2010-2018; 2019. US Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States. The estimates for the 2010-2018 dataset are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. Median age is calculated based on single year of age. The estimates for 2019 are based on a one-year dataset that was published on the US Census website in 2021. For population estimates methodology statements, see http://www.census.gov/popest/methodology/index.html.

The Population online databases contain data from the US Census Bureau. The Census Estimates online database contains county-level population counts for years 1970 - 2000. The data comprise the April 1st Census counts for years 1970, 1980, 1990 and 2000, the July 1st intercensal estimates for years 1971-1979 and 1981-1989, and the July 1st postcensal estimates for years 1991-1999. The Census Projections online database contains population projections for years 2004-2030 by year, state, age, race and sex, produced by the Census Bureau in 2005. The data are produced by the United States Department of Commerce, U.S. Census Bureau, Population Division.

United States population health management market size reached USD 21.5 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 102.0 Billion by 2033, exhibiting a growth rate (CAGR) of 18.9% during 2025-2033. The increasing advances in healthcare information technology, including electronic health records (EHRs), data analytics, and interoperability, which have enhanced the capabilities of population health management solutions, are driving the market.

Abstract

The 2005 Vietnam Population and AIDS Indicator Survey (VPAIS) was designed with the objective of obtaining national and sub-national information about program indicators of knowledge, attitudes and sexual behavior related to HIV/AIDS. Data collection took place from 17 September 2005 until mid-December 2005.

The VPAIS was implemented by the General Statistical Office (GSO) in collaboration with the National Institute of Hygiene and Epidemiology (NIHE). ORC Macro provided financial and technical assistance for the survey through the USAID-funded MEASURE DHS program. Financial support was provided by the Government of Vietnam, the United States President’s Emergency Plan for AIDS Relief, the United States Agency for International Development (USAID), and the United States Centers for Disease Control and Prevention/Global AIDS Program (CDC/GAP).

The survey obtained information on sexual behavior, and knowledge, attitudes, and behavior regarding HIV/AIDS. In addition, in Hai Phong province, the survey also collected blood samples from survey respondents in order to estimate the prevalence of HIV. The overall goal of the survey was to provide program managers and policymakers involved in HIV/AIDS programs with strategic information needed to effectively plan, implement and evaluate future interventions.

The information is also intended to assist policymakers and program implementers to monitor and evaluate existing programs and to design new strategies for combating the HIV/AIDS epidemic in Vietnam. The survey data will also be used to calculate indicators developed by the United Nations General Assembly Special Session on HIV/AIDS (UNGASS), UNAIDS, WHO, USAID, the United States President’s Emergency Plan for AIDS Relief, and the HIV/AIDS National Response.

The specific objectives of the 2005 VPAIS were: • to obtain information on sexual behavior. • to obtain accurate information on behavioral indicators related to HIV/AIDS and other sexually transmitted infections. • to obtain accurate information on HIV/AIDS program indicators. • to obtain accurate estimates of the magnitude and variation in HIV prevalence in Hai Phong Province.

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49
• Men age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame for the 2005 Vietnam Population and AIDS Indicator Survey (VPAIS) was the master sample used by the General Statistical Office (GSO) for its annual Population Change Survey (PCS 2005). The master sample itself was constructed in 2004 from the 1999 Population and Housing Census. As was true for the VNDHS 1997 and the VNDHS 2002 the VPAIS 2005 is a nationally representative sample of the entire population of Vietnam.

The survey utilized a two-stage sample design. In the first stage, 251 clusters were selected from the master sample. In the second stage, a fixed number of households were systematically selected within each cluster, 22 households in urban areas and 28 in rural areas.

The total sample of 251 clusters is comprised of 97 urban and 154 rural clusters. HIV/AIDS programs have focused efforts in the four provinces of Hai Phong, Ha Noi, Quang Ninh and Ho Chi Minh City; therefore, it was determined that the sample should be selected to allow for representative estimates of these four provinces in addition to the national estimates. The selected clusters were allocated as follows: 35 clusters in Hai Phong province where blood samples were collected to estimate HIV prevalence; 22 clusters in each of the other three targeted provinces of Ha Noi, Quang Ninh and Ho Chi Minh City; and the remaining 150 clusters from the other 60 provinces throughout the country.

Prior to the VPAIS fieldwork, GSO conducted a listing operation in each of the selected clusters. All households residing in the sample points were systematically listed by teams of enumerators, using listing forms specially designed for this activity, and also drew sketch maps of each cluster. A total of 6,446 households were selected. The VPAIS collected data representative of: • the entire country, at the national level • for urban and rural areas • for three regions (North, Central and South), see Appendix for classification of regions. • for four target provinces: Ha Noi, Hai Phong, Quang Ninh and Ho Chi Minh City.

All women and men aged 15-49 years who were either permanent residents of the sampled households or visitors present in the household during the night before the survey were eligible to be interviewed in the survey. All women and men in the sample points of Hai Phong who were interviewed were asked to voluntarily give a blood sample for HIV testing. For youths aged 15-17, blood samples were drawn only after first obtaining consent from their parents or guardians.

(Refer Appendix A of the final survey report for details of sample implementation)

Mode of data collection

Face-to-face [f2f]

Research instrument

Two questionnaires were used in the survey, the Household Questionnaire and the Individual Questionnaire for women and men aged 15-49. The content of these questionnaires was based on the model AIDS Indicator Survey (AIS) questionnaires developed by the MEASURE DHS program implemented by ORC Macro.

In consultation with government agencies and local and international organizations, the GSO and NIHE modified the model questionnaires to reflect issues in HIV/AIDS relevant to Vietnam. These questionnaires were then translated from English into Vietnamese. The questionnaires were further refined after the pretest.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, relationship to the head of the household, education, basic material needs, survivorship and residence of biological parents of children under the age of 18 years and birth registration of children under the age of 5 years. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of drinking water, type of toilet facilities, type of material used in the flooring of the house, and ownership of various durable goods, in order to allow for the calculation of a wealth index. The Household Questionnaire also collected information regarding ownership and use of mosquito nets.

The Individual Questionnaire was used to collect information from all women and men aged 15-49 years.

All questionnaires were administered in a face-to-face interview. Because cultural norms in Vietnam restrict open discussion of sexual behavior, there is concern that this technique may contribute to potential under-reporting of sexual activity, especially outside of marriage.

All aspects of VPAIS data collection were pre-tested in July 2005. In total, 24 interviewers (12 men and 12 women) were involved in this task. They were trained for thirteen days (including three days of fieldwork practice) and then proceeded to conduct the survey in the various urban and rural districts of Ha Noi. In total, 240 individual interviews were completed during the pretest. The lessons learnt from the pretest were used to finalize the survey instruments and logistical arrangements for the survey and blood collection.

Cleaning operations

The data processing of the VPAIS questionnaire began shortly after the fieldwork commenced. The first stage of data editing was done by the field editors, who checked the questionnaires for completeness and consistency. Supervisors also reviewed the questionnaires in the field. The completed questionnaires were then sent periodically to the GSO in Ha Noi by mail for data processing.

The office editing staff first checked that questionnaires of all households and eligible respondents had been received from the field. The data were then entered and edited using CSPro, a software package developed collaboratively between the U.S. Census Bureau, ORC Macro, and SerPRO to process complex surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, as VPAIS staff was able to advise field teams of errors detected during data entry. The data entry and editing phases of the survey were completed by the end of December 2005.

Response rate

A total of 6,446 households were selected in the sample, of which 6,346 (98 percent) were found to be occupied at the time of the fieldwork. Occupied households include dwellings in which the household was present but no competent respondent was home, the household was present but refused the interview, and dwellings that were not found. Of occupied households, 6,337 were interviewed, yielding a household response rate close to 100 percent.

All women and men aged 15-49 years who were either permanent residents of the sampled households or visitors present in the household during the night before the survey were eligible to be interviewed in the survey. Within interviewed households, a total of 7,369 women aged 15-49 were identified as eligible for interview, of whom 7,289 were interviewed, yielding a response rate to the Individual interview of 99 percent among women. The high response rate was also achieved in male interviews. Among the 6,788 men aged 15-49 identified as eligible for interview, 6,707 were successfully interviewed, yielding a response rate of 99 percent.

Sampling error

Snapshot img

Population Health Management Market Size 2025-2029

The population health management market size is valued to increase USD 19.40 billion, at a CAGR of 10.7% from 2024 to 2029. Rising adoption of healthcare IT will drive the population health management market.

Major Market Trends & Insights

North America dominated the market and accounted for a 68% growth during the forecast period.
By Component - Software segment was valued at USD 16.04 billion in 2023
By End-user - Large enterprises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 113.32 billion
Market Future Opportunities: USD 19.40 billion
CAGR : 10.7%
North America: Largest market in 2023

Market Summary

The market encompasses a continually evolving landscape of core technologies and applications, service types, and regulatory frameworks. With the rising adoption of healthcare IT solutions, population health management platforms are increasingly being adopted to improve patient outcomes and reduce costs. According to a recent study, The market is expected to witness a significant growth, with over 30% of healthcare organizations implementing these solutions by 2025. The focus on personalized medicine and the need to manage the rising cost of healthcare are major drivers for this trend. Core technologies such as data analytics, machine learning, and telehealth are transforming the way healthcare providers manage patient populations.
Despite these opportunities, challenges such as data privacy concerns, interoperability issues, and the high cost of implementation persist. The market is further shaped by regional differences in regulatory frameworks and healthcare infrastructure. For instance, in North America, the Affordable Care Act has fueled the adoption of population health management solutions, while in Europe, the European Medicines Agency's focus on personalized medicine is driving demand.

What will be the Size of the Population Health Management Market during the forecast period?

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How is the Population Health Management Market Segmented and what are the key trends of market segmentation?

The population health management 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.

Component

  Software
  Services


End-user

  Large enterprises
  SMEs


Delivery Mode

  On-Premise
  Cloud-Based
  Web-Based
  On-Premise
  Cloud-Based


End-Use

  Providers
  Payers
  Employer Groups
  Government Bodies
  Providers
  Payers
  Employer Groups


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

The market is experiencing significant growth, with the software segment playing a crucial role in this expansion. Currently, remote patient monitoring solutions are witnessing a 25% adoption rate, enabling healthcare providers to monitor patients' health in real-time and intervene promptly when necessary. Additionally, predictive modeling and risk stratification models are being utilized to identify high-risk patients and provide personalized care plans, contributing to a 21% increase in disease management efficiency. Furthermore, the integration of electronic health records, wellness programs, care coordination platforms, and value-based care models is fostering a data-driven approach to healthcare, leading to a 19% reduction in healthcare costs.

Health equity initiatives and healthcare data analytics are essential components of population health management, ensuring equitable access to care and improving healthcare quality metrics. Looking ahead, the market is expected to grow further, with utilization management and care management programs seeing a 27% increase in implementation. Preventive health programs and clinical decision support systems are also anticipated to experience a 24% surge in adoption, emphasizing the importance of proactive care and early intervention. Moreover, population health strategies are evolving to incorporate behavioral health integration, interoperability standards, and disease registry data to provide comprehensive care. The use of disease prevalence data and public health surveillance is becoming increasingly crucial in addressing population health challenges and improving overall health outcomes.

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The Software segment was valued at USD 16.04 billion in 2019 and showed a gradual increase during the forecast period.

In conclusion, the market is

U.S. Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States. The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. Median age is calculated based on single year of age. For population estimates methodology statements, see http://www.census.gov/popest/methodology/index.html.

United States Unemployment: Management, Professional & Related data was reported at 1,575.000 Person th in Jun 2018. This records an increase from the previous number of 1,083.000 Person th for May 2018. United States Unemployment: Management, Professional & Related data is updated monthly, averaging 1,459.000 Person th from Jan 2000 (Median) to Jun 2018, with 222 observations. The data reached an all-time high of 3,034.000 Person th in Jul 2009 and a record low of 689.000 Person th in Dec 2000. United States Unemployment: Management, Professional & Related data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G016: Current Population Survey: Unemployment.

Goal 3Ensure healthy lives and promote well-being for all at all agesTarget 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live birthsIndicator 3.1.1: Maternal mortality ratioSH_STA_MORT: Maternal mortality ratioIndicator 3.1.2: Proportion of births attended by skilled health personnelSH_STA_BRTC: Proportion of births attended by skilled health personnel (%)Target 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live birthsIndicator 3.2.1: Under-5 mortality rateSH_DYN_IMRTN: Infant deaths (number)SH_DYN_MORT: Under-five mortality rate, by sex (deaths per 1,000 live births)SH_DYN_IMRT: Infant mortality rate (deaths per 1,000 live births)SH_DYN_MORTN: Under-five deaths (number)Indicator 3.2.2: Neonatal mortality rateSH_DYN_NMRTN: Neonatal deaths (number)SH_DYN_NMRT: Neonatal mortality rate (deaths per 1,000 live births)Target 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseasesIndicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populationsSH_HIV_INCD: Number of new HIV infections per 1,000 uninfected population, by sex and age (per 1,000 uninfected population)Indicator 3.3.2: Tuberculosis incidence per 100,000 populationSH_TBS_INCD: Tuberculosis incidence (per 100,000 population)Indicator 3.3.3: Malaria incidence per 1,000 populationSH_STA_MALR: Malaria incidence per 1,000 population at risk (per 1,000 population)Indicator 3.3.4: Hepatitis B incidence per 100,000 populationSH_HAP_HBSAG: Prevalence of hepatitis B surface antigen (HBsAg) (%)Indicator 3.3.5: Number of people requiring interventions against neglected tropical diseasesSH_TRP_INTVN: Number of people requiring interventions against neglected tropical diseases (number)Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-beingIndicator 3.4.1: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory diseaseSH_DTH_NCOM: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability)SH_DTH_NCD: Number of deaths attributed to non-communicable diseases, by type of disease and sex (number)Indicator 3.4.2: Suicide mortality rateSH_STA_SCIDE: Suicide mortality rate, by sex (deaths per 100,000 population)SH_STA_SCIDEN: Number of deaths attributed to suicide, by sex (number)Target 3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcoholIndicator 3.5.1: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disordersSH_SUD_ALCOL: Alcohol use disorders, 12-month prevalence (%)SH_SUD_TREAT: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disorders (%)Indicator 3.5.2: Alcohol per capita consumption (aged 15 years and older) within a calendar year in litres of pure alcoholSH_ALC_CONSPT: Alcohol consumption per capita (aged 15 years and older) within a calendar year (litres of pure alcohol)Target 3.6: By 2020, halve the number of global deaths and injuries from road traffic accidentsIndicator 3.6.1: Death rate due to road traffic injuriesSH_STA_TRAF: Death rate due to road traffic injuries, by sex (per 100,000 population)Target 3.7: By 2030, ensure universal access to sexual and reproductive health-care services, including for family planning, information and education, and the integration of reproductive health into national strategies and programmesIndicator 3.7.1: Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methodsSH_FPL_MTMM: Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods (% of women aged 15-49 years)Indicator 3.7.2: Adolescent birth rate (aged 10–14 years; aged 15–19 years) per 1,000 women in that age groupSP_DYN_ADKL: Adolescent birth rate (per 1,000 women aged 15-19 years)Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for allIndicator 3.8.1: Coverage of essential health servicesSH_ACS_UNHC: Universal health coverage (UHC) service coverage indexIndicator 3.8.2: Proportion of population with large household expenditures on health as a share of total household expenditure or incomeSH_XPD_EARN25: Proportion of population with large household expenditures on health (greater than 25%) as a share of total household expenditure or income (%)SH_XPD_EARN10: Proportion of population with large household expenditures on health (greater than 10%) as a share of total household expenditure or income (%)Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contaminationIndicator 3.9.1: Mortality rate attributed to household and ambient air pollutionSH_HAP_ASMORT: Age-standardized mortality rate attributed to household air pollution (deaths per 100,000 population)SH_STA_AIRP: Crude death rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_STA_ASAIRP: Age-standardized mortality rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_AAP_MORT: Crude death rate attributed to ambient air pollution (deaths per 100,000 population)SH_AAP_ASMORT: Age-standardized mortality rate attributed to ambient air pollution (deaths per 100,000 population)SH_HAP_MORT: Crude death rate attributed to household air pollution (deaths per 100,000 population)Indicator 3.9.2: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (exposure to unsafe Water, Sanitation and Hygiene for All (WASH) services)SH_STA_WASH: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (deaths per 100,000 population)Indicator 3.9.3: Mortality rate attributed to unintentional poisoningSH_STA_POISN: Mortality rate attributed to unintentional poisonings, by sex (deaths per 100,000 population)Target 3.a: Strengthen the implementation of the World Health Organization Framework Convention on Tobacco Control in all countries, as appropriateIndicator 3.a.1: Age-standardized prevalence of current tobacco use among persons aged 15 years and olderSH_PRV_SMOK: Age-standardized prevalence of current tobacco use among persons aged 15 years and older, by sex (%)Target 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade-Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for allIndicator 3.b.1: Proportion of the target population covered by all vaccines included in their national programmeSH_ACS_DTP3: Proportion of the target population with access to 3 doses of diphtheria-tetanus-pertussis (DTP3) (%)SH_ACS_MCV2: Proportion of the target population with access to measles-containing-vaccine second-dose (MCV2) (%)SH_ACS_PCV3: Proportion of the target population with access to pneumococcal conjugate 3rd dose (PCV3) (%)SH_ACS_HPV: Proportion of the target population with access to affordable medicines and vaccines on a sustainable basis, human papillomavirus (HPV) (%)Indicator 3.b.2: Total net official development assistance to medical research and basic health sectorsDC_TOF_HLTHNT: Total official development assistance to medical research and basic heath sectors, net disbursement, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_HLTHL: Total official development assistance to medical research and basic heath sectors, gross disbursement, by recipient countries (millions of constant 2018 United States dollars)Indicator 3.b.3: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basisSH_HLF_EMED: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basis (%)Target 3.c: Substantially increase health financing and the recruitment, development, training and retention of the health workforce in developing countries, especially in least developed countries and small island developing StatesIndicator 3.c.1: Health worker density and distributionSH_MED_DEN: Health worker density, by type of occupation (per 10,000 population)SH_MED_HWRKDIS: Health worker distribution, by sex and type of occupation (%)Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risksIndicator 3.d.1: International Health Regulations (IHR) capacity and health emergency preparednessSH_IHR_CAPS: International Health Regulations (IHR) capacity, by type of IHR capacity (%)Indicator 3.d.2: Percentage of bloodstream infections due to selected antimicrobial-resistant organismsiSH_BLD_MRSA: Percentage of bloodstream infection due to methicillin-resistant Staphylococcus aureus (MRSA) among patients seeking care and whose

The 1965 National Fertility Survey was the first of three surveys that succeeded the Growth of American Families surveys (1955 and 1960) aimed at examining marital fertility and family planning in the United States. Currently married women were queried on the following main topics: residence history, marital history, education, income and employment, family background, religiosity, attitudes toward contraception and sterilization, birth control pill use and other methods of contraception, fecundity, family size, fertility expectations and intentions, abortion, and world population growth. Respondents were asked about their residence history, including what state they grew up in, whether they had lived with both of their parents at the age of 14, and whether they had spent any time living on a farm. Respondents were also asked a series of questions about their marital history. Specifically, they were asked about the duration of their current marriage, whether their current marriage was their first marriage, total number of times they had been married, how previous marriages ended, length of engagement, and whether their husband had children from a previous marriage. Respondents were asked what was the highest grade of school that they had completed, whether they had attended a co-ed college, and to give the same information about their husbands. Respondents were asked about their 1965 income, both individual and combined, their occupation, whether they had been employed since marriage, if and when they stopped working, and whether they were self-employed. They were also asked about their husband's recent employment status. With respect to family background, respondents were asked about their parents' and their husband's parents' nationalities, education, religious preferences, and total number children born alive to their mother and mother-in-law, respectively. In addition, respondents were asked about their, and their husband's, religious practices including their religious preferences, whether they had ever received any Catholic education, how religious-minded they perceived themselves to be, how often they prayed at home, and how often they went to see a minister, rabbi, or priest. Respondents were asked to give their opinions with respect to contraception and sterilization. They were asked whether they approved or disapproved of contraception in general, as well as specific forms of contraception, whether information about birth control should be available to married and unmarried couples, and whether the federal government should support birth control programs in the United States and in other countries. They were also asked whether they approved or disapproved of sterilization operations for men and women and whether they thought such a surgery would impair a man's sexual ability. Respondents were asked about their own knowledge and use of birth control pills. They were asked if they had ever used birth control pills and when they first began using them. They were then asked to give a detailed account of their use of birth control pills between 1960 and 1965. Respondents were also asked to explain when they discontinued use of birth control pills and what the motivation was for doing so. Respondents were also asked about their reproductive cycle, the most fertile days in their cycle, the regularity of their cycle, and whether there were any known reasons why they could not have or would have problems having children. Respondents were asked about their ideal number of children, whether they had their ideal number of children or if they really wanted fewer children, as well as whether their husbands wanted more or less children than they did. Respondents were then asked how many additional births they expected, how many total births they expected, when they expected their next child, and at what age they expected to have their last child. Respondents were asked how they felt about interrupting a pregnancy and whether they approved of abortion given different circumstances such as if the pregnancy endangered the woman's health, if the woman was not married, if the couple could not afford another child, if the couple did not want another child, if the woman thought the child would be deformed, or if the woman had been raped. Respondents were also asked to share their opinions with respect to world population growth. T

Animal Population Control Market Outlook

According to our latest research, the global animal population control market size in 2024 stands at USD 2.47 billion, with a robust compound annual growth rate (CAGR) of 6.8% projected through the forecast period. By 2033, the market is expected to reach a value of USD 4.84 billion, reflecting the growing emphasis on animal welfare, public health, and sustainable management practices. The primary growth factor driving this market is the increasing awareness among governments and animal welfare organizations regarding the adverse effects of uncontrolled animal populations, including zoonotic disease transmission, ecological imbalance, and public safety concerns.

One of the most significant growth drivers for the animal population control market is the heightened focus on public health and zoonotic disease prevention. As urbanization accelerates and human-animal interactions become more frequent, the risk of disease transmission from stray and wild animals to humans has increased. Governments and health agencies worldwide are investing heavily in animal birth control programs, vaccination campaigns, and sterilization initiatives to mitigate the spread of diseases such as rabies, leptospirosis, and other zoonoses. These efforts are further bolstered by international organizations like the World Health Organization (WHO) and World Organisation for Animal Health (OIE), which advocate for humane and effective animal population management as a critical component of global health security. The integration of advanced sterilization techniques, including non-surgical and chemical methods, has also expanded the toolkit available to veterinarians and animal welfare professionals, making population control more accessible and efficient.

Another pivotal factor fueling the expansion of the animal population control market is the increasing involvement of animal welfare organizations and non-governmental organizations (NGOs). These entities play a crucial role in implementing on-ground sterilization drives, awareness campaigns, and rescue operations, especially in regions with high stray animal populations. Their collaborations with local governments, veterinary clinics, and international donors have led to the development of sustainable and scalable population control programs. Additionally, the rising trend of pet adoption and responsible pet ownership in developed and emerging economies has amplified the demand for sterilization and contraceptive solutions for companion animals. This shift in societal attitudes towards animal welfare is not only driving market growth but also encouraging innovation in non-invasive and reversible contraception methods, which are gaining traction due to their ethical and practical benefits.

Technological advancements and regulatory support have also played a significant role in shaping the animal population control market. Innovations in non-surgical sterilization, such as immunocontraceptives and chemical sterilants, are providing safer and more cost-effective alternatives to traditional surgical procedures. Regulatory agencies in several countries are streamlining approval processes for new contraceptive products, recognizing their potential to address overpopulation humanely and efficiently. Furthermore, the integration of digital technologies for tracking, monitoring, and managing animal populations is enhancing the effectiveness of control programs. These technological developments, coupled with favorable government policies and funding, are expected to sustain the market's upward trajectory throughout the forecast period.

From a regional perspective, North America currently dominates the animal population control market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The United States, in particular, has set benchmarks with its extensive spay/neuter programs, robust regulatory framework, and active participation from animal welfare organizations. Europe is witnessing steady growth, driven by stringent animal welfare laws and increasing public awareness. Meanwhile, the Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, rising stray animal populations, and government initiatives to curb zoonotic diseases. Latin America and the Middle East & Africa are also showing promising potential, with increasing investments in animal health infrastructure and population control measures. These regional dynamics hi

The Population - Bridged-Race July 1st Estimates online databases report bridged-race population estimates of the July 1st resident population of the United States, based on Census 2000 counts, for use in calculating vital rates. These estimates result from "bridging" the 31 race categories used in Census 2000, as specified in the 1997 Office of Management and Budget (OMB) standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (Asian or Pacific Islander, Black or African American, American Indian or Alaska Native, White). Many data systems, such as vital statistics, are continuing to use the 1977 OMB standards during the transition to full implementation of the 1997 OMB standards. Postcensal estimates are available for year 2000 - 2009; intercensal estimates are available for the years 1990-1999. Obtain population counts by Year, State, County, Race (4-categories), Ethnicity, Sex and Age (1-year or 5-year groups). The data are released by the National Center for Health Statistics.

The 2018 edition of Woods and Poole Complete U.S. Database provides annual historical data from 1970 (some variables begin in 1990) and annual projections to 2050 of population by race, sex, and age, employment by industry, earnings of employees by industry, personal income by source, households by income bracket and retail sales by kind of business. The Complete U.S. Database contains annual data for all economic and demographic variables for all geographic areas in the Woods & Poole database (the U.S. total, and all regions, states, counties, and CBSAs). The Complete U.S. Database has following components: Demographic & Economic Desktop Data Files: There are 122 files covering demographic and economic data. The first 31 files (WP001.csv – WP031.csv) cover demographic data. The remaining files (WP032.csv – WP122.csv) cover economic data. Demographic DDFs: Provide population data for the U.S., regions, states, Combined Statistical Areas (CSAs), Metropolitan Statistical Areas (MSAs), Micropolitan Statistical Areas (MICROs), Metropolitan Divisions (MDIVs), and counties. Each variable is in a separate .csv file. Variables: Total Population Population Age (breakdown: 0-4, 5-9, 10-15 etc. all the way to 85 & over) Median Age of Population White Population Population Native American Population Asian & Pacific Islander Population Hispanic Population, any Race Total Population Age (breakdown: 0-17, 15-17, 18-24, 65 & over) Male Population Female Population Economic DDFs: The other files (WP032.csv – WP122.csv) provide employment and income data on: Total Employment (by industry) Total Earnings of Employees (by industry) Total Personal Income (by source) Household income (by brackets) Total Retail & Food Services Sales ( by industry) Net Earnings Gross Regional Product Retail Sales per Household Economic & Demographic Flat File: A single file for total number of people by single year of age (from 0 to 85 and over), race, and gender. It covers all U.S., regions, states, CSAs, MSAs and counties. Years of coverage: 1990 - 2050 Single Year of Age by Race and Gender: Separate files for number of people by single year of age (from 0 years to 85 years and over), race (White, Black, Native American, Asian American & Pacific Islander and Hispanic) and gender. Years of coverage: 1990 through 2050. DATA AVAILABLE FOR 1970-2019; FORECASTS THROUGH 2050

The files in the data directory contain estimates of population and poverty.

The school districts for which we have estimates were 
identified in the **2022 school district mapping survey**,
which asked about all school districts as of January 1, 2023 and 
used school district boundaries for the 2021-2022 school year.

The 2022 estimates are consistent with the population controls and 
income concepts used in the American Community Survey single-year 
estimates.  

There is one file for each of the states, the District of Columbia, and 
the entire United States. Each file contains the FIPS state code, 
Department of Education Common Core of Data (CCD) ID numbers, District names, 
the total population, population of school-age children, and estimated 
number of school-age children in poverty related to the head of the household.

United States Employment: Management, Professional & Related data was reported at 61,349.000 Person th in Jun 2018. This records a decrease from the previous number of 62,360.000 Person th for May 2018. United States Employment: Management, Professional & Related data is updated monthly, averaging 46,418.000 Person th from Jan 1983 (Median) to Jun 2018, with 426 observations. The data reached an all-time high of 63,067.000 Person th in Mar 2018 and a record low of 28,533.000 Person th in Jan 1983. United States Employment: Management, Professional & Related data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G013: Current Population Survey: Employment.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..This table provides geographical mobility for persons relative to their residence at the time they were surveyed. The characteristics crossed by geographical mobility reflect the current survey year..The number of people moving out of Alaska to a different state has been overestimated in previous years due to collection issues. See Errata Notes for details..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

United States Unemployment: Management, Business & Financial Operations data was reported at 536.000 Person th in Jun 2018. This records an increase from the previous number of 448.000 Person th for May 2018. United States Unemployment: Management, Business & Financial Operations data is updated monthly, averaging 607.000 Person th from Jan 2000 (Median) to Jun 2018, with 222 observations. The data reached an all-time high of 1,243.000 Person th in Dec 2010 and a record low of 276.000 Person th in Apr 2000. United States Unemployment: Management, Business & Financial Operations data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G016: Current Population Survey: Unemployment.

Graph and download economic data for Population (POPTHM) from Jan 1959 to Aug 2025 about population and USA.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.Using these data, the COVID-19 community level was classified as low, medium, or high.COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.Archived Data Notes:This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflect

USD 6702.21 Million in 2024; projected USD 27038.2 Million by 2033; CAGR 16.83%.

The North America Population Health Management market report offers a thorough competitive analysis, mapping key players’ strategies, market share, and business models. It provides insights into competitor dynamics, helping companies align their strategies with the current market landscape and future trends.