A survey of people from 30 different countries around the world found that mental health was the biggest health problem respondents said was facing their country in 2025. Other health problems reported by respondents included cancer, stress, and obesity. The COVID-19 pandemic The COVID-19 pandemic impacted almost every country in the world and was the biggest global health crisis in recent history. It resulted in hundreds of millions of cases and millions of deaths, causing unprecedented disruption in health care systems. Lockdowns imposed in many countries to halt the spread of the virus also resulted in a rise of mental health issues as feelings of stress, isolation, and hopelessness arose. However, vaccines to combat the virus were developed at record speed, and many countries have now vaccinated large shares of their population. Nevertheless, in 2025, *** percent of respondents still stated that COVID-19 was the biggest health problem facing their country. Mental health issues One side effect of the COVID-19 pandemic has been a focus on mental health around the world. The two most common mental health issues worldwide are anxiety disorders and depression. In 2021, it was estimated that around *** percent of the global population had an anxiety disorder, while **** percent suffered from depression. Rates of depression are higher among females than males, with some *** percent of females suffering from depression, compared to *** percent of men. However, rates of suicide in most countries are higher among men than women. One positive outcome of the COVID-19 pandemic and the spotlight it shined on mental health may be a decrease in stigma surrounding mental health issues and seeking help for such issues. This would be a positive development, as many people around the world do not or cannot receive the necessary treatment they need for their mental health.

In 2021, there were over ** million deaths from all types of cardiovascular diseases all over the world. This statistic describes the number of deaths caused by selected chronic diseases worldwide in 2021. Chronic disease has widespread consequences on both individuals, impacting both quality and length of life, as well as on societies and governments worldwide. Chronic disease The burden of chronic diseases, which is made up of the resulting disabilities and deaths, is increasing all over the globe. In 2022, lung cancer caused over *** million deaths worldwide, accounting for the highest number of cancer deaths. Furthermore, it is estimated that by 2045, there will be *** million people living with diabetes all over the globe. Although chronic diseases are not curable, their risk factors are highly preventable, usually through individual lifestyle and behavioral modifications. Public policies have been put into place in many countries worldwide to promote healthier lifestyles, for example by limiting the consumption of tobacco and alcohol. Impact on societies Chronic diseases can result in a heavy economic burden due to related health care costs and through the loss of workforce. Countries of all income statuses are affected by chronic diseases, with the leading causes of death in high-income countries from chronic disease. Moreover, the rising impact of chronic disease in low-income countries leads to a double burden, as they are forced to deal with both infectious diseases and non-communicable diseases. Weak health systems and poor economies often pose limits to these countries’ abilities to cope as well.

This dataset provides comprehensive statistics on global health, focusing on various diseases, treatments, and outcomes. The data spans multiple countries and years, offering valuable insights for health research, epidemiology studies, and machine learning applications. The dataset includes information on the prevalence, incidence, and mortality rates of major diseases, as well as the effectiveness of treatments and healthcare infrastructure.

Dataset Use Cases:

This dataset can be used for:

• Healthcare Policy Analysis: Understanding which diseases are most prevalent and which countries require more investment in healthcare infrastructure.
• Epidemiological Studies: Studying the correlation between disease prevalence and socio-economic factors like income, education, and urbanization.
• Machine Learning Models: Training predictive models to forecast disease trends, mortality rates, and treatment effectiveness based on historical data.
• Global Health Research: Identifying regions that need targeted interventions or public health campaigns.

It is estimated that around **** percent of the population in the United States has been diagnosed with an infectious disease. Infectious diseases are caused by bacteria, viruses and other organisms and can be spread from person to person, through insect or animal bites, or through contaminated food or water. Some of the most common infectious diseases include HIV/AIDS, influenza, malaria, tuberculosis and hepatitis.

HIV/AIDS

HIV/AIDS is one of the most well-known infectious diseases worldwide. There are currently almost ** million people worldwide living with HIV and it is responsible for just under a million deaths per year. HIV treatment has improved dramatically over the last few decades but access to treatment varies. The poorer regions of the world still suffer disproportionately from HIV with the majority of those infected living in Africa.

Tuberculosis

Like HIV/AIDS, tuberculosis also impacts the poorer regions of the world more than developed nations. Tuberculosis impacts the lungs of those infected and is currently the tenth leading cause of death worldwide. The countries with the highest incidence rates of tuberculosis include India, China, Indonesia, and the Philippines. In India alone tuberculosis was responsible for around ******* deaths in 2018.

BackgroundFoodborne diseases are important worldwide, resulting in considerable morbidity and mortality. To our knowledge, we present the first global and regional estimates of the disease burden of the most important foodborne bacterial, protozoal, and viral diseases.Methods and FindingsWe synthesized data on the number of foodborne illnesses, sequelae, deaths, and Disability Adjusted Life Years (DALYs), for all diseases with sufficient data to support global and regional estimates, by age and region. The data sources included varied by pathogen and included systematic reviews, cohort studies, surveillance studies and other burden of disease assessments. We sought relevant data circa 2010, and included sources from 1990–2012. The number of studies per pathogen ranged from as few as 5 studies for bacterial intoxications through to 494 studies for diarrheal pathogens. To estimate mortality for Mycobacterium bovis infections and morbidity and mortality for invasive non-typhoidal Salmonella enterica infections, we excluded cases attributed to HIV infection. We excluded stillbirths in our estimates. We estimate that the 22 diseases included in our study resulted in two billion (95% uncertainty interval [UI] 1.5–2.9 billion) cases, over one million (95% UI 0.89–1.4 million) deaths, and 78.7 million (95% UI 65.0–97.7 million) DALYs in 2010. To estimate the burden due to contaminated food, we then applied proportions of infections that were estimated to be foodborne from a global expert elicitation. Waterborne transmission of disease was not included. We estimate that 29% (95% UI 23–36%) of cases caused by diseases in our study, or 582 million (95% UI 401–922 million), were transmitted by contaminated food, resulting in 25.2 million (95% UI 17.5–37.0 million) DALYs. Norovirus was the leading cause of foodborne illness causing 125 million (95% UI 70–251 million) cases, while Campylobacter spp. caused 96 million (95% UI 52–177 million) foodborne illnesses. Of all foodborne diseases, diarrheal and invasive infections due to non-typhoidal S. enterica infections resulted in the highest burden, causing 4.07 million (95% UI 2.49–6.27 million) DALYs. Regionally, DALYs per 100,000 population were highest in the African region followed by the South East Asian region. Considerable burden of foodborne disease is borne by children less than five years of age. Major limitations of our study include data gaps, particularly in middle- and high-mortality countries, and uncertainty around the proportion of diseases that were foodborne.ConclusionsFoodborne diseases result in a large disease burden, particularly in children. Although it is known that diarrheal diseases are a major burden in children, we have demonstrated for the first time the importance of contaminated food as a cause. There is a need to focus food safety interventions on preventing foodborne diseases, particularly in low- and middle-income settings.

Heart conditions were the most common causes of death in Mexico in 2023. During that period, more than ******* people died in the North American country as a result from said conditions. Diabetes mellitus ranked second, with over ******* deaths registered that year. Obesity in MexicoObesity and being overweight can worsen many risk factors for developing heart conditions, prediabetes, type 2 diabetes, and gestational diabetes, which in the case of a COVID-19 infection can lead to a severe course of the disease. In 2020, Mexico was reported as having one of the largest overweight and/or obese population in Latin America, with ** percent of people in the country having a body mass index higher than 25. In 2022, obesity was announced as being one of the most common illnesses experienced in Mexico, with over ******* cases estimated. In a decade from now, it is predicted that about *** million children in Mexico will suffer from obesity. If estimations are correct, this North American country will belong to the world’s top 10 countries with the most obese children in 2030. Physical activity in MexicoIt is not only a matter of food intake. A 2023 survey found, for instance, that only **** percent of Mexican population practiced sports and physical activities in their free time, a figure that has decreased in comparison to 2013. Less than ** percent of the physically active Mexicans practice sports for fun. However, the vast majority were motivated by health reasons.

Context

In the shadows of the Covid-19 pandemic, there is another global health crisis that has gone largely unnoticed. This is the Noncommunicable Disease (NCD) pandemic.

The WHO website describes NCDs as follows:

Noncommunicable diseases (NCDs), also known as chronic diseases, tend to be of long duration and are the result of a combination of genetic, physiological, environmental and behaviours factors.

The main types of NCDs are cardiovascular diseases (like heart attacks and stroke), cancers, chronic respiratory diseases (such as chronic obstructive pulmonary disease and asthma) and diabetes.

NCDs disproportionately affect people in low- and middle-income countries where more than three quarters of global NCD deaths – 32million – occur.

Key facts:

• Noncommunicable diseases (NCDs) kill 41 million people each year, equivalent to 71% of all deaths globally.
• Each year, 15 million people die from a NCD between the ages of 30 and 69 years; over 85% of these "premature" deaths occur in low- and middle-income > * countries.
• Cardiovascular diseases account for most NCD deaths, or 17.9 million people annually, followed by cancers (9.0 million), respiratory diseases (3.9million), and diabetes (1.6 million).
• These 4 groups of diseases account for over 80% of all premature NCD deaths.
• Tobacco use, physical inactivity, the harmful use of alcohol and unhealthy diets all increase the risk of dying from a NCD.
• Detection, screening and treatment of NCDs, as well as palliative care, are key components of the response to NCDs.

Content

This data repository consists of 3 CSV files: WHO-cause-of-death-by-NCD.csv is the main dataset, which provides the percentage of deaths caused by NCDs out of all causes of death, for each nation globally. Metadata_Country.csv and Metadata_Indicator.csv provide additional metadata which is helpful for interpreting the main CSV.

The data collected spans a period from 2000 to 2016. The main CSV has columns for every year from 1960 to 2019. It is advisable to drop all redundant columns where no data was collected.

Furthermore, it is advisable to merge Metadata_Country.csv with the main CSV as it provides valuable additional information, particularly on the economic situation of each nation.

Acknowledgements

This dataset has been extracted from The World Bank 'Cause of death, by non-communicable diseases (% of total)' Dataset, derived based on the data from WHO's Global Health Estimates. It is freely provided under a Creative Commons Attribution 4.0 International License (CC BY 4.0), with the additional terms as stated on the World Bank website: World Bank Terms of Use for Datasets.

Inspiration

I would be interested to see some good data wrangling (dropping redundant columns), as well as kernels interpreting additional information in 'SpecialNotes' column in Metadata_country.csv

It would also be great to see what different factors influence NCDs: most of all, the geopolitical factors. Would be great to see some choropleth visualisations to get an idea of which regions are most affected by NCDs.

JP: Prevalence of Severe Wasting: Weight for Height: Male: % of Children under 5 data was reported at 0.300 % in 2010. JP: Prevalence of Severe Wasting: Weight for Height: Male: % of Children under 5 data is updated yearly, averaging 0.300 % from Dec 2010 (Median) to 2010, with 1 observations. JP: Prevalence of Severe Wasting: Weight for Height: Male: % of Children under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Health Statistics. Prevalence of severe wasting, male, is the proportion of boys under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Background: International travel during the Coronavirus disease 2019 (COVID-19) pandemic carries a certain magnitude of infection risk both to travelers and their destination, which may be difficult to assess in the early stage. The characteristics of common infectious diseases of tourists may provide some clues to identify the high-risk travelers and protect susceptible population.Methods: From among 48,444 travelers screened at Shanghai Port, we analyzed 577 travelers with 590 infectious diseases for age, sex, disease type, and World Health Organization (WHO) regions. We used the Joinpoint Regression Program to identify the average percent changes (APC) in the various trends among these individuals.Results: Hepatitis B, syphilis, and HIV were the most common infectious diseases in travelers entering China, and Hepatitis B, pulmonary tuberculosis, and syphilis in Chinese nationals traveling abroad (overall detection rates, 1.43 and 0.74%, respectively; P < 0.05). Africa (2.96%), the Americas (1.68%), and the Western Pacific (1.62%) exhibited the highest detection rates. This trend did not decrease since the COVID-19 pandemic (P > 0.05) and rather showed an upward trend with increasing age [APC 95% CI = 5.46 (3.41,7.56)%, P < 0.05]. However, there were no evident trends in monthly infection rates of travelers exiting and entering China from different WHO regions (all P > 0.05).Conclusion: Travelers always carry a transmission risk of common infectious diseases. It may be reasonable to adjust strategies for airport screening and quarantine according to the age and departure area of travelers to prevent and control new infectious diseases.

ObjectiveWe analyzed the health needs of the adult population accessing public health facilities in the Iraqi Kurdistan, a region facing both demographic and epidemiological transitions while undergoing post-crisis recovery. We investigates the prevalence and distribution of communicable and non-communicable diseases using real-world data from a digital surveillance system.MethodsData collected across public health centers (PHC) were extracted from the KRG-DHIS2 digital health platform. All records from adult patients were coded using the WHO ICD-10. Diagnoses were grouped into: Communicable, maternal, neonatal and nutritional diseases (CMNNDs), Non-communicable diseases (NCDs), Injuries, Ill-defined diseases. Statistical analyses included descriptive statistics, age-related trends and sex-specific comparisons.ResultsA total of 1,040,695 health events were recorded (years 2016–2022) across 96 PHC: 899,173 were classified as either CMNNDs (41.1%) or NCDs (58.9%). Significant sex and age differences were observed across all major diagnostic categories. NCDs were more common in all age groups and increased significantly with age, while CMNNDs predominated among younger adults. Females accounted for 63.4% of all health events and exhibited higher rates of visits for endocrine, genitourinary, and hematologic conditions. Respiratory system diseases were the most common diagnoses across all ages, followed by genitourinary and digestive system diseases.ConclusionThis study provides critical evidence for understanding health service utilization and disease burden in Iraqi Kurdistan, using a real-time digital surveillance system. The findings confirm the presence of a double burden of disease in a population undergoing rapid transition and underscore the need for integrated, age-and sex-sensitive health interventions.

Since 2008, HIV/AIDS remains the most fatal infectious disease in China. In 2021, almost ** out of one million people in China died from AIDS. Tuberculosis stood at the second place, while rabies ranked the fourth.

Who are the high risk groups?

The HIV/AIDS epidemic has become a growing concern for the major population in China. A majority of new infections were the result from sexual transmission. Although the prevalence rate has been relatively low, the trend of new diagnoses in people aged from 15 to 24 years has been alarming, with gay men disproportionately represented.

Children under the age of ** are the most vulnerable group to contract common infectious diseases like influenza and HFMD. The Chinese government has thus introduced healthcare initiatives dedicated to vaccinating children up to the age of ** under the Extended Program for Immunization (EPI). The efforts have been fruitful with significant improvement in the healthcare status of children under the age of **** in the country.

How is disease controlled in China?

The world’s most populous nation has made considerable efforts in tracking and preventing the spread of infectious diseases. Alongside geographical and demographic challenges, the mortality rate of infectious diseases has seen a slight increase over the recent years. Seasonal diseases, especially Influenza and mumps, are easily widespread and have pressed the demand for efficient disease prevention and control. In response, the Chinese government has ramped up the supply of influenza vaccines and HPV vaccines.

Heart Disease Deaths in Oklahoma

Current Trends and Target Rates

By Oklahoma [source]

About this dataset

This dataset contains an overview of historical heart disease death rates in Oklahoma from 2000 to 2018. The dataset consists of yearly figures and target figures for the numbers of deaths due to heart diseases, allowing a comparison between the expected rate and the actual rate over time. This data is important as it can be used to analyze trends in heart disease death rates, helping inform public health initiatives and policy decisions

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How to use the dataset

This dataset includes the number of death due to heart disease in Oklahoma. It provides a single, comprehensive data set that captures detailed information on the historical prevalence of heart disease death rates in the state. This dataset can be used for various research or analytical purposes such as epidemiological studies or health services planning.

To use this dataset, one must first understand that it contains three main pieces: the year of reported deaths, the actual number of deaths related to heart disease during each year and a target total for expected deaths from heart disease per year, which are used as reference points when analyzing other years. The years column includes all relevant dates while historical data column provides more specifics such as exact numbers and percentages related to those who perished due to heart-related conditions.

By utilizing this data set users can easily find out how many persons died due to cardiac-related diseases along with what risks were most prevalent at certain times over that period by comparing provided figures with reference targets at any given time slice in question (time point). Additionally, one can observe trends carefully within different groups such as males versus females or rural versus urban locations thus allowing them more robust insight into factors associated with mortality from cardiac conditions across different demographics

Research Ideas

• Identifying which geographic areas in Oklahoma are at highest risk for heart disease and creating targeted public health initiatives to reduce its incidence.
• Determining correlations between changes in vital health indicators (e.g., increase of physical activity) with changes in heart disease death rates to better inform policy and research direction.
• Analyzing overall mortality rates compared to other counties or states with comparable demographics to assess the effectiveness of existing public health interventions over time

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: res_heart_disease_deaths_kdjx-hayj.csv | Column name | Description | |:--------------------|:-----------------------------------------------------------------------------------------------------------------------------------------| | Years | The year associated with the data. (Integer) | | Historical Data | The number of deaths due to heart disease in Oklahoma in that particular year from 2000-2018. (Integer) | | Target | A value generated based on Historical Data indicating what should be targeted as a baseline performance measure going forward. (Integer) |

File: res_heart_disease_deaths_-_column_chart_3a28-gndr.csv | Column name | Description | |:--------------------|:-----------------------------------------------------------------------------------------------------------------------------------------| | Years | The year associated with the data. (Integer) | | Historical Data | The number of deaths due to heart disease in Oklahoma in that particular year from 2000-2018. (Integer) | | Target | A value generated based on Historical Data indicating what should be targeted as a baseline performance measure going forward. (Integer) |

Acknowledgements

...

Snapshot img

Infectious Disease Market Size 2025-2029

The infectious disease market size is forecast to increase by USD 160.8 billion at a CAGR of 14.7% between 2024 and 2029.

The market is experiencing significant growth due to the rising prevalence of bacterial diseases such as Clostridium and Staphylococcus, which necessitate advanced diagnostics. Immunodiagnostics and next-generation sequencing (NGS) are emerging as key technologies in infectious disease diagnostics, offering faster and more accurate results than traditional methods. The development of novel drugs for tuberculosis (TB) and sepsis is another growth driver, as is the increasing demand for molecular diagnostics. However, the market faces challenges such as the adverse effects of generic drugs and the high cost of developing new anti-infective drugs. The use of NGS in infectious disease diagnostics is a major trend, enabling the identification of multiple pathogens in a single test and facilitating personalized treatment plans.
In summary, the market is driven by the rising prevalence of infectious diseases, the development of novel drugs, and the adoption of advanced diagnostics, but is challenged by the high cost of drug development and the adverse effects of generic drugs. Immunodiagnostics and NGS are key technologies driving market growth.

What will be the Size of the Infectious Disease Market During the Forecast Period?

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The market encompasses diagnostic tools and technologies designed to promptly identify various pathogens, including bacteria, viruses, and parasites. This market is driven by the urgent need for accurate and rapid results in diverse healthcare settings, such as point-of-care diagnostic testing in urgent care centers, emergency rooms, and ambulances. The importance of infectious disease diagnostics extends beyond healthcare facilities, as personal health and infection control are increasingly prioritized in everyday life. 
Market dynamics are influenced by several factors, including inadequate infrastructure and poor water sanitation in certain regions, which contribute to the spread of infectious diseases. The ongoing demand for improved patient outcomes necessitates the development of advanced diagnostic technologies, such as immunodiagnostics, clinical microbiology, DNA sequencing, next-generation sequencing (NGS), DNA microarray, and various tests for diseases like hepatitis, syphilis, mosquito-borne diseases, gonorrhea, and RNA viruses.
Healthcare professionals are under constant pressure to provide accurate diagnoses and implement effective infection control measures. As a result, there is a growing emphasis on training and education to ensure the proper use and interpretation of diagnostic tools. The market is expected to continue growing as the global population's healthcare needs evolve and advancements in diagnostics technology are made.

How is this Infectious Disease Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Drugs
  Vaccines


End-user

  Hospital
  Multispecialty clinic
  Others


Type

  Bacterial infections
  Viral infections
  Fungal infections
  Parasitic infections


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy


  Asia

    China
    India
    Japan


  Rest of World (ROW)

By Product Insights

The drugs segment is estimated to witness significant growth during the forecast period. The market is driven by several key factors, including increasing government initiatives and non-profit organization efforts, the prevalence of various infectious diseases, and rising research and development funding. Infectious diseases such as influenza, giardiasis, HIV/AIDS, mononucleosis, and the common cold continue to pose a significant health concern. Point-of-care diagnostic testing, which offers rapid results and prompt diagnosis, is increasingly being adopted in urgent care centers, emergency rooms, ambulances, and physician offices. Inadequate infrastructure, poor water sanitation, and lack of training for healthcare professionals remain challenges in controlling the spread of infectious diseases. Pathogens such as bacteria, viruses, fungi, and parasites can cause respiratory diseases, hospital-acquired infections, sexually transmitted infections, and mosquito-borne diseases.

Technologies like chest X-rays, CT scans, physical exams, laboratory tests, PCR testing, and immunodiagnostics are used for diagnosis. Infection control, personal health, hygiene, and preventative healthcare are essential to mitigate the impact of infectious diseases. The market for infectious disease diagnostics includes kits, cons

Humans live in complex socio-ecological systems where we interact with parasites and pathogens that spend time in abiotic and biotic environmental reservoirs (e.g., water, air, soil, other vertebrate hosts, vectors, intermediate hosts). Through a synthesis of published literature, we reviewed the life cycles and environmental persistence of 150 parasites and pathogens tracked by the World Health Organization's Global Burden of Disease study. We used those data to derive the time spent in each component of a pathogen's life cycle, including total time spent in humans versus all environmental stages. We found that nearly all infectious organisms were “environmentally mediated” to some degree, meaning that they spend time in reservoirs and can be transmitted from those reservoirs to human hosts. Correspondingly, many infectious diseases were primarily controlled through environmental interventions (e.g., vector control, water sanitation), whereas few (14%) were primarily controlled by integrated methods (i.e., combining medical and environmental interventions). Data on critical life history attributes for most of the 150 parasites and pathogens were difficult to find and often uncertain, potentially hampering efforts to predict disease dynamics and model interactions between life cycle time scales and infection control strategies. We hope that this synthetic review and associated database serve as a resource for understanding both common patterns among parasites and pathogens and important variability and uncertainty regarding particular infectious diseases. These insights can be used to improve systems-based approaches for controlling environmentally mediated diseases of humans in an era where the environment is rapidly changing.

Context

A straightforward way to assess the health status of a population is to focus on mortality – or concepts like child mortality or life expectancy, which are based on mortality estimates. A focus on mortality, however, does not take into account that the burden of diseases is not only that they kill people, but that they cause suffering to people who live with them. Assessing health outcomes by both mortality and morbidity (the prevalent diseases) provides a more encompassing view on health outcomes. This is the topic of this entry. The sum of mortality and morbidity is referred to as the ‘burden of disease’ and can be measured by a metric called ‘Disability Adjusted Life Years‘ (DALYs). DALYs are measuring lost health and are a standardized metric that allow for direct comparisons of disease burdens of different diseases across countries, between different populations, and over time. Conceptually, one DALY is the equivalent of losing one year in good health because of either premature death or disease or disability. One DALY represents one lost year of healthy life. The first ‘Global Burden of Disease’ (GBD) was GBD 1990 and the DALY metric was prominently featured in the World Bank’s 1993 World Development Report. Today it is published by both the researchers at the Institute of Health Metrics and Evaluation (IHME) and the ‘Disease Burden Unit’ at the World Health Organization (WHO), which was created in 1998. The IHME continues the work that was started in the early 1990s and publishes the Global Burden of Disease study.

Content

In this Dataset, we have Historical Data of different cause of deaths for all ages around the World. The key features of this Dataset are: Meningitis, Alzheimer's Disease and Other Dementias, Parkinson's Disease, Nutritional Deficiencies, Malaria, Drowning, Interpersonal Violence, Maternal Disorders, HIV/AIDS, Drug Use Disorders, Tuberculosis, Cardiovascular Diseases, Lower Respiratory Infections, Neonatal Disorders, Alcohol Use Disorders, Self-harm, Exposure to Forces of Nature, Diarrheal Diseases, Environmental Heat and Cold Exposure, Neoplasms, Conflict and Terrorism, Diabetes Mellitus, Chronic Kidney Disease, Poisonings, Protein-Energy Malnutrition, Road Injuries, Chronic Respiratory Diseases, Cirrhosis and Other Chronic Liver Diseases, Digestive Diseases, Fire, Heat, and Hot Substances, Acute Hepatitis.

Dataset Glossary (Column-wise)

• 01. Country/Territory - Name of the Country/Territory
• 02. Code - Country/Territory Code
• 03. Year - Year of the Incident
• 04. Meningitis - No. of People died from Meningitis
• 05. Alzheimer's Disease and Other Dementias - No. of People died from Alzheimer's Disease and Other Dementias
• 06. Parkinson's Disease - No. of People died from Parkinson's Disease
• 07. Nutritional Deficiencies - No. of People died from Nutritional Deficiencies
• 08. Malaria - No. of People died from Malaria
• 09. Drowning - No. of People died from Drowning
• 10. Interpersonal Violence - No. of People died from Interpersonal Violence
• 11. Maternal Disorders - No. of People died from Maternal Disorders
• 12. Drug Use Disorders - No. of People died from Drug Use Disorders
• 13. Tuberculosis - No. of People died from Tuberculosis
• 14. Cardiovascular Diseases - No. of People died from Cardiovascular Diseases
• 15. Lower Respiratory Infections - No. of People died from Lower Respiratory Infections
• 16. Neonatal Disorders - No. of People died from Neonatal Disorders
• 17. Alcohol Use Disorders - No. of People died from Alcohol Use Disorders
• 18. Self-harm - No. of People died from Self-harm
• 19. Exposure to Forces of Nature - No. of People died from Exposure to Forces of Nature
• 20. Diarrheal Diseases - No. of People died from Diarrheal Diseases
• 21. Environmental Heat and Cold Exposure - No. of People died from Environmental Heat and Cold Exposure
• 22. Neoplasms - No. of People died from Neoplasms
• 23. Conflict and Terrorism - No. of People died from Conflict and Terrorism
• 24. Diabetes Mellitus - No. of People died from Diabetes Mellitus
• 25. Chronic Kidney Disease - No. of People died from Chronic Kidney Disease
• 26. Poisonings - No. of People died from Poisoning
• 27. Protein-Energy Malnutrition - No. of People died from Protein-Energy Malnutrition
• 28. Chronic Respiratory Diseases - No. of People died from Chronic Respiratory Diseases
• 29. Cirrhosis and Other Chronic Liver Diseases - No. of People died from Cirrhosis and Other Chronic Liver Diseases
• 30. Digestive Diseases - No. of People died from Digestive Diseases
• 31. Fire, Heat, and Hot Substances - No. of People died from Fire or Heat or any Hot Substances
• ...

The graph shows the changes in the impact factor of ^ and its corresponding percentile for the sake of comparison with the entire literature. Impact Factor is the most common scientometric index, which is defined by the number of citations of papers in two preceding years divided by the number of papers published in those years.

IntroductionThe demographic shift leads to a tremendous increase in age-related diseases, which are often chronic. Therefore, a focus of chronic disease management should be set on the maintenance or even improvement of the patients’ quality of life (QoL). One indicator to objectively measure QoL is the EQ-5D questionnaire, which was validated in a disease- and world region-specific manner. The aim of this study was to conduct a systematic literature review and meta-analysis on the QoL across the most frequent chronic diseases that utilized the EQ-5D and performed a disease-specific meta-analysis for treatment-dependent QoL improvement.Materials and methodsThe most common chronic disease in Germany were identified by their ICD-10 codes, followed by a systematic literature review of these ICD-10 codes and the EQ-5D index values. Finally, out of 10,016 independently -screened studies by two persons, 538 studies were included in the systematic review and 216 studies in the meta-analysis, respectively.ResultsWe found significant medium to large effect sizes of treatment effects, i.e., effect size >0.5, in musculoskeletal conditions with the exception of fractures, for chronic depression and for stroke. The effect size did not differ significantly from zero for breast and lung cancer and were significantly negative for fractures.ConclusionOur analysis showed a large variation between baseline and post-treatment scores on the EQ-5D health index, depending on the health condition. We found large gains in health-related quality of life mainly for interventions for musculoskeletal disease.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020150936, PROSPERO identifier CRD42020150936.

About Dataset

Context:

A straightforward way to assess the health status of a population is to focus on mortality – or concepts like child mortality or life expectancy, which are based on mortality estimates. A focus on mortality, however, does not take into account that the burden of diseases is not only that they kill people, but that they cause suffering to people who live with them. Assessing health outcomes by both mortality and morbidity (the prevalent diseases) provides a more encompassing view on health outcomes. This is the topic of this entry. The sum of mortality and morbidity is referred to as the ‘burden of disease’ and can be measured by a metric called ‘Disability Adjusted Life Years‘ (DALYs).

DALYs are measuring lost health and are a standardized metric that allow for direct comparisons of disease burdens of different diseases across countries, between different populations, and over time. Conceptually, one DALY is the equivalent of losing one year in good health because of either premature death or disease or disability. One DALY represents one lost year of healthy life. The first ‘Global Burden of Disease’ (GBD) was GBD 1990 and the DALY metric was prominently featured in the World Bank’s 1993 World Development Report. Today it is published by both the researchers at the Institute of Health Metrics and Evaluation (IHME) and the ‘Disease Burden Unit’ at the World Health Organization (WHO), which was created in 1998. The IHME continues the work that was started in the early 1990s and publishes the Global Burden of Disease study.

Content:

In this Dataset, we have Historical Data of different cause of deaths for all ages around the World. The key features of this Dataset are: Meningitis, Alzheimer's Disease and Other Dementias, Parkinson's Disease, Nutritional Deficiencies, Malaria, Drowning, Interpersonal Violence, Maternal Disorders, HIV/AIDS, Drug Use Disorders, Tuberculosis, Cardiovascular Diseases, Lower Respiratory Infections, Neonatal Disorders, Alcohol Use Disorders, Self-harm, Exposure to Forces of Nature, Diarrheal Diseases, Environmental Heat and Cold Exposure, Neoplasms, Conflict and Terrorism, Diabetes Mellitus, Chronic Kidney Disease, Poisonings, Protein-Energy Malnutrition, Road Injuries, Chronic Respiratory Diseases, Cirrhosis and Other Chronic Liver Diseases, Digestive Diseases, Fire, Heat, and Hot Substances, Acute Hepatitis.

Dataset Glossary (Column-wise):

1. Country/Territory - Name of the Country/Territory
2. Code - Country/Territory Code
3. Year - Year of the Incident
4. Meningitis - No. of People died from Meningitis
5. Alzheimer's Disease and Other Dementias - No. of People died from Alzheimer's Disease and Other Dementias
6. Parkinson's Disease - No. of People died from Parkinson's Disease
7. Nutritional Deficiencies - No. of People died from Nutritional Deficiencies
8. Malaria - No. of People died from Malaria
9. Drowning - No. of People died from Drowning
10. Interpersonal Violence - No. of People died from Interpersonal Violence
11. Maternal Disorders - No. of People died from Maternal Disorders
12. Drug Use Disorders - No. of People died from Drug Use Disorders
13. Tuberculosis - No. of People died from Tuberculosis
14. Cardiovascular Diseases - No. of People died from Cardiovascular Diseases
15. Lower Respiratory Infections - No. of People died from Lower Respiratory Infections
16. Neonatal Disorders - No. of People died from Neonatal Disorders
17. Alcohol Use Disorders - No. of People died from Alcohol Use Disorders
18. Self-harm - No. of People died from Self-harm
19. Exposure to Forces of Nature - No. of People died from Exposure to Forces of Nature
20. Diarrheal Diseases - No. of People died from Diarrheal Diseases
21. Environmental Heat and Cold Exposure - No. of People died from Environmental Heat and Cold Exposure
22. Neoplasms - No. of People died from Neoplasms
23. Conflict and Terrorism - No. of People died from Conflict and Terrorism
24. Diabetes Mellitus - No. of People died from Diabetes Mellitus
25. Chronic Kidney Disease - No. of People died from Chronic Kidney Disease
26. Poisonings - No. of People died from Poisoning
27. Protein-Energy Malnutrition - No. of People died from Protein-Energy Malnutrition
28. Chronic Respiratory Diseases - No. of People died from Chronic Respiratory Diseases
29. Cirrhosis and Other Chronic Liver Diseases - No. of People died from Cirrhosis and Other Chronic Liver Diseases
30. Digestive Diseases - No. of People died from Digestive Diseases
31. Fire, Heat, and Hot Substances - No. of People died from Fire or Heat or any Hot Substances
32. Acute Hepatitis - No. of People died from Acute Hepatitis Structure of the Dataset

Acknowledgement:

This Dataset is created from Our World in Data. This Dataset falls under open access under the Creative Commons BY license. You can check the FAQ for more informa...

Cardiovascular diseases cover all diseases of the heart and blood vessels – including heart attacks and strokes, atherosclerosis, ischemic heart disease, hypertensive diseases, cardiomyopathy, and others.

These diseases tend to develop gradually with age, especially when people have risk factors like high blood pressure, smoking, alcohol use, poor diet, and air pollution.

Together, cardiovascular diseases are the most common cause of death globally.

In 2000, around 14 million people died from cardiovascular diseases globally, while in 2019, close to 18 million died.

The rising death toll is largely due to a growing and aging global population. Death rates from cardiovascular diseases have actually fallen in many countries – as our ability to prevent and treat them has improved.

Large declines in smoking; improvements in screening, diagnosis, and monitoring; and advances in medical treatments, public health initiatives, emergency care, and surgical procedures, have all helped to reduce the impact of cardiovascular diseases on people’s lives.

Yet large disparities remain globally. The impact of cardiovascular diseases can be reduced much further with greater understanding and public health efforts.

Original Data

Acknowlegement

Foto von Kenny Eliason auf Unsplash

Background: Sexually transmitted infections (STIs) are contagious infections caused by bacteria, viruses or parasites typically diffused by sexual contact. Over the past few years, determinants such as urbanization and globalization modified human interactions and, consequently, have shaped the transmission, diffusion and persistence of infection in the population affecting the epidemiological behavior of STIs. Lately, there has been an increase in the number of STIs worldwide. The most common STIs around the globe include chlamydia, gonorrhea, and syphilis, which are caused by bacteria and can be easily treated with antibiotics. The re-emergence of these infections among the population represents a serious public health threat due to severe complications on the reproductive and neonatal health. Since these infections remain at high levels in the population, the World Health Organization included gonorrhea and syphilis on their prioritizing list to cease STIs epidemics, setting the goal of reducing by 90% the incidence of syphilis and gonorrhea by 2030. To ensure that this goal is achieved, a collective effort from different countries is necessary in order to understand the dynamics of STIs through surveillance. Spatial differences in STIs occurrence have been commonly seen between countries and regions. Although national estimates facilitate international comparisons, these cannot solve heterogeneity at the geographical level where public health actions usually take place. For that, it is important to monitor disease variation and identify high-risk communities using finer scales in order to develop targeted interventions towards the reduction of the burden of STIs. Despite the growing number of STIs cases reported in Portugal, a limited number of studies have investigated the epidemiology of these infections and, as far as we know, none have analyzed their spatial distribution and geographical determinants.Objective: This study aimed to map the spatial distribution, at the municipality level, of the most common STIs in Portugal: chlamydia, gonorrhea, and syphilis between 2015 and 2017; analyze the occurrence of spatial overlap between these STIs; identify high rate areas across Portuguese municipalities; and determine the association of these bacterial infections with contextual characteristics, namely, socioeconomic deprivation, urbanicity level, and population density. Methods: STIs notifications, at municipality level, for the period 2015-2017 were obtained from Portugal’s Epidemiologic Surveillance System (SINAVE), a real-time electronic platform used to collect data on communicable diseases and other public health risks. All notifications were geocoded according to the municipality of occurrence of the infection. To characterize the context of the STIs place of occurrence, the municipalities’ socioeconomic deprivation, urbanicity level and population density were used. Population density, at the municipality level, (inhabitants per squared kilometer) was obtained from the Portuguese National Institute of Statistics (INE). The population density was then categorized into quintiles, from quintile 1 (Q1) (lowest density) to quintile 5 (Q5) (highest density). Urbanicity level was determined according to the classification of the urban areas, published by Statistics Portugal in 2014. This classification groups the Portuguese parishes (a smaller administrative unit than municipalities) into three classes: predominantly urban areas, moderately urban areas and predominantly rural areas. As our unit of analysis was the municipality, we calculated an urbanicity index (U.I.) of each municipality by using a weighted average based on the parishes’ information. This U.I. was later categorized into quintiles, from least urban (Q1) to most urban (Q5). Lastly, the European deprivation index was used to classify the municipalities according to their level of socioeconomic deprivation which was categorized into quintiles (Q1: least deprived - Q5: most deprived). Spatial Bayesian models were used to calculate smoothed standardized notification rates, identify high and low rate areas and estimate associations (Relative Risk, RR, 95% Credible Intervals, 95%CrI). The resulting maps were created using ArcMap 10.5.1.Results: There were 4819 reported cases of chlamydia, gonorrhea and syphilis accounting for 15.3%, 33.2%, and 51.5% of the notifications, respectively. From 2015 to 2017, there was an increase in the number of cases of STIs (1432, 1448, and 1939 cases). The highest increase (110%) was observed in chlamydia infections with 173, 201, and 363 cases. A 40% rise in gonorrhoea (468, 474, 656) and an increase of 16% in syphilis (791, 773, 920) was also registered. For chlamydia, gonorrhea, and syphilis most notifications were observed in men, were mainly acquired by heterosexual contact, and affected mostly younger people. STIs notification rates were substantially higher in Porto and Lisbon Metropolitan Areas and concentrically disperse around those. Notification rates of the three STIs were strongly correlated (r>0.8). Rates of gonorrhea and syphilis were associated with population density (Q1-lowest density vs. Q5-highest RR=2.10 95%CrI 1.08-4.25 and RR=3.16 95%CrI 2.00-5.13, respectively). Notifications of chlamydia and syphilis increased with urbanity level (Q1- least urban vs. Q5-most RR=9.64, 95%CrI 1.73-93.59 and RR=1.92, 95%CrI 1.30-2.88, respectively). We also found that notification rates of gonorrhea were associated with socioeconomic deprivation (Q1-least vs. Q5-most deprived RR=1.75, 95%CrI 1.07-2.88).Figure 1 – Spatial distribution of the age-sex-standardized notification rates (/100,000 inhabitants) and identification of high rate municipalities for chlamydia, gonorrhea and syphilis (2015–2017, Portugal).Conclusions: These findings indicate that, in Portugal, there are wide spatial inequalities in STIs notification rates, which were predominantly concentrated in the two metropolitan areas of the country. Besides, different contextual factors influence the occurrence of STIs in the population. Our findings can contribute to guide more targeted interventions to reduce STIs incidence as it provides useful information on specific risk factors that might assist to explain differences in the studied STIs and target appropriate programs towards certain sociodemographic groups and geographic areas that could benefit most from an intervention. As notification rates of the three STIs are strongly correlated, combined interventions may be useful to increase the effectiveness of interventions and, in this way, achieve better health outcomes in a heterogeneous population. Some valuable approaches that could improve STIs morbidity patterns include: strengthening surveillance among subpopulations who are especially at risk of acquiring STIs, namely in the metropolitan areas; improve people’s knowledge about their sexual health through education and counselling in healthcare services and schools; and promote safe sexual health behaviors as well as periodic screening programs.