ArcGIS REST Services Directory Login
JSON

ItemInfo

Item Information

snippet: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations, Small island developing States (SIDS), Trend Data
summary: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations, Small island developing States (SIDS), Trend Data
extent: [[-180,-90],[180,90]]
accessInformation:
thumbnail: thumbnail/thumbnail.png
maxScale: 1.7976931348623157E308
typeKeywords: ["ArcGIS","ArcGIS Server","Data","Map Service","Service"]
description: <p><u><strong>Short Name</strong></u><br> New HIV infections per 1,000 uninfected population<br></p> <p><u><strong>Full Name</strong></u><br> Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations<br></p> <p><u><strong>Domain</strong></u><br> Sexual and reproductive health<br></p> <p><u><strong>Sub-domain</strong></u><br> HIV/AIDS and STIs<br></p> <p><u><strong>Tags</strong></u><br> Latin America and the Caribbean Key Indicators, Montevideo Consensus, SDG Target 3.3, Strategic Plan<br></p> <p><u><strong>Definition</strong></u><br> The number of new HIV infections per 1,000 uninfected population, by sex, age and key populations as defined as the number of new HIV infections per 1,000 persons among the uninfected population.<br></p> <p><u><strong>Method of Calculation</strong></u><br> Longitudinal data on individuals newly infected with HIV would be the most accurate source of data to measure HIV incidence, however these data are rarely available for representative populations. Special diagnostic tests in surveys or from health facilities can also be used to obtain data on HIV incidence but these require very large samples to accurately estimate HIV incidence and the latter are also rarely representative. HIV incidence is thus modelled using the Spectrum software. The software incorporates data on HIV prevalence, the number of people on treatment, demographics and other relevant indicators to estimate historical HIV incidence, among other indicators. A full description of the model is available in peer-reviewed articles and in the most recent UNAIDS Global AIDS Update Reports. <a href="https://onlinelibrary.wiley.com/toc/17582652/2021/24/S">Link</a> <a href="https://www.unaids.org/en/resources/documents/2021/2021-global-aids-updat">Link</a><br></p> <p><u><strong>Expected Frequency of Data Dissemination</strong></u><br> Annual<br></p> <p><u><strong>Geospatial Dimension Availability</strong></u><br> Country (geolev0), Landlocked developing countries (LLDCs), Least Developed Countries (LDCs), SDG Regions, SDG Sub-Regions, Small island developing States (SIDS), World<br></p> <p><u><strong>Time Dimension Availability</strong></u><br> 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021<br></p> <p><u><strong>Disaggregation Dimension Availability</strong></u><br> Age group: <em>15 to 24 years old, 15 to 49 years old, 50 years old and over, Under 15 years old</em><br>Sex: <em>Female, Male</em><br></p> <p><u><strong>References</strong></u><br> SDG Indicator 3.3.1 metadata: <a href="https://unstats.un.org/sdgs/metadata/files/Metadata-03-03-01.pdf">Link</a><br></p>
licenseInfo:
catalogPath:
title: hv_i202_gl7
type: Map Service
url:
tags: ["Latin America and the Caribbean Key Indicators","Montevideo Consensus","SDG Target 3.3","Strategic Plan"]
culture: en-US
portalUrl:
name: hv_i202_gl7
guid: C07EC387-8EA3-499B-8CFF-5821681F5EBA
minScale: 0
spatialReference: GCS_WGS_1984