HIV testing

 

Why look at patterns in HIV testing?

  • HIV testing is an early step in the HIV prevention, engagement and care cascade and is a critical step in order for people living with HIV to know their status and be linked to HIV care. HIV testing is also an important gateway to services for people who are HIV-negative. This step is closely tied to the first UNAIDS 90-90-90 target.
  • Trends in HIV testing can be useful for measuring the success of HIV testing initiatives and for interpreting trends in new HIV diagnoses.
  • HIV test positivity rates (i.e. the percent of HIV tests that are HIV-positive) can provide insight into which sub-populations have a higher level of HIV risk. However, positivity rates should be interpreted with caution as they are influenced by both HIV risk as well as the number and types of people getting tested and it is difficult to disentangle these effects.
  • These data include information on the number of HIV tests in Ontario (NOT the number of unique individuals tested). This means trends may reflect changes in both the number of times an individual gets tested in a year as well as the total number of unique people who get tested.

 

Where do these data come from?

  • These data come from the Public Health Ontario Laboratory (PHOL), which conducts centralized HIV diagnostic testing for the province.
  • When someone is tested for HIV in Ontario, the health care provider conducting the test (e.g. a physician, nurse or HIV counselor) fills out an HIV test requisition form that is sent to PHOL. The requisition collects information on the individual getting tested for HIV, including their age, sex and HIV risk factors.
  • If a test is HIV-positive, a Laboratory Enhancement Program (LEP) form is sent to the health care provider who conducted the test in order to collect further information on the individual tested. This includes information collected on the test requisition, as well as additional information. However, only data from the test requisition are used for HIV testing data, as LEP data is not available for HIV-negative tests.
  • More information on the source of these data can be found here.

 

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

  • All HIV diagnostic testing conducted by health care providers in Ontario is done by PHOL and is therefore included in these data.
  • Age, sex and geography data on the test requisition are very complete and available for more than 93% of HIV tests.
  • Trends in HIV tests are presented as numbers and, where possible, as a testing rate (i.e. the number of tests per 1,000 people). While the number of tests are influenced by the size of the underlying population (e.g. greater population = greater number of tests), rates take population size into account and remove it as a possible explanatory factor for any observed differences over time or between populations.

 

 What are some of the limitations of these data?

  • Prenatal tests with an HIV-negative result are not included in these data, as they are part of an HIV testing program that is offered to all pregnant individuals. Approximately 200,000 HIV-negative prenatal tests are conducted in Ontario each year. However, HIV-positive prenatal tests ARE included in these data for the calculation of positivity rates. In recent years, the annual number of HIV-positive prenatal tests ranged from five to 16.
  • Information on health region and local health integration network (LHIN) is only available from 2011 onwards, as address of residence was not collected prior to that year.
  • Race/ethnicity, country of birth and transgender status were not collected on the HIV test requisition form prior to 2018. Lack of race/ethnicity and country of birth information means it was not possible to look at tests by priority population in the testing data. A revised requisition which collects these data was implemented in early 2018.
  • Instead of priority populations, HIV testing data are broken down by exposure category, which are meant to represent an individual’s most likely risk of HIV infection based on reported risk factors documented on the HIV test requisition. Unlike priority populations, exposure categories are mutually exclusive – meaning that an individual getting tested can only be assigned to one category.
  • Risk factor information is missing or indicated as “none” for over half of test requisition forms, and therefore an exposure category could not be assigned. These tests were excluded from the exposure category data. Due to the extent of missing information, exposure category data are presented as the percent of HIV tests where exposure category was known. The total number of tests by exposure category is not presented as they are underestimates.
  • If a specific exposure category is more likely to be missing information compared to others (for example, individuals from a specific exposure category may be less likely to disclose their risk factors to a provider), that category may be underrepresented in the data. This could introduce bias into the data.