As of 2023, the countries with the highest death rates worldwide were Monaco, Bulgaria, and Latvia. In these countries, there were ** to ** deaths per 1,000 people. The country with the lowest death rate is Qatar, where there is just *** death per 1,000 people. Leading causes of death The leading causes of death worldwide are, by far, cardiovascular diseases, accounting for ** percent of all deaths in 2021. That year, there were **** million deaths worldwide from ischaemic heart disease and **** million from stroke. Interestingly, a worldwide survey from that year found that people greatly underestimate the proportion of deaths caused by cardiovascular disease, but overestimate the proportion of deaths caused by suicide, interpersonal violence, and substance use disorders. Death in the United States In 2023, there were around **** million deaths in the United States. The leading causes of death in the United States are currently heart disease and cancer, accounting for a combined ** percent of all deaths in 2023. Lung and bronchus cancer is the deadliest form of cancer worldwide, as well as in the United States. In the U.S. this form of cancer is predicted to cause around ****** deaths among men alone in the year 2025. Prostate cancer is the second-deadliest cancer for men in the U.S. while breast cancer is the second deadliest for women. In 2023, the tenth leading cause of death in the United States was COVID-19. Deaths due to COVID-19 resulted in a significant rise in the total number of deaths in the U.S. in 2020 and 2021 compared to 2019, and it was the third leading cause of death in the U.S. during those years.

The leading causes of death in Massachusetts are cancer, heart disease, unintentional injury, stroke, and chronic lower respiratory disease. These mortality rates tend to be higher for people of color; and Black residents have a higher premature mortality rate overall and Asian residents have a higher rate of mortality due to stroke.

This statistic shows the overall mortality rate from infectious diseases in China from 2015 to 2021. In 2021, approximately **** out of 100,000 people in China died due to communicable diseases, an increase from the year prior mainly due to the high mortality rate of the coronavirus infection.

ObjectivesThe aim of this study is to describe, visualize, and compare the trends and epidemiological features of the mortality rates of 10 notifiable respiratory infectious diseases in China from 2004 to 2020.SettingData were obtained from the database of the National Infectious Disease Surveillance System (NIDSS) and reports released by the National and local Health Commissions from 2004 to 2020. Spearman correlations and Joinpoint regression models were used to quantify the temporal trends of RIDs by calculating annual percentage changes (APCs) in the rates of mortality.ResultsThe overall mortality rate of RIDs was stable across China from 2004 to 2020 (R = −0.38, P = 0.13), with an APC per year of −2.2% (95% CI: −4.6 to 0.3; P = 0.1000). However, the overall mortality rate of 10 RIDs in 2020 decreased by 31.80% (P = 0.006) compared to the previous 5 years before the COVID-19 pandemic. The highest mortality occurred in northwestern, western, and northern China. Tuberculosis was the leading cause of RID mortality, and mortality from tuberculosis was relatively stable throughout the 17 years (R = −0.36, P = 0.16), with an APC of −1.9% (95% CI −4.1 to 0.4, P = 0.1000). Seasonal influenza was the only disease for which mortality significantly increased (R = 0.73, P = 0.00089), with an APC of 29.70% (95% CI 16.60–44.40%; P = 0.0000). The highest yearly case fatality ratios (CFR) belong to avian influenza A H5N1 [687.5 per 1,000 (33/48)] and epidemic cerebrospinal meningitis [90.5748 per 1,000 (1,010/11,151)]. The age-specific CFR of 10 RIDs was highest among people over 85 years old [13.6551 per 1,000 (2,353/172,316)] and was lowest among children younger than 10 years, particularly in 5-year-old children [0.0552 per 1,000 (58/1,051,178)].ConclusionsThe mortality rates of 10 RIDs were relatively stable from 2004 to 2020 with significant differences among Chinese provinces and age groups. There was an increased mortality trend for seasonal influenza and concerted efforts are needed to reduce the mortality rate of seasonal influenza in the future.

Since 2008, HIV/AIDS remains the most fatal infectious disease in China. In 2021, almost ** out of one million people in China died from AIDS. Tuberculosis stood at the second place, while rabies ranked the fourth.

Who are the high risk groups?

The HIV/AIDS epidemic has become a growing concern for the major population in China. A majority of new infections were the result from sexual transmission. Although the prevalence rate has been relatively low, the trend of new diagnoses in people aged from 15 to 24 years has been alarming, with gay men disproportionately represented.

Children under the age of ** are the most vulnerable group to contract common infectious diseases like influenza and HFMD. The Chinese government has thus introduced healthcare initiatives dedicated to vaccinating children up to the age of ** under the Extended Program for Immunization (EPI). The efforts have been fruitful with significant improvement in the healthcare status of children under the age of **** in the country.

How is disease controlled in China?

The world’s most populous nation has made considerable efforts in tracking and preventing the spread of infectious diseases. Alongside geographical and demographic challenges, the mortality rate of infectious diseases has seen a slight increase over the recent years. Seasonal diseases, especially Influenza and mumps, are easily widespread and have pressed the demand for efficient disease prevention and control. In response, the Chinese government has ramped up the supply of influenza vaccines and HPV vaccines.

For each model, we report the results for the linear (regression model analysis) and the non-linear (smoothing model analysis) components. The sign of the estimate indicates whether the linear trend was positive or negative. The models were run using a binomial distribution of errors (number of deaths/number of cases). Diseases are ordered by increasing values of CFR (deaths/cases). The column Replicates indicates the number of replicated datasets per disease. After a sequential Bonferroni correction, the non-linear trend for Western equine encephalitis was not statistically significant.

Estimated all-cause and cause-specific mortality rates by GBD and HIV disease classifications in Kisumu County, Kenya (2019).

The table reports the estimates (with SE and 95% CI), z and P values for the parameters retained in the model with the lowest BIC value. Number of observations = 873; number of deaths/number of cases = 143,877/5,624,790.

Abstract: Mortality in prisons, a basic indicator of the right to health for incarcerated persons, has never been studied extensively in Brazil. An assessment of all-cause and cause-specific mortality in prison inmates was conducted in 2016-2017 in the state of Rio de Janeiro, based on data from the Mortality Information System and Prison Administration. Mortality rates were compared between prison population and general population after standardization. The leading causes of death in inmates were infectious diseases (30%), cardiovascular diseases (22%), and external causes (12%). Infectious causes featured HIV/AIDS (43%) and TB (52%, considering all deaths with mention of TB). Only 0.7% of inmates who died had access to extramural health services. All-cause mortality rate was higher among prison inmates than in the state’s general population. Among inmates, mortality from infectious diseases was 5 times higher, from TB 15 times higher, and from endocrine diseases (especially diabetes) and cardiovascular diseases 1.5 and 1.3 times higher, respectively, while deaths from external causes were less frequent in prison inmates. The study revealed important potentially avoidable excess deaths in prisons, reflecting lack of care and exclusion of this population from the Brazilian Unified National Health System. This further highlights the need for a precise and sustainable real-time monitoring system for deaths, in addition to restructuring of the prison staff through implementation of the Brazilian National Policy for Comprehensive Healthcare for Persons Deprived of Freedom in the Prison System in order for inmates to fully access their constitutional right to health with the same quality and timeliness as the general population.

BackgroundIn resource-limited countries with weak healthcare systems, women of reproductive age are particularly vulnerable during times of conflict. In Tigray, Ethiopia, where a war broke out on 04 November 2020, there is a lack of information on causes of death (CoD) among women of reproductive age. This study aims to determine the underlying CoD among women of reproductive age during the armed conflict in Tigray.MethodsThis community-based survey was carried out in six Tigray zones, excluding the western zone for security reasons. We used a multistage stratified cluster sampling method to select the smallest administrative unit known as Tabiya. Data were collected using a standardized 2022 WHO Verbal Autopsy (VA) tool. The collected data were analyzed using the InterVA model using R analytic software. The study reported both group-based and cause-specific mortality fractions.ResultsA total of 189,087 households were screened and 832 deaths were identified among women of reproductive age. The Global Burden of Disease classification showed that infectious and maternal disorders were the leading CoD, accounting for 42.9% of all deaths. External causes contributed to 26.4% of fatalities, where assault accounted for 13.2% of the deaths. Maternal deaths made up 30.0% of the overall mortality rate. HIV/AIDS was the primary CoD, responsible for 13.2% of all deaths and 54.0% of infectious causes. Other significant causes included obstetric hemorrhage (11.7%) and other and unspecified cardiac disease (6.6%).ConclusionsThe high proportion of infectious diseases related CoD, including HIV/AIDS, as well as the occurrence of uncommon external CoD among women, such as assault, and a high proportion of maternal deaths are likely the result of the impact of war in the region. This highlights the urgent need for targeted interventions to address these issues and prioritize sexual and reproductive health as well as maternal health in Tigray.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

This paper used Our World data for coronavirus disease-2019 (COVID-19) death count, test data, stringency, and transmission count and prepared a path model for COVID-19 deaths. We augmented the model with age structure-related variables and comorbidity via non-communicable diseases for 117 countries of the world for September 23, 2021, on a cross-section basis. A broad-based global quantitative study incorporating these two prominent channels with regional variation was unavailable in the existing literature. Old age and comorbidity were identified as two prime determinants of COVID-19 mortality. The path model showed that after controlling for these factors, one SD increase in the proportion of persons above 65, above 70, or of median age raised COVID-19 mortality by more than 0.12 SDs for 117 countries. The regional intensity of death is alarmingly high in South America, Europe, and North America compared with Oceania. After controlling for regions, the figure was raised to 0.213, which was even higher. For old age, the incremental coefficient was the highest for South America (0.564), and Europe (0.314), which were substantially higher than in Oceania. The comorbidity channel via non-communicable diseases illustrated that one SD increase in non-communicable disease intensity increased COVID-19 mortality by 0.132 for the whole sample. The regional figure for the non-communicable disease was 0.594 for South America and 0.358 for Europe compared with the benchmark region Oceania. The results were statistically significant at a 10% level of significance or above. This suggested that we should prioritize vaccinations for the elderly and people with comorbidity via non-communicable diseases like heart disease, cancer, chronic respiratory disease, and diabetes. Further attention should be given to South America and Europe, which are the worst affected regions of the world.

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.

One in every 100 children dies before completing one year of life. Around 68 percent of infant mortality is attributed to deaths of children before completing 1 month. 15,000 children die every day – Child mortality is an everyday tragedy of enormous scale that rarely makes the headlines Child mortality rates have declined in all world regions, but the world is not on track to reach the Sustainable Development Goal for child mortality Before the Modern Revolution child mortality was very high in all societies that we have knowledge of – a quarter of all children died in the first year of life, almost half died before reaching the end of puberty Over the last two centuries all countries in the world have made very rapid progress against child mortality. From 1800 to 1950 global mortality has halved from around 43% to 22.5%. Since 1950 the mortality rate has declined five-fold to 4.5% in 2015. All countries in the world have benefitted from this progress In the past it was very common for parents to see children die, because both, child mortality rates and fertility rates were very high. In Europe in the mid 18th century parents lost on average between 3 and 4 of their children Based on this overview we are asking where the world is today – where are children dying and what are they dying from?

5.4 million children died in 2017 – Where did these children die? Pneumonia is the most common cause of death, preterm births and neonatal disorders is second, and diarrheal diseases are third – What are children today dying from? This is the basis for answering the question what can we do to make further progress against child mortality? We will extend this entry over the course of 2020.

@article{owidchildmortality, author = {Max Roser, Hannah Ritchie and Bernadeta Dadonaite}, title = {Child and Infant Mortality}, journal = {Our World in Data}, year = {2013}, note = {https://ourworldindata.org/child-mortality} }

Senegal SN: Mortality Rate: Under-5: Male: per 1000 Live Births data was reported at 49.400 Ratio in 2017. This records a decrease from the previous number of 54.000 Ratio for 2015. Senegal SN: Mortality Rate: Under-5: Male: per 1000 Live Births data is updated yearly, averaging 71.100 Ratio from Dec 1990 (Median) to 2017, with 5 observations. The data reached an all-time high of 145.900 Ratio in 1990 and a record low of 49.400 Ratio in 2017. Senegal SN: Mortality Rate: Under-5: Male: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Senegal – Table SN.World Bank.WDI: Health Statistics. Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

BackgroundAccording to one USA Renal Data System report, 57% of end-stage renal disease (ESRD) cases are attributed to hypertensive and diabetic nephropathy. Yet, trends in hypertension related ESRD mortality rates in adults ≥ 35 years of age have not been studied.ObjectivesThe aim of this retrospective study was to analyze the different trends hypertension related ESRD death rates among adults in the United States.MethodsDeath records from the CDC (Centers for Disease Control and Prevention Wide-Ranging OnLine Data for Epidemiologic Research) database were analyzed from 1999 to 2020 for hypertension related ESRD mortality in adults ≥ 35 years of age. Age-Adjusted mortality rates (AAMRs) per 100,000 persons and annual percent change (APC) were calculated and stratified by year, sex, race/ethnicity, place of death, and geographic location.ResultsHypertension-related ESRD caused a total of 721,511 deaths among adults (aged ≥ 35 years) between 1999 and 2020. The overall AAMR for hypertension related ESRD deaths in adults was 9.70 in 1999 and increased all the way up to 43.7 in 2020 (APC: 9.02; 95% CI: 8.19-11.04). Men had consistently higher AAMRs than woman during the analyzed years from 1999 (AAMR men: 10.8 vs women: 9) to 2020 (AAMR men: 52.2 vs women: 37.2). Overall AAMRs were highest in Non-Hispanic (NH) Black or African American patients (45.7), followed by NH American Indian or Alaska Natives (24.7), Hispanic or Latinos (23.4), NH Asian or Pacific Islanders (19.3), and NH White patients (15.4). Region-wise analysis also showed significant variations in AAMRs (overall AAMR: West 21.2; South: 21; Midwest: 18.3; Northeast: 14.2). Metropolitan areas had slightly higher AAMRs (19.1) than nonmetropolitan areas (19). States with AAMRs in 90th percentile: District of Columbia, Oklahoma, Mississippi, Tennessee, Texas, and South Carolina, had roughly double rates compared to states in 10th percentile.ConclusionsOverall hypertension related ESRD AAMRs among adults were seen to increase in almost all stratified data. The groups associated with the highest death rates were NH Black or African Americans, men, and populations in the West and metropolitan areas of the United States. Strategies and policies targeting these at-risk groups are required to control the rising hypertension related ESRD mortality.

Highly pathogenic avian influenza virus (HPAIV) has caused extensive mortalities in wild birds, with a disproportionate impact on raptors since 2021. The population-level impact of HPAIV can be informed by telemetry studies that track large samples of initially healthy, wild birds. We leveraged movement data from 71 rough-legged hawks (Buteo lagopus) across all major North American migratory bird flyways concurrent with the 2022–2023 HPAIV outbreak and identified a total of 29 mortalities, of which 11 were confirmed, and an additional ~9 were estimated to have been caused by HPAIV. We estimated a 28% HPAIV cause-specific mortality rate among rough-legged hawks during a single year concurrent with the HPAIV outbreak in North America. Additionally, the overall annual mortality rate during the HPAIV outbreak (47%) was significantly higher than baseline annual mortality rates (3–17%), suggesting that HPAIV-caused deaths were additive above baseline mortality levels. HPAIV mortalities were c..., , # Increased mortality rates caused by highly pathogenic avian influenza virus in a migratory raptor

Dataset DOI: 10.5061/dryad.n2z34tn92

Description of the data and file structure

We leveraged movement data from GPS-tracked rough-legged hawks Buteo lagopus that coincided with the HPAIV panzootic in North America to determine its effect on annual mortality. All missing and unavailable data represented as NAÂ

Files and variables

File: AnnualMortality.csv

Description:Â spreadsheet used to analyze the HPAIV effect on annual mortality.

Variables

• index: index number
• tagid: transmitter ID (unique to an individual hawk)
• year: 12-month study period. 2020 = 1-Mar-2020 to 28-Feb-2021, etc...
• date_begin: date within the 12-month study period that tracking began
• date_end:Â date within the 12-month study period that tracking ended
• duration: tracking duration (number of days)
• fate: individual fate during the 12-month study period...,

Recent increases in emergent infectious diseases have raised concerns about the population stability of some marine species. The complexity and expense of studying diseases in marine systems often dictate that conservation and management decisions are made without quantitative data on population-level impacts of disease. Mark-recapture is a powerful, underutilized, tool for calculating impacts of disease on population size and structure, even in the absence of etiological information. We applied logistic regression models to mark-recapture data to obtain estimates of disease-associated mortality rates in three commercially-important marine species: snow crab (Chionoecetes opilio) in Newfoundland, Canada, that experience sporadic epizootics of bitter crab disease; striped bass (Morone saxatilis) in the Chesapeake Bay, USA, that experience chronic dermal and visceral mycobacteriosis; and American lobster (Homarus americanus) in the Southern New England stock, that experience chronic epizootic shell disease. All three diseases decreased survival of diseased hosts. Survival of diseased adult male crabs was 1% (0.003 – 0.022, 95% CI) that of uninfected crabs indicating nearly complete mortality of infected crabs in this life stage. Survival of moderately and severely diseased striped bass (which comprised 15% and 11% of the population, respectively) was 84% (70 – 100%, 95% CI), and 54% (42- 68%, 95% CI) and that of healthy striped bass. The disease-adjusted yearly natural mortality rate for striped bass was 0.29, nearly double the previously accepted value, which did not include disease. Survival of moderately and severely diseased lobsters was 30% (15 – 60%, 95% CI) that of healthy lobsters and survival of mildly diseased lobsters was 45% (27 – 75%, 95% CI) that of healthy lobsters. High disease mortality in ovigerous females may explain the poor recruitment and rapid declines observed in this population. Stock assessments should account for disease-related mortality when resource management options are evaluated.

Sweden SE: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 89.900 % in 2016. This records an increase from the previous number of 89.100 % for 2015. Sweden SE: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 89.950 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 90.700 % in 2010 and a record low of 89.100 % in 2015. Sweden SE: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank.WDI: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.; ; Derived based on the data from WHO's Global Health Estimates.; Weighted average;

Purpose:This dataset contains the Age-Adjusted Heart Disease Mortality Rate Per 100,000 Persons by Colorado Census Tract; Underlying Cause of Death Heart Disease (2019-2023). Numerator data are calculated from the 2019-2023 Colorado Department of Public Health and Environment Colorado Death Statistics. Population estimates for the denominator are calculated from the 2019-2023 U.S. Census American Community Survey. This dataset supports the CDPHE Community Health Equity Map application.Update Schedule and URL: This dataset is updated annually (September) and is provided using death data directly assembled from the Colorado Department of Public Health and Environment Colorado Death Statistics. For inquiries about vital statistics or for data requests contact cdphe.healthstatistics@state.co.us, or use the data request system. Fields Description:GEOID: 11-digit Census Tract FIPS Identifier COUNTY: County NameNAME: Census Tract NameHD_ADJRATE: Age-Adjusted Heart Disease Mortality Rate Per 100,000 Persons (2019-2023, Colorado Death Statistics and U.S. Census American Community Survey)HD_L95CI: Heart Disease Mortality Rate Lower 95% Confidence IntervalHD_U95CI: Heart Disease Mortality Rate Upper 95% Confidence IntervalHD_STATEADJRATE: Statewide Age-Adjusted Heart Disease Mortality Rate Per 100,000 Persons (2019-2023, Colorado Death Statistics and U.S. Census American Community Survey)HD_SL95CI: Statewide Heart Disease Mortality Rate Lower 95% Confidence IntervalHD_SU95CI: Statewide Heart Disease Mortality Rate Upper 95% Confidence IntervalHD_DISPLAY: Heart Disease Mortality Rate Census Tract Map Display Designation (Estimate is Higher Than State Average Confidence Interval, Lower Than State Average Confidence Interval, Not Different Than State Average Confidence Interval, No Events or Data Suppressed)