We obtained the analyzed data from the public repository of the Global Burden of Disease (GBD) study (https://vizhub.healthdata.org/sdg/#0 and http://ghdx.healthdata.org/record/ihme-data/gbd-2017-health-related-sdgs-1990-2030). However, under the request of the International Journal for Equity in Health in order to contribute to transparency and replicability of research, the authors of the study entitled “Human resources for health and maternal mortality in Latin America and the Caribbean over the last three decades: a systemic-perspective reflections”, made the data available. Any other use than exploring or replicating the results of the above-mentioned paper is not authorized and shall not be used without the previous authorization of the investigators. If you are interested in analyzing this database for original research purposes please contact Edson Serván Mori (eservan@insp.mx).

This layer represents the percentage of total Disability-Adjusted Life Year attributable to paratyphoid fever for 5-14 year-old females in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbdNote : Value -99 indicates that no data is available.A detailed description of the methodology and additional resources related to this topic can be found here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the IHME website: http://www.healthdata.org/gbd

This layer represents the percentage of total Disability-Adjusted Life Year attributable to hepatitis A for 15-49 year-old males in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

This layer represents the percentage of total Disability-Adjusted Life Year attributable to hepatitis E for 50-69 year-old males in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

This layer represents the percentage of Disability-Adjusted Life Year attributable to unsafe sanitation in 2015, for 5 to 14 year-old males. Data for other age ranges are also available in the table.One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

This layer represents the percentage of total Disability-Adjusted Life Year attributable to unsafe water sources for 15-49 year-old males in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

The Global Health Data Exchange (GHDx) is a catalog that provides relevant data on population health. The catalog contains surveys, censuses, vital statistics, and other health-related data. The GHDx was created by the Institute for Health Metrics and Evaluations (IHME), an independent global health research center at the University of Washington. The GHDx is a place where information about data is brought together, discussed, and featured in the context of health and demographic research. The GHDx raises awareness about different groups collecting data worldwide and provides standardized citations to encourage appropriate acknowledgment of data owners’ contributions.

We obtained the analyzed data from the public repository of the Global Burden of Disease (GBD) study (http://ghdx.healthdata.org). However, under the request of The Lancet Regional Health – Americas and in order to contribute to transparency and replicability of research, the authors of the study entitled “Persistent inequities in maternal mortality in Latin America and the Caribbean, 1990-2019”, made the data available. Any other use than exploring or replicating the results of the above-mentioned paper is not authorized and shall not be used without the previous authorization of the investigators. If you are interested in analyzing this database for original research purposes please contact Edson Serván Mori (eservan@insp.mx).

This is a dataset from the GBD database (http://ghdx.healthdata.org/gbd-results-tool), including the disability-adjusted life years (DALYs), deaths, prevalence, incidence, DALYs and deaths due to short gestation and low birth weight in early and late neonates with neonatal sepsis in China and the United States. Date Submitted: 2023-06-27

This layer represents the percentage of total Disability-Adjusted Life Year attributable to hepatitis E for 50-69 year-old females in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

This layer represents the percentage of total Disability-Adjusted Life Years (DALYs) attributable to the lack of access to handwashing facility in 2015, for 5 to 14 year-old males.One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

This is a dataset from the GBD database (http://ghdx.healthdata.org/gbd-results-tool), including the incidence, prevalence, disability-adjusted life years (DALYs), years of life lost (YLLs), years of lost due to disability (YLDs), and DALYs due to high BMI of asthma in children aged 1-14 years in China and the United States. Date Submitted: 2023-01-20

This layer represents the percentage of total Disability-Adjusted Life Year attributable to typhoid fever for 15-49 year-old males in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

We collected county-level cumulative COVID-19 confirmed cases and death from Mar 25 to Nov 12, 2020, across the contiguous United States from USAFacts (usafacts.org). We considered Mar 25 to Jun 3 as the “1st wave”, Jun 4 to Sep 2 as the “2nd wave”, and Sep 3 to Nov 12 as the “3rd wave” of COVID-19. For the 2nd and 3rd waves, we analyzed the targeted counties in the sunbelt region (including AL, AZ, AR, CA, FL, GA, KS, LA, MS, NV, NM, NC, OK, SC, TX, TN, and UT states) and great plains region (including IA, IL, IN, KS, MI, MO, MN, ND, NE, OH, SD, and WI states), respectively. MIR, as a proxy for survival rate, is calculated by dividing the number of confirmed deaths in each county by the confirmed cases in the same county at the same time-period multiplied by 100. MIR ranges from 0%-100%, 100% indicating the worst situation where all confirmed cases have died.

Thirty-eight potential risk factors (covariates), including county-level MR of comorbidities & disorders, demographics & social factors, and environmental factors, were retrieved from the University of Washington Global Health Data Exchange (http://ghdx.healthdata.org/us-data). Comorbidities and disorders include CVD, cardiomyopathy and myocarditis and myocarditis, hypertensive heart disease, peripheral vascular disease, atrial fibrillation, cerebrovascular disease, diabetes, hepatitis, HIV/AIDS, tuberculosis (TB), lower respiratory infection, interstitial lung disease and pulmonary sarcoidosis, asthma, COPD, ischemia, mesothelioma, tracheal cancer, leukemia, pancreatic cancer, rheumatic disease, drug use disorder, and alcohol use disorder. Demographics & social factors include age, female African American%, female white American%, male African American%, male white American%, Asian%, smokers%, unemployed%, income rate, food insecurity, fair/poor health, and uninsured%. Environmental factors include county population density, air quality index (AQI), temperature, and PM. A descriptive table, including all potential risk factors, is provided in Table S1).

BackgroundThe burden of chronic respiratory diseases has changed over the three decades. This study aims to describe the spatiotemporal trends of prevalence, mortality, and disability-adjusted life years (DALY) due to chronic respiratory diseases (CRDs) worldwide during 1990–2019 using data from the Global Burden of Disease Study 2019 (GBD 2019).MethodsThe prevalence, mortality, and DALY attributable to CRDs and risk factors from 1990 to 2019 were estimated. We also assessed the driving factors and potentiality for improvement with decomposition and frontier analyses, respectively.ResultsIn 2019, 454.56 [95% uncertainty interval (UI): 417.35–499.14] million individuals worldwide had a CRD, showing a 39·8% increase compared with 1990. Deaths due to CRDs were 3.97 (95%UI: 3.58–4.30) million, and DALY in 2019 was 103.53 (95%UI: 94.79–112.27) million. Declines by average annual percent change (AAPC) were observed in age-standardized prevalence rates (ASPR) (0.64% decrease), age-standardized mortality rates (ASMR) (1.92%), and age-standardized DALY rates (ASDR) (1.72%) globally and in 5 socio-demographic index (SDI) regions. Decomposition analyses represented that the increase in overall CRDs DALY was driven by aging and population growth. However, chronic obstructive pulmonary disease (COPD) was the leading driver of increased DALY worldwide. Frontier analyses witnessed significant improvement opportunities at all levels of the development spectrum. Smoking remained a leading risk factor (RF) for mortality and DALY, although it showed a downward trend. Air pollution, a growing factor especially in relatively low SDI regions, deserves our attention.ConclusionOur study clarified that CRDs remain the leading causes of prevalence, mortality, and DALY worldwide, with growth in absolute numbers but declines in several age-standardized estimators since 1990. The estimated contribution of risk factors to mortality and DALY demands the need for urgent measures to improve them.Systematic review registrationhttp://ghdx.healthdata.org/gbd-results-tool.

This layer represents the percentage of total Disability-Adjusted Life Year attributable to unsafe water sources for 15-49 year-old females in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

This layer represents the percentage of total Disability-Adjusted Life Year attributable to unsafe water, sanitation and handwashing for 15-49 year-old males in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd

BackgroundThe burden of chronic respiratory diseases has changed over the three decades. This study aims to describe the spatiotemporal trends of prevalence, mortality, and disability-adjusted life years (DALY) due to chronic respiratory diseases (CRDs) worldwide during 1990–2019 using data from the Global Burden of Disease Study 2019 (GBD 2019).MethodsThe prevalence, mortality, and DALY attributable to CRDs and risk factors from 1990 to 2019 were estimated. We also assessed the driving factors and potentiality for improvement with decomposition and frontier analyses, respectively.ResultsIn 2019, 454.56 [95% uncertainty interval (UI): 417.35–499.14] million individuals worldwide had a CRD, showing a 39·8% increase compared with 1990. Deaths due to CRDs were 3.97 (95%UI: 3.58–4.30) million, and DALY in 2019 was 103.53 (95%UI: 94.79–112.27) million. Declines by average annual percent change (AAPC) were observed in age-standardized prevalence rates (ASPR) (0.64% decrease), age-standardized mortality rates (ASMR) (1.92%), and age-standardized DALY rates (ASDR) (1.72%) globally and in 5 socio-demographic index (SDI) regions. Decomposition analyses represented that the increase in overall CRDs DALY was driven by aging and population growth. However, chronic obstructive pulmonary disease (COPD) was the leading driver of increased DALY worldwide. Frontier analyses witnessed significant improvement opportunities at all levels of the development spectrum. Smoking remained a leading risk factor (RF) for mortality and DALY, although it showed a downward trend. Air pollution, a growing factor especially in relatively low SDI regions, deserves our attention.ConclusionOur study clarified that CRDs remain the leading causes of prevalence, mortality, and DALY worldwide, with growth in absolute numbers but declines in several age-standardized estimators since 1990. The estimated contribution of risk factors to mortality and DALY demands the need for urgent measures to improve them.Systematic review registrationhttp://ghdx.healthdata.org/gbd-results-tool.

This is a repository of global and regional human population data collected from: the databases of scenarios assessed by the Intergovernmental Panel on Climate Change (Sixth Assessment Report, Special Report on 1.5 C; Fifth Assessment Report), multi-national databases of population projections (World Bank, International Database, United Nation population projections), and other very long-term population projections (Resources for the Future).

More specifically, it contains:

- in `other_pop_data` folder files from World Bank, the International Database from the US Census, and from IHME

- in the `SSP` folder, the Shared Socioeconomic Pathways, as in the version 2.0 downloaded from IIASA and as in the version 3.0 downloaded from IIASA workspace

- in the `UN` folder, the demographic projections from UN

- `IAMstat.xlsx`, an overview file of the metadata accompanying the scenarios present in the IPCC databases

- `RFF.csv`, an overview file containing the population projections obtained by Resources For the Future

'- the remaining `.csv` files with names `AR6#`, `AR5#`, `IAMC15#` contain the IPCC scenarios assessed by the IPCC for preparing the IPCC assessment reports. They can be downloaded from AR5, SR 1.5, and AR6

This data in intended to be downloaded for use together with the package downloadable here.

The dataset was used as a supporting material for the paper "Underestimating demographic uncertainties in the synthesis process of the IPCC" accepted on npj Climate Action (DOI : 10.1038/s44168-024-00152-y).

This layer represents the percentage of total Disability-Adjusted Life Year attributable to typhoid fever for 15-49 year-old females in 2015. One DALY can be thought of as one lost year of "healthy" life. The sum of DALYs across a population help to quantify the burden of disease, and to evaluate the gap between current health status and an ideal health situation. Data for other age ranges are also available in the table.Estimates and additional related resources can be found in the Global Burden of Study here: http://ghdx.healthdata.org/gbd-2015 For more information, visit the Institute for Health Metrics and Evaluation website: http://www.healthdata.org/gbd