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;

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.

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;

Introduction

• HIV (human immunodeficiency virus) is a virus that attacks the body's immune system. If HIV is not treated, it can lead to AIDS (acquired immunodeficiency syndrome) which currently has no cure. Once people get HIV, they have it for life. But with proper medical care, HIV can be controlled. Symptoms: Influenza-like illness; Fatigue… Treatments: Management of HIV/AIDS Type of infectious agent: Virus (Human Immunodeficiency Virus) • AIDS (acquired immune deficiency syndrome) is the name used to describe a number of potentially life-threatening infections and illnesses that happen when one’s immune system has been severely damaged by the HIV virus. While AIDS cannot be transmitted from 1 person to another, the HIV virus can.

Dataset

The data set contains data of the following:- 1. The top causes of deaths in the world 2. Total number of deaths due to HIV/AIDS 3. ART (Anti Retro-viral Therapy) coverage among people living with HIV 4. Knowledge among young citizens (15-24years) about HIV/AIDS 5. Population of HIV/AIDS patients living with TB and their death rate 6. Life expectancy rate among HIV/AIDS patients 7. HIV/AIDS Patients in different age groups 8. Women population living with HIV 9. Young women in India having the knowledge of HIV/AIDS 10. HIV/AIDS deaths in Indian states

Data was scrapped from the official website of UNICEF -https://data.unicef.org/ and https://data.gov.in/

Ask Phase

• Data gives the trend of increasing no. of HIV/AIDS patients across the world • The information available for each country is percentage of total Global AIDS patients • Time period traced is 2000-2019 • Key Questions to answer:  Which countries and regions are affected the most?  How are the different age groups affected?  How much is the ART (Anti Retro-viral Therapy) coverage among the patients and what is the life expectancy rate?  What percentage of the population is aware of the prevention and causes of HIV/AIDS

Prepare phase.

• By tabulating and filtering the data the required data was obtained to bring out observations. • Data was formatted to the desired format to perform further calculations. • Sorting of data region wise. • Columns with inconsistent and empty cells were deleted. • The data of India was extracted for further analysis • Duplicate entries and undesired data was removed

Process phase

For cleaning the dataset for further analysis MS Excel was used due to small data. • Used sumifs() functions to aggregate the data region wise • Used sumif() to segregate the no. of patients within different age groups • Used sumifs() to find the total number of TB patients among HIV deaths. • Used countif() to find the percentage of male and female patients. • Sorted data to find the top and bottom nation with most and least HIV/AIDS patients

Analyze phase

• Formed the following pivot tables to answer key target questions  Year v/s number of death rates  Country v/s death numbers to bring out nation wise deaths  Causes of death v/s the number of deaths to bring at which position AIDS causes causality  Year v/s percentage of life expectancy to observe the pattern of no. of survivors

Visualization phase

The data was visualized using Tableau.

Presentaion

The final presentation was prepared by accumulating all observations and inferences which is linked below https://docs.google.com/presentation/d/1NEX10Vz5u5Va3CrTLVbvsUHZjO-fn8EOeiOHkP03T3Q/edit?usp=sharing

This directory is for at-risk for HIV and eligible persons living with HIV in New York City seeking HIV medical and supportive services. The agencies and their listed programs receive CDC and Ryan White Part-A funding to provide: Targeted-Testing among Priority Populations, Food and Nutrition Services, Health Education and Risk Reduction Services, Harm Reduction Services, Legal Services, Mental Health Services, Case Management and Care Coordination Services, and Supportive Counseling Services. To be eligible to recieve these services, prospective clients must: 1)be HIV-positive; 2) have a total household income below 435% of the Federal Poverty Level (FPL) (this is the same as the income eligible guidelines for the New York State AIDS Drug Assistance Program (ADAP) and higher than the income eligiblity guidelines for Medicaid in New York State); and 3) reside in New York City or the counties of Westchester, Rockland, and Putnam. For providers, to make a referral, please contact the program directly using the information provided in the diretory (please be sure to call before directing clients to the program). When making a referral, you may also find it useful to talk to your client about executing a release of information form authorizing you to share confidential health and HIV-related information with another service provider in order to coordinate care (for more information, go to https://www.health.ny.gov/diseases/aids/providers/forms/informedconsent.htm).

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;

Description: This data file contains household information about the people who usually live and slept there (the previous night) as per the time of the interview. Their age, sex, relationship to household head, marital status, race, language spoken, are included. The data set contains 300 variables and 10864 cases. Abstract: Background: This is the first in a series of national HIV household surveys conducted in South Africa. The survey was commissioned by the Nelson Mandela Children's Fund and the Nelson Mandela Foundation. The key aims were to determine the HIV prevalence in the general population, identify risk factors that increase vulnerability of South Africans to HIV infections, to identify the contexts within which sexual behaviour occurs and the obstacles to risk reduction and to determine the level of exposure of all sectors of society to current prevention. The Nelson Mandela Children's Fund requested the HSRC to assess the impact of current HIV and AIDS education and awareness programmes designed to slow down the epidemic, including infection rates, stigma, care and support for affected individuals and families. Methodology: Sampling methods: multi-stage cluster stratified sample stratified by province, settlement geography (geotype) and predominant race group in each area. A systematic sample of 15 households was drawn from each of 1 000 census enumeration areas (EAs). In each household, one person was randomly selected in each of four mutually exclusive age groups (2-11 years; 12-14 years; 15-24 years; 25+ years). Field workers administered questionnaires to selected respondents and also collected oral fluid specimens for HIV testing. Results: This study sampled a cross-section of 9 963 South Africans aged two years and older. HIV is a generalised epidemic in South Africa that extends to all age groups, geographic areas and race groups. It showed 11.4 % were HIV positive, 15.6 per cent of them aged between 15 and 49. Women (12.8% HIV positive) were more at risk of infection than men (9.5% HIV positive). Urban informal settlements have the highest incidence of HIV infection (21.3%). Free State showed the highest prevalence (14.9%) with Eastern Cape having the lowest (6.6%). Higher rates of infection (5.6%) are also found in children aged 2-14 and Africans (10.2%). Awareness of HIV status was low. Only 18.9% reported that they were previously tested. Fewer women (3.9%) reported more than one sexual partner as compared to men (13.5%). Condom use at last sex was low among both women (24.7%) and men (30.3%). Knowledge of HIV and AIDS is generally high, with sexual behaviour changes taking root in encouragingly low numbers of sexual partners and high levels of abstinence among the youth. There is still great uncertainty of the relationship between HIV and AIDS and popular myths. South Africans from all walks of life are at risk. In particular, wealthy Africans have the same levels of risk as poorer Africans - whereas in other race groups, poorer people are more vulnerable to infection. Conclusions: The study recommended the expansion of voluntary counseling and testing. Prevention programmes ought to focus on reduction on multiple partners and increased condom use. It further recommended, inter alia, that HIV/AIDS prevention programmes be intensified for people living in informal settlements, campaigns be implemented using mass media to address myths and misconceptions and that information needs in rural communities and poorer households due to lack of access to mass media channels, should be attended to. Clinical measurements Face-to-face interview

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

United States US: Children: 0-14 Living with HIV data was reported at 2,500.000 Person in 2019. This records a decrease from the previous number of 2,800.000 Person for 2018. United States US: Children: 0-14 Living with HIV data is updated yearly, averaging 3,700.000 Person from Dec 2010 (Median) to 2019, with 10 observations. The data reached an all-time high of 4,700.000 Person in 2010 and a record low of 2,500.000 Person in 2019. United States US: Children: 0-14 Living with HIV 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: Social: Health Statistics. Children living with HIV refers to the number of children ages 0-14 who are infected with HIV.;UNAIDS estimates.;;

Spatial analysis at different levels can help understand spatial variation of human immunodeficiency virus (HIV) infection, disease drivers, and targeted interventions. Combining spatial analysis and the evaluation of the determinants of the HIV burden in Southern African countries is essential for a better understanding of the disease dynamics in high-burden settings.The study countries were selected based on the availability of demographic and health surveys (DHS) and corresponding geographic coordinates. We used multivariable regression to evaluate the determinants of HIV burden and assessed the presence and nature of HIV spatial autocorrelation in six Southern African countries.The overall prevalence of HIV for each country varied between 11.3% in Zambia and 22.4% in South Africa. The HIV prevalence rate was higher among female respondents in all six countries. There were reductions in prevalence estimates in most countries yearly from 2011 to 2020. The hotspot cluster findings show that the major cities in each country are the key sites of high HIV burden. Compared with female respondents, the odds of being HIV positive were lesser among the male respondents. The probability of HIV infection was higher among those who had sexually transmitted infections (STI) in the last 12 months, divorced and widowed individuals, and women aged 25 years and older.Our research findings show that analysis of survey data could provide reasonable estimates of the wide-ranging spatial structure of the HIV epidemic in Southern African countries. Key determinants such as individuals who are divorced, middle-aged women, and people who recently treated STIs, should be the focus of HIV prevention and control interventions. The spatial distribution of high-burden areas for HIV in the selected countries was more pronounced in the major cities. Interventions should also be focused on locations identified as hotspot clusters.

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.

Description: The adult and youth data of the SABSSM 2002 study cover information from adults and youths 15 years and older on topics ranging from biographical information, media and communication, male circumcision, marital status and marriage practice, partner and partner characteristics, sexual behaviour and practices, voluntary counseling and testing (VCT), sexual orientation, interpersonal communication, practices around widowhood, knowledge and perceptions of HIV and AIDS, stigma, hospitalisation and health status. The data set consists of 643 variables and 9788 cases. Abstract: Background: This is the first in a series of national HIV household surveys conducted in South Africa. The survey was commissioned by the Nelson Mandela Children's Fund and the Nelson Mandela Foundation. The key aims were to determine the HIV prevalence in the general population, identify risk factors that increase vulnerability of South Africans to HIV infections, to identify the contexts within which sexual behaviour occurs and the obstacles to risk reduction and to determine the level of exposure of all sectors of society to current prevention. The Nelson Mandela Children's Fund requested the HSRC to assess the impact of current HIV and AIDS education and awareness programmes designed to slow down the epidemic, including infection rates, stigma, care and support for affected individuals and families. Methodology: Sampling methods: multi-stage cluster stratified sample stratified by province, settlement geography (geotype) and predominant race group in each area. A systematic sample of 15 households was drawn from each of 1 000 census enumeration areas (EAs). In each household, one person was randomly selected in each of four mutually exclusive age groups (2-11 years; 12-14 years; 15-24 years; 25+ years). Field workers administered questionnaires to selected respondents and also collected oral fluid specimens for HIV testing. Results: This study sampled a cross-section of 9 963 South Africans aged two years and older. HIV is a generalised epidemic in South Africa that extends to all age groups, geographic areas and race groups. It showed 11.4 % were HIV positive, 15.6 per cent of them aged between 15 and 49. Women (12.8% HIV positive) were more at risk of infection than men (9.5% HIV positive). Urban informal settlements have the highest incidence of HIV infection (21.3%). Free State showed the highest prevalence (14.9%) with Eastern Cape having the lowest (6.6%). Higher rates of infection (5.6%) are also found in children aged 2-14 and Africans (10.2%). Awareness of HIV status was low. Only 18.9% reported that they were previously tested. Fewer women (3.9%) reported more than one sexual partner as compared to men (13.5%). Condom use at last sex was low among both women (24.7%) and men (30.3%). Knowledge of HIV and AIDS is generally high, with sexual behaviour changes taking root in encouragingly low numbers of sexual partners and high levels of abstinence among the youth. There is still great uncertainty of the relationship between HIV and AIDS and popular myths. South Africans from all walks of life are at risk. In particular, wealthy Africans have the same levels of risk as poorer Africans - whereas in other race groups, poorer people are more vulnerable to infection. Conclusions: The study recommended the expansion of voluntary counselling and testing. Prevention programmes ought to focus on reduction on multiple partners and increased condom use. It further recommended, inter alia, that HIV/AIDS prevention programmes be intensified for people living in informal settlements, campaigns be implemented using mass media to address myths and misconceptions and that information needs in rural communities and poorer households due to lack of access to mass media channels, should be attended to. Clinical measurements Face-to-face interview Focus group Observation South African population, 2 years and older from urban formal, urban informal, rural formal, rural informal settlements. This project used the HSRC's master sample (HSRC 2002). A master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the master sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs). Although the 2001 census data are not yet available, it was decided to use the 2001 EAs for the master sample because the sampling units would remain relevant for future surveys conducted by the HSRC within five to ten years' time. In addition, the HSRC would soon have access to the most recent census statistics over this period for weighting of future survey results, including this study. The sample was designed with two main explicit strata, namely, provinces and the geography type (geotype) of the EA. In the 2001 census, the four geotypes are urban formal, urban informal, rural formal (including commercial farms) and tribal areas (i.e. the deep rural areas). In the formal urban areas, race was also used as a third stratification variable. What this means is that the Master Sample has been 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. The census 2001 EA data provided by Stats SA for drawing the sample contained an estimate of the number of dwelling units (DUs) or visiting points (VPs). 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. The visiting point is the Secondary Sampling Unit (SSU) in each of the selected PSUs. In this study, all people in all 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 2-14, 15-24 and 25 years and older. These individuals constituted the Ultimate Sampling Units (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 11 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 11 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 11 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. Overall, a total of 14 450 potential participants composed of 4 001 children, 3 720 youths and 6 729 adults were selected for the survey and 13 518 (93.6%) were actually visited. A small proportion (6.4%) of potential respondents could not be approached due to logistic constraints that were unavoidable in a study of such magnitude. Among the 13 518 individuals who were selected and contacted for the survey, 9 963 (73.7%) persons agreed to be interviewed, and 8 840 (65.4%) agreed to also give a specimen for an HIV test. 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. In fact, the aim was to obtain 1 200 Indian households, 1 800 coloured households, 2 200 white households and 4 800 African households, a total thus of 10 000 households. 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). A 70% response rate was assumed and a HIV+ prevalence rate of 20%. However, the total refusal and non-contact rate was much higher than expected. Nevertheless, all cases where the interview could have been done were included in the analysis.

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

Description: The child data of the SABSSM 2002 study include information from the children 12-14 years on various topics topics such as biographical information, knowledge and communication about HIV and AIDS, the child's home environment, care and protection, sexual experience and behaviour, circumcision, hospitalisation history and health status. The data set contains 420 variables and 998 cases. Abstract: Background: This is the first in a series of national HIV household surveys conducted in South Africa. The survey was commissioned by the Nelson Mandela Children's Fund and the Nelson Mandela Foundation. The key aims were to determine the HIV prevalence in the general population, identify risk factors that increase vulnerability of South Africans to HIV infections, to identify the contexts within which sexual behaviour occurs and the obstacles to risk reduction and to determine the level of exposure of all sectors of society to current prevention. The Nelson Mandela Children's Fund requested the HSRC to assess the impact of current HIV and AIDS education and awareness programmes designed to slow down the epidemic, including infection rates, stigma, care and support for affected individuals and families. Methodology: Sampling methods: multi-stage cluster stratified sample stratified by province, settlement geography (geotype) and predominant race group in each area. A systematic sample of 15 households was drawn from each of 1 000 census enumeration areas (EAs). In each household, one person was randomly selected in each of four mutually exclusive age groups (2-11 years; 12-14 years; 15-24 years; 25+ years). Field workers administered questionnaires to selected respondents and also collected oral fluid specimens for HIV testing. Results: This study sampled a cross-section of 9 963 South Africans aged two years and older. HIV is a generalised epidemic in South Africa that extends to all age groups, geographic areas and race groups. It showed 11.4 % were HIV positive, 15.6 per cent of them aged between 15 and 49. Women (12.8% HIV positive) were more at risk of infection than men (9.5% HIV positive). Urban informal settlements have the highest incidence of HIV infection (21.3%). Free State showed the highest prevalence (14.9%) with Eastern Cape having the lowest (6.6%). Higher rates of infection (5.6%) are also found in children aged 2-14 and Africans (10.2%). Awareness of HIV status was low. Only 18.9% reported that they were previously tested. Fewer women (3.9%) reported more than one sexual partner as compared to men (13.5%). Condom use at last sex was low among both women (24.7%) and men (30.3%). Knowledge of HIV and AIDS is generally high, with sexual behaviour changes taking root in encouragingly low numbers of sexual partners and high levels of abstinence among the youth. There is still great uncertainty of the relationship between HIV and AIDS and popular myths. South Africans from all walks of life are at risk. In particular, wealthy Africans have the same levels of risk as poorer Africans - whereas in other race groups, poorer people are more vulnerable to infection. Conclusions: The study recommended the expansion of voluntary counseling and testing. Prevention programmes ought to focus on reduction on multiple partners and increased condom use. It further recommended, inter alia, that HIV/AIDS prevention programmes be intensified for people living in informal settlements, campaigns be implemented using mass media to address myths and misconceptions and that information needs in rural communities and poorer households due to lack of access to mass media channels, should be attended to. Clinical measurements Face-to-face interview Focus group Observation South African population, 2 years and older from urban formal, urban informal, rural formal, rural informal settlements. This project used the HSRC's master sample (HSRC 2002). A master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the master sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs). Although the 2001 census data are not yet available, it was decided to use the 2001 EAs for the master sample because the sampling units would remain relevant for future surveys conducted by the HSRC within five to ten years' time. In addition, the HSRC would soon have access to the most recent census statistics over this period for weighting of future survey results, including this study. The sample was designed with two main explicit strata, namely, provinces and the geography type (geotype) of the EA. In the 2001 census, the four geotypes are urban formal, urban informal, rural formal (including commercial farms) and tribal areas (i.e. the deep rural areas). In the formal urban areas, race was also used as a third stratification variable. What this means is that the Master Sample has been 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. The census 2001 EA data provided by Stats SA for drawing the sample contained an estimate of the number of dwelling units (DUs) or visiting points (VPs). 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. The visiting point is the Secondary Sampling Unit (SSU) in each of the selected PSUs. In this study, all people in all 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 2-14, 15-24 and 25 years and older. These individuals constituted the Ultimate Sampling Units (USUs) of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa (see Figure 2). 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 11 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 11 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 11 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. Overall, a total of 14 450 potential participants composed of 4 001 children, 3 720 youths and 6 729 adults were selected for the survey and 13 518 (93.6%) were actually visited. A small proportion (6.4%) of potential respondents could not be approached due to logistic constraints that were unavoidable in a study of such magnitude. Among the 13 518 individuals who were selected and contacted for the survey, 9 963 (73.7%) persons agreed to be interviewed, and 8 840 (65.4%) agreed to also give a specimen for an HIV test. 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. In fact, the aim was to obtain 1 200 Indian households, 1 800 coloured households, 2 200 white households and 4 800 African households, a total thus of 10 000 households. 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). A 70% response rate was assumed and a HIV+ prevalence rate of 20%. However, the total refusal and noncontact rate was much higher than expected. Nevertheless, all cases where the interview could have been done were included in the analysis.

Abbreviations: HPTN: HIV Prevention Trials Network; HIVNET: HIV Network for Prevention Trials; MAA: multi-assay algorithm; LAg-Avidity: limited antigen avidity assay; BioRad-Avidity: avidity assay based on the BioRad 1/2+O EIA; HRM: high resolution melting.aCross-sectional HIV incidence estimates were obtained by testing samples collected at the end of follow-up in three clinical cohorts: HPTN 064, HIVNET 001, and HPTN 061. The number of HIV-infected vs. HIV-uninfected individuals included in the cross-sectional survey is shown.bParticipants in HPTN 064 were followed for either 6 or 12 months.cFor HPTN 064, 33 study participants had samples available for analysis; 28 were seropositive at enrollment, one had acute HIV infection at enrollment, and four acquired HIV infection during the study. For HIVNET 001, 79 of 90 HIV-infected study participants had samples available for analysis; all 79 participants were HIV-uninfected at study enrollment. For HPTN 061, 246 participants had samples available for analysis; 218 were seropositive at study enrollment, three had acute HIV infection at enrollment, and 25 acquired HIV infection during the study.d73 of these 79 samples were among the 808 samples from HIVNET 001 that were used to determine the window periods and shadows for the MAAs (see Figures 1 and 2).eOne specimen classed as MAA positive by the HRM-based MAA was classified as MAA negative by the ambiguity-based MAA.fOne specimen that was classified as MAA negative by the HRM-based MAA was classified as MAA positive by the ambiguity-based MAA.gOne specimen failed analysis with sequence ambiguity. Because the MAA could not be completed, this specimen was excluded from incidence calculations.

Description: The guardian data of the SABSSM 2002 study cover information from the parents or care givers of children 2-11 years on matters ranging from biographical information of the child and parent/guardian, the child's home environment, care and protection, sources of information on HIV and AIDS, media impact and the health status of the child. The data set contains 380 variables and 2732 cases. Abstract: Background: This is the first in a series of national HIV household surveys conducted in South Africa. The survey was commissioned by the Nelson Mandela Children's Fund and the Nelson Mandela Foundation. The key aims were to determine the HIV prevalence in the general population, identify risk factors that increase vulnerability of South Africans to HIV infections, to identify the contexts within which sexual behaviour occurs and the obstacles to risk reduction and to determine the level of exposure of all sectors of society to current prevention. The Nelson Mandela Children's Fund requested the HSRC to assess the impact of current HIV and AIDS education and awareness programmes designed to slow down the epidemic, including infection rates, stigma, care and support for affected individuals and families. Methodology: Sampling methods: multi-stage cluster stratified sample stratified by province, settlement geography (geotype) and predominant race group in each area. A systematic sample of 15 households was drawn from each of 1 000 census enumeration areas (EAs). In each household, one person was randomly selected in each of four mutually exclusive age groups (2-11 years; 12-14 years; 15-24 years; 25+ years). Field workers administered questionnaires to selected respondents and also collected oral fluid specimens for HIV testing. Results: This study sampled a cross-section of 9 963 South Africans aged two years and older. HIV is a generalised epidemic in South Africa that extends to all age groups, geographic areas and race groups. It showed 11.4 % were HIV positive, 15.6 per cent of them aged between 15 and 49. Women (12.8% HIV positive) were more at risk of infection than men (9.5% HIV positive). Urban informal settlements have the highest incidence of HIV infection (21.3%). Free State showed the highest prevalence (14.9%) with Eastern Cape having the lowest (6.6%). Higher rates of infection (5.6%) are also found in children aged 2-14 and Africans (10.2%). Awareness of HIV status was low. Only 18.9% reported that they were previously tested. Fewer women (3.9%) reported more than one sexual partner as compared to men (13.5%). Condom use at last sex was low among both women (24.7%) and men (30.3%). Knowledge of HIV and AIDS is generally high, with sexual behaviour changes taking root in encouragingly low numbers of sexual partners and high levels of abstinence among the youth. There is still great uncertainty of the relationship between HIV and AIDS and popular myths. South Africans from all walks of life are at risk. In particular, wealthy Africans have the same levels of risk as poorer Africans - whereas in other race groups, poorer people are more vulnerable to infection. Conclusions: The study recommended the expansion of voluntary counseling and testing. Prevention programmes ought to focus on reduction on multiple partners and increased condom use. It further recommended, inter alia, that HIV/AIDS prevention programmes be intensified for people living in informal settlements, campaigns be implemented using mass media to address myths and misconceptions and that information needs in rural communities and poorer households due to lack of access to mass media channels, should be attended to. Clinical measurements Face-to-face interview Focus group Observation South African population, 2 years and older from urban formal, urban informal, rural formal, rural informal settlements. This project used the HSRC's master sample (HSRC 2002). A master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the master sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs). Although the 2001 census data are not yet available, it was decided to use the 2001 EAs for the master sample because the sampling units would remain relevant for future surveys conducted by the HSRC within five to ten years' time. In addition, the HSRC would soon have access to the most recent census statistics over this period for weighting of future survey results, including this study. The sample was designed with two main explicit strata, namely, provinces and the geography type (geotype) of the EA. In the 2001 census, the four geotypes are urban formal, urban informal, rural formal (including commercial farms) and tribal areas (i.e. the deep rural areas). In the formal urban areas, race was also used as a third stratification variable. What this means is that the Master Sample has been 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. The census 2001 EA data provided by Stats SA for drawing the sample contained an estimate of the number of dwelling units (DUs) or visiting points (VPs). 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. The visiting point is the Secondary Sampling Unit (SSU) in each of the selected PSUs. In this study, all people in all 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 2-14, 15-24 and 25 years and older. These individuals constituted the Ultimate Sampling Units (USUs) of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa (see Figure 2). 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 11 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 11 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 11 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. Overall, a total of 14 450 potential participants composed of 4 001 children, 3 720 youths and 6 729 adults were selected for the survey and 13 518 (93.6%) were actually visited. A small proportion (6.4%) of potential respondents could not be approached due to logistic constraints that were unavoidable in a study of such magnitude. Among the 13 518 individuals who were selected and contacted for the survey, 9 963 (73.7%) persons agreed to be interviewed, and 8 840 (65.4%) agreed to also give a specimen for an HIV test. 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. In fact, the aim was to obtain 1 200 Indian households, 1 800 coloured households, 2 200 white households and 4 800 African households, a total thus of 10 000 households. 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). A 70% response rate was assumed and a HIV+ prevalence rate of 20%. However, the total refusal and noncontact rate was much higher than expected. Nevertheless, all cases where the interview could have been done were included in the analysis.

United States US: Newly Infected with HIV: Children: Aged 0-14 data was reported at 200.000 Number in 2019. This stayed constant from the previous number of 200.000 Number for 2018. United States US: Newly Infected with HIV: Children: Aged 0-14 data is updated yearly, averaging 200.000 Number from Dec 2010 (Median) to 2019, with 10 observations. The data reached an all-time high of 500.000 Number in 2012 and a record low of 200.000 Number in 2019. United States US: Newly Infected with HIV: Children: Aged 0-14 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: Social: Health Statistics. Number of children (ages 0-14) newly infected with HIV.;UNAIDS estimates.;;This indicator is related to Sustainable Development Goal 3.3.1 [https://unstats.un.org/sdgs/metadata/].

Context

HealthStats compiles an extensive array of health, nutrition, and population statistics gleaned from a diverse array of global sources. Encompassing themes ranging from population dynamics to health financing and disease prevalence, this repository covers a broad spectrum of indicators, including immunization rates, infectious diseases, HIV/AIDS, and population projections. Additionally, HealthStats presents nuanced statistics categorized by wealth quintiles, offering a comprehensive view of societal disparities.

Content

Within this dataset, a compendium of 470 indicators sheds light on critical metrics such as immunization rates, malnutrition prevalence, and vitamin A supplementation across 266 countries worldwide. Spanning a timeframe from 1960 to 2022, this data collection encapsulates yearly statistics, providing a comprehensive historical perspective on health, nutrition, and population dynamics.

Dataset Structure

This dataset (health_nutrition_population_statistics.csv) covering from 1960 up to 2022 includes the following columns:

Questions for Exploration

• Are there unexpected correlations or shifts in indicators that warrant inclusion for a more holistic understanding?
• Is there a discernible relationship between condom use and HIV transmission rates among newborns, and how have these trends evolved over time?
• Identifying countries with the highest iodized salt consumption and tracking changes over time could reveal intriguing patterns. Are there other indicators that correlate significantly with this consumption trend?

Acknowledgment

The primary dataset was retrieved from the World Bank's Data Catalog. I would like to express our sincere appreciation to the World Bank team for providing the core data used in this dataset.

© Image credit: Freepik

The 2004 Malawi Demographic and Health Survey (MDHS) is a nationally representative survey of 11,698 women age 1549 and 3,261 men age 15-54. The main purpose of the 2004 MDHS is to provide policymakers and programme managers with detailed information on fertility, family planning, childhood and adult mortality, maternal and child health, as well as knowledge of and attitudes related to HIV/AIDS and other sexually transmitted infections (STIs). The 2004 MDHS is designed to provide data to monitor the population and health situation in Malawi as a followup of the 1992 and 2000 MDHS surveys, and the 1996 Malawi Knowledge, Attitudes, and Practices in Health Survey. New features of the 2004 MDHS include the collection of information on use of mosquito nets, domestic violence, anaemia testing of women and children under 5, and HIV testing of adults. The 2004 MDHS survey was implemented by the National Statistical Office (NSO). The Ministry of Health and Population, the National AIDS Commission (NAC), the National Economic Council, and the Ministry of Gender contributed to the development of the questionnaires for the survey. Most of the funds for the local costs of the survey were provided by multiple donors through the NAC. The United States Agency for International Development (USAID) provided additional funds for the technical assistance through ORC Macro. The Department for International Development (DfID) of the British Government, the United Nations Children's Fund (UNICEF), and the United Nations Population Fund (UNFPA) also provided funds for the survey. The Centers of Disease Control and Prevention provided technical assistance in HIV testing. The survey used a two-stage sample based on the 1998 Census of Population and Housing and was designed to produce estimates for key indicators for ten large districts in addition to estimates for national, regional, and urban-rural domains. Fieldwork for the 2004 MDHS was carried out by 22 mobile interviewing teams. Data collection commenced on 4 October 2004 and was completed on 31 January 2005. The principal aim of the 2004 MDHS project was to provide up-to-date information on fertility and childhood mortality levels, nuptiality, fertility preferences, awareness and use of family planning methods, use of maternal and child health services, and knowledge and behaviours related to HIV/AIDS and other sexually transmitted infections. It was designed as a follow-on to the 2000 MDHS survey, a national-level survey of similar scope. The 2004 MDHS survey, unlike the 2000 MDHS, collected blood samples which were later tested for HIV in order to estimate HIV prevalence in Malawi. In broad terms, the 2004 MDHS survey aimed to: Assess trends in Malawi's demographic indicators, principally fertility and mortality Assist in the monitoring and evaluation of Malawi's health, population, and nutrition programmes Advance survey methodology in Malawi and contribute to national and international databases Provide national-level estimates of HIV prevalence for women age 15-49 and men age 15-54. In more specific terms, the 2004 MDHS survey was designed to: Provide data on the family planning and fertility behaviour of the Malawian population and thereby enable policymakers to evaluate and enhance family planning initiatives in the country Measure changes in fertility and contraceptive prevalence and analyse the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and important social and economic factors Examine basic indicators of maternal and child health and welfare in Malawi, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, and use of immunisation services. Particular emphasis was placed on malaria programmes, including malaria prevention activities and treatment of episodes of fever. Provide levels and patterns of knowledge and behaviour related to the prevention of HIV/AIDS and other sexually transmitted infections Provide national estimates of HIV prevalence Measure the level of infant and adult mortality including maternal mortality at the national level Assess the status of women in the country. MAIN FINDINGS Fertility Fertility Levels and Trends. While there has been a significant decline in fertility in the past two decades from 7.6 children in the early 1980s to 6.0 children per woman in the early 2000s, compared with selected countries in Eastern and Southern Africa, such as Zambia, Tanzania, Mozambique, Kenya, and Uganda, the total fertility rate (TFR) in Malawi is high, lower only than Uganda (6.9). Family planning Knowledge of Contraception. Knowledge of family planning is nearly universal, with 97 percent of women age 15-49 and 97 percent of men age 15-54 knowing at least one modern method of family planning. The most widely known modern methods of contraception among all women are injectables (93 percent), the pill and male condom (90 percent each), and female sterilisation (83 percent). Maternal health Antenatal Care. There has been little change in the coverage of antenatal care (ANC) from a medical professional since 2000 (93 percent in 2004 compared with 91 percent in 2000). Most women receive ANC from a nurse or a midwife (82 percent), although 10 percent go to a doctor or a clinical officer. A small proportion (2 percent) receives ANC from a traditional birth attendant, and 5 percent do not receive any ANC. Only 8 percent of women initiated ANC before the fourth month of pregnancy, a marginal increase from 7 percent in the 2000 MDHS. Adult and Maternal Mortality. Comparison of data from the 2000 and 2004 MDHS surveys indicates that mortality for both women and men has remained at the same levels since 1997 (11-12 deaths per 1,000). Child health Childhood Mortality. Data from the 2004 MDHS show that for the 2000-2004 period, the infant mortality rate is 76 per 1,000 live births, child mortality is 62 per 1,000, and the under-five mortality rate is 133 per 1,000 live births. Nutrition Breastfeeding Practices. Breastfeeding is nearly universal in Malawi. Ninety-eight percent of children are breastfed for some period of time. The median duration of breastfeeding in Malawi in 2004 is 23.2 months, one month shorter than in 2000. HIV/AIDS Awareness of AIDS. Knowledge of AIDS among women and men in Malawi is almost universal. This is true across age group, urban-rural residence, marital status, wealth index, and education. Nearly half of women and six in ten men can identify the two most common misconceptions about the transmission of HIV-HIV can be transmitted by mosquito bites, and HIV can be transmitted by supernatural means-and know that a healthy-looking person can have the AIDS virus.