0.12 STEMI per center (decreasing from 0.130 in 2018 to 0.102 in 2020, P=0.016). Time series analysis showed that lower temperature and higher concentration of CO and PM10 were all significantly associated with an increased rate of STEMI (all P<0.05), whereas COVID-19 outbreak, lockdown, and stringency of government policies were all inversely associated with STEMI (all P<0.05). Notably, environmental features impacted as early as 28 days before the event (all P<0.05), even if same or prior day associations proved stronger (all P<0.05). Multivariable analysis suggested that maximum temperature (P=0.001) and PM10 (P=0.033) were the strongest predictor of STEMI, even after accounting for COVID-19-related countermeasures (P=0.043)., Conclusions: Lower temperature and higher concentrations of CO and PM10 are associated with significant increases in the rate of STEMI in a large Latin American metropolitan area. The reduction in STEMI cases seen during the COVID-19 pandemic is at least in part mediated by improvements in pollution, especially reductions in PM10.

Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000-19., Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000-19. Temperature variability was calculated as the SD of the average of the same and previous days' minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades., Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901-2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2-4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7-5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3-10·4), followed by Europe (4·4%, 2·2-5·6) and Africa (3·3, 1·9-4·6)., Interpretation: Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability., Funding: Australian Research Council, Australian National Health & Medical Research Council., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous days' minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: -0.33 to 1.69), 1.34% (95% CI: -0.14 to 2.73), 1.99% (95% CI: 0.29-3.57), and 2.73% (95% CI: 0.76-4.50) of total deaths for Q1-Q4 (first quartile-fourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25-9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: -0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health., Competing Interests: The authors declare no competing interests., (© 2022 The Author(s).)

Background: Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale., Methods: We collected data from 658 communities in 43 countries under different climates. We estimated temperature-mortality associations to derive the MMT for each community using Poisson regression with distributed lag nonlinear models. We investigated the variation in MMT by climatic zone using a mixed-effects meta-analysis and explored the association with climatic and socioeconomic indicators., Results: The geographical distribution of MMTs varied considerably by country between 14.2 and 31.1 °C decreasing by latitude. For climatic zones, the MMTs increased from alpine (13.0 °C) to continental (19.3 °C), temperate (21.7 °C), arid (24.5 °C), and tropical (26.5 °C). The MMT percentiles (MMTPs) corresponding to the MMTs decreased from temperate (79.5th) to continental (75.4th), arid (68.0th), tropical (58.5th), and alpine (41.4th). The MMTs indreased by 0.8 °C for a 1 °C rise in a community's annual mean temperature, and by 1 °C for a 1 °C rise in its SD. While the MMTP decreased by 0.3 centile points for a 1 °C rise in a community's annual mean temperature and by 1.3 for a 1 °C rise in its SD., Conclusions: The geographical distribution of the MMTs and MMTPs is driven mainly by the mean annual temperature, which seems to be a valuable indicator of overall adaptation across populations. Our results suggest that populations have adapted to the average temperature, although there is still more room for adaptation., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report., (Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: Due to ambiguities in terminology, acute lower respiratory infections (ALRI) in childhood are frequently not properly recorded, especially during outpatient visits. A tool that accurately identifies them, would assess the impact on respiratory health of massive harms, and design policies to prevent or mitigate their effects. We aimed to design an algorithm that allows identifying children with ALRI based on data from the electronic clinical record (ECR) of the Government of the City of Buenos Aires (GCBA)., Methods: From the ECR-GCBA database, we randomly selected 1000 outpatient visits of patients aged under 2 years. Terms showing that the visit was due to LARI were searched using an algorithm based on hard rules. Another dataset including 800 visits was used to adjust the algorithm and, finally, its performance was tested in a third dataset of 800 queries corresponding to the entire year 2018., Results: In the validation set, our tool identified LARI with sensitivity 88.24%, specificity 97.5%, PPV 86.07% and NPV 97.93%., Conclusion: Our search algorithm allows us to identify with acceptable precision the outpatient visits related to LARI in children under 2 years of age from electronic clinical records., (Universidad Nacional de Córdoba)

Background: Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM 2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM 2·5 and mortality across various regions of the world., Methods: For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000-16. Daily concentrations of wildfire-related PM 2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25° × 0·25° resolution. The association between wildfire-related PM 2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM 2·5 exposure was calculated., Findings: 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/m 3 increase in the 3-day moving average (lag 0-2 days) of wildfire-related PM 2·5 exposure were 1·019 (95% CI 1·016-1·022) for all-cause mortality, 1·017 (1·012-1·021) for cardiovascular mortality, and 1·019 (1·013-1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48-0·75) of all-cause deaths, 0·55% (0·43-0·67) of cardiovascular deaths, and 0·64% (0·50-0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM 2·5 exposure during the study period., Interpretation: Short-term exposure to wildfire-related PM 2·5 was associated with increased risk of mortality. Urgent action is needed to reduce health risks from the increasing wildfires., Funding: Australian Research Council, Australian National Health & Medical Research Council., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures., Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature-mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature-mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division., Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967-5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58-11·07) of all deaths (8·52% [6·19-10·47] were cold-related and 0·91% [0·56-1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60-87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000-03 to 2016-19, the global cold-related excess death ratio changed by -0·51 percentage points (95% eCI -0·61 to -0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13-0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe., Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios., Funding: Australian Research Council and the Australian National Health and Medical Research Council., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions., Methods: DTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985-2015) and future (2020-99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk., Findings: The time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by -0·4 to 1·6°C), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2-7·4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0·05% additional DTR mortality risk per 1°C increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1·4-10·3% in 2090-99., Interpretation: This study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health., Funding: Korea Ministry of Environment., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Pollution and climate have an impact on pediatric respiratory diseases; few studies have assessed this in the Autonomous City of Buenos Aires., Objective: To assess the impact of the interaction between air pollutants and climate on the Emergency Department visits for acute lower respiratory tract infection (ALRTI) in a children's hospital., Methods: Ecological, time-series study with generalized additive models that included total visits and visits for ALRTI to the Emergency Department between 2012 and 2016. A series with 7-day moving averages for ALRTI visits was founded as a bias control measure. Predictors were daily levels of air pollutants (carbon monoxide, nitrous dioxide, particulate matter < 10 μ) and meteorological variables (temperature, humidity). Pollutants were measured at three monitoring stations. Temporal variables (day of the week, warm/cold semester) were controlled., Results: There were 455 256 total visits; 17 298 accounted for visits for ALRTI. A correlation was established only between total visits and day of the week (Mondays and Saturdays, more visits; Thursdays, less visits). Less visits for ALRTI were recorded in the warm semester compared to the cold semester (relative risk = 0.23; 95 % confidence interval: 0.29-0.18; p < 0.001). One monitoring station did not show any correlation; the other two stations showed a weak correlation between carbon monoxide and particulate matter < 10 μ and visits for ALRTI., Conclusion: The season accurately accounts for the increased number of total visits and visits for ALRTI. Although there was a correlation between the level of certain pollutants and the number of visits, its impact was irrelevant., Competing Interests: The authors report no conflicts of interest in this work., (Sociedad Argentina de Pediatría.)

An increase in the global health burden of temperature was projected for 459 locations in 28 countries worldwide under four representative concentration pathway scenarios until 2099. We determined that the amount of temperature increase for each 100 ppm increase in global CO 2 concentrations is nearly constant, regardless of climate scenarios. The overall average temperature increase during 2010-2099 is largest in Canada (1.16 °C/100 ppm) and Finland (1.14 °C/100 ppm), while it is smallest in Ireland (0.62 °C/100 ppm) and Argentina (0.63 °C/100 ppm). In addition, for each 1 °C temperature increase, the amount of excess mortality is increased largely in tropical countries such as Vietnam (10.34%p/°C) and the Philippines (8.18%p/°C), while it is decreased in Ireland (-0.92%p/°C) and Australia (-0.32%p/°C). To understand the regional variability in temperature increase and mortality, we performed a regression-based modeling. We observed that the projected temperature increase is highly correlated with daily temperature range at the location and vulnerability to temperature increase is affected by health expenditure, and proportions of obese and elderly population., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

This study aimed to analyze mortality during heat waves in the city of Buenos Aires, Argentina, in 2005-2015. We used a time series design with generalized additive models, linking mortality to days of heat waves throughout the period, and to days of the heat wave in 2013, the longest wave since 1906, controlling for time variables, mean temperature, and humidity. Risk of death from natural causes increased by 14% (RR = 1.140; 95%CI: 1.108-1.173) during heat waves when compared to the other days in the hot season. The increase occurred in both sexes and in all age groups, and individuals under 15 years of age were more affected (RR = 1.167; 95%CI: 1.019-1.335) as were those over 84 years (RR = 1.201; 95%CI: 1.098-1.313). The heat wave in December 2013 showed an increase of 43% (RR = 1.428; 95%CI: 1.399-1.457) in total daily deaths, increasing to 51% in individuals over 84 years (RR = 1.515; 95%CI: 1.372-1.674) and 65% (RR = 1.647; 95%CI: 1.367-1.986) for renal causes. We conclude that heat waves pose a significant risk of death, differing according to sex and age in the population of Buenos Aires.

Background: There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature., Objectives: We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset., Methods: In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific associations were summarized using meta-analytic techniques., Results: Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1-3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly., Discussion: The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430.

Objective: to evaluate the impact of air pollution and weather changes on the number of visits to a pediatric emergency department in Buenos Aires, Argentina., Materials and Methods: we designed an ecological time-series study using generalized additive models (GAM) for the period 2012-2014. The outcome variable was the number of daily visits to a pediatric emergency department taking into account daily consultations. The potential predictors were the average daily air pollution levels (carbon monoxide -CO-, nitrogen dioxide -NO2-, particulate matter 10 microns or less in diameter -PM10-) and weather variables (temperature, humidity, wind speed and direction, and rainfall) and we controlled by weekday and long-time trend., Results: the number of visits during the winter months (286 daily) was significantly higher than those in the other seasons (p <0.0001). The change in air pollution levels did not show a significant and consistent correlation with the visits. Temperature, relative humidity, rainfall, and wind speed and direction were not significant variables for any of the examined lags., Conclusions: Considering the population and variables of our study, air pollution does not affect the health outcomes, as does seasonal epidemics. Studies that examine other health variables are necessary to establish the impact of air pollution on children’s health in Buenos Aires.

Introduction: Global climate change circulation pattern respiratory syncytial virus (RSV). We assessed whether RSV season has changed over the past 20 years and its correlation with mean annual temperature., Methods: Cross-sectional study that included records of RSV and temperatures from Buenos Aires (1995-2014). RSV season onset, offset and duration, and its correlation with mean annual temperature were described for each year., Results: A total of 8109 RSV infections were identified. The duration of RSV season reduced significantly (1995: 29 weeks vs. 2014: 17 weeks; R: 0.6; p < 0.001) due to an early ending (1995: week 45 vs. 2014: week 33; R: 0.6; p < 0.001). No correlation was observed between mean annual temperature and RSV season start, end and duration., Conclusions: Over the past 20 years, RSV season shortened significantly, but no correlation with temperature was observed., (Sociedad Argentina de Pediatría.)

Based on the theoretical framework of environmental risk, this article discusses the management of air quality in the Autonomous City of Buenos Aires in relation to current and potential impacts of toxic gases and global climate change on the health of the population. Information on historical and current management of the air was linked to the results of the South American Emissions, Megacities and Climate research project to assess danger, exposure, vulnerability and uncertainty as the dimensions of risk. By contextualizing public policies developed in recent decades on this subject, it was possible to identify emerging configurations of risk and uncertainties as accelerators of social vulnerability. On the one hand, the fact that there is a positive correlation between mortality, changes in temperature and air pollution was confirmed. On the other hand, it became clear that there is a disconnect between air quality management and health care management, while limitations were found in the proposed mitigation measures relating to emissions of greenhouse gases produced by fuel, revealing uncertainties regarding their efficacy.