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 dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

This dataset is about countries per year in Canada. It has 1 row and is filtered where the date is 2021. It features 4 columns: country, region, and death rate.

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

This Alberta Official Statistic compares the infant mortality rate across all five Alberta Health Services Continuum Zones for the combined years 2011 to 2014. The infant mortality rates are broken down by neonatal mortality (deaths occurring prior to 28 days) and post-neonatal mortality (deaths occurring between 28 days and < 1 year of age). Confidence intervals are presented to assist in interpretation. Alberta is divided into five continuum zones as follows: South, Calgary, Central, Edmonton, and North.

Number and percentage of deaths, by place of death (in hospital or non-hospital), 1991 to most recent year.

Canada CA: Mortality Rate: Under-5: Male: per 1000 Live Births data was reported at 5.400 Ratio in 2023. This records a decrease from the previous number of 5.500 Ratio for 2022. Canada CA: Mortality Rate: Under-5: Male: per 1000 Live Births data is updated yearly, averaging 8.650 Ratio from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 36.400 Ratio in 1960 and a record low of 5.400 Ratio in 2023. Canada CA: 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 Canada – Table CA.World Bank.WDI: Social: 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. Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation. This is a sex-disaggregated indicator for Sustainable Development Goal 3.2.1 [https://unstats.un.org/sdgs/metadata/].

Provides the age-standardized mortality rates per 100,000 population, for the three selected causes of death and all causes combined. The three selected causes of death are Circulatory System, Neoplasms and External Causes (Injury). Age standardization is a technique applied to make rates comparable across groups with different age distributions. A simple rate is defined as the number of people with a particular condition divided by the whole population. An age-standardized rate is defined as the number of people with a condition divided by the population within each age group. Standardizing (adjusting) the rate across age groups allows a more accurate comparison between populations that have different age structures. Age standardization is typically done when comparing rates across time periods, different geographic areas, and or population sub-groups (e.g. ethnic group). This indicator dataset contains information at both Local Geographic Area (for example, Lacombe, Red Deer - North, Calgary - West Bow, etc.) and Alberta levels. Local geographic area refers to 132 geographic areas created by Alberta Health (AH) and Alberta Health Services (AHS) based on census boundaries. This table is the part of "Alberta Health Primary Health Care - Community Profiles" report published March 2015

Additional File 3. Provides data to support the results pertaining to the percentage change analyses reported in the main text of the manuscript

Canada CA: Mortality Rate: Infant: per 1000 Live Births data was reported at 4.400 Ratio in 2023. This records a decrease from the previous number of 4.500 Ratio for 2022. Canada CA: Mortality Rate: Infant: per 1000 Live Births data is updated yearly, averaging 6.500 Ratio from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 27.800 Ratio in 1960 and a record low of 4.400 Ratio in 2023. Canada CA: Mortality Rate: Infant: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Social: Health Statistics. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given 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. Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

This table provides the age-standardized mortality rates per 100,000 population, for the three selected causes of death and all causes combined for both the local geographic area and Alberta for the most recent three-year period available. The three selected causes of death are Circulatory System, Neoplasms and External Causes (Injury). Age standardization is a technique applied to make rates comparable across groups with different age distributions. A simple rate is defined as the number of people with a particular condition divided by the whole population. An age-standardized rate is defined as the number of people with a condition divided by the population within each age group. Standardizing (adjusting) the rate across age groups allows a more accurate comparison between populations that have different age structures. Age standardization is typically done when comparing rates across time periods, different geographic areas, and or population sub-groups (e.g. ethnic group). This indicator dataset contains information at both Local Geographic Area (for example, Lacombe, Red Deer - North, Calgary - West Bow, etc.) and Alberta levels. Local geographic area refers to 132 geographic areas created by Alberta Health (AH) and Alberta Health Services (AHS) based on census boundaries. This table is the part of "Alberta Health Primary Health Care - Community Profiles" report published March 2015

Context

The data comes from the dataset maintained and updated by the Johns Hopkins University Center for Systems Science and Engineering. Tableau cleans, reshapes, and makes this data ready for your analysis.

Content

The data represent a point-in-time snapshot of to-date totals of confirmed cases and total deaths.

Here are the fields included:

Case_type: Confirmed Cases and total deaths Cases: Point in time snapshot of to-date totals (i.e., Mar 22 is inclusive of all prior dates) Date: Jan 23, 2020 - Present Country_region: Provided for all countries Province_state: Provided for Australia, Canada, China, Denmark, France, Netherlands, United Kingdom, United States Admin2: US only - County name FIPS: US only - 5-digit Federal Information Processing Standard Combined_Key: US only - Combination of Admin 2, State_Province, and Country_Region Lat Long Location Table Names: The Table Name is used to delineate the specific Johns Hopkins datasets that were used: JHU Timeseries - Country-level data (non-US) is sourced from the current JHU Global Timeseries dataset, provided to the public once per day JHU Timeseries - US data through Mar 23 (state-level) is sourced from the Mar 22 JHU Global Timeseries dataset JHU Daily - US data from Mar 23 (county-level) is sourced from the JHU Daily datasets (e.g., Mar 23 + Mar 24 + Mar 25, etc.)

Four datasets are presented here. The original dataset is a collection of the COVID-19 data maintained by Our World in Data. It includes data on confirmed cases, and deaths, as well as other variables of potential interest for ten countries such as Australia, Brazil, Canada, China, Denmark, France, Israel, Italy, the United Kingdom, and the United States. The original dataset includes the data from the date of 31st December in 2019 to 31st May in 2020 with a total of 1.530 instances and 19 features. This dataset is collected from a variety of sources (the European Centre for Disease Prevention and Control, United Nations, World Bank, Global Burden of Disease, Blavatnik School of Government, etc.). After the original dataset is pre-processed by cleaning and removing some data including unnecessary and blank. Then, all strings are converted numeric values, and some new features such as continent, hemisphere, year, month, and day are added by extracting the original features. After that, the processed original dataset is organized for prediction of the number of new cases of COVID-19 for 1 day, 3 days, and 10 days ago and three datasets (Dataset-1, 2, 3) are created for that.

Number and percentage of deaths, by month and place of residence, 1991 to most recent year.

The share of the population with overweight in the United States was forecast to continuously increase between 2024 and 2029 by in total 1.6 percentage points. After the fifteenth consecutive increasing year, the overweight population share is estimated to reach 77.43 percent and therefore a new peak in 2029. Notably, the share of the population with overweight of was continuously increasing over the past years.Overweight is defined as a body mass index (BMI) of more than 25.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the share of the population with overweight in countries like Canada and Mexico.

Background: Substantial mortality occurs after hospital discharge in children younger than 5 years with suspected sepsis, especially in low-income countries. A better understanding of its epidemiology is needed for effective interventions to reduce child mortality in these countries. We evaluated risk factors for death after discharge in children admitted to hospital for suspected sepsis in Uganda, and assessed how these differed by age, time of death, and location of death. Methods: In this prospective observational cohort study, we recruited 0-60-month-old children admitted with suspected sepsis from the community to the paediatric wards of six Ugandan hospitals. The primary outcome was six-month post-discharge mortality among those discharged alive. We evaluated the interactive impact of age, time of death, and location of death on risk factors for mortality. Findings: 6,545 children were enrolled, with 6,191 discharged alive. The median (interquartile range) time from discharge to death was 28 (9-74) days, with a six-month post-discharge mortality rate of 5·5%, constituting 51% of total mortality. Deaths occurred at home (45%), in-transit to care (18%), or in hospital (37%) during a subsequent readmission. Post-discharge death was strongly associated with weight-for-age z-scores < -3 (adjusted risk ratio [aRR] 4·7, 95% CI 3·7–5·8 vs a Z score of >–2), referral for further care (7·3, 5·6–9·5), and unplanned discharge (3·2, 2·5–4·0). The hazard ratio of those with severe anaemia increased with time since discharge, while the hazard ratios of discharge vulnerabilities (unplanned, poor feeding) decreased with time. Age influenced the effect of several variables, including anthropometric indices (less impact with increasing age), anaemia (greater impact), and admission temperature (greater impact). Data Collection Methods: All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge. Data Processing Methods: For this analysis, data from both cohorts (0-6 months and 6-60 months) were combined and analysed as a single dataset. We used periods of overlapping enrolment (72% of total enrolment months) between the two cohorts to determine site-specific proportions of children who were 0-6 and 6-60 months of age. These proportions were used to weight the cohorts for the calculation of overall mortality rate. Z-scores were calculated using height and weight. Hematocrit was converted to hemoglobin. Distance to hospital was calculated using latitude and longitude. Extra symptom and diagnosis categories were created based on text field in these two variables. BCS score was created by summing all individual components. Abbreviations: MUAC -mid upper arm circumference wfa – weight for age wfl – weight for length bmi – body mass index lfa – length for age abx - antibiotics hr – heart rate rr – respiratory rate antimal - antimalarial sysbp – systolic blood pressure diasbp – diastolic blood pressure resp – respiratory cap - capillary BCS - Blantyre Coma Scale dist- distance hos - hospital ed - education disch - discharge dis -discharge fu – follow-up pd – post-discharge loc - location materl - maternal Ethics Declaration: This study was approved by the Mbarara University of Science and Technology Research Ethics Committee (No. 15/10-16), the Uganda National Institute of Science and Technology (HS 2207), and the University of British Columbia / Children & Women’s Health Centre of British Columbia Research Ethics Board (H16-02679). This manuscript adheres to the guidelines for STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). Study Protocol & Supplementary Materials: Smart Discharges to improve post-discharge health outcomes in children: A prospective before-after study with staggered implementation, 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.

Number of deaths caused by external causes of morbidity and mortality, by age group and sex, 2000 to most recent year.

La CNESST listens to your data needs! Answer our questionnaire.## Do you use or have specific needs in connection with [CNESST] data (https://www.cnesst.gouv.qc.ca/fr)? Take a few minutes to answer the following questionnaire: Consultation on your CNESST data needs To communicate with us about: - the questionnaire, write to us about: - the questionnaire, write to us at donnees.ouvertes@cnesst.gouv.qc.ca. - of a technical problem, write to us at consultation@cnesst.gouv.qc.ca or call us on 1 donnees.ouvertes@cnesst.gouv.qc.ca 866 216-7918, specifying the title of the consultation. Thanks for your participation! # # The dataset shows death claims accepted by the CNESST from January 1 to December 31. The CNESST administers the occupational health and safety regime. The Law on Industrial Accidents and Occupational Diseases (LATMP) aims to compensate for occupational injuries and the consequences they cause for beneficiaries. The death claims presented in the data set meet the following criteria: * They are the consequence of a work accident or an occupational disease within the meaning of the LATMP. * These claims represent people who were covered by the occupational health and safety insurance plan administered by the CNESST. * The date of registration of the acceptance of the death claim is between January 1 and December 31 of the reference year. Note that the death may have occurred during a year prior to the reference year.

AbstractThe prevalence of disease-driven mass mortality events is increasing, but our understanding of spatial variation in their magnitude, timing, and triggers are often poorly resolved. Here, we use a novel range-wide dataset comprised of 48,810 surveys to quantify how Sea Star Wasting Disease affected Pycnopodia helianthoides, the sunflower sea star, across its range from Baja California, Mexico to the Aleutian Islands, USA. We found that the outbreak occurred more rapidly, killed a greater percentage of the population, and left fewer survivors in the southern half of the species’ range. Pycnopodia now appears to be functionally extinct (> 99.2% declines) from Baja California, Mexico to Cape Flattery, Washington, USA and exhibited severe declines (> 87.8%) from the Salish Sea to the Gulf of Alaska. The importance of temperature in predicting Pycnopodia distribution rose 450% after the outbreak, suggesting these latitudinal gradients may stem from an interaction between disease severity and warmer waters. We found no evidence of population recovery in the years since the outbreak. Natural recovery in the southern half of the range is unlikely over the short-term and assisted recovery will likely be required for recovery in the southern half of the range on ecologically-relevant time scales., MethodsThirty research groups from Canada, the United States, Mexico, including First Nations, shared 34 datasets containing field surveys of Pycnopodia (Table S1). The data included 48,810 surveys from 1967 to 2020 derived from trawls, remotely operated vehicles, SCUBA dives, and intertidal surveys. We compiled survey data into a standardized format that included at minimum the coordinates, date, depth, area surveyed, and occurrence of Pycnopodia for each survey. When datasets contained more than one survey at a site in the same day (e.g. multiple transects), we divided the total Pycnopodia count in all surveys by the total survey area and averaged the latitude, longitude, and depth as necessary. Using breaks in data coverage, political boundaries, and biogeographic breaks we assigned each survey to one of twelve regions: Aleutian Islands, west Gulf of Alaska (GOA), east Gulf of Alaska, southeast Alaska, British Columbia (excluding the Salish Sea), Salish Sea (including the Puget Sound), Washington outer coast (excluding the Puget Sound), Oregon, northern California, central California, southern California, and the Pacific coast of Baja California (Fig. S1; see Supplementary Material)., Usage notesDocumentation, data, and code accompanying Hamilton et al., 2021 Pycnopodia Rangewide Assessment paper. Data MasterPycno_ToShare: Dec_lat = latitude in decimal degrees. Numeric. Dec_lon = longitude in decimal degrees. Numeric. Depth = depth in meters. Numeric. Pres_abs = presence or absence of Pycnopodia on that survey. Binary. Presence = 1, absence = 0 Density_m2 = density in meters squared if available for that set of surveys. Numeric. NA = no density data available for that survey. Source = shorthand name of the group that shared the data with us and the type of data (e.g. trawl, dive). To get further info on who that dataset, group, and group contact, see Table S1. Character. Note: When datasets contained more than one survey at a site in the same day (e.g. multiple transects), we divided the total Pycnopodia count in all surveys by the total survey area and averaged the latitude, longitude, and depth as necessary in order to minimize the impacts of pseudoreplication on the dataset. Used in MaxentSWD_Final and Density-Inc_Models_Figs_Tables_ToShare. CrashEventsForRPlot: Crash Dates were determined trends in Pycnopodia occurrence (site-level presence or absence) to estimate ‘crash date’, defined as the date when the occurrence rate of Pycnopodia in a region decreased by 75% from pre-outbreak levels. Used in OutbreakTimelineFigs_ToShare.R EpidemicPhases: See manuscript methods for information on how the column ‘EpidemicPhases’ was created. “Start-End” specifies whether that date was the start or the end of that epidemic phase for that region. Used in OutbreakTimelineFigs_ToShare.R Incidence_2012-2019: Columns G-J were calculated by fitting a logistic regression model to the occurrence of Pycnopodia over time for each region. We fit a logistic regression model to the occurrence of Pycnopodia from 1/1/2012 to 12/31/2019 to model the shape of the population decline for each region (Fig. 1a). From these models, we 1) estimated regional Pycnopodia occurrence rates on 1/1/2012 and 12/31/2019, 2) calculated the predicted occurrence value corresponding to a 75% decline in starting versus ending occurrence in each region, and 3) solved the inverse logistic equations for the date at which this occurrence value was predicted. All other columns are identifying information derived ... Visit https://dataone.org/datasets/sha256%3Ad5473633780710452e0d852d4a25d7e05c82c63b26e6c94b9d9e5f493924d8c3 for complete metadata about this dataset.

BackgroundCombination antiretroviral therapy (ART) has significantly increased survival among HIV-positive adults in the United States (U.S.) and Canada, but gains in life expectancy for this region have not been well characterized. We aim to estimate temporal changes in life expectancy among HIV-positive adults on ART from 2000–2007 in the U.S. and Canada.MethodsParticipants were from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD), aged ≥20 years and on ART. Mortality rates were calculated using participants' person-time from January 1, 2000 or ART initiation until death, loss to follow-up, or administrative censoring December 31, 2007. Life expectancy at age 20, defined as the average number of additional years that a person of a specific age will live, provided the current age-specific mortality rates remain constant, was estimated using abridged life tables.ResultsThe crude mortality rate was 19.8/1,000 person-years, among 22,937 individuals contributing 82,022 person-years and 1,622 deaths. Life expectancy increased from 36.1 [standard error (SE) 0.5] to 51.4 [SE 0.5] years from 2000–2002 to 2006–2007. Men and women had comparable life expectancies in all periods except the last (2006–2007). Life expectancy was lower for individuals with a history of injection drug use, non-whites, and in patients with baseline CD4 counts