51 datasets found
  1. Life expectancy by continent and gender 2024

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Life expectancy by continent and gender 2024 [Dataset]. https://www.statista.com/statistics/270861/life-expectancy-by-continent/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    In 2024, the average life expectancy in the world was 71 years for men and 76 years for women. The lowest life expectancies were found in Africa, while Oceania and Europe had the highest. What is life expectancy?Life expectancy is defined as a statistical measure of how long a person may live, based on demographic factors such as gender, current age, and most importantly the year of their birth. The most commonly used measure of life expectancy is life expectancy at birth or at age zero. The calculation is based on the assumption that mortality rates at each age were to remain constant in the future. Life expectancy has changed drastically over time, especially during the past 200 years. In the early 20th century, the average life expectancy at birth in the developed world stood at 31 years. It has grown to an average of 70 and 75 years for males and females respectively, and is expected to keep on growing with advances in medical treatment and living standards continuing. Highest and lowest life expectancy worldwide Life expectancy still varies greatly between different regions and countries of the world. The biggest impact on life expectancy is the quality of public health, medical care, and diet. As of 2022, the countries with the highest life expectancy were Japan, Liechtenstein, Switzerland, and Australia, all at 84–83 years. Most of the countries with the lowest life expectancy are mostly African countries. The ranking was led by the Chad, Nigeria, and Lesotho with 53–54 years.

  2. Global life expectancy from birth in selected regions 1820-2020

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Global life expectancy from birth in selected regions 1820-2020 [Dataset]. https://www.statista.com/statistics/1302736/global-life-expectancy-by-region-country-historical/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Africa, Asia, LAC, North America, Europe
    Description

    A global phenomenon, known as the demographic transition, has seen life expectancy from birth increase rapidly over the past two centuries. In pre-industrial societies, the average life expectancy was around 24 years, and it is believed that this was the case throughout most of history, and in all regions. The demographic transition then began in the industrial societies of Europe, North America, and the West Pacific around the turn of the 19th century, and life expectancy rose accordingly. Latin America was the next region to follow, before Africa and most Asian populations saw their life expectancy rise throughout the 20th century.

  3. World: annual birth rate, death rate, and rate of natural population change...

    • statista.com
    Updated Jul 28, 2025
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    Statista (2025). World: annual birth rate, death rate, and rate of natural population change 1950-2100 [Dataset]. https://www.statista.com/statistics/805069/death-rate-worldwide/
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    Dataset updated
    Jul 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    The COVID-19 pandemic increased the global death rate, reaching *** in 2021, but had little to no significant impact on birth rates, causing population growth to dip slightly. On a global level, population growth is determined by the difference between the birth and death rates, known as the rate of natural change. On a national or regional level, migration also affects population change. Ongoing trends Since the middle of the 20th century, the global birth rate has been well above the global death rate; however, the gap between these figures has grown closer in recent years. The death rate is projected to overtake the birth rate in the 2080s, which means that the world's population will then go into decline. In the future, death rates will increase due to ageing populations across the world and a plateau in life expectancy. Why does this change? There are many reasons for the decline in death and birth rates in recent decades. Falling death rates have been driven by a reduction in infant and child mortality, as well as increased life expectancy. Falling birth rates were also driven by the reduction in child mortality, whereby mothers would have fewer children as survival rates rose - other factors include the drop in child marriage, improved contraception access and efficacy, and women choosing to have children later in life.

  4. Child mortality in the United States 1800-2020

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Child mortality in the United States 1800-2020 [Dataset]. https://www.statista.com/statistics/1041693/united-states-all-time-child-mortality-rate/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1800 - 2020
    Area covered
    United States
    Description

    The child mortality rate in the United States, for children under the age of five, was 462.9 deaths per thousand births in 1800. This means that for every thousand babies born in 1800, over 46 percent did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, and the rate has dropped to its lowest point ever in 2020 where it is just seven deaths per thousand births. Although the child mortality rate has decreased greatly over this 220 year period, there were two occasions where it increased; in the 1870s, as a result of the fourth cholera pandemic, smallpox outbreaks, and yellow fever, and in the late 1910s, due to the Spanish Flu pandemic.

  5. d

    IPCC Climate Change Data: NIES99 A1t Model: 2080 Radiance

    • dataone.org
    • knb.ecoinformatics.org
    Updated Aug 14, 2015
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    Intergovernmental Panel on Climate Change (IPCC) (2015). IPCC Climate Change Data: NIES99 A1t Model: 2080 Radiance [Dataset]. http://doi.org/10.5063/AA/dpennington.306.1
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    Dataset updated
    Aug 14, 2015
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    Intergovernmental Panel on Climate Change (IPCC)
    Time period covered
    Jan 1, 2080 - Dec 31, 2080
    Area covered
    Earth
    Description

    The model used here is a coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model (Abe-Ouchi et al., 1996). The spatial resolution is T21 spectral truncation (roughly 5.6 degrees latitude/longitude) and 20 vertical levels for the atmospheric part, and roughly 2.8 degrees horizontal grid and 17 vertical levels for the oceanic part. Flux adjustment for atmosphere-ocean heat and water exchange is applied to prevent a drift of the modelled climate. The atmospheric model adopts a radiation scheme based on the k-distribution, two-stream discrete ordinate method (DOM) (Nakajima and Tanaka, 1986). This scheme can deal with absorption, emission and scattering by gases, clouds and aerosol particles in a consistent manner. In the calculation of sulphate aerosol optical properties, the volumetric mode radius of the sulphate particle in dry environment is assumed to be 0.2 micron. The hygroscopic growth of the sulphate is considered by an empirical fit of d'Almeida et al. (1991). The vertical distribution of the sulphate aerosol is assumed to be constant in the lowest 2 km of the atmosphere. The concentrations of greenhouse gases are represented by equivalent-CO2. Three integrations are made for 200 model years (1890-2090). In the control experiment (CTL), the globally uniform concentration of greenhouse gases is kept constant at 345 ppmv CO2-equivalent and the concentration of sulphate is set to zero. In the experiment GG, the concentration of greenhouse gases is gradually increased, while that of sulphate is set to zero. In the experiments GS, the increase in anthropogenic sulphate as well as that in greenhouse gases is given and the aerosol scattering (the direct effect of aerosol) is explicitly represented in the way described above. The indirect effect of aerosol is not included in any experiment. The scenario of atmospheric concentrations of greenhouse gases and sulphate aerosols is given in accordance with Mitchell and Johns (1997). The increase in greenhouse gases is based on the historical record from 1890 to 1990 and is increased by 1 percent / yr (compound) after 1990. For sulphate aerosols, geographical distributions of sulphate loading for 1986 and 2050, which are estimated by a sulphur cycle model (Langer and Rodhe, 1991), are used as basic patterns. Based on global and annual mean sulphur emission rates, the 1986 pattern is scaled for years before 1990; the 2050 pattern is scaled for years after 2050; and the pattern is interpolated from the two basic ones for intermediate years to give the time series of the distribution. The sulphur emission rate in the future is based on the IPCC IS92a scenario. The sulphate concentration is offset in our run so that it starts from zero at 1890. The seasonal variation of sulphate concentration is ignored. Discussion on the results of the experiments will be found in Emori et al. (1999). Climate sensitivity of the CCSR/NIES model derived by equilibrium runs is estimated to be 3.5 degrees Celsius. Global-Mean Temperature, Precipitation and CO2 Changes (w.r.t. 1961-90) for the CCSR/NIES model. From the IPCC website: The A1 Family storyline is a case of rapid and successful economic development, in which regional averages of income per capita converge - current distinctions between poor and rich countries eventually dissolve. In this scenario family, demographic and economic trends are closely linked, as affluence is correlated with long life and small families (low mortality and low fertility). Global population grows to some nine billion by 2050 and declines to about seven billion by 2100. Average age increases, with the needs of retired people met mainly through their accumulated savings in private pension systems. The global economy expands at an average annual rate of about three percent to 2100. This is approximately the same as average global growth since 1850, although the conditions that lead to a global economic in productivity and per capita incomes are unparalleled in history. Income per capita reaches about US$21,000 by 2050. While the high average level of income per capita contributes to a great improvement in the overall health and social conditions of the majority of people, this world is not without its problems. In particular, many communities could face some of the problems of social exclusion encountered by the wealthiest countries in the 20th century and in many places income growth could come with increased pressure on the global commons. Energy and mineral resources are abundant in this scenario family because of rapid technical progress, which both reduce the resources need to produce a given level of output and increases the economically recoverable reserves. Final energy intensity (energy use per unit of GDP) decreases at a... Visit https://dataone.org/datasets/doi%3A10.5063%2FAA%2Fdpennington.306.1 for complete metadata about this dataset.

  6. o

    Global, Regional, And National Under-5 Mortality, Adult Mortality,...

    • explore.openaire.eu
    Updated Jan 1, 2017
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    Haidong Wang; Amanuel Alemu Abajobir; Kalkidan Hassen Abate; Burcu Küçük Biçer (2017). Global, Regional, And National Under-5 Mortality, Adult Mortality, Age-Specific Mortality, And Life Expectancy, 1970-2016: A Systematic Analysis For The Global Burden Of Disease Study 2016 [Dataset]. https://explore.openaire.eu/search/other?orpId=od_4268::9ad8f2b350836bbb05bbd2b5e29d6abb
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    Dataset updated
    Jan 1, 2017
    Authors
    Haidong Wang; Amanuel Alemu Abajobir; Kalkidan Hassen Abate; Burcu Küçük Biçer
    Description

    Background Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. Methods We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0.5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Sociodemographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. Findings Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86.9 years (95% UI 86.7-87.2), and for men in Singapore, at 81.3 years (78.8-83.7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap be...

  7. d

    IPCC Climate Change Data: NIES99 A1f Model: 2020 Minimum Temperature

    • dataone.org
    • knb.ecoinformatics.org
    Updated Aug 14, 2015
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    Intergovernmental Panel on Climate Change (IPCC) (2015). IPCC Climate Change Data: NIES99 A1f Model: 2020 Minimum Temperature [Dataset]. http://doi.org/10.5063/AA/dpennington.294.1
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    Dataset updated
    Aug 14, 2015
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    Intergovernmental Panel on Climate Change (IPCC)
    Time period covered
    Jan 1, 2020 - Dec 31, 2020
    Area covered
    Earth
    Description

    The model used here is a coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model (Abe-Ouchi et al., 1996). The spatial resolution is T21 spectral truncation (roughly 5.6 degrees latitude/longitude) and 20 vertical levels for the atmospheric part, and roughly 2.8 degrees horizontal grid and 17 vertical levels for the oceanic part. Flux adjustment for atmosphere-ocean heat and water exchange is applied to prevent a drift of the modelled climate. The atmospheric model adopts a radiation scheme based on the k-distribution, two-stream discrete ordinate method (DOM) (Nakajima and Tanaka, 1986). This scheme can deal with absorption, emission and scattering by gases, clouds and aerosol particles in a consistent manner. In the calculation of sulphate aerosol optical properties, the volumetric mode radius of the sulphate particle in dry environment is assumed to be 0.2 micron. The hygroscopic growth of the sulphate is considered by an empirical fit of d'Almeida et al. (1991). The vertical distribution of the sulphate aerosol is assumed to be constant in the lowest 2 km of the atmosphere. The concentrations of greenhouse gases are represented by equivalent-CO2. Three integrations are made for 200 model years (1890-2090). In the control experiment (CTL), the globally uniform concentration of greenhouse gases is kept constant at 345 ppmv CO2-equivalent and the concentration of sulphate is set to zero. In the experiment GG, the concentration of greenhouse gases is gradually increased, while that of sulphate is set to zero. In the experiments GS, the increase in anthropogenic sulphate as well as that in greenhouse gases is given and the aerosol scattering (the direct effect of aerosol) is explicitly represented in the way described above. The indirect effect of aerosol is not included in any experiment. The scenario of atmospheric concentrations of greenhouse gases and sulphate aerosols is given in accordance with Mitchell and Johns (1997). The increase in greenhouse gases is based on the historical record from 1890 to 1990 and is increased by 1 percent / yr (compound) after 1990. For sulphate aerosols, geographical distributions of sulphate loading for 1986 and 2050, which are estimated by a sulphur cycle model (Langer and Rodhe, 1991), are used as basic patterns. Based on global and annual mean sulphur emission rates, the 1986 pattern is scaled for years before 1990; the 2050 pattern is scaled for years after 2050; and the pattern is interpolated from the two basic ones for intermediate years to give the time series of the distribution. The sulphur emission rate in the future is based on the IPCC IS92a scenario. The sulphate concentration is offset in our run so that it starts from zero at 1890. The seasonal variation of sulphate concentration is ignored. Discussion on the results of the experiments will be found in Emori et al. (1999). Climate sensitivity of the CCSR/NIES model derived by equilibrium runs is estimated to be 3.5 degrees Celsius. Global-Mean Temperature, Precipitation and CO2 Changes (w.r.t. 1961-90) for the CCSR/NIES model. From the IPCC website: The A1 Family storyline is a case of rapid and successful economic development, in which regional averages of income per capita converge - current distinctions between poor and rich countries eventually dissolve. In this scenario family, demographic and economic trends are closely linked, as affluence is correlated with long life and small families (low mortality and low fertility). Global population grows to some nine billion by 2050 and declines to about seven billion by 2100. Average age increases, with the needs of retired people met mainly through their accumulated savings in private pension systems. The global economy expands at an average annual rate of about three percent to 2100. This is approximately the same as average global growth since 1850, although the conditions that lead to a global economic in productivity and per capita incomes are unparalleled in history. Income per capita reaches about US$21,000 by 2050. While the high average level of income per capita contributes to a great improvement in the overall health and social conditions of the majority of people, this world is not without its problems. In particular, many communities could face some of the problems of social exclusion encountered by the wealthiest countries in the 20th century and in many places income growth could come with increased pressure on the global commons. Energy and mineral resources are abundant in this scenario family because of rapid technical progress, which both reduce the resources need to produce a given level of output and increases the economically recoverable reserves. Final energy intensity (energy use per unit of GDP) decreases at a... Visit https://dataone.org/datasets/doi%3A10.5063%2FAA%2Fdpennington.294.1 for complete metadata about this dataset.

  8. e

    IPCC Climate Change Data: NIES99 A1f Model: 2080 Mean Temperature

    • knb.ecoinformatics.org
    • dataone.org
    Updated Jan 6, 2015
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    Intergovernmental Panel on Climate Change (IPCC) (2015). IPCC Climate Change Data: NIES99 A1f Model: 2080 Mean Temperature [Dataset]. http://doi.org/10.5063/AA/dpennington.297.1
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    Dataset updated
    Jan 6, 2015
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    Intergovernmental Panel on Climate Change (IPCC)
    Time period covered
    Jan 1, 2080 - Dec 31, 2080
    Area covered
    Earth
    Description

    The model used here is a coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model (Abe-Ouchi et al., 1996). The spatial resolution is T21 spectral truncation (roughly 5.6 degrees latitude/longitude) and 20 vertical levels for the atmospheric part, and roughly 2.8 degrees horizontal grid and 17 vertical levels for the oceanic part. Flux adjustment for atmosphere-ocean heat and water exchange is applied to prevent a drift of the modelled climate. The atmospheric model adopts a radiation scheme based on the k-distribution, two-stream discrete ordinate method (DOM) (Nakajima and Tanaka, 1986). This scheme can deal with absorption, emission and scattering by gases, clouds and aerosol particles in a consistent manner. In the calculation of sulphate aerosol optical properties, the volumetric mode radius of the sulphate particle in dry environment is assumed to be 0.2 micron. The hygroscopic growth of the sulphate is considered by an empirical fit of d'Almeida et al. (1991). The vertical distribution of the sulphate aerosol is assumed to be constant in the lowest 2 km of the atmosphere. The concentrations of greenhouse gases are represented by equivalent-CO2. Three integrations are made for 200 model years (1890-2090). In the control experiment (CTL), the globally uniform concentration of greenhouse gases is kept constant at 345 ppmv CO2-equivalent and the concentration of sulphate is set to zero. In the experiment GG, the concentration of greenhouse gases is gradually increased, while that of sulphate is set to zero. In the experiments GS, the increase in anthropogenic sulphate as well as that in greenhouse gases is given and the aerosol scattering (the direct effect of aerosol) is explicitly represented in the way described above. The indirect effect of aerosol is not included in any experiment. The scenario of atmospheric concentrations of greenhouse gases and sulphate aerosols is given in accordance with Mitchell and Johns (1997). The increase in greenhouse gases is based on the historical record from 1890 to 1990 and is increased by 1 percent / yr (compound) after 1990. For sulphate aerosols, geographical distributions of sulphate loading for 1986 and 2050, which are estimated by a sulphur cycle model (Langer and Rodhe, 1991), are used as basic patterns. Based on global and annual mean sulphur emission rates, the 1986 pattern is scaled for years before 1990; the 2050 pattern is scaled for years after 2050; and the pattern is interpolated from the two basic ones for intermediate years to give the time series of the distribution. The sulphur emission rate in the future is based on the IPCC IS92a scenario. The sulphate concentration is offset in our run so that it starts from zero at 1890. The seasonal variation of sulphate concentration is ignored. Discussion on the results of the experiments will be found in Emori et al. (1999). Climate sensitivity of the CCSR/NIES model derived by equilibrium runs is estimated to be 3.5 degrees Celsius. Global-Mean Temperature, Precipitation and CO2 Changes (w.r.t. 1961-90) for the CCSR/NIES model. From the IPCC website: The A1 Family storyline is a case of rapid and successful economic development, in which regional averages of income per capita converge - current distinctions between poor and rich countries eventually dissolve. In this scenario family, demographic and economic trends are closely linked, as affluence is correlated with long life and small families (low mortality and low fertility). Global population grows to some nine billion by 2050 and declines to about seven billion by 2100. Average age increases, with the needs of retired people met mainly through their accumulated savings in private pension systems. The global economy expands at an average annual rate of about three percent to 2100. This is approximately the same as average global growth since 1850, although the conditions that lead to a global economic in productivity and per capita incomes are unparalleled in history. Income per capita reaches about US$21,000 by 2050. While the high average level of income per capita contributes to a great improvement in the overall health and social conditions of the majority of people, this world is not without its problems. In particular, many communities could face some of the problems of social exclusion encountered by the wealthiest countries in the 20th century and in many places income growth could come with increased pressure on the global commons. Energy and mineral resources are abundant in this scenario family because of rapid technical progress, which both reduce the resources need to produce a given level of output and increases the economically recoverable reserves. Final energy intensity (energy use per unit of GDP) decreases at a... Visit https://dataone.org/datasets/doi%3A10.5063%2FAA%2Fdpennington.297.1 for complete metadata about this dataset.

  9. COVID-19 Trends for Countries

    • hub.arcgis.com
    Updated Apr 8, 2020
    + more versions
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    Urban Observatory by Esri (2020). COVID-19 Trends for Countries [Dataset]. https://hub.arcgis.com/maps/UrbanObservatory::covid-19-trends-for-countries
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    Dataset updated
    Apr 8, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center. -- Esri COVID-19 Trend Report for 3-9-2022 --0 (-0) Countries are in Emergent trend41 (-3) Countries are in Spreading trend.61 (+2) Countries are in Epidemic trend.54 (+0) Countries have Controlled trend.41 (+1) Countries have End Stage trend.Strongest spike in past two days was in US at 64,861 new cases.Strongest spike in past five days was in US at 64,861 new cases.Strongest spike in outbreak was 424 days ago in US at 1,354,505 new cases. Global Total Confirmed COVID-19 Case Rate of 8620.91 per 100,000Global Active Confirmed COVID-19 Case Rate of 37.24 per 100,000Global COVID-19 Mortality Rate of 87.69 per 100,000 21 countries with over 200 per 100,000 active cases.5 countries with over 500 per 100,000 active cases.3 countries with over 1,000 per 100,000 active cases.1 country with over 2,000 per 100,000 active cases.Nauru is worst at 4,354.54 per 100,000.See the full methodology for information about how COVID-19 Trends are produced.

  10. n

    Data from: Divergent climate change effects on widespread dryland plant...

    • data.niaid.nih.gov
    • datasetcatalog.nlm.nih.gov
    • +2more
    zip
    Updated Apr 12, 2022
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    Kyle Palmquist (2022). Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients [Dataset]. http://doi.org/10.5061/dryad.3tx95x6ht
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    zipAvailable download formats
    Dataset updated
    Apr 12, 2022
    Dataset provided by
    Marshall University
    Authors
    Kyle Palmquist
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    Plant community response to climate change will be influenced by individual plant responses that emerge from competition for limiting resources that fluctuate through time and vary across space. Projecting these responses requires an approach that integrates environmental conditions and species interactions that result from future climatic variability. Dryland plant communities are being substantially affected by climate change because their structure and function are closely tied to precipitation and temperature, yet impacts vary substantially due to environmental heterogeneity, especially in topographically complex regions. Here, we quantified the effects of climate change on big sagebrush (Artemisia tridentata Nutt.) plant communities that span 76 million ha in the western United States. We used an individual-based plant simulation model that represents intra- and inter-specific competition for water availability, which is represented by a process-based soil water balance model. For dominant plant functional types, we quantified changes in biomass and characterized agreement among 52 future climate scenarios. We then used a multivariate matching algorithm to generate fine-scale interpolated surfaces of functional type biomass for our study area. Results suggest geographically divergent responses of big sagebrush to climate change (changes in biomass of -20% to +27%), declines in perennial C3 grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C4 grasses. The largest declines in big sagebrush, perennial C3 grass and perennial forb biomass were simulated in warm, dry sites. In contrast, we simulated no change or increases in functional type biomass in cold, moist sites. There was high agreement among climate scenarios on climate change impacts to functional type biomass, except for big sagebrush. Collectively, these results suggest divergent responses to warming in moisture-limited vs. temperature-limited sites and potential shifts in the relative importance of some of the dominant functional types that result from competition for limiting resources. Methods We applied STEPWAT2, a plant community, gap dynamics model that integrates an annual time step, individual-based plant simulation model (STEPPE) and a daily, process-based soil water balance model (SOILWAT2) to understand plant community response to climate change in 200 big sagebrush plant communities. STEPWAT2 simulates establishment, competition, growth, and mortality of multiple plant species and functional types based on life-history traits and on soil water availability in multiple soil layers, which is frequently the limiting resource in dryland plant communities.We used version 1.0.0 of an R program called rSFSTEP2 (https://github.com/DrylandEcology/rSFSTEP2/releases/tag/v.1.0.0) to run STEPWAT2 simulations for all 200 sites for 300 years and 200 iterations. Simulations were conducted for 300 years because STEPWAT2 initiates with no vegetation, and it takes ~100 years for plant communities to reach a steady-state. Thus, all analyses here focus on characterizing biomass in the last 200 years after steady state conditions were reached but where biomass fluctuated due to stochastic (i.e. establishment) and deterministic (i.e. mortality due to low resource availability) processes. We simulated each site under current climatic conditions (1980-2010) and future climatic conditions derived from 13 Global Climate Models (GCMs) for representative concentration pathways RCP4.5 and RCP8.5 for both mid-century (2030-2060) and end-century (2071-2100) for a total of 52 future climate scenarios. We simulated plant communities under a light grazing regime where grazing occurred annually and was implemented by removing a fraction of the current year’s growth for each functional type. We calculated the mean biomass and density of each functional type over the last 200 years of the simulations for each site and RCP/GCM/time period combination (N = 53). This yielded 200 means (one for each site) for each functional type/RCP/GCM/time period combination (for a total of 424 means per site). Thereafter, for each site/functional type/RCP/time period combination, we sorted mean biomass and mean density (N = 13) for the 13 GCMs and identified the median value. We used the median as a measure of central tendency rather than the mean to moderate the impact of extreme values from individual GCMs. For each site, functional type, RCP, and future time period (2030-2060, 2070-2100), we calculated the absolute change in median biomass and median density from current to future conditions and percentage change scaled to the maximum biomass simulated under current conditions.To investigate if climate change will alter the biomass and composition of plant functional types, we quantified absolute and percentage change in median biomass for each functional type and examined whether the relative importance of functional types changed from current to future conditions by ranking median biomass under current conditions and examining whether that ranking changed in the future. To assess how changes in functional type biomass and composition vary along environmental gradients dictated by climate and ecohydrology, we quantified relationships between change in median biomass (g/m2) for the dominant plant functional types (big sagebrush, perennial C3 grasses, perennial C4 grasses, and perennial forbs), and climatic and ecohydrological variables: (annual precipitation (mm), precipitation falling as rain (mm), rain/precipitation ratio, and mean annual temperature (°C) snowpack (SWE, mm), the number of wet days in surface (0-30 cm) and subsurface (30-160 cm) soil layers, and the transpiration from surface and subsurface soil layers).

  11. E

    Global burden of respiratory infections associated with seasonal influenza...

    • find.data.gov.scot
    • dtechtive.com
    csv, txt
    Updated Mar 10, 2020
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    University of Edinburgh. Usher Institute, Centre for Global Health (2020). Global burden of respiratory infections associated with seasonal influenza in young children in 2018: a systematic review and modelling study [Dataset]. http://doi.org/10.7488/ds/2778
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    csv(0.0459 MB), csv(0.0849 MB), txt(0.0166 MB), csv(0.0579 MB), csv(0.0605 MB), csv(0.3107 MB), csv(0.2451 MB), csv(0.1298 MB), csv(0.4116 MB)Available download formats
    Dataset updated
    Mar 10, 2020
    Dataset provided by
    University of Edinburgh. Usher Institute, Centre for Global Health
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Background # Seasonal influenza virus is a common cause of acute lower respiratory infection (ALRI) in young children. In 2008, we estimated that 20 million influenza-virus-associated ALRI and 1 million influenza-virus-associated severe ALRI occurred in children under 5 years globally. Despite this substantial burden, only a few low-income and middle-income countries have adopted routine influenza vaccination policies for children and, where present, these have achieved only low or unknown levels of vaccine uptake. Moreover, the influenza burden might have changed due to the emergence and circulation of influenza A/H1N1pdm09. We aimed to incorporate new data to update estimates of the global number of cases, hospital admissions, and mortality from influenza-virus-associated respiratory infections in children under 5 years in 2018. # Methods # We estimated the regional and global burden of influenza-associated respiratory infections in children under 5 years from a systematic review of 100 studies published between Jan 1, 1995, and Dec 31, 2018, and a further 57 high-quality unpublished studies. We adapted the Newcastle-Ottawa Scale to assess the risk of bias. We estimated incidence and hospitalisation rates of influenza-virus-associated respiratory infections by severity, case ascertainment, region, and age. We estimated in-hospital deaths from influenza virus ALRI by combining hospital admissions and in-hospital case-fatality ratios of influenza virus ALRI. We estimated the upper bound of influenza virus-associated ALRI deaths based on the number of in-hospital deaths, US paediatric influenza-associated death data, and population-based childhood all-cause pneumonia mortality data in six sites in low-income and lower-middle-income countries. # Findings # In 2018, among children under 5 years globally, there were an estimated 109*5 million influenza virus episodes (uncertainty range [UR] 63*1-190*6), 10*1 million influenza-virus-associated ALRI cases (6*8-15*1); 870 000 influenza-virus-associated ALRI hospital admissions (543 000-1 415 000), 15 300 in-hospital deaths (5800-43 800), and up to 34 800 (13 200-97 200) overall influenza-virus-associated ALRI deaths. Influenza virus accounted for 7% of ALRI cases, 5% of ALRI hospital admissions, and 4% of ALRI deaths in children under 5 years. About 23% of the hospital admissions and 36% of the in-hospital deaths were in infants under 6 months. About 82% of the in-hospital deaths occurred in low-income and lower-middle-income countries. # Interpretation # A large proportion of the influenza-associated burden occurs among young infants and in low-income and lower middle-income countries. Our findings provide new and important evidence for maternal and paediatric influenza immunisation, and should inform future immunisation policy particularly in low-income and middle-income countries.

  12. Deadliest natural disasters worldwide 1950-2024

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Deadliest natural disasters worldwide 1950-2024 [Dataset]. https://www.statista.com/statistics/268029/natural-disasters-by-death-toll-since-1980/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    From 1950 to 2024, the cyclone Bhola that hit Bangladesh in 1970 was the deadliest natural disaster in the world. The exact death toll is impossible to calculate, but it is estimated that over 300,000 lives were lost as a result of the cyclone. The Tangshan earthquake in China in 1976 is estimated to have caused the second-highest number of fatalities. The Haiti earthquake The fifth-deadliest natural disaster during this period was the earthquake in Haiti in 2010. However, death tolls vary between 100,000 and 316,000, meaning that some estimates make it the deadliest natural disaster in the world since 1950, and the deadliest earthquake since 1900. Sixty percent of the country’s hospitals and eighty percent of the country’s schools were destroyed. It was the worst earthquake to hit the Caribbean in 200 years, with a magnitude of 7.0 at its epicenter only 25 kilometers away from Haiti’s capital, Port-au-Prince. Poor construction practices were to blame for many of the deaths; Haiti’s buildings were not earthquake resistant and were not built according to building code due to a lack of licensed building professionals. High population density was also to blame for the high number of fatalities. One fourth of the country’s inhabitants lived in the Port-au-Prince area, meaning half of the country’s population was directly affected by the earthquake. Increasing extreme weather As global warming continues to accelerate climate change, it is estimated that natural catastrophes such as cyclones, rainfalls, landslides, and heat waves will intensify in the coming years and decades. For instance, the economic losses caused by natural disasters worldwide increased since 2015. Moreover, it is expected that countries in the Global South will be affected the most by climate change in the coming years, and many of these are already feeling the impact of climate change.

  13. D

    Oxytocin Receptor Antagonists Market Report | Global Forecast From 2025 To...

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
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    Dataintelo (2024). Oxytocin Receptor Antagonists Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-oxytocin-receptor-antagonists-market
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    pdf, csv, pptxAvailable download formats
    Dataset updated
    Dec 3, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Oxytocin Receptor Antagonists Market Outlook



    The global oxytocin receptor antagonists market size is projected to grow significantly from approximately USD 200 million in 2023 to USD 350 million by 2032, reflecting a compound annual growth rate (CAGR) of around 6.5%. This growth is driven by increasing research in the field of therapeutic treatments for conditions such as preterm labor and autism spectrum disorder, as well as a rising incidence of postpartum hemorrhage. The expanding pharmaceutical research and development sector, combined with an increased focus on women's health, particularly in emerging markets, further accelerates the market's expansion over the coming years.



    One of the primary growth factors for the oxytocin receptor antagonists market is the increasing prevalence of preterm labor, which remains a significant concern worldwide. The demand for effective therapeutic interventions to manage and mitigate preterm births is fueling the development and commercialization of oxytocin receptor antagonists. Advancements in pharmaceutical research have emphasized the need for drugs that can safely delay labor, thereby reducing neonatal mortality and morbidity rates. With preterm labor contributing to a substantial portion of neonatal deaths globally, there has been a marked increase in healthcare initiatives and government support for the development of innovative solutions in this space, propelling market growth.



    Another substantial contributor to the market's growth is the rising awareness and diagnosis of autism spectrum disorder (ASD). As the understanding of ASD's complex etiology grows, researchers are exploring the role of oxytocin pathways, with receptor antagonists emerging as a potential therapeutic avenue. The identification of specific biomarkers and the development of targeted therapies are enhancing treatment protocols, thus driving demand within this market segment. Increasing investments in research to understand and develop effective treatments for ASD are creating a fertile ground for the expansion of oxytocin receptor antagonist applications, leading to steady market growth.



    Additionally, the management of postpartum hemorrhage remains a critical area where oxytocin receptor antagonists are finding increased application. With postpartum hemorrhage being a leading cause of maternal mortality globally, particularly in low-resource settings, there is an urgent need for effective treatments. The pharmaceutical industry is responding with enhanced research efforts to develop more efficient and accessible formulations of oxytocin receptor antagonists. This focus not only supports market expansion but also underscores the vital role of these drugs in improving maternal health outcomes and reducing mortality rates associated with childbirth complications.



    The regional outlook for the oxytocin receptor antagonists market is shaped by varying healthcare landscapes and investment levels in different parts of the world. North America holds a significant share of the market, driven by extensive research initiatives, advanced healthcare infrastructure, and a high incidence of related medical conditions. In Europe, the market is also seeing steady growth, supported by robust regulatory frameworks and a strong focus on research and development. Meanwhile, the Asia Pacific region is anticipated to witness the fastest growth rate, fueled by increasing healthcare investments, government support, and a growing focus on maternal health. Latin America and the Middle East & Africa, while smaller in market size, are also expected to see gradual growth, driven by improving healthcare access and rising awareness of maternal and neonatal health issues.



    Product Type Analysis



    The oxytocin receptor antagonists market is categorized into two primary product types: peptide antagonists and non-peptide antagonists. Peptide antagonists are naturally occurring or synthetic peptides designed to inhibit the action of oxytocin by binding to its receptors. These antagonists are significant due to their specificity and effectiveness in blocking oxytocin's physiological effects, which are crucial in conditions such as preterm labor. The development of peptide-based drugs is propelled by ongoing research that aims to enhance their stability and bioavailability, which can potentially increase their therapeutic application and market penetration.



    Non-peptide antagonists, on the other hand, represent a novel and promising area within this market. These small molecules offer advantages in terms of oral bioavailability and ease of synthesis compared to p

  14. f

    Table_1_Trends in Incidence and Mortality of Stroke in China From 1990 to...

    • frontiersin.figshare.com
    docx
    Updated Jun 8, 2023
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    Tong Sun; Siyang Chen; Ke Wu; Min Sun; Xianyan Zhang; Chao You (2023). Table_1_Trends in Incidence and Mortality of Stroke in China From 1990 to 2019.DOCX [Dataset]. http://doi.org/10.3389/fneur.2021.759221.s001
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    docxAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    Frontiers
    Authors
    Tong Sun; Siyang Chen; Ke Wu; Min Sun; Xianyan Zhang; Chao You
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    Objective: Stroke is a leading cause of mortality and morbidity globally. This study aimed to analyze the burden and 30-year trends of ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) in China.Methods: Data that include incidence and mortality of stroke in China from January 1, 1990 to December 31, 2019 were derived from the Global Burden of Disease (GBD) study 2019. The absolute numbers of incident cases and deaths over the time, and age-standardized rates per 100,000, such as age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR), were analyzed.Results: In 2019, there were 3.9 (95% uncertainty intervals (UI) 3.4–4.5) million incident cases and 2.1 (3.4–4.5) million deaths related to stroke in China. The ASIR and ASMR of stroke in China was 200 (176–230) and 127 (110–144). From 1990 to 2019, the ASIR of ischemic stroke had increased by 35.0% (29.0–40.0) while the ASIR of ICH and SAH had decreased by −53.0% (−56.0 to −50.0) and by −39.0% (−44.0 to −35.0), respectively. The ASMR of ischemic stroke had increased by 3.0% (−26.0 to 16.0) while the ASMR of ICH and SAH had decreased by −48.0% (−59.0 to −38.0) and by −84.0% (−89.0 to −69.0), respectively.Conclusion: Although the incidence and mortality rates of stroke in China were decreased from 1990 to 2019, the number of incident cases and deaths nearly doubled. A sharp increase in the incidence rate of ischemic stroke was observed. A higher incidence rate of ischemic stroke in the women was also observed.

  15. Annual life expectancy in the United States 1850-2100

    • statista.com
    Updated Jul 31, 2025
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    Statista (2025). Annual life expectancy in the United States 1850-2100 [Dataset]. https://www.statista.com/statistics/1040079/life-expectancy-united-states-all-time/
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    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

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

  16. K

    Kiribati Child mortality - data, chart | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated May 12, 2020
    + more versions
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    Globalen LLC (2020). Kiribati Child mortality - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Kiribati/child_mortality/
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    csv, excel, xmlAvailable download formats
    Dataset updated
    May 12, 2020
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2022
    Area covered
    Kiribati
    Description

    Kiribati: Deaths of children under five years of age per 1000 live births: The latest value from 2022 is 56 deaths per 1000 births, a decline from 58 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 Kiribati from 1960 to 2022 is 99 deaths per 1000 births. The minimum value, 56 deaths per 1000 births, was reached in 2022 while the maximum of 200 deaths per 1000 births was recorded in 1960.

  17. U.S. - Infant mortality rate 1960-2022

    • statista.com
    Updated Oct 18, 2024
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    Statista (2024). U.S. - Infant mortality rate 1960-2022 [Dataset]. https://www.statista.com/statistics/195950/infant-mortality-rate-in-the-united-states-since-1990/
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    Dataset updated
    Oct 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

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

  18. t

    Probability of dying among adolescents ages 10-19 years (per 1,000)....

    • timeseriesexplorer.com
    Updated May 31, 2024
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    World Bank Group (2024). Probability of dying among adolescents ages 10-19 years (per 1,000). Ethiopia | Population Estimates And Projections [Dataset]. https://www.timeseriesexplorer.com/6df7bfbed27951b9ca4c699e47cd5aca/d61094958d4f9e5ced0152d4b9f7833c/
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    Dataset updated
    May 31, 2024
    Dataset provided by
    Time Series Explorer
    World Bank Group
    Area covered
    Ethiopia
    Description

    SH.DYN.1019. Probability of dying between age 10-19 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year. This database presents population and other demographic estimates and projections from 1960 to 2050, covering more than 200 economies. It includes population data by various age groups, sex, urban/rural; fertility data; mortality data; and migration data.

  19. Global adult mortality rate 1990-2022, by gender

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Global adult mortality rate 1990-2022, by gender [Dataset]. https://www.statista.com/statistics/1328285/global-adult-mortality-rate-gender/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Over the past three decades, the global death rates of both genders decreased. However, there was an increase during the COVID-19 pandemic among both women and men. In 2022, there were *** deaths per 1,000 men between 15 and 60 years, and *** per 1,000 women of the same age.

  20. e

    IPCC Climate Change Data: NIES99 A1t Model: 2050 Maximum Temperature

    • knb.ecoinformatics.org
    • dataone.org
    Updated Aug 14, 2015
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    Intergovernmental Panel on Climate Change (IPCC) (2015). IPCC Climate Change Data: NIES99 A1t Model: 2050 Maximum Temperature [Dataset]. http://doi.org/10.5063/AA/dpennington.310.1
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    Dataset updated
    Aug 14, 2015
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    Intergovernmental Panel on Climate Change (IPCC)
    Time period covered
    Jan 1, 2050 - Dec 31, 2050
    Area covered
    Earth
    Description

    The model used here is a coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model (Abe-Ouchi et al., 1996). The spatial resolution is T21 spectral truncation (roughly 5.6 degrees latitude/longitude) and 20 vertical levels for the atmospheric part, and roughly 2.8 degrees horizontal grid and 17 vertical levels for the oceanic part. Flux adjustment for atmosphere-ocean heat and water exchange is applied to prevent a drift of the modelled climate. The atmospheric model adopts a radiation scheme based on the k-distribution, two-stream discrete ordinate method (DOM) (Nakajima and Tanaka, 1986). This scheme can deal with absorption, emission and scattering by gases, clouds and aerosol particles in a consistent manner. In the calculation of sulphate aerosol optical properties, the volumetric mode radius of the sulphate particle in dry environment is assumed to be 0.2 micron. The hygroscopic growth of the sulphate is considered by an empirical fit of d'Almeida et al. (1991). The vertical distribution of the sulphate aerosol is assumed to be constant in the lowest 2 km of the atmosphere. The concentrations of greenhouse gases are represented by equivalent-CO2. Three integrations are made for 200 model years (1890-2090). In the control experiment (CTL), the globally uniform concentration of greenhouse gases is kept constant at 345 ppmv CO2-equivalent and the concentration of sulphate is set to zero. In the experiment GG, the concentration of greenhouse gases is gradually increased, while that of sulphate is set to zero. In the experiments GS, the increase in anthropogenic sulphate as well as that in greenhouse gases is given and the aerosol scattering (the direct effect of aerosol) is explicitly represented in the way described above. The indirect effect of aerosol is not included in any experiment. The scenario of atmospheric concentrations of greenhouse gases and sulphate aerosols is given in accordance with Mitchell and Johns (1997). The increase in greenhouse gases is based on the historical record from 1890 to 1990 and is increased by 1 percent / yr (compound) after 1990. For sulphate aerosols, geographical distributions of sulphate loading for 1986 and 2050, which are estimated by a sulphur cycle model (Langer and Rodhe, 1991), are used as basic patterns. Based on global and annual mean sulphur emission rates, the 1986 pattern is scaled for years before 1990; the 2050 pattern is scaled for years after 2050; and the pattern is interpolated from the two basic ones for intermediate years to give the time series of the distribution. The sulphur emission rate in the future is based on the IPCC IS92a scenario. The sulphate concentration is offset in our run so that it starts from zero at 1890. The seasonal variation of sulphate concentration is ignored. Discussion on the results of the experiments will be found in Emori et al. (1999). Climate sensitivity of the CCSR/NIES model derived by equilibrium runs is estimated to be 3.5 degrees Celsius. Global-Mean Temperature, Precipitation and CO2 Changes (w.r.t. 1961-90) for the CCSR/NIES model. From the IPCC website: The A1 Family storyline is a case of rapid and successful economic development, in which regional averages of income per capita converge - current distinctions between poor and rich countries eventually dissolve. In this scenario family, demographic and economic trends are closely linked, as affluence is correlated with long life and small families (low mortality and low fertility). Global population grows to some nine billion by 2050 and declines to about seven billion by 2100. Average age increases, with the needs of retired people met mainly through their accumulated savings in private pension systems. The global economy expands at an average annual rate of about three percent to 2100. This is approximately the same as average global growth since 1850, although the conditions that lead to a global economic in productivity and per capita incomes are unparalleled in history. Income per capita reaches about US$21,000 by 2050. While the high average level of income per capita contributes to a great improvement in the overall health and social conditions of the majority of people, this world is not without its problems. In particular, many communities could face some of the problems of social exclusion encountered by the wealthiest countries in the 20th century and in many places income growth could come with increased pressure on the global commons. Energy and mineral resources are abundant in this scenario family because of rapid technical progress, which both reduce the resources need to produce a given level of output and increases the economically recoverable reserves. Final energy intensity (energy use per unit of GDP) decreases at a... Visit https://dataone.org/datasets/doi%3A10.5063%2FAA%2Fdpennington.310.1 for complete metadata about this dataset.

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Statista (2025). Life expectancy by continent and gender 2024 [Dataset]. https://www.statista.com/statistics/270861/life-expectancy-by-continent/
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Life expectancy by continent and gender 2024

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22 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2024
Area covered
Worldwide
Description

In 2024, the average life expectancy in the world was 71 years for men and 76 years for women. The lowest life expectancies were found in Africa, while Oceania and Europe had the highest. What is life expectancy?Life expectancy is defined as a statistical measure of how long a person may live, based on demographic factors such as gender, current age, and most importantly the year of their birth. The most commonly used measure of life expectancy is life expectancy at birth or at age zero. The calculation is based on the assumption that mortality rates at each age were to remain constant in the future. Life expectancy has changed drastically over time, especially during the past 200 years. In the early 20th century, the average life expectancy at birth in the developed world stood at 31 years. It has grown to an average of 70 and 75 years for males and females respectively, and is expected to keep on growing with advances in medical treatment and living standards continuing. Highest and lowest life expectancy worldwide Life expectancy still varies greatly between different regions and countries of the world. The biggest impact on life expectancy is the quality of public health, medical care, and diet. As of 2022, the countries with the highest life expectancy were Japan, Liechtenstein, Switzerland, and Australia, all at 84–83 years. Most of the countries with the lowest life expectancy are mostly African countries. The ranking was led by the Chad, Nigeria, and Lesotho with 53–54 years.

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