United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 0.500 % in 2014. This stayed constant from the previous number of 0.500 % for 2013. United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 0.500 % from Dec 2008 (Median) to 2014, with 7 observations. The data reached an all-time high of 0.500 % in 2014 and a record low of 0.500 % in 2014. United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.; ; UNAIDS estimates.; Weighted Average;

United States US: Incidence of HIV: per 1,000 Uninfected Population Aged 15-49 data was reported at 0.220 Ratio in 2018. This stayed constant from the previous number of 0.220 Ratio for 2017. United States US: Incidence of HIV: per 1,000 Uninfected Population Aged 15-49 data is updated yearly, averaging 0.250 Ratio from Dec 1990 (Median) to 2018, with 29 observations. The data reached an all-time high of 0.290 Ratio in 1990 and a record low of 0.220 Ratio in 2018. United States US: Incidence of HIV: per 1,000 Uninfected Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Number of new HIV infections among uninfected populations ages 15-49 expressed per 1,000 uninfected population in the year before the period.; ; UNAIDS estimates.; Weighted average;

This dataset helps to investigate the Spatial Accessibility to HIV Testing, Treatment, and Prevention Services in Illinois and Chicago, USA. The main components are: population data, healthcare data, GTFS feeds, and road network data. The core components are: 1) GTFS which contains GTFS (General Transit Feed Specification) data which is provided by Chicago Transit Authority (CTA) from Google's GTFS feeds. Documentation defines the format and structure of the files that comprise a GTFS dataset: https://developers.google.com/transit/gtfs/reference?csw=1. 2) HealthCare contains shapefiles describing HIV healthcare providers in Chicago and Illinois respectively. The services come from Locator.HIV.gov. 3) PopData contains population data for Chicago and Illinois respectively. Data come from The American Community Survey and AIDSVu. AIDSVu (https://map.aidsvu.org/map) provides data on PLWH in Chicago at the census tract level for the year 2017 and in the State of Illinois at the county level for the year 2016. The American Community Survey (ACS) provided the number of people aged 15 to 64 at the census tract level for the year 2017 and at the county level for the year 2016. The ACS provides annually updated information on demographic and socio economic characteristics of people and housing in the U.S. 4) RoadNetwork contains the road networks for Chicago and Illinois respectively from OpenStreetMap using the Python osmnx package. The abstract for our paper is: Accomplishing the goals outlined in “Ending the HIV (Human Immunodeficiency Virus) Epidemic: A Plan for America Initiative” will require properly estimating and increasing access to HIV testing, treatment, and prevention services. In this research, a computational spatial method for estimating access was applied to measure distance to services from all points of a city or state while considering the size of the population in need for services as well as both driving and public transportation. Specifically, this study employed the enhanced two-step floating catchment area (E2SFCA) method to measure spatial accessibility to HIV testing, treatment (i.e., Ryan White HIV/AIDS program), and prevention (i.e., Pre-Exposure Prophylaxis [PrEP]) services. The method considered the spatial location of MSM (Men Who have Sex with Men), PLWH (People Living with HIV), and the general adult population 15-64 depending on what HIV services the U.S. Centers for Disease Control (CDC) recommends for each group. The study delineated service- and population-specific accessibility maps, demonstrating the method’s utility by analyzing data corresponding to the city of Chicago and the state of Illinois. Findings indicated health disparities in the south and the northwest of Chicago and particular areas in Illinois, as well as unique health disparities for public transportation compared to driving. The methodology details and computer code are shared for use in research and public policy.

Users can access population data related to the screening, prevalence, and incidence of HIV and AIDS in the United States. Background The HIV/AIDS Statistics and Surveillance data is maintained by the Centers for Disease Control. Annual reports, fact sheets, slide sets, and basic statistics are available in a variety of formats. Fact sheets are available for a variety of subgroups including but not limited to examining HIV prevalence among different races, ages, and sexual orientations. Slide sets looking at HIV and AIDS prevalence among different groups and different regions are also available. The HIV Surveillance Report is available on an annual basis. User functionality Data is presented in report or fact sheet format and can be downloaded in PDF or HTML formats. Slide sets are available in PDF or PowerPoint format. Basic statistics and other information is avaible in HTML format. Data Notes The data sources are clearly referenced for each report, chart, and fact sheet. The most recent data is from 2009. Reports are published annually in the late summer or early fall

This data set contains Quarterly Results and yearly Targets by Operating Unit, Sub-National Units 1–2, PSNU Prioritization, Coarse Age and Sex for Fiscal Years 2016 – 2020 and the following subset of Testing and Treatment indicators: HTS_TST (People receiving testing and counseling services), HTS_TST_POS (People newly testing positive for HIV), TX_CURR (People currently receiving ART), TX_NEW (People newly enrolled in ART), TX_PVLS (Viral Load Documented) and TX_RET (People who have remained in treatment 12 months after ART initiation). Data can be downloaded as a compressed (zip) file, which contains text files in csv (comma separated values) format. For indicator definitions, please consult the latest MER Indicator Reference Guide.For additional PEPFAR data, please visit data.pepfar.gov. Unless otherwise noted, the content, data, documentation, code, and related materials on data.pepfar.gov is public domain and made available with a Creative Commons CC0 1.0 Universal dedication and license-free (per US Code 17 USC § 105). Citation of data.pepfar.gov as a source of the data is appreciated.

United States US: Incidence of HIV: % of Uninfected Population Aged 15-49 data was reported at 0.020 % in 2014. This stayed constant from the previous number of 0.020 % for 2013. United States US: Incidence of HIV: % of Uninfected Population Aged 15-49 data is updated yearly, averaging 0.030 % from Dec 2008 (Median) to 2014, with 7 observations. The data reached an all-time high of 0.030 % in 2012 and a record low of 0.020 % in 2014. United States US: Incidence of HIV: % of Uninfected Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Number of new HIV infections among uninfected populations ages 15-49 expressed per 100 uninfected population in the year before the period.; ; UNAIDS estimates.; Weighted Average;

BackgroundIn 2015, there were approximately 40,000 new HIV diagnoses in the United States. Pre-exposure prophylaxis (PrEP) is an effective strategy that reduces the risk of HIV acquisition; however, uptake among those who can benefit from it has lagged. In this study, we 1) compared the characteristics of patients who were prescribed PrEP with individuals newly diagnosed with HIV infection, 2) identified the specialties of practitioners prescribing PrEP, 3) identified metropolitan statistical areas (MSAs) within the US where there is relatively low uptake of PrEP, and 4) reported median amounts paid by patients and third-party payors for PrEP.Methods and findingsWe analyzed prescription drug claims for individuals prescribed PrEP in the Integrated Dataverse (IDV) from Symphony Health for the period of September 2015 to August 2016 to describe PrEP patients, prescribers, relative uptake, and payment methods in the US. Data were available for 75,839 individuals prescribed PrEP, and findings were extrapolated to approximately 101,000 individuals, which is less than 10% of the 1.1 million adults for whom PrEP was indicated. Compared to individuals with newly diagnosed HIV infection, PrEP patients were more likely to be non-Hispanic white (45% versus 26.2%), older (25% versus 19% at ages 35–44), male (94% versus 81%), and not reside in the South (30% versus 52% reside in the South).Using a ratio of the number of PrEP patients within an MSA to the number of newly diagnosed individuals with HIV infection, we found MSAs with relatively low uptake of PrEP were concentrated in the South. Of the approximately 24,000 providers who prescribed PrEP, two-thirds reported primary care as their specialty. Compared to the types of payment methods that people living with diagnosed HIV (PLWH) used to pay for their antiretroviral treatment in 2015 to 2016 reported in the Centers for Disease Control and Prevention (CDC) HIV Surveillance Special Report, PrEP patients were more likely to have used commercial health insurance (80% versus 35%) and less likely to have used public healthcare coverage or a publicly sponsored assistance program to pay for PrEP (12% versus 45% for Medicaid). Third-party payors covered 95% of the costs of PrEP. Overall, we estimated the median annual per patient out-of-pocket spending on PrEP was approximately US$72. Limitations of this study include missing information on prescription claims of patients not included in the database, and for those included, some patients were missing information on patient diagnosis, race/ethnicity, educational attainment, and income (34%–36%).ConclusionsOur findings indicate that in 2015–2016, many individuals in the US who could benefit from being on PrEP were not receiving this HIV prevention medication, and those prescribed PrEP had a significantly different distribution of characteristics from the broader population that is at risk for acquiring HIV. PrEP patients were more likely to pay for PrEP using commercial or private insurance, whereas PLWH were more likely to pay for their antiretroviral treatment using publicly sponsored programs. Addressing the affordability of PrEP and otherwise promoting its use among those with indications for PrEP represents an important opportunity to help end the HIV epidemic.

This dataset is about countries in Central America. It has 8 rows. It features 3 columns: incidence of HIV, and population.

aCases of HIV infection newly diagnosed HIV infection in Australia in 2010 including cases previously diagnosed overseas. All new diagnoses inAustralia in 2010, reported by 31 March 2012. All new diagnoses includes cases previously diagnosed overseas, some of whom have received treatment for HIV infection. The heterosexual contact category includes 53M, 80F, total 133 cases from high prevalence countries and 42M, 12F, total 54 cases whose exposure was attributed to heterosexual contact with a partner from a high prevalence country.bThis dataset is not nationally representative; it includes data from 4 of the 13 provinces and territories and one of these jurisdictions was incomplete (nominal cases only). Across all 13 P/Ts, a total of 2,358 HIV cases were reported in 2010.cHIV surveillance includes the whole country except Sardegna region (coverage 97.8%). Data reported by 31 December 2010.dData Source: New HIV Diagnoses Information System (SINIVIH in Spanish). In 2011, SINIVIH was implemented in 17 out of 19 Autonomous Region, and coverage was 71% of the total Spanish population. While information on first CD4 count after diagnosis is available in all Regions, information on DATE of CD4 count determination is currently available only in seven (Aragon, Asturias, Canary Islands, Castile-Leon, Madrid, Murcia and Navarre). This seven regions provided 1519 (52.2%) of the total 2907 new HIV diagnoses notified in 2010. Information on date of CD4 count was missing in 248 (16%) of the 1519 new HIV diagnoses. Information on viral load determination within 3 months after HIV diagnosis is not collected.eIncludes cases of HIV infection diagnosed in 14 jurisdictions of the United States and reported by 31 December 2011. Estimated numbers resulted from statistical adjustment that accounted for missing risk-factor information, but not for reporting delays and incomplete reporting. Age group 10–19 includes 13–19 only.fMSM, men who have sex with men; IDU, injection drug use.

Description: In the combined data set three individual data sets were merged; parents/guardians for children to 11 years, children 12 to 14 years, youths and adults 15 years and older. The data set has modules that contain information on biographical data, orphan status, school attendance, media, communication and norms, knowledge, attitudes, beliefs and values about HIV/AIDS, sexual history, sexually transmitted infections, delivery and care details, male circumcision, HIV testing and risk perception, drug and alcohol use, health status, and violence in relationships. The datasets also contains biological markers such as HIV status, exposure to ARVs, viral load suppression and HIV drug resistance. The data set contains 1 090 variables and 66 615 cases. Abstract: This is the fifth wave in a series of national cross-sectional surveys that have been undertaken every three years since 2002, by a research consortium led by the Human Sciences Research Council (HSRC). The study design and methods were based on the methods used and validated in the previous four surveys conducted by the HSRC in 2002, 2005, 2008 and 2012. The 2017 survey employed a slightly similar methodology compared to 2002, 2005 and 2008 surveys. In the first two surveys (2002 and 2005), a maximum of three people was randomly sampled in each household, based on pre-determined age categories, namely a child aged 2-14 years, a youth aged 15-24 years, and an adult aged 25 years or older. In 2008, infants aged 2 years and younger were included in the sample as a fourth possible person. In 2012, all household members were included in the survey, and the same approach was used in 2017, making it the fifth national-level repeat survey. The main objectives of the survey were to undertake the following analyses on a household-level of a nationally representative sample of adults and children in South Africa: To estimate the HIV prevalence at national, provincial and selected district levels among adults and children in South Africa. To estimate the extent of exposure to antiretroviral therapy (ART) and the level of HIV drug resistance (HIVDR) at national, provincial and selected district levels among adults and children in South Africa. To review the progress in reaching UNAIDS 90-90-90 goals for total HIV epidemic control. Furthermore, to undertake the following analyses at the national and provincial levels and for selected districts:

BackgroundConventional epidemiological surveillance of infectious diseases is focused on characterization of incident infections and estimation of the number of prevalent infections. Advances in methods for the analysis of the population-level genetic variation of viruses can potentially provide information about donors, not just recipients, of infection. Genetic sequences from many viruses are increasingly abundant, especially HIV, which is routinely sequenced for surveillance of drug resistance mutations. We conducted a phylodynamic analysis of HIV genetic sequence data and surveillance data from a US population of men who have sex with men (MSM) and estimated incidence and transmission rates by stage of infection.Methods and FindingsWe analyzed 662 HIV-1 subtype B sequences collected between October 14, 2004, and February 24, 2012, from MSM in the Detroit metropolitan area, Michigan. These sequences were cross-referenced with a database of 30,200 patients diagnosed with HIV infection in the state of Michigan, which includes clinical information that is informative about the recency of infection at the time of diagnosis. These data were analyzed using recently developed population genetic methods that have enabled the estimation of transmission rates from the population-level genetic diversity of the virus. We found that genetic data are highly informative about HIV donors in ways that standard surveillance data are not. Genetic data are especially informative about the stage of infection of donors at the point of transmission. We estimate that 44.7% (95% CI, 42.2%–46.4%) of transmissions occur during the first year of infection.ConclusionsIn this study, almost half of transmissions occurred within the first year of HIV infection in MSM. Our conclusions may be sensitive to un-modeled intra-host evolutionary dynamics, un-modeled sexual risk behavior, and uncertainty in the stage of infected hosts at the time of sampling. The intensity of transmission during early infection may have significance for public health interventions based on early treatment of newly diagnosed individuals.Please see later in the article for the Editors' Summary

The Philippines reported about ****** HIV cases, an increase from the previous year. The number of reported HIV cases has gradually increased since 2012, aside from a significant dip in 2020. The state of HIV As the monthly average number of people newly diagnosed with HIV increases, the risk it poses threatens the lives of Filipinos. HIV is a sexually transmitted infection that attacks the body’s immune system, with more males being diagnosed than females. In 2022, the majority of people newly diagnosed with HIV were those between the age of 25 and 34 years, followed by those aged 15 and 24. There is still no cure for HIV and without treatment, it could lead to other severe illnesses such as tuberculosis and cancers such as lymphoma and Kaposi’s sarcoma. However, HIV is now a manageable chronic illness that can be treated with proper medication. What are the leading causes of death in the Philippines? Between January and September 2024, preliminary figures have shown that ischaemic heart disease was the leading cause of death in the Philippines. The prevalence of heart diseases in the nation has been closely attributed to the Filipino diet, which was described as having a high fat, high cholesterol, and high sodium content. In addition, acute respiratory infections and hypertension also registered the highest morbidity rate among leading diseases in the country in 2021.

BackgroundCombination antiretroviral therapy (ART) has significantly increased survival among HIV-positive adults in the United States (U.S.) and Canada, but gains in life expectancy for this region have not been well characterized. We aim to estimate temporal changes in life expectancy among HIV-positive adults on ART from 2000–2007 in the U.S. and Canada.MethodsParticipants were from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD), aged ≥20 years and on ART. Mortality rates were calculated using participants' person-time from January 1, 2000 or ART initiation until death, loss to follow-up, or administrative censoring December 31, 2007. Life expectancy at age 20, defined as the average number of additional years that a person of a specific age will live, provided the current age-specific mortality rates remain constant, was estimated using abridged life tables.ResultsThe crude mortality rate was 19.8/1,000 person-years, among 22,937 individuals contributing 82,022 person-years and 1,622 deaths. Life expectancy increased from 36.1 [standard error (SE) 0.5] to 51.4 [SE 0.5] years from 2000–2002 to 2006–2007. Men and women had comparable life expectancies in all periods except the last (2006–2007). Life expectancy was lower for individuals with a history of injection drug use, non-whites, and in patients with baseline CD4 counts

The Find Ryan White HIV/AIDS Medical Care Providers tool is a locator that helps people living with HIV/AIDS access medical care and related services. Users can search for Ryan White-funded medical care providers near a specific complete address, city and state, state and county, or ZIP code. Search results are sorted by distance away and include the Ryan White HIV/AIDS facility name, address, approximate distance from the search point, telephone number, website address, and a link for driving directions. HRSA's Ryan White program funds an array of grants at the state and local levels in areas where most needed. These grants provide medical and support services to more than a half million people who otherwise would be unable to afford care.

Since the People Living with HIV Stigma Index was launched in 2008, shifts in the HIV epidemic, growth in the evidence base on how different populations are affected by stigma, and changes in the global response to HIV — particularly given the recommendation of early initiation of treatment — have highlighted the need to update and strengthen the Stigma Index as a measurement and advocacy tool. In October 2015, with support from USAID/PEPFAR, Project SOAR established a small working group (SWG) with representatives from the Global Network of People Living with HIV (GNP+), the International Community of Women Living with HIV (ICW), the Joint United Nations Programme on HIV/AIDS (UNAIDS), USAID, and several experts within and external to SOAR. The SWG outlined a process for evaluating and updating the Stigma Index that would be transparent and incorporate as many perspectives as possible in the process. The updated draft survey was then formally pilot-tested before being finalized and disseminated in late 2017.

Description: This data set contains information on adults aged 25 years and older: biographical data, media, communication and norms, knowledge and perceptions of HIV/AIDS, male circumcision, sexual debut, partners and partner characteristics, condoms, vulnerability, HIV testing, alcohol and substance use, general perceptions about government, health and violence in the community. The data set contains 516 variables and 10501 cases. Abstract: South Africa continues to have the largest number of people living with HIV/AIDS in the World. This study intends to understand the determinants that lead South Africans to be vulnerable and susceptible to HIV. This is the third in a series of household surveys conducted by Human Sciences Research Council (HSRC), that allow for tracking of HIV and associated determinants over time using a slightly same methodology used in 2002 and 2005 survey, making it the third national-level repeat survey. The 2002 and 2005 surveys included individuals aged 2+ years living in South Africa while 2008 survey included individuals of all ages living in South Africa, including infants younger than 2 years of age. The interval of three years since 2002 allows for an exploration of shifts over time against a complex of demographic and other variables, as well as allowing for investigation of the new areas. The survey provides the first nationally representative HIV incidence estimates. The study key objectives were to: determine the prevalence of HIV infection in South Africa; examine the incidence of HIV infection in South Africa; assess the relationship between behavioural factors and HIV infection in South Africa; describe trends in HIV prevalence, HIV incidence, and risk behaviour in South Africa over the period 2002-2008; investigate the link between social, values, and cultural determinants and HIV infection in South Africa; assess the type and frequency of exposure to major national behavioural change communication programmes and assess their relationship to HIV prevention, AIDS treatment, care, and support; describe male circumcision practices in South Africa and assess its acceptability as a method of HIV prevention; collect data on the health conditions of South Africans; and contribute to the analysis of the impact of HIV/AIDS on society. In the 13440 valid households or visiting points, 10856 agreed to participate in the survey, 23369 individuals (no more than 4 per household, including infants under 2 years) were eligible to be interviewed, and 20826 individuals completed the interview. Of the 23369 eligible individuals, 15031 agreed to provide a blood specimen for HIV testing and were anonymously linked to the behavioural questionnaires. the household response rate was 80.8%, the individual response rate was 89.1% and the overall response rate for HIV testing was 64.3%. Clinical measurements Face-to-face interview Focus group Observation South African population, all ages from urban formal, urban informal, rural formal (farms), rural informal (tribal area) settlements. As in previous surveys, a multi-stage disproportionate, stratified sampling approach was used. A total of 1 000 census enumeration areas (EAs) from the 2001 population census were selected from a database of 86 000 EAs and mapped in 2007 using aerial photography to create a new updated Master Sample as a basis for sampling visiting points/households. The selection of EAs was stratified by province and locality type. Locality types were identified as urban formal, urban informal, rural formal (including commercial farms), and rural informal. In the formal urban areas, race was also used as a third stratification variable (based on the predominant race group in the selected EA at the time of the 2001 census). The allocation of EAs to different stratification categories was disproportionate; that means, over-sampling or over-allocation of EAs was done, for example, in areas that were dominated by Indian, coloured or white race groups to ensure that the minimum required sample size in those smaller race groups was obtained. The Master Sample was designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. A maximum of four visits were made to each VP to optimise response. Fieldworkers enumerated household members, using a random number generator to select the respondent and then preceded with the interview. All people in the households, resident at the visiting point were initially listed, after which the eligible individual was randomly selected in each of the following three age groups: under 2 years, 2-14 years, 15-24 years and 25+ years. These individuals constituted the USUs of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa. These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 15 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 15 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 15 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. The VP questionnaire was administered by the fieldworker, and in follow-up, participant selection was made by the supervisor. Participants aged 12 years and older who consented were all interviewed and also asked to provide dried blood spots (DBS) specimens for HIV testing. In case of 0-11 years, parents/guardians were interviewed but DBS specimens were obtained from the children. The sample size estimate for the 2008 survey was guided by the (1) requirement for measuring change over time in order to detect a change in HIV prevalence of 5 percentage points in each of the main reporting domains, namely gender, age-group, race, locality type, and province (5% level of significance, 80% power, two-sided test), and (2) the requirement of an acceptable precision of estimates per reporting domain; that is, to be able to estimate HIV prevalence in each of the main reporting domains with a precision level of less than 4%, which is equivalent to the expected width of the 95% confidence interval (z-score at the 95% level for two-sided test). A design effect of 2 was assumed. Overall, a total of 20826 interviewed participants composed of 4981 children (0-14 years), 5344 youths (15-24 years) and 10501 adults (25+ years) were interviewed. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group. The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). More females (68.9%) than males (62.02%) were tested for HIV. The 25+ years age group was the most compliant (68.8%), and 2-14 years the least (58.9%). The highest testing response rate was found in urban informal settlements (72.5%) and the lowest in urban formal areas (62.8%).

All figures are given as % (95% CI) unless noted. There were 61 counties in the top decile and 551 in the remaining deciles.

The Sexually Transmitted Disease (STD) Morbidity online databases on CDC WONDER contain case reports reported from the 50 United States and D.C., Puerto Rico, Virgin Islands and Guam. The online databases report the number of cases and disease incidence rates by year, state, disease, age, sex of patient, type of STD, and area of report. Data are produced by the U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention (CDC), National Center for HIV/AIDS, viral Hepatitis, STD and TB Prevention (NCHHSTP).

Number of cases attributable to heterosexual contact, statistically adjusted to account for reporting delays and missing risk factor information, but not for incomplete reporting.†Per 100,000 heterosexuals.§ Hispanics/Latinos may be of any race.¶ Other race includes American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, unknown race/ethnicity, and multiple races.* Relative standard error >30% for meta-analysis estimate of the population proportion heterosexual for this group.Note. Data include persons age 13 years and older with a diagnosis of HIV infection regardless of stage of disease at diagnosis. CI = confidence interval