Indicator 3.3.1 Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations

Goal.3. Ensure healthy lives and promote well-being for all at all ages

Taget 3.1. By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseases.

3.3.1. Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations

2024

Achieving this target will positively impact multiple SDG goals and by reaching other goals will improve countries ability to reduce new HIV infections. The goals that are linked to HIV include goals 1 through 8,10, 11, 16 and 17.

Kenya National Bureau of Statistics

Senior Manager, Population Statistics

Population Statistics

Compiling Population Statistics Data

+254-735-004-401

P.O. Box 30266–00100 

dpss@knbs.or.ke

Definition:

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.

Number of newly infected people per 1,000 uninfected population.

Not applicable

KDHS 2022

Household based- where respondents were subjected to a questionnaire.

Every 5 Years

2023

Kenya National Bureau of Statistics

Kenya National Bureau of Statistics

The Kenya National Bureau of Statistics (KNBS) is established under the Statistics Act, 2006 as the principal agency of the Government for collecting, analysing and disseminating statistical data in Kenya and as the custodian of official statistical information

The incidence rate provides a measure of progress toward preventing onward transmission of HIV. Although other indicators are also very important to the HIV epidemic, HIV incidence reflects success in prevention programmes and, to some extent, successful treatment programmes, as those will also lead to lower HIV incidence.

The methods and limitations for estimating HIV incidence vary based on the data and surveillance systems available in countries. - Countries with high HIV prevalence in the general population have relatively strong surveillance systems with household surveys contributing to the information required to estimate incidence. In epidemics concentrated in key populations, the surveillance systems for key hard-to-reach populations are often not comparable over time due to changing survey and sampling methods. The estimated size of key populations, a critical input to the Spectrum model for concentrated epidemics, can also lead to important under or over estimation of HIV incidence in concentrated epidemics. - In many countries trends in recent new infections rely on prevalence data from routine antenatal clinic testing. If those data are biased because women with known positive HIV status are not captured when calculating prevalence, or women found to be negative at initial antenatal care visit are retested later in the pregnancy, the derived incidence trends might be biased. While some limitations of the models are reflected in the uncertainty bounds the measurement biases and the uncertainty caused by these biases are not easily quantified and are thus not included. - Although HIV prevalence and incidence among children appears to be reasonably robust in generalized epidemics, estimating the paediatric HIV epidemic in concentrated epidemics remains a challenge because no robust measures of fertility exist among key populations living with HIV. - Currently UNAIDS only supports the HIV estimates development in countries with populations greater than 250,000. This is primarily due to support capacity at UNAIDS.

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.

Stakeholders are invited to validate the data before it is Published.

A description of the methodology is available from the latest Global AIDS Update reports in the methods annex. Resources are also available at HIVtools.unaids.org. Countries are provided with capacity building workshops on the methods every other year. In addition, they are supported by in-country UNAIDS advisers in roughly 45 countries. Where no in-country specialists are available, remote assistance is provided. Training videos and documentation are also available at: HIVtools.unaids.org

The Kenya National Bureau of Statistics is ISO certified based on 9001:2015 Standard requirements. The processes of compilation, production, publication and dissemination of data, including quality control, are carried out following the methodological framework and standards established by the KNBS, in compliance with the Internationally acceptable standards

The KNBS adheres to Kenya Statistical Quality Assurance Framework (KesQAF) that underlines principles to be assured in managing the statistical production processes and output.

Data consistency and quality checks are conducted through Technical Working Groups (TWGs) before publication and dissemination

The processes of compilation, production, publication and dissemination of data, including quality control are subjected to a set criteria and standards to ensure conformity.

Data Availability:

Data are available by age and sex, however there are methodological challenges in estimating incidence among key populations.

Disaggregation:

General population, Age groups (0-14, 15-24, 15-49, 50+ years, All ages), sex (male, female, both). Key

population data are currently not available as methods are being developed.

KDHS Report 2023

https://www.dhsprogram.com/

https://onlinelibrary.wiley.com/toc/17582652/2021/24/S5 https://www.unaids.org/en/resources/documents/2021/2021-global-aids-update