This technical update of the 2020 viral load data quality module provides further guidance on the recommended data quality assurance activities, updated web annexes to support country implementation, and generic budgets for viral load testing data quality monitoring activities. These are part of ongoing efforts to standardize approaches to ensure that accurate and timely HIV viral load testing data and results are available for both clinical use and to strengthen programme monitoring. This aligns with recommendations outlined in the 2022 WHO Consolidated guidelines on person-centred HIV strategic information on data quality assessment and improvement. The updated guidance on the priority indicators and the key elements of data quality include: - Key indicators to be included in data quality monitoring activities; - Main activities to be included in the viral load testing data quality assessment process; - The calculation of viral load test turnaround times; - Considerations for data quality assessments for sites with electronic data systems; - Sampling for national data quality assessments of sites and clinical records; - Data quality monitoring via lot-quality assurance sampling; - Considerations for facilities with point-of-care or near point-of-care viral load testing; - Considerations for data quality assessments of viral load testing data for pregnant and breastfeeding women; and - Recording the limitations and challenges of data quality monitoring assurance activities.

To ensure that countries can effectively benefit from digital health investments, “digital adaptation kits” (DAKs) are designed to facilitate the accurate reflection of WHO’s clinical, public health and data use guidelines in the digital systems that countries are adopting. DAKs are operational, software-neutral, standardized documentations that distil clinical, public health and data use guidance into a format that can be transparently incorporated into digital systems. For this particular DAK, the operational requirements are based on systems that provide the functionalities of digital tracking and decision support (DTDS) and include components such as personas, workflows, core data elements, decision-support algorithms, scheduling logic and reporting indicators. Web annexes provide certain components in additional detail including: data dictionary (Web Annex A), decision-support logic (Web Annex B), indicator definitions (Web Annex C), and functional and non-functional requirements (Web Annex D). Data elements within the DAK (Web Annex A) are mapped to standards-based terminology, such as the International Classification of Diseases (ICD), to facilitate interoperability. This DAK focuses on providing the content requirements for a DTDS system for HIV care used by health workers in primary health care settings. It also includes cross- cutting elements focused on the client, such as self-care interventions.

WHO’s laboratory-based acquired drug resistance survey method yields robust estimates of acquired HIV drug resistance in adults, children and adolescents taking both dolutegravir and non-dolutegravir based regimens by genotyping remnant specimens from routine viral load testing. Results are used to inform programme decision making regarding optimal ART regimens and support evaluation of programme quality with respect to maximizing viral load suppression and minimizing emergence of resistance in people taking ART.

The purpose of this document is to provide guidance to national AIDS programmes and partners on the use of indicators to measure and report on the country response. The 2016 United Nations Political Declaration on Ending AIDS, adopted at the United Nations General Assembly High-Level Meeting on AIDS in June 2016, mandated UNAIDS to support countries in reporting on the commitments in the Political Declaration. The Political Declaration on Ending AIDS built on three previous political declarations: the 2001 Declaration of Commitment on HIV/AIDS, the 2006 Political Declaration on HIV/AIDS and the 2011 Political Declaration on HIV and AIDS.