Number of infant deaths and infant mortality rates, by age group (neonatal and post-neonatal), 1991 to most recent year.

Background: Our previous study analyzed the age trajectory of mortality (ATM) in 14 European countries, while this study aimed at investigating ATM in other continents and in countries with a higher level of mortality. Data from 11 Non-European countries were used.Methods: The number of deaths was extracted from the WHO mortality database. The Halley method was used to calculate the mortality rates in all possible calendar years and all countries combined. This method enables us to combine more countries and more calendar years in one hypothetical population.Results: The age trajectory of total mortality (ATTM) and also ATM due to specific groups of diseases were very similar in the 11 non-European countries and in the 14 European countries. The level of mortality did not affect the main results found in European countries. The inverse proportion was valid for ATTM in non-European countries with two exceptions.Slower or no mortality decrease with age was detected in the first year of life, while the inverse proportion model was valid for the age range (1, 10) years in most of the main chapters of ICD10.Conclusions: The decrease in child mortality with age may be explained as the result of the depletion of individuals with congenital impairment. The majority of deaths up to the age of 10 years were related to congenital impairments, and the decrease in child mortality rate with age was a demonstration of population heterogeneity. The congenital impairments were latent and may cause death even if no congenital impairment was detected.

Background: Our previous study analyzed the age trajectory of mortality (ATM) in 14 European countries, while this study aimed at investigating ATM in other continents and in countries with a higher level of mortality. Data from 11 Non-European countries were used.Methods: The number of deaths was extracted from the WHO mortality database. The Halley method was used to calculate the mortality rates in all possible calendar years and all countries combined. This method enables us to combine more countries and more calendar years in one hypothetical population.Results: The age trajectory of total mortality (ATTM) and also ATM due to specific groups of diseases were very similar in the 11 non-European countries and in the 14 European countries. The level of mortality did not affect the main results found in European countries. The inverse proportion was valid for ATTM in non-European countries with two exceptions.Slower or no mortality decrease with age was detected in the first year of life, while the inverse proportion model was valid for the age range (1, 10) years in most of the main chapters of ICD10.Conclusions: The decrease in child mortality with age may be explained as the result of the depletion of individuals with congenital impairment. The majority of deaths up to the age of 10 years were related to congenital impairments, and the decrease in child mortality rate with age was a demonstration of population heterogeneity. The congenital impairments were latent and may cause death even if no congenital impairment was detected.

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.

The National Child Development Study (NCDS) is a continuing longitudinal study that seeks to follow the lives of all those living in Great Britain who were born in one particular week in 1958. The aim of the study is to improve understanding of the factors affecting human development over the whole lifespan.

The NCDS has its origins in the Perinatal Mortality Survey (PMS) (the original PMS study is held at the UK Data Archive under SN 2137). This study was sponsored by the National Birthday Trust Fund and designed to examine the social and obstetric factors associated with stillbirth and death in early infancy among the 17,000 children born in England, Scotland and Wales in that one week. Selected data from the PMS form NCDS sweep 0, held alongside NCDS sweeps 1-3, under SN 5565.

Survey and Biomeasures Data (GN 33004):
To date there have been ten attempts to trace all members of the birth cohort in order to monitor their physical, educational and social development. The first three sweeps were carried out by the National Children's Bureau, in 1965, when respondents were aged 7, in 1969, aged 11, and in 1974, aged 16 (these sweeps form NCDS1-3, held together with NCDS0 under SN 5565). The fourth sweep, also carried out by the National Children's Bureau, was conducted in 1981, when respondents were aged 23 (held under SN 5566). In 1985 the NCDS moved to the Social Statistics Research Unit (SSRU) - now known as the Centre for Longitudinal Studies (CLS). The fifth sweep was carried out in 1991, when respondents were aged 33 (held under SN 5567). For the sixth sweep, conducted in 1999-2000, when respondents were aged 42 (NCDS6, held under SN 5578), fieldwork was combined with the 1999-2000 wave of the 1970 Birth Cohort Study (BCS70), which was also conducted by CLS (and held under GN 33229). The seventh sweep was conducted in 2004-2005 when the respondents were aged 46 (held under SN 5579), the eighth sweep was conducted in 2008-2009 when respondents were aged 50 (held under SN 6137), the ninth sweep was conducted in 2013 when respondents were aged 55 (held under SN 7669), and the tenth sweep was conducted in 2020-24 when the respondents were aged 60-64 (held under SN 9412).

A Secure Access version of the NCDS is available under SN 9413, containing detailed sensitive variables not available under Safeguarded access (currently only sweep 10 data). Variables include uncommon health conditions (including age at diagnosis), full employment codes and income/finance details, and specific life circumstances (e.g. pregnancy details, year/age of emigration from GB).

Four separate datasets covering responses to NCDS over all sweeps are available. National Child Development Deaths Dataset: Special Licence Access (SN 7717) covers deaths; National Child Development Study Response and Outcomes Dataset (SN 5560) covers all other responses and outcomes; National Child Development Study: Partnership Histories (SN 6940) includes data on live-in relationships; and National Child Development Study: Activity Histories (SN 6942) covers work and non-work activities. Users are advised to order these studies alongside the other waves of NCDS.

From 2002-2004, a Biomedical Survey was completed and is available under End User Licence (EUL) (SN 8731) and Special Licence (SL) (SN 5594). Proteomics analyses of blood samples are available under SL SN 9254.

Linked Geographical Data (GN 33497):
A number of geographical variables are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies.

Linked Administrative Data (GN 33396):
A number of linked administrative datasets are available, under more restrictive access conditions, which can be linked to the NCDS EUL and SL access studies. These include a Deaths dataset (SN 7717) available under SL and the Linked Health Administrative Datasets (SN 8697) available under Secure Access.

Multi-omics Data and Risk Scores Data (GN 33592)
Proteomics analyses were run on the blood samples collected from NCDS participants in 2002-2004 and are available under SL SN 9254. Metabolomics analyses were conducted on respondents of sweep 10 and are available under SL SN 9411.

Additional Sub-Studies (GN 33562):
In addition to the main NCDS sweeps, further studies have also been conducted on a range of subjects such as parent migration, unemployment, behavioural studies and respondent essays. The full list of NCDS studies available from the UK Data Service can be found on the NCDS series access data webpage.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from NCDS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Further information about the full NCDS series can be found on the Centre for Longitudinal Studies website.

The National Child Development Deaths Dataset, 1958-2014: Special Licence Access contains data on known deaths among members of the NCDS birth cohort from 1958 to 2013. Information on deaths has been taken from the records maintained by the organisations responsible for the study over the life time of the study: the National Birthday Trust Fund, the National Children’s Bureau (NCB), the Social Statistics Research Unit (SSRU) and the CLS. The information has been gleaned from a variety of sources, including death certificates and other information from the National Health Service Central Register (NHSCR), and from relatives and friends during survey activities and cohort maintenance work by telephone, letter and e-mail. It includes all deaths up to 31st December 2013. In only 6 cases are the date of death unknown. By the end of December 8.7 per cent of the cohort were known to have died.

The National Child Development Study Response and Outcomes Dataset, 1958-2013 (SN 5560) covers other responses and outcomes of the cohort members and should be used alongside this dataset.

For the 3rd edition (July 2018) an updated version of the data was deposited. The new edition includes data on known deaths among members of the National Child Development Study (NCDS) birth cohort up to 2016. The user guide has also been updated.

This data tracks the deaths of children up to 18 years old and whether or not the child, youth or their family were involved with a children's aid society within 12 months of their death. This data is provided to the Office of the Chief Coroner by the Registrar General of Ontario and by children's aid societies and has not been independently verified by the Office of the Chief Coroner.

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

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken out by age group. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update.

Data are reported daily, with timestamps indicated in the daily briefings posted at: portal.ct.gov/coronavirus. Data are subject to future revision as reporting changes.

Starting in July 2020, this dataset will be updated every weekday.

Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

Effective June 28, 2023, this dataset will no longer be updated. Similar data are accessible from CDC WONDER (https://wonder.cdc.gov/mcd-icd10-provisional.html).

Deaths involving coronavirus disease 2019 (COVID-19) with a focus on ages 0-18 years in the United States.

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.

Background: Mortality rate rapidly decreases with age after birth, and, simultaneously, the spectrum of death causes show remarkable changes with age. This study analyzed age-associated decreases in mortality rate from diseases of all main chapters of the 10th revision of the International Classification of Diseases.Methods: The number of deaths was extracted from the mortality database of the World Health Organization. As zero cases could be ascertained for a specific age category, the Halley method was used to calculate the mortality rates in all possible calendar years and in all countries combined.Results: All causes mortality from the 1st day of life to the age of 10 years can be represented by an inverse proportion model with a single parameter. High coefficients of determination were observed for total mortality in all populations (arithmetic mean = 0.9942 and standard deviation = 0.0039).Slower or no mortality decrease with age was detected in the 1st year of life, while the inverse proportion method was valid for the age range [1, 10) years in most of all main chapters with three exceptions. The decrease was faster for the chapter “Certain conditions originating in the perinatal period” (XVI).The inverse proportion was valid already from the 1st day for the chapter “Congenital malformations, deformations and chromosomal abnormalities” (XVII).The shape of the mortality decrease was very different for the chapter “Neoplasms” (II) and the rates of mortality from neoplasms were age-independent in the age range [1, 10) years in all populations.Conclusion: The theory of congenital individual risks of death is presented and can explain the results. If it is valid, latent congenital impairments may be present among all cases of death that are not related to congenital impairments. All results are based on published data, and the data are presented as a supplement.

This dataset explores the child's finalization age at adoption by state. The ages are grouped as under 1, 1-5, 6-10, 11-15, 16-18, 19 and older. This dataset is from October 2005 - September 2006 (Fiscal year 2006).

These statistics are derived from two data sources: the Maternity Indicators dataset where a mother’s intention to breastfeed prior to birth is recorded and the National Community Child Health Database (NCCHD) where data for breastfeeding at birth and for babies turning 10 days, 6 weeks and 6 months is recorded and refers to records where there was any breastfeeding. Both data sources are provided to the Welsh Government by Digital Health and Care Wales (DHCW). The Maternity Indicators dataset was established in 2016. It combines records from a mother’s initial assessment with a child’s birth record and enables Welsh Government to monitor its initial set of outcome indicators and performance measures (Maternity Indicators). These were established to measure the effectiveness and quality of Welsh maternity services. The Maternity Indicators dataset allows us to analyse characteristics of the mother’s pregnancy and birth process, of which ‘intention to breastfeed’ is one. The process for producing this data is complex largely because there can be multiple initial assessment data and records for both initial assessments and births are not always complete. The NCCHD was established in 2004 and consists of anonymised records for all children born, resident or treated in Wales and born after 1987. The database brings together data from local Community Child Health System databases which are held by local health boards (LHBs), and its main function is to provide an online record of a child’s health and care from birth to leaving school age. The statistics used in this release are based on the data recorded at birth and shortly after birth. Full details of every data item available on both the Maternity Indicators dataset and National Community Child Health Database are available through the NHS Wales Data Dictionary: http://www.datadictionary.wales.nhs.uk/#!WordDocuments/datasetstructure20.htm

Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases among people who received additional or booster doses were reported from 31 jurisdictions; 30 jurisdictions also reported data on deaths among people who received one or more additional or booster dose; 28 jurisdictions reported cases among people who received two or more additional or booster doses; and 26 jurisdictions reported deaths among people who received two or more additional or booster doses. This list will be updated as more jurisdictions participate. Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6 months through 1 year, half of the single-year population counts for ages 0 through 1 year were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred. For the primary series analysis, age-standardized rates include ages 12 years and older from April 4, 2021 through December 4, 2021, ages 5 years and older from December 5, 2021 through July 30, 2022 and ages 6 months and older from July 31, 2022 onwards. For the booster dose analysis, age-standardized rates include ages 18 years and older from September 19, 2021 through December 25, 2021, ages 12 years and older from December 26, 2021, and ages 5 years and older from June 5, 2022 onwards. Small numbers could contribute to less precision when calculating death rates among some groups. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage. Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated with a primary series either overall or with a booster dose. Publications: Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290. Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138

Note: Data elements were retired from HERDS on 10/6/23 and this dataset was archived.

This dataset includes the cumulative number and percent of healthcare facility-reported fatalities for patients with lab-confirmed COVID-19 disease by reporting date and age group. This dataset does not include fatalities related to COVID-19 disease that did not occur at a hospital, nursing home, or adult care facility. The primary goal of publishing this dataset is to provide users with information about healthcare facility fatalities among patients with lab-confirmed COVID-19 disease.

The information in this dataset is also updated daily on the NYS COVID-19 Tracker at https://www.ny.gov/covid-19tracker.

The data source for this dataset is the daily COVID-19 survey through the New York State Department of Health (NYSDOH) Health Electronic Response Data System (HERDS). Hospitals, nursing homes, and adult care facilities are required to complete this survey daily. The information from the survey is used for statewide surveillance, planning, resource allocation, and emergency response activities. Hospitals began reporting for the HERDS COVID-19 survey in March 2020, while Nursing Homes and Adult Care Facilities began reporting in April 2020. It is important to note that fatalities related to COVID-19 disease that occurred prior to the first publication dates are also included.

The fatality numbers in this dataset are calculated by assigning age groups to each patient based on the patient age, then summing the patient fatalities within each age group, as of each reporting date. The statewide total fatality numbers are calculated by summing the number of fatalities across all age groups, by reporting date. The fatality percentages are calculated by dividing the number of fatalities in each age group by the statewide total number of fatalities, by reporting date. The fatality numbers represent the cumulative number of fatalities that have been reported as of each reporting date.

Number of deaths and age-specific mortality rates for selected grouped causes, by age group and sex, 2000 to most recent year.

Time series data for the statistic Number of under-five deaths, female and country Netherlands. Indicator Definition:Number of female children dying before reaching age five.The indicator "Number of under-five deaths, female" stands at 0.296 Thousand as of 12/31/2023, the lowest value at least since 12/31/1961, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -3.90 percent compared to the value the year prior.The 1 year change in percent is -3.90.The 3 year change in percent is -1.99.The 5 year change in percent is -2.31.The 10 year change in percent is -8.36.The Serie's long term average value is 0.827 Thousand. It's latest available value, on 12/31/2023, is 64.20 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2023, to it's latest available value, on 12/31/2023, is +0.0%.The Serie's change in percent from it's maximum value, on 12/31/1960, to it's latest available value, on 12/31/2023, is -85.86%.

The 2008 Sierra Leone Demographic and Health Survey (SLDHS) is the first DHS survey to be held in Sierra Leone. Teams visited 353 sample points across Sierra Leone and collected data from a nationally representative sample of 7,374 women age 15-49 and 3,280 men age 15-59. The primary purpose of the 2008 SLDHS is to provide policy-makers and planners with detailed information on Demography and health. This is the first Demographic and Health Survey conducted in Sierra Leone and was carried out by Statistics Sierra Leone (SSL) in collaboration with the Ministry of Health and Sanitation. The 2008 SLDHS was funded by the Sierra Leone government, UNFPA, UNDP, UNICEF, DFID, USAID, and The World Bank. WHO, WFP and UNHCR provided logistical support. ICF Macro, an ICF International Company, provided technical support for the survey through the MEASURE DHS project. MEASURE DHS is sponsored by the United States Agency for International Development (USAID) to assist countries worldwide in obtaining information on key population and health indicators. The purpose of the SLDHS is to collect national- and regional-level data on fertility and contraceptive use, marriage and sexual activity, fertility preferences, breastfeeding practices, nutritional status of women and young children, childhood and adult mortality, maternal and child health, female genital cutting, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections, adult health, and other issues. The survey obtained detailed information on these topics from women of reproductive age and, for certain topics, from men as well. The 2008 SLDHS was carried out from late April 2008 to late June 2008, using a nationally representative sample of 7,758 households. The survey results are intended to assist policymakers and planners in assessing the current health and population programmes and in designing new strategies for improving reproductive health and health services in Sierra Leone. MAIN RESULTS FERTILITY Survey results indicate that there has been little or no decline in the total fertility rate over the past two decades, from 5.7 children per woman in 1980-85 to 5.1 children per woman for the three years preceding the 2008 SLDHS (approximately 2004-07). Fertility is lower in urban areas than in rural areas (3.8 and 5.8 children per woman, respectively). Regional variations in fertility are marked, ranging from 3.4 births per woman in the Western Region (where the capital, Freetown, is located) to almost six births per woman in the Northern and Eastern regions. Women with no education give birth to almost twice as many children as women who have been to secondary school (5.8 births, compared with 3.1 births). Fertility is also closely associated with household wealth, ranging from 3.2 births among women in the highest wealth quintile to 6.3 births among women in the lowest wealth quintile, a difference of more than three births. Research has demonstrated that children born too close to a previous birth are at increased risk of dying. In Sierra Leone, only 18 percent of births occur within 24 months of a previous birth. The interval between births is relatively long; the median interval is 36 months. FAMILY PLANNING The vast majority of Sierra Leonean women and men know of at least one method of contraception. Contraceptive pills and injectables are known to about 60 percent of currently married women and 49 percent of married men. Male condoms are known to 58 percent of married women and 80 percent of men. A higher proportion of respondents reported knowing a modern method of family planning than a traditional method. About one in five (21 percent) currently married women has used a contraceptive method at some time-19 percent have used a modern method and 6 percent have used a traditional method. However, only about one in twelve currently married women (8 percent) is currently using a contraceptive method. Modern methods account for almost all contraceptive use, with 7 percent of married women reporting use of a modern method, compared with only 1 percent using a traditional method. Injectables and the pill are the most widely used methods (3 and 2 percent of married women, respectively), followed by LAM and male condoms (less than 1 percent each). CHILD HEALTH Examination of levels of infant and child mortality is essential for assessing population and health policies and programmes. Infant and child mortality rates are also used as indices reflecting levels of poverty and deprivation in a population. The 2008 survey data show that over the past 15 years, infant and under-five mortality have decreased by 26 percent. Still, one in seven Sierra Leonean children dies before reaching age five. For the most recent five-year period before the survey (approximately calendar years 2003 to 2008), the infant mortality rate was 89 deaths per 1,000 live births and the under-five mortality rate was 140 deaths per 1,000 live births. The neonatal mortality rate was 36 deaths per 1,000 live births and the post-neonatal mortality rate was 53 deaths per 1,000 live births. The child mortality rate was 56 deaths per 1,000 children surviving to age one year. Mortality rates at all ages of childhood show a strong relationship with the length of the preceding birth interval. Under-five mortality is three times higher among children born less than two years after a preceding sibling (252 deaths per 1,000 births) than among children born four or more years after a previous child (deaths 81 per 1,000 births). MATERNAL HEALTH Almost nine in ten mothers (87 percent) in Sierra Leone receive antenatal care from a health professional (doctor, nurse, midwife, or MCH aid). Only 5 percent of mothers receive antenatal care from a traditional midwife or a community health worker; 7 percent of mothers do not receive any antenatal care. In Sierra Leone, over half of mothers have four or more antenatal care (ANC) visits, about 20 percent have one to three ANC visits, and only 7 percent have no antenatal care at all. The survey shows that not all women in Sierra Leone receive antenatal care services early in pregnancy. Only 30 percent of mothers obtain antenatal care in the first three months of pregnancy, 41 percent make their first visit in the fourth or fifth month, and 17 percent in have their first visit in the sixth or seventh month. Only 1 percent of women have their first ANC visit in their eighth month of pregnancy or later. BREASTFEEDING AND NUTRITION Poor nutritional status is one of the most important health and welfare problems facing Sierra Leone today and particularly afflicts women and children. The data show that 36 percent of children under five are stunted (too short for their age) and 10 percent of children under five are wasted (too thin for their height). Overall, 21 percent of children are underweight, which may reflect stunting, wasting, or both. For women, at the national level 11 percent of women are considered to be thin (body mass index

Time series data for the statistic Number of under-five deaths, female and country Peru. Indicator Definition:Number of female children dying before reaching age five.The indicator "Number of under-five deaths, female" stands at 3.76 Thousand as of 12/31/2023, the lowest value at least since 12/31/1961, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -2.39 percent compared to the value the year prior.The 1 year change in percent is -2.39.The 3 year change in percent is -5.77.The 5 year change in percent is -6.89.The 10 year change in percent is -18.17.The Serie's long term average value is 23.58 Thousand. It's latest available value, on 12/31/2023, is 84.06 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2023, to it's latest available value, on 12/31/2023, is +0.0%.The Serie's change in percent from it's maximum value, on 12/31/1970, to it's latest available value, on 12/31/2023, is -92.69%.

This dataset explores the prior relationship of adoptive parents to their adoptee children during fiscal year 2006 (from October 1, 2005 to September 30, 2006). *The data from Maryland, Nebraska, New York, Ohio, Rhode Island and Washington was questionable due to the large percentage of missing data. *Iowa does not track non-welfare stepparent adoptions. Law defines relative as the fourth degree of consanguinity. *Nebraska includes great aunt/uncle, great grandparent, great great great grandparent, great great aunt/uncle, great great great grandparent, great great great aunt/uncle, adoptive sibling, biological sibling, first and second cousins, grandparent, parent-in-law, aunt/uncle. Fictive kin (ie. Godparents) are not included.