Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.

Among the ten major virus outbreaks in the last 50 years, Marburg ranked first in terms of the fatality rate with 80 percent. In comparison, the recent novel coronavirus, originating from the Chinese city of Wuhan, had an estimated fatality rate of 2.2 percent as of January 31, 2020.

Alarming COVID-19 fatality rate in Mexico More than 812,000 people worldwide had died from COVID-19 as of August 24, 2020. Three of the most populous countries in the world have reported particularly large numbers of coronavirus-related deaths: Mexico, Brazil, and the United States. Out of those three nations, Mexico has the highest COVID-19 death rate, with around one in ten confirmed cases resulting in death. The high fatality rate in Mexico indicates that cases may be much higher than reported because testing capacity has been severely stretched.

Post-lockdown complacency a real danger In March 2020, each infected person was estimated to transmit the COVID-19 virus to between 1.5 and 3.5 other people, which was a higher infection rate than the seasonal flu. The coronavirus is primarily spread through respiratory droplets, and transmission commonly occurs when people are in close contact. As lockdowns ease around the world, people are being urged not to become complacent; continue to wear face coverings and practice social distancing, which can help to prevent further infections.

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

From the mid-19th century until today, life expectancy at birth in the United States has roughly doubled, from 39.4 years in 1850 to 79.6 years in 2025. It is estimated that life expectancy in the U.S. began its upward trajectory in the 1880s, largely driven by the decline in infant and child mortality through factors such as vaccination programs, antibiotics, and other healthcare advancements. Improved food security and access to clean water, as well as general increases in living standards (such as better housing, education, and increased safety) also contributed to a rise in life expectancy across all age brackets. There were notable dips in life expectancy; with an eight year drop during the American Civil War in the 1860s, a seven year drop during the Spanish Flu empidemic in 1918, and a 2.5 year drop during the Covid-19 pandemic. There were also notable plateaus (and minor decreases) not due to major historical events, such as that of the 2010s, which has been attributed to a combination of factors such as unhealthy lifestyles, poor access to healthcare, poverty, and increased suicide rates, among others. However, despite the rate of progress slowing since the 1950s, most decades do see a general increase in the long term, and current UN projections predict that life expectancy at birth in the U.S. will increase by another nine years before the end of the century.

BackgroundReducing neonatal and child mortality is a key component of the health-related sustainable development goal (SDG), but most low and middle income countries lack data to monitor child mortality on an annual basis. We tested a mortality monitoring system based on the continuous recording of pregnancies, births and deaths by trained community-based volunteers (CBV).Methods and findingsThis project was implemented in 96 clusters located in three districts of the Northern Region of Ghana. Community-based volunteers (CBVs) were selected from these clusters and were trained in recording all pregnancies, births, and deaths among children under 5 in their catchment areas. Data collection lasted from January 2012 through September 2013. All CBVs transmitted tallies of recorded births and deaths to the Ghana Birth and deaths registry each month, except in one of the study districts (approximately 80% reporting). Some events were reported only several months after they had occurred. We assessed the completeness and accuracy of CBV data by comparing them to retrospective full pregnancy histories (FPH) collected during a census of the same clusters conducted in October-December 2013. We conducted all analyses separately by district, as well as for the combined sample of all districts. During the 21-month implementation period, the CBVs reported a total of 2,819 births and 137 under-five deaths. Among the latter, there were 84 infant deaths (55 neonatal deaths and 29 post-neonatal deaths). Comparison of the CBV data with FPH data suggested that CBVs significantly under-estimated child mortality: the estimated under-5 mortality rate according to CBV data was only 2/3 of the rate estimated from FPH data (95% Confidence Interval for the ratio of the two rates = 51.7 to 81.4). The discrepancies between the CBV and FPH estimates of infant and neonatal mortality were more limited, but varied significantly across districts.ConclusionsIn northern Ghana, a community-based data collection systems relying on volunteers did not yield accurate estimates of child mortality rates. Additional implementation research is needed to improve the timeliness, completeness and accuracy of such systems. Enhancing pregnancy monitoring, in particular, may be an essential step to improve the measurement of neonatal mortality.

Life expectancy at birth and at age 65, by sex, on a three-year average basis.

The coronavirus disease (COVID-19) pandemic has had unprecedented consequences for Canada's aging population with the majority of COVID-19 deaths (approximately 80% during 2020) occurring among adults aged 65 years and older. Both advanced age and underlying chronic diseases and conditions contribute to these severe outcomes. Excess mortality refers to additional mortality above the expected level (based on mortality in the same period in the preceding year or averaged over several preceding years in the same population). This measure allows for the measurement of death directly and indirectly related to COVID-19 and provides a summary measure of its whole system impact in addition to its impact on mortality.

In 2022, the infant mortality rate in the United States was 5.4 out of every 1,000 live births. This is a significant decrease from 1960, when infant mortality was at around 26 deaths out of every 1,000 live births. What is infant mortality? The infant mortality rate is the number of deaths of babies under the age of one per 1,000 live births. There are many causes for infant mortality, which include birth defects, low birth weight, pregnancy complications, and sudden infant death syndrome. In order to decrease the high rates of infant mortality, there needs to be an increase in education and medicine so babies and mothers can receive the proper treatment needed. Maternal mortality is also related to infant mortality. If mothers can attend more prenatal visits and have more access to healthcare facilities, maternal mortality can decrease, and babies have a better chance of surviving in their first year. Worldwide infant mortality rates Infant mortality rates vary worldwide; however, some areas are more affected than others. Afghanistan suffered from the highest infant mortality rate in 2024, and the following 19 countries all came from Africa, with the exception of Pakistan. On the other hand, Slovenia had the lowest infant mortality rate that year. High infant mortality rates can be attributed to lack of sanitation, technological advancements, and proper natal care. In the United States, Massachusetts had the lowest infant mortality rate, while Mississippi had the highest in 2022. Overall, the number of neonatal and post neonatal deaths in the United States has been steadily decreasing since 1995.

BackgroundGlobal and regional projections of mortality and burden of disease by cause for the years 2000, 2010, and 2030 were published by Murray and Lopez in 1996 as part of the Global Burden of Disease project. These projections, which are based on 1990 data, continue to be widely quoted, although they are substantially outdated; in particular, they substantially underestimated the spread of HIV/AIDS. To address the widespread demand for information on likely future trends in global health, and thereby to support international health policy and priority setting, we have prepared new projections of mortality and burden of disease to 2030 starting from World Health Organization estimates of mortality and burden of disease for 2002. This paper describes the methods, assumptions, input data, and results. Methods and FindingsRelatively simple models were used to project future health trends under three scenarios—baseline, optimistic, and pessimistic—based largely on projections of economic and social development, and using the historically observed relationships of these with cause-specific mortality rates. Data inputs have been updated to take account of the greater availability of death registration data and the latest available projections for HIV/AIDS, income, human capital, tobacco smoking, body mass index, and other inputs. In all three scenarios there is a dramatic shift in the distribution of deaths from younger to older ages and from communicable, maternal, perinatal, and nutritional causes to noncommunicable disease causes. The risk of death for children younger than 5 y is projected to fall by nearly 50% in the baseline scenario between 2002 and 2030. The proportion of deaths due to noncommunicable disease is projected to rise from 59% in 2002 to 69% in 2030. Global HIV/AIDS deaths are projected to rise from 2.8 million in 2002 to 6.5 million in 2030 under the baseline scenario, which assumes coverage with antiretroviral drugs reaches 80% by 2012. Under the optimistic scenario, which also assumes increased prevention activity, HIV/AIDS deaths are projected to drop to 3.7 million in 2030. Total tobacco-attributable deaths are projected to rise from 5.4 million in 2005 to 6.4 million in 2015 and 8.3 million in 2030 under our baseline scenario. Tobacco is projected to kill 50% more people in 2015 than HIV/AIDS, and to be responsible for 10% of all deaths globally. The three leading causes of burden of disease in 2030 are projected to include HIV/AIDS, unipolar depressive disorders, and ischaemic heart disease in the baseline and pessimistic scenarios. Road traffic accidents are the fourth leading cause in the baseline scenario, and the third leading cause ahead of ischaemic heart disease in the optimistic scenario. Under the baseline scenario, HIV/AIDS becomes the leading cause of burden of disease in middle- and low-income countries by 2015. ConclusionsThese projections represent a set of three visions of the future for population health, based on certain explicit assumptions. Despite the wide uncertainty ranges around future projections, they enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends, such as the ageing of the population, the continued spread of HIV/AIDS in many regions, and the continuation of the epidemiological transition in developing countries. The results depend strongly on the assumption that future mortality trends in poor countries will have a relationship to economic and social development similar to those that have occurred in the higher-income countries.

Background: In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. Methods: We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1000 admissions with 95% confidence intervals (95%CI). Findings: ur search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95%CI 3.4-4.7%]. The most common causes of mortality (deaths/1000 admissions) were infectious (12 [95%CI 9-14]); respiratory (9 [95%CI 5-13]); and gastrointestinal (9 [95%CI 6-11]). Common causes of admission (cases/1000 admissions) were respiratory (255 [95%CI 231-280]); infectious (214 [95%CI193-234]); and gastrointestinal (166 [95%CI 143-190]). We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Implications: Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation. NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

Background:Mortality following hospital discharge remains a significant threat to child health, particularly in resource-limited settings. In Uganda, the Smart Discharges risk-prediction models have demonstrated success in their ability to predict those at highest risk of death after discharge and use this to guide a risk-based approach to post-discharge care in children admitted with suspected sepsis. Respective prediction models for post-discharge mortality in ages 0-6 months and ages 6-60 months were developed in this cohort but have not yet been validated outside of Uganda. This study aimed to externally validate existing risk prediction models for pediatric post-discharge mortality within the Rwandan context. Methods: Prospective cohort of children 0d-60 mos admitted with suspected sepsis at two hospitals in Rwanda: Ruhengeri Referral Hospital in Musanze (rural) and University Hospital of Kigali in Kigali (urban) from May 2022 to February 2023. Vital status follow up was conducted at 2-, 4- and 6-months post-discharge. Five existing models from Smart Discharges Uganda were validated in this cohort: two models for children 0-6 months, and three for children 6-60 months. Models were applied to each participant in the Rwanda cohort to obtain a risk score which was then used to calculate predicted probability of post-discharge death. Model performance was evaluated by comparing to observed outcomes and to determine sensitivity, specificity, and AUROC. Threshold was set at 80% sensitivity. . Findings:In a cohort of 1218 children, 1123 children (96.7%) completed follow up. The overall rate of post-discharge mortality was 4.8% (n=58). The highest performing models had an AUROC of 0.75 (0-6 mos) and 0.74 (6-60mos), respectively. All five prediction models tested achieved an AUROC greater than 0.7 (range 0.706 - 0.738). Model degradation (determined by the percent reduction in AUC between the original model and the derived model) was relatively low, ranging from from 1.1% to 7.7%. Calibration plots showed good calibration for all models at predicted probabilities below 10%. There were too few outcomes to assess calibration among those at higher levels of predicted risk. Data Processing Methods: Ethics Declaration: Ethical approval was obtained from the University of Rwanda College of Medicine and Health Sciences (No 411/CMHS IRB/2021); University Teaching Hospital of Kigali (EC/CHUK/005/2022), University of California San Francisco (381688) and the University of British Columbia (H21-02795). NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

In 2023, the age-specific death rate for men aged 90 or over in England and Wales was 248.1 per one thousand population, and 215.1 for women. Except for infants that were under the age of one, younger age groups had the lowest death rate, with the death rate getting progressively higher in older age groups.

BAPC model projections of mortality and DALYs rates for each disease stage in China from 2022 to 2035, with 50%, 60%, 70%, 80%, and 95% uncertainty intervals.

Recent studies project that temperature-related mortality will be the largest source of future damage from climate change, with particular concern for the elderly (whom it is believed bear the largest heat-related mortality risk) and humid heat extremes (which physiology suggests may have dire consequences for human health). Here, we study heat and mortality in Mexico, a country that exhibits a unique combination of universal mortality microdata and among the most extreme humid heat exposures. By combining detailed measurements of wet-bulb temperature with granular, age-specific outcome data, we find that younger people are particularly vulnerable to heat while older people are particularly vulnerable to cold: those under 35 years old account for 75% of recent heat-related deaths and 87% of heat-related lost life years while those 50 and older account for 96% of cold-related deaths and 80% of cold-related lost life years. We develop high-resolution projections of humid heat and associat..., , , Climate projections for *Heat disproportionately kills young people: evidence from wet-bulb temperature in Mexico *(https://doi.org/10.1126/sciadv.adq3367)

This repo contains climate projections produced for the paper "Heat disproportionately kills young people: evidence from wet-bulb temperature in Mexico." Scripts and other data needed for replication can be found at https://doi.org/10.5281/zenodo.14182718.

The structure of the files in this repo follows the pattern:

_.pq

All files are parquet format, written using arrow v17.

Each file represents a time series of weather variables for each of Mexico's second-order administrative units (municipalities). Projections are made at the level of weather stations active during the study's historical data period and mapped to municipalities according to the methods described in the paper. The variables in each file are: date, scenario (GHG emissions ...

Background: Incident hemodialysis patients have the highest mortality in the first several months after starting dialysis treatments. We hypothesized that the patterns and risk factors associated with this early mortality differ from those in later dialysis therapy periods. Methods: We examined mortality patterns and predictors during the first several months of hemodialysis treatment in 18,707 incident patients since the first week of hemodialysis therapy and estimated the population attributable fractions for selected time periods in the first 24 months. Results: The 18,707 incident hemodialysis patients were 45% women and 54% diabetics. The standardized mortality ratios (95% confidence interval) in the 1st to 3rd month of hemodialysis therapy were 1.81 (1.74–1.88), 1.79 (1.72–1.86), and 1.34 (1.27–1.40), respectively. The standardized mortality ratio reached prevalent mortality only by the 7th month. No survival advantage for African Americans existed in the first 6 months. Patients with low albumin <3.5 g/dl had the highest proportion of infection-related deaths while patients with higher albumin levels had higher cardiovascular deaths including 76% of deaths during the first 3 months. Use of catheter as vascular access and hypoalbuminemia <3.5 g/dl explained 34% (17–54%) and 33% (19–45%) of all deaths in the first 90 days, respectively. Conclusions: Incident hemodialysis patients have the highest mortality during the first 6 months including 80% higher death risk in the first 2 months. The presence of a central venous catheter and hypoalbuminemia <3.5 g/dl each explain one third of all deaths in the first 90 days.

Nigeria suffers some of the highest rates of maternal and perinatal mortality in the world. Poor quality of obstetric care is a key factor, and although not quantified at a national level, local studies suggest that high rates of maternal and perinatal deaths are due to clinical management errors in hospitals. This project therefore explored the nature of existing practices and quality of clinical management of three leading causes of maternal and perinatal deaths (primary postpartum haemorrhage, eclampsia, and obstructed labour); implement an intervention package aimed at improving the quality of clinical management of these causes of deaths; and test the effectiveness of this package on quality of care indicators and maternal and perinatal outcomes.

The study follows a quasi-experimental research design, using interrupted time series analysis for assessment over a three year period. Six public secondary care hospitals and two public tertiary care hospitals in both north and south of Nigeria were selected randomly. Formative research was conducted in all eight hospitals, and thereafter the intervention will be carried out in four hospitals, with the remaining four hospitals functioning as control sites.

Clinical outcomes will be compared between intervention and control sites in a total of 2334 cases of PPH, preeclampsia/eclampsia and obstructed labour (based on an anticipated 50% reduction in case fatality rates, significance level of 0.05 and 80% power). This will consist of 1167 cases in the intervention sites and 1167 in the control sites. Maternal and perinatal mortality rates will serve as primary outcome measures. Secondary outcomes involve quality of care drawn from United Nations process indicators, skilled attendance index and data derived from this formative audit phase of the project.

The results will enable the identification of a system-wide quality of care framework for improving the delivery of emergency obstetric care for the prevention of maternal and perinatal morbidity and mortality in Nigeria.

Abstract The aim of this paper is to propose indicators of adequacy and to estimate correction factors for deaths reported to SIM. In 2014, we carried out a Proactive Search to capture deaths that occurred in 2012 in a sample of municipalities in the regions North and Northeast, and the states of Minas Gerais, Mato Grosso and Goiás. To characterize the coverage of deaths information, we proposed indicators of adequacy by municipality. Correction factors were estimated for individuals one year of age or older and younger than 1 year old. Among the deaths of people aged one year or more, the coverage was above 90% in 12 states. As for infant deaths, the coverage was less than 80% in 7 states. The results of the regression models showed association between the correction factors estimated and the proposed indicators of adequacy. We found very poor death information in 227 municipalities, for which the reported number of infant deaths even after correction, could not reach the minimum expected. Although the progress made in information of vital data in Brazil is recognized, the results show that our greatest challenge is to reach rural and remote municipalities, which do not yet have adequate vital information.

Animal mortality caused by vehicle collisions is one of the main ecological impacts of roads. Amphibians are the most affected group and road fatalities have a significant impact on population dynamics and viability. Several studies on Iberian amphibians have shown the importance of country roads on amphibian road mortality, but still, little is known about the situation in northern Portugal. By being more permeable to amphibian passage, country roads represent a greater source of mortality than highways, which act as barriers. Thus, mitigation measures should be applied, but due to the extensive road network, the identification of precise locations (hotspots) and variables related to animal-vehicle collision is needed to plan these measures successfully. The aim of the study was to analyse the spatial occurrence and related factors linked to amphibian mortality on a number of country roads in northern Portugal, using spatial statistics implemented in GIS and applying a binary logistical regression. We surveyed 631 km of road corresponding to seven transects, and observed 404 individual amphibians: 74 (18.3%) alive and 330 (81.7%) road-killed. Bufo bufo represented 80% of the mortality records. Three transects showed clustered distribution of road-kills, and broadleaved forests and road ditches were the most important factors associated with hotspots of road-kill. Logistic regression models showed that habitat quality, Bufo bufo’s habitat preferences, and road ditches are positively associated with amphibians’ road mortality in northern Portugal, whereas average altitude and length of walls were negatively associated. This study is a useful tool to understand spatial occurrence of amphibian road-kills in the face of applying mitigation measures on country roads from northern Portugal. This study also considers the necessity of assessing the condition of amphibian local populations to understand their road-kills spatial patterns and the urgency to apply mitigation measures on country roads. Palabras clave: Amphibian, Mortality