The states with the highest rates of HIV diagnoses in 2022 included Georgia, Louisiana, and Florida. However, the states with the highest number of people with HIV were Texas, California, and Florida. In Texas, there were around 4,896 people diagnosed with HIV. HIV/AIDS diagnoses In 2022, there were an estimated 38,043 new HIV diagnoses in the United States, a slight increase compared to the year before. Men account for the majority of these new diagnoses. There are currently around 1.2 million people living with HIV in the United States. Deaths from HIV The death rate from HIV has decreased significantly over the past few decades. In 2023, there were only 1.3 deaths from HIV per 100,000 population, the lowest rate since the epidemic began. However, the death rate varies greatly depending on race or ethnicity, with the death rate from HIV for African Americans reaching 19.2 per 100,000 population in 2022, compared to just three deaths per 100,000 among the white population.

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.

Geographic distribution of rates of people living with HIV infection, 2016, by census tract, Santa Clara County. Source: Santa Clara County Public Health Department, enhanced HIV/AIDS reporting system (eHARS), data as of 4/30/2017. 2010 U.S. Census

Women's share of population ages 15+ living with HIV of United States of America slipped by 0.13% from 21.9 % in 2021 to 21.9 % in 2022. Since the 0.20% downward trend in 2012, women's share of population ages 15+ living with HIV declined by 2.10% in 2022. Prevalence of HIV is the percentage of people who are infected with HIV. Female rate is as a percentage of the total population with HIV.

People aged 15 to 59 years seen at HIV services in the UK, expressed as a rate per 1,000 population.Data is presented by area of residence, and exclude people diagnosed with HIV in England who are resident in Wales, Scotland, Northern Ireland or abroad.RationaleThe geographical distribution of people seen for HIV care and treatment is not uniform across or within regions in England. Knowledge of local diagnosed HIV prevalence and identification of local risk groups can be used to help direct resources for HIV prevention and treatment.In 2008, http://www.bhiva.org/HIV-testing-guidelines.aspx recommended that Local Authority and NHS bodies consider implementing routine HIV testing for all general medical admissions as well as new registrants in primary care where the diagnosed HIV prevalence exceeds 2 in 1,000 population aged 15 to 59 years.In 2017, guidelines were updated by https://www.nice.org.uk/guidance/NG60 which is co-badged with Public Health England. This guidance continues to define high HIV prevalence local authorities as those with a diagnosed HIV prevalence of between 2 and 5 per 1,000 and extremely high prevalence local authorities as those with a diagnosed HIV prevalence of 5 or more per 1,000 people aged 15 to 59 years.When this is applied to national late HIV diagnosis data, it shows that two-thirds of late HIV diagnoses occur in high-prevalence and extremely-high-prevalence local authorities. This means that if this recommendation is successfully applied in high and extremely-high-prevalence areas, it could potentially affect two-thirds of late diagnoses nationally.Local authorities should find out their diagnosed prevalence published in UKHSA's http://fingertips.phe.org.uk/profile/sexualhealth , as well as that of surrounding areas and adapt their strategy for HIV testing using the national guidelines.Commissioners can use these data to plan and ensure access to comprehensive and specialist local HIV care and treatment for HIV diagnosed individuals according to the http://www.medfash.org.uk/uploads/files/p17abl6hvc4p71ovpkr81ugsh60v.pdf and http://www.bhiva.org/monitoring-guidelines.aspx .Definition of numeratorThe number of people (aged 15 to 59 years) living with a diagnosed HIV infection and accessing HIV care at an NHS service in the UK and who are resident in England.Definition of denominatorResident population aged 15 to 59.The denominators for 2011 to 2023 are taken from the respective 2011 to 2023 Office for National Statistics (ONS) revised population estimates from the 2021 Census.Further details on the ONS census are available from the https://www.ons.gov.uk/census .CaveatsData is presented by geographical area of residence. Where data on residence were unavailable, residence have been assigned to the local health area of care.Every effort is made to ensure accuracy and completeness of the data, including web-based reporting with integrated checks on data quality. The overall data quality is high as the dataset is used for commissioning purposes and for the national allocation of funding. However, responsibility for the accuracy and completeness of data lies with the reporting service.Data is as reported but rely on ‘record linkage’ to integrate data and ‘de-duplication’ to prevent double counting of the same individual. The data may not be representative in areas where residence information is not known for a significant proportion of people accessing HIV care.Data supplied for previous years are updated on an annual basis due to clinic or laboratory resubmissions and improvements to data cleaning. Data may therefore differ from previous publications.Values are benchmarked against set thresholds and categorised into the following groups: <2 (low), 2 to 5 (high) and≥5 (extremely high). These have been determined by developments in national testing guidelines.The data reported in 2020 and 2021 is impacted by the reconfiguration of sexual health services during the national response to COVID-19.

Forecast: Number of Deaths Due to Tuberculosis (Excluding HIV Cases) in the US 2023 - 2027 Discover more data with ReportLinker!

Abstract

The 2005 Guyana HIV/AIDS Indicator Survey (GAIS) is the first household-based, comprehensive survey on HIV/AIDS to be carried out in Guyana. The 2005 GAIS was implemented by the Guyana Responsible Parenthood Association (GRPA) for the Ministry of Health (MoH). ORC Macro of Calverton, Maryland provided technical assistance to the project through its contract with the U.S. Agency for International Development (USAID) under the MEASURE DHS program. Funding to cover technical assistance by ORC Macro and for local costs was provided in their entirety by USAID/Washington and USAID/Guyana.

The 2005 GAIS is a nationally representative sample survey of women and men age 15-49 initiated by MoH with the purpose of obtaining national baseline data for indicators on knowledge/awareness, attitudes, and behavior regarding HIV/AIDS. The survey data can be effectively used to calculate valuable indicators of the President’s Emergency Plan for AIDS Relief (PEPFAR), the Joint United Nations Program on HIV/AIDS (UNAIDS), the United Nations General Assembly Special Session (UNGASS), the United Nations Children Fund (UNICEF) Orphan and Vulnerable Children unit (OVC), and the World Health Organization (WHO), among others. The overall goal of the survey was to provide program managers and policymakers involved in HIV/AIDS programs with information needed to monitor and evaluate existing programs; and to effectively plan and implement future interventions, including resource mobilization and allocation, for combating the HIV/AIDS epidemic in Guyana.

Other objectives of the 2005 GAIS include the support of dissemination and utilization of the results in planning, managing and improving family planning and health services in the country; and enhancing the survey capabilities of the institutions involved in order to facilitate the implementation of surveys of this type in the future.

The 2005 GAIS sampled over 3,000 households and completed interviews with 2,425 eligible women and 1,875 eligible men. In addition to the data on HIV/AIDS indicators, data on the characteristics of households and its members, malaria, infant and child mortality, tuberculosis, fertility, and family planning were also collected.

Geographic coverage

National

Analysis unit

• Individuals;
• Households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the 2005 GAIS is to provide estimates with acceptable precision for important population characteristics such as HIV/AIDS related knowledge, attitudes, and behavior. The population to be covered by the 2005 GAIS was defined as the universe of all women and men age 15-49 in Guyana.

The major domains to be distinguished in the tabulation of important characteristics for the eligible population are: • Guyana as a whole • The urban area and the rural area each as a separate major domain • Georgetown and the remainder urban areas.

Administratively, Guyana is divided into 10 major regions. For census purposes, each region is further subdivided in enumeration districts (EDs). Each ED is classified as either urban or rural. There is a list of EDs that contains the number of households and population for each ED from the 2002 census. The list of EDs is grouped by administrative units as townships. The available demarcated cartographic material for each ED from the last census makes an adequate sample frame for the 2005 GAIS.

The sampling design had two stages with enumeration districts (EDs) as the primary sampling units (PSUs) and households as the secondary sampling units (SSUs). The standard design for the GAIS called for the selection of 120 EDs. Twenty-five households were selected by systematic random sampling from a full list of households from each of the selected enumeration districts for a total of 3,000 households. All women and men 15-49 years of age in the sample households were eligible to be interviewed with the individual questionnaire.

The database for the recently completed 2002 Census was used as a sampling frame to select the sampling units. In the census frame, EDs are grouped by urban-rural location within the ten administrative regions and they are also ordered in each administrative unit in serpentine fashion. Therefore, this stratification and ordering will be also reflected in the 2005 GAIS sample.

Based on response rates from other surveys in Guyana, around 3,000 interviews of women and somewhat fewer of men expected to be completed in the 3,000 households selected.

Several allocation schemes were considered for the sample of clusters for each urban-rural domain. One option was to allocate clusters to urban and rural areas proportionally to the population in the area. According to the census, the urban population represents only 29 percent of the population of the country. In this case, around 35 clusters out of the 120 would have been allocated to the urban area. Options to obtain the best allocation by region were also examined. It should be emphasized that optimality is not guaranteed at the regional level but the power for analysis is increased in the urban area of Georgetown by departing from proportionality. Upon further analysis of the different options, the selection of an equal number of clusters in each major domain (60 urban and 60 rural) was recommended for the 2005 GAIS. As a result of the nonproportionalallocation of the number of EDs for the urban-rural and regional domains, the household sample for the 2005 GAIS is not a self-weighted sample.

The 2005 GAIS sample of households was selected using a stratified two-stage cluster design consisting of 120 clusters. The first stage-units (primary sampling units or PSUs) are the enumeration areas used for the 2002 Population and Housing Census. The number of EDs (clusters) in each domain area was calculated dividing its total allocated number of households by the sample take (25 households for selection per ED). In each major domain, clusters are selected systematically with probability proportional to size.

The sampling procedures are more fully described in "Guyana HIV/AIDS Indicator Survey 2005 - Final Report" pp.135-138.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of questionnaires were used in the survey, namely: the Household Questionnaire and the Individual Questionnaire. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program. In consultation with USAID/Guyana, MoH, GRPA, and other government agencies and local organizations, the model questionnaires were modified to reflect issues relevant to HIV/AIDS in Guyana. The questionnaires were finalized around mid-May.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. For each person listed, information was collected on sex, age, education, and relationship to the head of the household. An important purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview.

The Household Questionnaire also collected non-income proxy indicators about the household's dwelling unit, such as the source of water; type of toilet facilities; materials used for the floor, roof and walls of the house; and ownership of various durable goods and land. As part of the Malaria Module, questions were included on ownership and use of mosquito bednets.

The Individual Questionnaire was used to collect information from women and men age 15-49 years and covered the following topics: • Background characteristics (age, education, media exposure, employment, etc.) • Reproductive history (number of births and—for women—a birth history, birth registration, current pregnancy, and current family planning use) • Marriage and sexual activity • Husband’s background • Knowledge about HIV/AIDS and exposure to specific HIV-related mass media programs • Attitudes toward people living with HIV/AIDS • Knowledge and experience with HIV testing • Knowledge and symptoms of other sexually transmitted infections (STIs) • The malaria module and questions on tuberculosis

Cleaning operations

The processing of the GAIS questionnaires began in mid-July 2005, shortly after the beginning of fieldwork and during the first visit of the ORC Macro data processing specialist. Questionnaires for completed clusters (enumeration districts) were periodically submitted to GRPA offices in Georgetown, where they were edited by data processing personnel who had been trained specifically for this task. The concurrent processing of the data—standard for surveys participating in the DHS program—allowed GRPA to produce field-check tables to monitor response rates and other variables, and advise field teams of any problems that were detected during data entry. All data were entered twice, allowing 100 percent verification. Data processing, including data entry, data editing, and tabulations, was done using CSPro, a program developed by ORC Macro, the U.S. Bureau of Census, and SERPRO for processing surveys and censuses. The data entry and editing of the questionnaires was completed during a second visit by the ORC Macro specialist in mid-September. At this time, a clean data set was produced and basic tables with the basic HIV/AIDS indicators were run. The tables included in the current report were completed by the end of November 2005.

Response rate

• From a total of 3,055 households in the sample, 2,800 were occupied. Among these households, interviews were completed in 2,608, for a response rate of 93 percent. • A total of 2,776 eligible women were identified and

Dataset refers to the Statistics Relating to Notification of HIV Aids Cases and Deaths in Mauritius for the year 2000 to 2021

AM: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 53.000 % in 2022. This records an increase from the previous number of 48.000 % for 2021. AM: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 16.000 % from Dec 2000 (Median) to 2022, with 23 observations. The data reached an all-time high of 53.000 % in 2022 and a record low of 0.000 % in 2004. AM: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Armenia – Table AM.World Bank.WDI: Social: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.;UNAIDS estimates.;Weighted average;

Forecast: Number of Deaths Due to Tuberculosis (Excluding HIV Cases) in the US 2022 - 2026 Discover more data with ReportLinker!

This dataset contains death counts, crude rates and adjusted rates for selected causes of death by county and region. For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/, or go to the "About" tab.

In 2021, 1.9 million people in Nigeria were living with HIV. Women were the most affected group, counting 1.1 thousand individuals. Also, children up to age 14 who were HIV positive equaled 170 thousand.

This indicator provides information about the rate of persons living with HIV (persons per 100,000 population).Human immunodeficiency virus (HIV) infection remains a significant public health concern, with more than 59,000 Los Angeles County residents estimated to be currently living with HIV. Certain communities, such as low-income communities, communities of color, and sexual and gender minority communities, bear a disproportionate burden of this epidemic. The Ending the HIV Epidemic national initiative strives to eliminate the US HIV epidemic by 2030, focusing on four key strategies: Diagnose, Treat, Prevent, and Respond. Achieving this goal requires a collaborative effort involving cities, community organizations, faith-based institutions, healthcare professionals, and businesses. Together, they can create an environment that promotes prevention, reduces stigma, and empowers individuals to safeguard themselves and their partners from HIV. Stakeholders can advance health equity by focusing on the most affected communities and sub-populations.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Nigeria NG: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 33.000 % in 2017. This records an increase from the previous number of 31.000 % for 2016. Nigeria NG: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 9.000 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 33.000 % in 2017 and a record low of 0.000 % in 2002. Nigeria NG: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;

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

Georgia GE: Female Adults with HIV: % of Population Aged 15+ with HIV data was reported at 19.600 % in 2017. This records an increase from the previous number of 19.200 % for 2016. Georgia GE: Female Adults with HIV: % of Population Aged 15+ with HIV data is updated yearly, averaging 27.900 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 41.200 % in 1990 and a record low of 18.800 % in 2014. Georgia GE: Female Adults with HIV: % of Population Aged 15+ with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank.WDI: Health Statistics. Prevalence of HIV is the percentage of people who are infected with HIV. Female rate is as a percentage of the total population ages 15+ who are living with HIV.; ; UNAIDS estimates.; Weighted average;

Effect of suicide rates on life expectancy dataset

Abstract
In 2015, approximately 55 million people died worldwide, of which 8 million committed suicide. In the USA, one of the main causes of death is the aforementioned suicide, therefore, this experiment is dealing with the question of how much suicide rates affects the statistics of average life expectancy.
The experiment takes two datasets, one with the number of suicides and life expectancy in the second one and combine data into one dataset. Subsequently, I try to find any patterns and correlations among the variables and perform statistical test using simple regression to confirm my assumptions.

Data

The experiment uses two datasets - WHO Suicide Statistics[1] and WHO Life Expectancy[2], which were firstly appropriately preprocessed. The final merged dataset to the experiment has 13 variables, where country and year are used as index: Country, Year, Suicides number, Life expectancy, Adult Mortality, which is probability of dying between 15 and 60 years per 1000 population, Infant deaths, which is number of Infant Deaths per 1000 population, Alcohol, which is alcohol, recorded per capita (15+) consumption, Under-five deaths, which is number of under-five deaths per 1000 population, HIV/AIDS, which is deaths per 1 000 live births HIV/AIDS, GDP, which is Gross Domestic Product per capita, Population, Income composition of resources, which is Human Development Index in terms of income composition of resources, and Schooling, which is number of years of schooling.

LICENSE

THE EXPERIMENT USES TWO DATASET - WHO SUICIDE STATISTICS AND WHO LIFE EXPECTANCY, WHICH WERE COLLEECTED FROM WHO AND UNITED NATIONS WEBSITE. THEREFORE, ALL DATASETS ARE UNDER THE LICENSE ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 3.0 IGO (https://creativecommons.org/licenses/by-nc-sa/3.0/igo/).

[1] https://www.kaggle.com/szamil/who-suicide-statistics

[2] https://www.kaggle.com/kumarajarshi/life-expectancy-who

Abstract

Sierra Leone has just emerged from a ten- year civil war that significantly reduced the standard of living, and access to food for many people. The large scale destruction of most of the health and other social infrastructure that took place during the war intensified the problem of health service delivery and exacerbated poverty. A poor and undernourished population is easily susceptible to various diseases. The Civil conflict that ended in 2002 may have increased the risk for human immunodeficiency virus (HIV) transmission through the sexual abuse of teenage girls and women, drug abuse, migration, and displacement of the population. In addition, the problem of the spread of the disease is compounded by the low level of awareness and knowledge about HIV/AIDS particularly knowledge relating to its mode of transmission and methods of protection.

Recognizing the threat posed by the spread of HIV/AIDS, the government of Sierra Leone established the National HIV/AIDS Secretariat (NAS) as the main institution responsible for the development and implementation of effective strategies and programs geared towards the prevention and control of the spread of HIV/AIDS.

NAS commissioned Statistics Sierra Leone to undertake this first nationwide behavioural surveillance survey aimed at providing baseline data for use in designing behavioural change programs. The primary objective of this sentinel surveillance has been to provide national estimates on key indicators related to HIV prevention and infection for use in the development of a national database on HIV/AIDS in Sierra Leone.

The HIV/AIDS behavioural surveillance survey was carried out in 206 enumeration areas (EAs) used in the Sierra Leone Integrated Household survey (SLIHS for which comprehensive household listings existed. One locality within each selected EA was randomly selected. Using cumulative probability proportional to size sampling, fifteen and twenty households were selected for rural and urban EAs respectively. To reduce sample shortfall likely to arise due to migration, death etc. of the selected households, five replacement households were selected for both rural and urban EAs. In each selected household, one adolescent and one adult were interviewed. A total of 5374 respondents between the ages of 15-49 years were interviewed comprising 47 per cent males and 53 per cent females. In the households with more than one eligible respondent, use was made of the “Kish Selection Table” of random numbers to choose the member of the household to be interviewed. This procedure was adopted to reduce bias in the selection of respondents.

Geographic coverage

National Coverage

Analysis unit

At District Level: The units of analysis for the survey were the selected households. In each household, one Adolescent and one adult "Female" (15-49) was selected.

Universe

Selected EA's

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling for the BSS study followed the methodology used in the SLIHS (see annex).The BSS study was carried out in 206 EAS used in the SLIHS for which comprehensive household listings existed. Twenty EAs used in the SLIHS were unavailable which represented a shortfall of 8.4% of the original target sample size. The number of households interviewed in the urban and rural EAs was determined base on SLIHS methodology. Fifteen rural households and twenty urban households were targeted. One locality within each selected EA was randomly selected. The total number of persons in each of the selected EAs was added cumulatively for the entire locality and a sampling interval was fixed. Using a table of random numbers a number between one and the sampling interval was selected as starting household and subsequent households were selected by adding the fixed sampling interval. To reduce sample shortfall likely to arise due to migration, death etc. of the selected households, five replacement households were selected for both rural and urban EAs.

Sampling deviation

To minimize cost it was decided to repeat the study in the EAs used for the Sierra Leone Integrated Household Survey (SLIHS, 2003/2004). The SLIHS sample was representative of all the administrative districts, chiefdoms or wards in Sierra Leone and comprehensive and updated household listings existed for this sample of EAs. It was intended to carry out the study in all the EAs used in the SLIHS. However, the study was conducted in 206 EAs. Twenty EAs used in the SLIHS were unavailable which represented a shortfall of 8.4% of the original target sample size. The number of households interviewed in the urban and rural EAs was determined based on SLIHS methodology. Fifteen rural households and twenty urban households were targeted. One locality within each selected EA was randomly selected with probability proportional to size, using the number of listed households as size measure. The total number of households in each of the selected locality was added cumulatively for the entire locality and a sampling interval was fixed. Using a table of random numbers a number between one and the sampling interval was selected as starting household and subsequent households were selected by adding the fixed sampling interval. To reduce sample shortfall likely to arise due to migration, death etc. of the selected households, five replacement households were selected for both rural and urban EAs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey instrument that was used was the standard questionnaire, which included standardized UNAIDS indicators and also National HIV/AIDS Secretariat indicators which covered STI/HIV knowledge, risk perception, sexual and health-seeking behaviour. However, some questions were simplified or shortened and others were adjusted to suit local circumstances. The questionnaire consisted of sections about demographic characteristics of the household, Knowledge, opinions, behaviour and attitudes regarding sexually transmitted infections (STIs) and HIV/AIDS, sexual behaviour and condom use.

Cleaning operations

Completed questionnaires were verified and coded in Freetown by a team of five coders and one supervisor. The coding team checked each questionnaire to ensure that it was properly filled out. The questionnaires were then handed over to the Data Processing Division for processing. The IMPS software program was used to enter the data, which was transferred to SPSS for analysis.

Response rate

In each selected household, one adolescent and one adult were interviewed. A total of 5374 respondents between the ages of 15-49 years were interviewed comprising 47 percent males and 53 percent females.

Sampling error estimates

The Sierra Leone General Population HIV/AIDS Behavioural Surveillance Survey 2004 sampling frame was based on the 2003/2004 Sierra Leone Integrated Household Survey (SLIHS). The sample error was estimated at 5%.

Data appraisal

Other forms of data appraisal included data verification and coding.

Georgia GE: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 39.000 % in 2017. This records an increase from the previous number of 36.000 % for 2016. Georgia GE: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 11.500 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 39.000 % in 2017 and a record low of 0.000 % in 2003. Georgia GE: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;