Southern Asia had almost ************ deaths among children under age * in the year 1990. This number had decreased to around ************ deaths by the year 2022. The statistic shows the number of deaths among children under age five worldwide from 1990 to 2022, by region.

Germany DE: Number of Deaths Ages 5-14 Years data was reported at 535.000 Person in 2018. This records a decrease from the previous number of 577.000 Person for 2015. Germany DE: Number of Deaths Ages 5-14 Years data is updated yearly, averaging 692.000 Person from Dec 1990 (Median) to 2018, with 5 observations. The data reached an all-time high of 1,597.000 Person in 1990 and a record low of 535.000 Person in 2018. Germany DE: Number of Deaths Ages 5-14 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Health Statistics. Number of deaths of children ages 5-14 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; 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.

Child Death Rate (deaths per 100,000 children ages 114) is the number of deaths to children between ages 1 and 14, from all causes, per 100,000 children in this age range. The data are reported by place of residence, not place of death. SOURCES: * Death Statistics: U.S. Centers for Disease Control and Prevention, National Center for Health Statistics. * Population Statistics: U.S. Census Bureau.

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 dataset of U.S. mortality trends since 1900 highlights childhood mortality rates by age group for age at death. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Age groups for childhood death rates are based on age at death. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

Greece GR: Number of Deaths Ages 5-14 Years data was reported at 114.000 Person in 2017. This records a decrease from the previous number of 118.000 Person for 2015. Greece GR: Number of Deaths Ages 5-14 Years data is updated yearly, averaging 128.000 Person from Dec 1990 (Median) to 2017, with 5 observations. The data reached an all-time high of 276.000 Person in 1990 and a record low of 114.000 Person in 2017. Greece GR: Number of Deaths Ages 5-14 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Greece – Table GR.World Bank.WDI: Health Statistics. Number of deaths of children ages 5-14 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum;

Sweden SE: Number of Death: Under-5 data was reported at 342.000 Person in 2017. This records an increase from the previous number of 341.000 Person for 2016. Sweden SE: Number of Death: Under-5 data is updated yearly, averaging 752.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2,112.000 Person in 1960 and a record low of 337.000 Person in 2013. Sweden SE: Number of Death: Under-5 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. Number of children dying before reaching age five.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum;

In 2022, the leading causes of death for children aged one to four years in the United States were unintentional injuries and congenital malformations, deformations, and chromosomal abnormalities. At that time, around 31 percent of all deaths among these children were caused by unintentional injuries. Differences in causes of death among children by age Just as unintentional injuries are the leading cause of death among children aged one to four, it is also the leading cause of death for the age groups five to nine and 10 to 14. However, congenital malformations, deformations, and chromosomal abnormalities account for fewer deaths as children become older, while the share of deaths caused by cancer is higher among those aged five to nine and 10 to 14. In fact, cancer is the second leading cause of death among five to nine-year-olds, accounting for around 15 percent of all deaths. Sadly, the second leading cause of death among children aged 10 to 14 is intentional self-harm, with 13 percent of all deaths among those in this age group caused by suicide. Leading causes of death in the United States The leading causes of death in the United States are heart disease and malignant neoplasms. Together, these two diseases accounted for around 40 percent of all deaths in the United States in 2022. That year, COVID-19 was the fourth leading cause of death, with about six percent of all deaths caused by COVID-19. In 2022, the lifetime odds that the average person in the United States would die from heart disease was one in six, while the odds for cancer were one in seven and for COVID-19 one in 23.

The USA: Deaths of children under five years of age per 1000 live births: The latest value from 2022 is 6 deaths per 1000 births, unchanged from 6 deaths per 1000 births in 2021. In comparison, the world average is 25 deaths per 1000 births, based on data from 187 countries. Historically, the average for the USA from 1960 to 2022 is 14 deaths per 1000 births. The minimum value, 6 deaths per 1000 births, was reached in 2020 while the maximum of 30 deaths per 1000 births was recorded in 1960.

Finland FI: Number of Deaths Ages 5-9 Years data was reported at 20.000 Person in 2019. This records a decrease from the previous number of 21.000 Person for 2018. Finland FI: Number of Deaths Ages 5-9 Years data is updated yearly, averaging 36.000 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 63.000 Person in 1990 and a record low of 20.000 Person in 2019. Finland FI: Number of Deaths Ages 5-9 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Finland – Table FI.World Bank.WDI: Health Statistics. Number of deaths of children ages 5-9 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; 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.

Background: The reduction of child and adolescent deaths (defined as decedents aged 0–19 years) remains a crucial public health priority also in high-income countries such as Finland. There is evidence of a relationship between socioeconomic gradients and child mortality, but the association is considered complex and relatively poorly understood. Exploiting a Finnish dataset with nationwide coverage, the present study aimed to shed light on the sociodemographic predictors of child and adolescent mortality at the municipality level.Methods: A public database of Statistics Finland was queried for municipality-level data on sociodemographic traits and child and adolescent deaths in Finland during the years 2011–2018. The sociodemographic indicators included total population size, child and adolescent population size, sex distribution, mean age, education, unemployment, median income, population density, rurality, percentage of individuals living in their birth municipality, household size, overcrowded households, foreign language speakers, divorce rate, car ownership rate, and crime rate. The sociodemographic indicators were modeled against child and adolescent mortality by means of generalized estimating equations.Results: A total of 2,371 child and adolescent deaths occurred during the 8-year study period, yielding an average annual mortality rate of 26.7 per 100,000 individuals. Despite a fluctuating trend, the average annual decline in child and adolescent deaths was estimated to be 3% (95% confidence interval 1–5%). Of the sociodemographic indicators, population density was associated with higher child and adolescent mortality (rate ratio 1.03, 95% confidence interval 1.01–1.06), whereas the percentage of foreign language speakers was associated with lower child and adolescent mortality (0.96, 0.93–0.99).Conclusion: Densely populated areas should be the primary focus of efforts to reduce child and adolescent mortality. Of note is also the apparently protective effect of foreign language speakers for premature mortality. Future studies are welcomed to scrutinize the mediating pathways and individual-level factors behind the associations detected in this study.

This table contains data on mortality among children up to the age of 5 in the Netherlands, according to various characteristics. In this table, the data can be broken down into the following characteristics: - Stillbirths by gestational age, gender, mother married or unmarried, ranking number from the mother, single or multiple births, cause of death and mother's age; - Child mortality by gestational age, sex and age of the child; - Cause of death in stillbirths; - Cause of death in 0-year-olds; - Cause of death in 1 to 5 year olds. Data available from 1996 to 2014. Status of the figures: All figures included in the table are final. Changes as of March 31, 2016: None, this table has been discontinued. Changes as of March 22, 2016: The figures for 2013 (causes of death) and 2014 have been added. The total number of child deaths in the perinatal mortality 24+ and 28+ has been corrected for the years 1996 and 1997. For the year 1996 the difference is +7 and for the year 1997 +1. These corrections do not affect the other figures in the table. When will new numbers come out? Not applicable anymore. The information from this table is largely continued in a number of other tables. See section 3.

In 2022, the leading causes of death among children and adolescents in the United States aged 10 to 14 were unintentional injuries, intentional self-harm (suicide), and cancer. That year, unintentional injuries accounted for around 25 percent of all deaths among this age group. Leading causes of death among older teens Like those aged 10 to 14 years, the leading cause of death among older teenagers in the U.S. aged 15 to 19 years is unintentional injuries. In 2022, unintentional injuries accounted for around 37 percent of all deaths among older teens. However, unlike those aged 10 to 14, the second leading cause of death among teens aged 15 to 19 is assault or homicide. Sadly, the third leading cause of death among this age group is suicide, making suicide among the leading three causes of death for both age groups. Teen suicide Suicide remains a major problem among teenagers in the United States, as reflected in the leading causes of death among this age group. It was estimated that in 2021, around 22 percent of high school students in the U.S. considered attempting suicide in the past year, with this rate twice as high for girls than for boys. The states with the highest death rates due to suicide among adolescents aged 15 to 19 years are Montana, South Dakota, and New Mexico. In 2022, the death rate from suicide among this age group in Montana was 39 per 100,000 population. In comparison, New York, the state with the lowest rate, had just five suicide deaths among those aged 15 to 19 years per 100,000 population.

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.

In 2023, there were *** instances of death recorded among children under the age of five in Sweden, the lowest annual figure in the provided time interval. In general, the number of deaths has declined since the beginning of the provided time interval.

This table includes key figures on mortality in the Dutch population broken down by gender. The figures include totals and ratios of deceased persons, infant mortality, mortality in babies younger than 4 weeks and perinatal mortality (after a gestation period of 24 weeks or more and after a gestation period of 28 weeks or more). The table also presents figures on life expectancy at birth and average age at death. For additional information on Mortality the reader is referred to the Dutch tables. Data available from: 1950 Status of the figures: All data recorded in this publication are final data. The 2023 figures on stillbirths and (multiple) births are provisional, the other figures in the table are final. Changes as of 9 December 2024: The provisional figures on the number of live births and stillbirths do not include children who were born at a gestational age that is unknown. These cases were included in the final figures for previous years. However, the 2023 data shows a larger number of children born at an unknown gestational age than in previous years. Based on an internal analysis for 2022, it appears that in the majority of cases involving an unknown gestational age, the child was born at less than 24 weeks. To ensure that the provisional 2023 figures do not overestimate the number of stillborn children born at a gestational age of over 24 weeks, children born at an unknown gestational age have now been excluded. When will new figures be published? Final 2023 figures on the number of stillbirths and the number of births are expected to be added to the table in de third quarter of 2025. In the third quarter of 2025 final figures of 2024 will be published in this publication.

BackgroundDespite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In sub-Saharan Africa (SSA), the Millennium Development Goals (MDGs) for child mortality were met only by a few countries. Valid concerns exist as to whether the region would meet new Sustainable Development Goals (SDGs) for under-5 mortality. We therefore examine further sources of variation by assessing age patterns, trends, and forecasts of mortality rates.Methods and findingsData came from 106 nationally representative Demographic and Health Surveys (DHSs) with full birth histories from 31 SSA countries from 1990 to 2017 (a total of 524 country-years of data). We assessed the distribution of age at death through the following new demographic analyses. First, we used a direct method and full birth histories to estimate under-5 mortality rates (U5MRs) on a monthly basis. Second, we smoothed raw estimates of death rates by age and time by using a two-dimensional P-Spline approach. Third, a variant of the Lee–Carter (LC) model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) to adjust, validate, and minimize the risk of bias in survival, truncation, and recall in mortality estimation. Our mortality model revealed substantive declines of death rates at every age in most countries but with notable differences in the age patterns over time. U5MRs declined from 3.3% (annual rate of reduction [ARR] 0.1%) in Lesotho to 76.4% (ARR 5.2%) in Malawi, and the pace of decline was faster on average (ARR 3.2%) than that observed for infant (IMRs) (ARR 2.7%) and neonatal (NMRs) (ARR 2.0%) mortality rates. We predict that 5 countries (Kenya, Rwanda, Senegal, Tanzania, and Uganda) are on track to achieve the under-5 sustainable development target by 2030 (25 deaths per 1,000 live births), but only Rwanda and Tanzania would meet both the neonatal (12 deaths per 1,000 live births) and under-5 targets simultaneously. Our predicted NMRs and U5MRs were in line with those estimated by the UN IGME by 2030 and 2050 (they overlapped in 27/31 countries for NMRs and 22 for U5MRs) and by the Institute for Health Metrics and Evaluation (IHME) by 2030 (26/31 and 23/31, respectively). This study has a number of limitations, including poor data quality issues that reflected bias in the report of births and deaths, preventing reliable estimates and predictions from a few countries.ConclusionsTo our knowledge, this study is the first to combine full birth histories and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in SSA. We demonstrate that countries with a rapid pace of mortality reduction (ARR ≥ 3.2%) across ages would be more likely to achieve the SDG mortality targets. However, the lower pace of neonatal mortality reduction would prevent most countries from achieving those targets: 2 countries would reach them by 2030, 13 between 2030 and 2050, and 13 after 2050.

*All children in the cohort were aged 12 years or older at the time of ascertainment of deaths in 2007, thus losses from follow-up at younger ages were due to death or censoring alive on the date last seen (as recorded in hospital case notes). Between 12 and 15 years there are fewer children under follow-up (‘at risk’) in the older age groups as many children had not reached these ages and this reduced the precision of survival estimates after 12 years.Number of children dying or last seen (censored) during each year of follow-up.

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.