For the first time since the start of the COVID-19 pandemic, Asia Pacific country teams and development partners met in person in Bangkok, Thailand for the regional UNAIDS HIV estimates workshop. Huddled around laptops, groups came up with sometimes sobering national insights. 

Growing HIV infections among gay men. A far too high mother-to-child transmission rate. The expansion of the epidemic from key populations to other groups. The HIV estimates offer a snapshot of the epidemic and response that would otherwise be impossible to capture. How many people still need to be diagnosed or put on treatment? Where is the situation improving? And critically, who is being left behind?  

“Inequalities are holding back countries from reaching their goals and from ending AIDS. So this workshop was different from previous years in that the inequalities analysis cut across all five days. During the workshop, we guided countries to conduct an inequalities analysis on their national data sets. Countries requested additional support and more formal guidance from UNAIDS on how to analyse data to identify inequalities,” said Regional Strategic Information Adviser, Dr. Otilia Scutelniciuc. 

UNAIDS Regional Strategic Information Officer, Dr. Ye Yu Shwe, explained the value of applying an inequalities lens to the data analysis process. “When we talk about the HIV estimates process it is not just about producing numbers. It is about understanding the unequal impact of the epidemic on those who are most affected and unequal access to services,” he explained. This forms the basis for policy and programmatic recommendations to address gaps.  

The estimates exercise work neither start nor end with the workshop: “There is a year-round process to support countries to address their data gaps and data quality issues,” Dr. Scutelniciuc said.  

“HIV estimates are not stand-alone data. They are informed by data from other sources. Before and during the workshop we guided countries to scrutinize the data they have against the criteria required by the HIV estimates model. This is also an opportunity to identify other gaps and needs for post-workshop support to improve data availability and assure data quality,” she explained. 

Dr. Shwe noted that with funding support from USAID, the UNAIDS team supports a data quality assurance exercise before the workshop. It is specifically for countries with data quality challenges or those that have growing epidemics.   

“We work with the country team through our country offices. The results are used in the HIV estimation exercise. They can use this to adjust their data inputs and ensure the HIV estimates are accurate,” he said.