Explore the vast range of titles available.

Most of the epidemiological studies that have examined the detrimental effects of ambient hot and cold temperatures on human health have been conducted in high-income countries. In India, the limited evidence on temperature and health risks has focused mostly on the effects of heat waves and has mostly been from small scale studies. Here, we quantify heat and cold effects on mortality in India using a nationally representative study of the causes of death and daily temperature data for 2001-2013. We applied distributed-lag nonlinear models with case-crossover models to assess the effects of heat and cold on all medical causes of death for all ages from birth (n = 411,613) as well as on stroke (n = 19,753), ischaemic heart disease (IHD) (n = 40,003), and respiratory diseases (n = 23,595) among adults aged 30-69. We calculated the attributable risk fractions by mortality cause for extremely cold (0.4 to 13.8°C), moderately cold (13.8°C to cause-specific minimum mortality temperatures), moderately hot (cause-specific minimum mortality temperatures to 34.2°C), and extremely hot temperatures (34.2 to 39.7°C). We further calculated the temperature-attributable deaths using the United Nations' death estimates for India in 2015. Mortality from all medical causes, stroke, and respiratory diseases showed excess risks at moderately cold temperature and hot temperature. For all examined causes, moderately cold temperature was estimated to have higher attributable risks (6.3% [95% empirical confidence interval (eCI) 1.1 to 11.1] for all medical deaths, 27.2% [11.4 to 40.2] for stroke, 9.7% [3.7 to 15.3] for IHD, and 6.5% [3.5 to 9.2] for respiratory diseases) than extremely cold, moderately hot, and extremely hot temperatures. In 2015, 197,000 (121,000 to 259,000) deaths from stroke, IHD, and respiratory diseases at ages 30-69 years were attributable to moderately cold temperature, which was 12- and 42-fold higher than totals from extremely cold and extremely hot temperature, respectively. The main limitation of this study was the coarse spatial resolution of the temperature data, which may mask microclimate effects. Public health interventions to mitigate temperature effects need to focus not only on extremely hot temperatures but also moderately cold temperatures. Future absolute totals of temperature-related deaths are likely to depend on the large absolute numbers of people exposed to both extremely hot and moderately cold temperatures. Similar large-scale and nationally representative studies are required in other low- and middle-income countries to better understand the impact of future temperature changes on cause-specific mortality.

India has long been thought to have more snakebites than any other country. However, inadequate hospital-based reporting has resulted in estimates of total annual snakebite mortality ranging widely from about 1,300 to 50,000. We calculated direct estimates of snakebite mortality from a national mortality survey. We conducted a nationally representative study of 123,000 deaths from 6,671 randomly selected areas in 2001-03. Full-time, non-medical field workers interviewed living respondents about all deaths. The underlying causes were independently coded by two of 130 trained physicians. Discrepancies were resolved by anonymous reconciliation or, failing that, by adjudication. A total of 562 deaths (0.47% of total deaths) were assigned to snakebites. Snakebite deaths occurred mostly in rural areas (97%), were more common in males (59%) than females (41%), and peaked at ages 15-29 years (25%) and during the monsoon months of June to September. This proportion represents about 45,900 annual snakebite deaths nationally (99% CI 40,900 to 50,900) or an annual age-standardised rate of 4.1/100,000 (99% CI 3.6-4.5), with higher rates in rural areas (5.4/100,000; 99% CI 4.8-6.0), and with the highest state rate in Andhra Pradesh (6.2). Annual snakebite deaths were greatest in the states of Uttar Pradesh (8,700), Andhra Pradesh (5,200), and Bihar (4,500). Snakebite remains an underestimated cause of accidental death in modern India. Because a large proportion of global totals of snakebites arise from India, global snakebite totals might also be underestimated. Community education, appropriate training of medical staff and better distribution of antivenom, especially to the 13 states with the highest prevalence, could reduce snakebite deaths in India.

National malaria death rates are difficult to assess because reliably diagnosed malaria is likely to be cured, and deaths in the community from undiagnosed malaria could be misattributed in retrospective enquiries to other febrile causes of death, or vice-versa. We aimed to estimate plausible ranges of malaria mortality in India, the most populous country where the disease remains common. Full-time non-medical field workers interviewed families or other respondents about each of 122 000 deaths during 2001–03 in 6671 randomly selected areas of India, obtaining a half-page narrative plus answers to specific questions about the severity and course of any fevers. Each field report was sent to two of 130 trained physicians, who independently coded underlying causes, with discrepancies resolved either via anonymous reconciliation or adjudication. Of all coded deaths at ages 1 month to 70 years, 2681 (3·6%) of 75 342 were attributed to malaria. Of these, 2419 (90%) were in rural areas and 2311 (86%) were not in any health-care facility. Death rates attributed to malaria correlated geographically with local malaria transmission ratesderived independently from the Indian malaria control programme. The adjudicated results show 205 000 malaria deaths per year in India before age 70 years (55 000 in early childhood, 30 000 at ages 5–14 years, 120 000 at ages 15–69 years); 1·8% cumulative probability of death from malaria before age 70 years. Plausible lower and upper bounds (on the basis of only the initial coding) were 125 000–277 000. Malaria accounted for a substantial minority of about 1·3 million unattended rural fever deaths attributed to infectious diseases in people younger than 70 years. Despite uncertainty as to which unattended febrile deaths are from malaria, even the lower bound greatly exceeds the WHO estimate of only 15 000 malaria deaths per year in India (5000 early childhood, 10 000 thereafter). This low estimate should be reconsidered, as should the low WHO estimate of adult malaria deaths worldwide. US National Institutes of Health, Canadian Institute of Health Research, Li Ka Shing Knowledge Institute.

In the absence of forest ecosystem time series data, monitoring proxies such as the enhanced vegetation index (EVI) can inform the capacity of forests to provide ecosystem services. We used MODIS-derived EVI at 250 m and 16-day resolution and Breaks for Additive and Seasonal Trend (BFAST) algorithms to monitor forest EVI changes (breaks and trends) in and around the Algonquin Provincial Park (Ontario, Canada) from 2003 to 2022. We found that relatively little change occurred in forest EVI pixels and that most of the change occurred in non-protected forest areas. Only 5.3% (12,348) of forest pixels experienced one or more EVI breaks and 27.8% showed detectable EVI trends. Most breaks were negative (11,969, 75.3%; positive breaks: 3935, 24.7%) with a median magnitude of change of −755.5 (median positive magnitude: 722.6). A peak of negative breaks (2487, 21%) occurred in the year 2013 while no clear peak was seen among positive breaks. Most breaks (negative and positive) and trends occurred in the eastern region of the study area. Boosted regression trees revealed that the most important predictors of the magnitude of change were forest age, summer droughts, and warm winters. These were among the most important variables that explained the magnitude of negative (R2 = 0.639) and positive breaks (R2 = 0.352). Forest composition and protection status were only marginally important. Future work should focus on assessing spatial clusters of EVI breaks and trends to understand local drivers of forest vegetation health and their potential relation to forest ecosystem services.

Studies on the extent to which long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5) contributes to adult mortality in India are few, despite over 99% of Indians being exposed to levels that the World Health Organization (WHO) considers unsafe.BACKGROUNDStudies on the extent to which long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5) contributes to adult mortality in India are few, despite over 99% of Indians being exposed to levels that the World Health Organization (WHO) considers unsafe.We conducted a retrospective cohort study within the Million Death Study (MDS) to provide the first-ever quantification of national mortality from exposure to PM2.5 in India from 1999 to 2014.OBJECTIVEWe conducted a retrospective cohort study within the Million Death Study (MDS) to provide the first-ever quantification of national mortality from exposure to PM2.5 in India from 1999 to 2014.We calculated relative risks (RRs) by linking a total of ten 3-y intervals of satellite-based estimated PM2.5 exposure to deaths 3 to 5 y later in over 7,400 small villages or urban blocks covering a total population of 6.8 million. We applied using a model-based geostatistical model, adjusted for individual age, sex, and year of death; smoking prevalence, rural/urban residency, area-level female illiteracy, languages, and spatial clustering and unit-level variation.METHODSWe calculated relative risks (RRs) by linking a total of ten 3-y intervals of satellite-based estimated PM2.5 exposure to deaths 3 to 5 y later in over 7,400 small villages or urban blocks covering a total population of 6.8 million. We applied using a model-based geostatistical model, adjusted for individual age, sex, and year of death; smoking prevalence, rural/urban residency, area-level female illiteracy, languages, and spatial clustering and unit-level variation.PM2.5 exposure levels increased from 1999 to 2014, particularly in central and eastern India. Among 212,573 deaths at ages 15-69 y, after spatial adjustment, we found a significant RR of 1.09 [95% credible interval (CI): 1.04, 1.14] for stroke deaths per 10-μg/m3 increase in PM2.5 exposure, but no significant excess for deaths from chronic respiratory disease and ischemic heart disease (IHD), all nonaccidental causes, and total mortality (after excluding stroke). Spatial adjustment attenuated the RRs for chronic respiratory disease and IHD but raised those for stroke. The RRs were consistent in various sensitivity analyses with spatial adjustment, including stratifying by levels of solid fuel exposure, by sex, and by age group, addition of climatic variables, and in supplementary case-control analyses using injury deaths as controls.RESULTSPM2.5 exposure levels increased from 1999 to 2014, particularly in central and eastern India. Among 212,573 deaths at ages 15-69 y, after spatial adjustment, we found a significant RR of 1.09 [95% credible interval (CI): 1.04, 1.14] for stroke deaths per 10-μg/m3 increase in PM2.5 exposure, but no significant excess for deaths from chronic respiratory disease and ischemic heart disease (IHD), all nonaccidental causes, and total mortality (after excluding stroke). Spatial adjustment attenuated the RRs for chronic respiratory disease and IHD but raised those for stroke. The RRs were consistent in various sensitivity analyses with spatial adjustment, including stratifying by levels of solid fuel exposure, by sex, and by age group, addition of climatic variables, and in supplementary case-control analyses using injury deaths as controls.Direct epidemiological measurements, despite inherent limitations, yielded associations between mortality and long-term PM2.5 inconsistent with those reported in earlier models used by the WHO to derive estimates of PM2.5 mortality in India. The modest RRs in our study are consistent with near or null mortality effects. They suggest suitable caution in estimating deaths from PM2.5 exposure based on MDS results and even more caution in extrapolating model-based associations of risk derived mostly from high-income countries to India. https://doi.org/10.1289/EHP9538.DISCUSSIONDirect epidemiological measurements, despite inherent limitations, yielded associations between mortality and long-term PM2.5 inconsistent with those reported in earlier models used by the WHO to derive estimates of PM2.5 mortality in India. The modest RRs in our study are consistent with near or null mortality effects. They suggest suitable caution in estimating deaths from PM2.5 exposure based on MDS results and even more caution in extrapolating model-based associations of risk derived mostly from high-income countries to India. https://doi.org/10.1289/EHP9538.

Documentation of the demographic and geographical details of changes in cause-specific neonatal (younger than 1 month) and 1–59-month mortality in India can guide further progress in reduction of child mortality. In this study we report the changes in cause-specific child mortality between 2000 and 2015 in India. Since 2001, the Registrar General of India has implemented the Million Death Study (MDS) in 1·3 million homes in more than 7000 randomly selected areas of India. About 900 non-medical surveyors do structured verbal autopsies for deaths recorded in these homes. Each field report is assigned randomly to two of 404 trained physicians to classify the cause of death, with a standard process for resolution of disagreements. We combined the proportions of child deaths according to the MDS for 2001–13 with annual UN estimates of national births and deaths (partitioned across India's states and rural or urban areas) for 2000–15. We calculated the annual percentage change in sex-specific and cause-specific mortality between 2000 and 2015 for neonates and 1–59-month-old children. The MDS captured 52 252 deaths in neonates and 42 057 deaths at 1–59 months. Examining specific causes, the neonatal mortality rate from infection fell by 66% from 11·9 per 1000 livebirths in 2000 to 4·0 per 1000 livebirths in 2015 and the rate from birth asphyxia or trauma fell by 76% from 9·0 per 1000 livebirths in 2000 to 2·2 per 1000 livebirths in 2015. At 1–59 months, the mortality rate from pneumonia fell by 63% from 11·2 per 1000 livebirths in 2000 to 4·2 per 1000 livebirths in 2015 and the rate from diarrhoea fell by 66% from 9·4 per 1000 livebirths in 2000 to 3·2 per 1000 livebirths in 2015 (with narrowing girl–boy gaps). The neonatal tetanus mortality rate fell from 1·6 per 1000 livebirths in 2000 to less than 0·1 per 1000 livebirths in 2015 and the 1–59-month measles mortality rate fell from 3·3 per 1000 livebirths in 2000 to 0·3 per 1000 livebirths in 2015. By contrast, mortality rates for prematurity or low birthweight rose from 12·3 per 1000 livebirths in 2000 to 14·3 per 1000 livebirths in 2015, driven mostly by increases in term births with low birthweight in poorer states and rural areas. 29 million cumulative child deaths occurred from 2000 to 2015. The average annual decline in mortality rates from 2000 to 2015 was 3·3% for neonates and 5·4% for children aged 1–59 months. Annual declines from 2005 to 2015 (3·4% decline for neonatal mortality and 5·9% decline in 1–59-month mortality) were faster than were annual declines from 2000 to 2005 (3·2% decline for neonatal mortality and 4·5% decline in 1–59-month mortality). These faster declines indicate that India avoided about 1 million child deaths compared with continuation of the 2000–05 declines. To meet the 2030 Sustainable Development Goals for child mortality, India will need to maintain the current trajectory of 1–59-month mortality and accelerate declines in neonatal mortality (to >5% annually) from 2015 onwards. Continued progress in reduction of child mortality due to pneumonia, diarrhoea, malaria, and measles at 1–59 months is feasible. Additional attention to low birthweight is required. National Institutes of Health, Disease Control Priorities Network, Maternal and Child Epidemiology Estimation Group, and University of Toronto.

Background: Studies on the extent to which long-term exposure to ambient particulate matter (PM) with aerodynamic diameter [less than or equal to]2.5 [micro]m ([PM.sub.2.5]) contributes to adult mortality in India are few, despite over 99% of Indians being exposed to levels that the World Health Organization (WHO) considers unsafe. Objective: We conducted a retrospective cohort study within the Million Death Study (MDS) to provide the first-ever quantification of national mortality from exposure to [PM.sub.2.5] in India from 1999 to 2014. Methods: We calculated relative risks (RRs) by linking a total of ten 3-y intervals of satellite-based estimated [PM.sub.2.5] exposure to deaths 3 to 5 y later in over 7,400 small villages or urban blocks covering a total population of 6.8 million. We applied using a model-based geostatistical model, adjusted for individual age, sex, and year of death; smoking prevalence, rural/urban residency, area-level female illiteracy, languages, and spatial clustering and unit-level variation. Results: [PM.sub.2.5] exposure levels increased from 1999 to 2014, particularly in central and eastern India. Among 212,573 deaths at ages 15-69 y, after spatial adjustment, we found a significant RR of 1.09 [95% credible interval (CI): 1.04, 1.14] for stroke deaths per 10-[micro]g/[m.sup.3] increase in [PM.sub.2.5] exposure, but no significant excess for deaths from chronic respiratory disease and ischemic heart disease (IHD), all nonaccidental causes, and total mortality (after excluding stroke). Spatial adjustment attenuated the RRs for chronic respiratory disease and IHD but raised those for stroke. The RRs were consistent in various sensitivity analyses with spatial adjustment, including stratifying by levels of solid fuel exposure, by sex, and by age group, addition of climatic variables, and in supplementary case-control analyses using injury deaths as controls. Discussion: Direct epidemiological measurements, despite inherent limitations, yielded associations between mortality and long-term [PM.sub.2.5] inconsistent with those reported in earlier models used by the WHO to derive estimates of [PM.sub.2.5] mortality in India. The modest RRs in our study are consistent with near or null mortality effects. They suggest suitable caution in estimating deaths from [PM.sub.2.5] exposure based on MDS results and even more caution in extrapolating model-based associations of risk derived mostly from high-income countries to India.

Background Malaria in India has been difficult to measure. Mortality and morbidity are not comprehensively reported, impeding efforts to track changes in disease burden. However, a set of blood measures has been collected regularly by the National Malaria Control Program in most districts since 1958. Methods Here, we use principal components analysis to combine these measures into a single index, the Summary Index of Malaria Surveillance (SIMS), and then test its temporal and geographic stability using subsets of the data. Results The SIMS correlates positively with all its individual components and with external measures of mortality and morbidity. It is highly consistent and stable over time (1995-2005) and regions of India. It includes measures of both vivax and falciparum malaria, with vivax dominant at lower transmission levels and falciparum dominant at higher transmission levels, perhaps due to ecological specialization of the species. Conclusions This measure should provide a useful tool for researchers looking to summarize geographic or temporal trends in malaria in India, and can be readily applied by administrators with no mathematical or scientific background. We include a spreadsheet that allows simple calculation of the index for researchers and local administrators. Similar principles are likely applicable worldwide, though further validation is needed before using the SIMS outside India.

The incidence of infection during SARS-CoV-2 viral waves, the factors associated with infection, and the durability of antibody responses to infection among Canadian adults remain undocumented. To assess the cumulative incidence of SARS-CoV-2 infection during the first 2 viral waves in Canada by measuring seropositivity among adults. The Action to Beat Coronavirus study conducted 2 rounds of an online survey about COVID-19 experience and analyzed immunoglobulin G levels based on participant-collected dried blood spots (DBS) to assess the cumulative incidence of SARS-CoV-2 infection during the first and second viral waves in Canada. A sample of 19 994 Canadian adults (aged ≥18 years) was recruited from established members of the Angus Reid Forum, a public polling organization. The study comprised 2 phases (phase 1 from May 1 to September 30, 2020, and phase 2 from December 1, 2020, to March 31, 2021) that generally corresponded to the first (April 1 to July 31, 2020) and second (October 1, 2020, to March 1, 2021) viral waves. SARS-CoV-2 immunoglobulin G seropositivity (using a chemiluminescence assay) by major geographic and demographic variables and correlation with COVID-19 symptom reporting. Among 19 994 adults who completed the online questionnaire in phase 1, the mean (SD) age was 50.9 (15.4) years, and 10 522 participants (51.9%) were female; 2948 participants (14.5%) had self-identified racial and ethnic minority group status, and 1578 participants (8.2%) were self-identified Indigenous Canadians. Among participants in phase 1, 8967 had DBS testing. In phase 2, 14 621 adults completed online questionnaires, and 7102 of those had DBS testing. Of 19 994 adults who completed the online survey in phase 1, fewer had an educational level of some college or less (4747 individuals [33.1%]) compared with the general population in Canada (45.0%). Survey respondents were otherwise representative of the general population, including in prevalence of known risk factors associated with SARS-CoV-2 infection. The cumulative incidence of SARS-CoV-2 infection among unvaccinated adults increased from 1.9% in phase 1 to 6.5% in phase 2. The seropositivity pattern was demographically and geographically heterogeneous during phase 1 but more homogeneous by phase 2 (with a cumulative incidence ranging from 6.4% to 7.0% in most regions). The exception was the Atlantic region, in which cumulative incidence reached only 3.3% (odds ratio [OR] vs Ontario, 0.46; 95% CI, 0.21-1.02). A total of 47 of 188 adults (25.3%) reporting COVID-19 symptoms during phase 2 were seropositive, and the OR of seropositivity for COVID-19 symptoms was 6.15 (95% CI, 2.02-18.69). In phase 2, 94 of 444 seropositive adults (22.2%) reported having no symptoms. Of 134 seropositive adults in phase 1 who were retested in phase 2, 111 individuals (81.8%) remained seropositive. Participants who had a history of diabetes (OR, 0.58; 95% CI, 0.38-0.90) had lower odds of having detectable antibodies in phase 2. The Action to Beat Coronavirus study found that the incidence of SARS-CoV-2 infection in Canada was modest until March 2021, and this incidence was lower than the levels of population immunity required to substantially reduce transmission of the virus. Ongoing vaccination efforts remain central to reducing viral transmission and mortality. Assessment of future infection-induced and vaccine-induced immunity is practicable through the use of serial online surveys and participant-collected DBS.

Acute abdominal conditions have high case-fatality rates in the absence of timely surgical care. In India, and many other low-income and middle-income countries, few population-based studies have quantified mortality from surgical conditions and related mortality to access to surgical care. We aimed to describe the spatial and socioeconomic distributions of deaths from acute abdomen (DAA) in India and to quantify potential access to surgical facilities in relation to such deaths. We examined deaths from acute abdominal conditions within a nationally representative, population-based mortality survey of 1·1 million Indian households and linked these to nationally representative facility data. Spatial clustering of deaths from acute abdominal conditions was calculated with the Getis-Ord Gi* statistic from about 4000 postal codes. We compared high or low acute abdominal mortality clusters for their geographic access to well-resourced surgical care (24 h surgical and anaesthesia services, blood bank, critical care beds, basic laboratory, and radiology). 923 (1·1%) of 86 806 study deaths in those aged 0–69 years were identified as deaths from acute abdominal conditions, corresponding to an estimated 72 000 deaths nationally in India in 2010. Most deaths occurred at home (71%), in rural areas (87%), and were caused by peptic ulcer disease (79%). There was wide variation in rates of deaths from acute abdominal conditions. We identified 393 high-mortality geographic clusters and 567 low-mortality clusters. High-mortality clusters of acute abdominal conditions were located significantly further from well-resourced hospitals than were low-mortality clusters. The odds ratio of a postal code area being a high-mortality cluster was 4·4 (99% CI 3·2–6·0) for living 50 km or more from well-resourced district hospitals (rising to an OR of 16·1 for >100 km), after adjustment for socioeconomic status and caste. Improvements in human and physical resources at existing public hospitals are required to reduce deaths from acute abdominal conditions in India. Had all of the Indian population had access to well-resourced hospitals within 50 km, more than 50 000 deaths from acute abdominal conditions could have been averted in 2010, and likely more from other emergency surgical conditions. Our geocoded facility data were limited to public district hospitals. However, noting the high rate of catastrophic health expenditures in India, we chose to focus on publicly provided services which are the only option usually available to the poor. The Bill & Melinda Gates Foundation, Dalla Lana School of Public Health, and Canadian Institute of Health Research.