New HIV diagnoses

 

Why look at patterns in new HIV diagnoses?

  • HIV diagnosis is an early step in the HIV prevention, engagement and care cascade and is critical in order for people living with HIV to be linked to care.
  • Information on new diagnoses is useful for understanding how many people and who will require HIV care.
  • Trends in new HIV diagnoses can provide insight into trends in HIV infections, as well as populations who may be at greater risk of HIV infection. However, new HIV diagnoses and HIV infections are not equivalent. For example, 881 new HIV diagnoses in 2016 does not mean there were 881 new HIV infections in that year. This is because many people can be infected for years before being diagnosed. Also, new HIV diagnoses include people who were diagnosed with HIV outside of Ontario, moved to the province, and were tested again.
  • Trends in new HIV diagnoses should be interpreted with caution as they are influenced by the number of new HIV infections as well as HIV testing and migration patterns and it is difficult to disentangle these different effects.

 

Where do these data come from?

  • Data on new HIV diagnoses come from the Public Health Ontario Laboratory (PHOL), which conducts centralized HIV diagnostic testing for the province.
  • When someone gets an HIV test in Ontario, the health care provider conducting the test (e.g. a physician or HIV counselor) fills out a form which is sent to PHOL. This form, known as an HIV test requisition, collects information on the individual getting tested for HIV, including their sex, age and HIV risk factors.
  • If the test result is HIV-positive, a second form (known as the Laboratory Enhancement Program form, or LEP form) is sent to the provider who conducted the test in order to collect information that may have been missed on the first form. Since 2009, the LEP form has collected information on race/ethnicity and country of birth, data which has only been collected on the HIV test requisition since 2018. Data from both forms are combined to describe trends in new HIV diagnoses in Ontario.
  • More information on this data can be found here.

 

What are some of the strengths of these data and our approach to presenting it?

  • New HIV diagnoses are broken down by the overlapping priority populations outlined in Ontario’s provincial HIV/AIDS strategy. Unlike the categories traditionally used to describe new diagnoses (known as exposure categories), these priority populations are not mutually exclusive. This means that an HIV diagnosis can be assigned to more than one priority population (if applicable) – an approach which better represents Ontario’s HIV epidemic.
  • Trends in new diagnoses are presented as numbers as well as rates per 100,000 people. While the number of diagnoses are influenced by the size of the underlying population, rates take this into account and remove population size as a possible explanatory factor for any observed differences.
  • Diagnoses are aggregated over two-year periods to describe trends by priority population and race/ethnicity. This is done to reduce the effects of year-to-year variation (which can be particularly influential for populations with a small number of diagnoses) and more clearly present trends over time.

 

 What are some of the limitations of these data?

  • The annual number of new HIV diagnoses may be higher than the actual number of individuals who were diagnosed in that year, as individuals diagnosed through non-nominal testing (anonymous, coded) may also receive a nominal test when entering care and be counted twice.
  • Information on race/ethnicity and priority population is missing for about a third of new HIV diagnoses. Also, there is no option for transgender identity on the HIV test requisition form. Changes to the requisition form implemented in 2018 will hopefully decrease missing information and improve documentation of trans men and women.
  • If a specific priority population is more likely to be missing information on HIV risk factors or race/ethnicity, that population may be underrepresented in the data. Also, due to the extent of missing data, the number of diagnoses attributed to a specific race/ethnicity or priority population is likely an underestimate of the actual number.
  • Documentation of information on the requisition/LEP forms may vary from provider to provider. For example, some providers may ask the person getting tested about their HIV risk factors and race/ethnicity, while other providers may make assumptions.