In December of 2017, researchers from the Public Health Agency of Canada and the Dalla Lana School of Public Health at the University of Toronto released the 2016 HIV Surveillance Report and Supplementary tables. In the Canadian Communicable Disease Report (CCDR) article, the researchers downplay the impact of rising HIV rates, and indeed even downplay the existence of such an increase. Canada’s HIV response needs to be strengthened to address these realities, and not be allowed to languish in an atmosphere of complacency. The fight against HIV is not over, and we cannot be complacent when an average of 6.4 new HIV diagnoses are given daily.
Number of new infections
In perhaps the most incongruous interpretation of the data, the researchers state that an 11.6% increase in the number of new HIV infections from 2015 to 2016 is “slight”. However, by looking closer at their data, we can see that it is actually the largest increase noted since 1997 (see this chart with the data from their Figure 1, along with the calculated rates of change).
We can note the following from the data given on number of cases and rate of infection:
- The number of new infections in 2016 was the largest year-over-year increase since 1997.
- The number of new infections had been going down since 2009, but have been going back up for the last two years.
- The rate of infections per 100,000 people had been staying the same or going down for 7 years, but saw a sharp increase of 10.3% in 2016, which, like the number of cases, is the largest increase in the data.
Geographic Distribution
In general, the interpretation in the CCDR article is straightforward. We can note the following from the data given in the article:
- The two provinces with the largest proportion of new infections are Ontario (881 new infections, 37.6% of the overall total) and Quebec (593 new infections, 25.3% of the overall total).
- The two provinces with the highest rate of infection are Saskatchewan (15.1 new infections per 100,000 people) and Manitoba (9.5 new infections per 100,000 people).
- The difference between the largest share of infections and the highest rate of infection demonstrates that not only is reducing the number of infections important, but also taking into account the impact that HIV can have on a community when rates of infection are high.
Age distribution
In the supplementary tables, the information on age is broken down by both gender and geographical location. We can note the following from the data:
- All age groups saw an increase in the number of new infections from 2015 to 2016.
- Youth aged 15-29 accounted for:
- 6% (574) of cases in 2016
- 6% (558) of cases in 2015
- 2% (475) of cases in 2014
- 9% (493) of cases in 2013
- 4% (507) of cases in 2012
- Between 2015 and 2016 youth aged 15-19 had the largest proportional increase (20%) while youth aged 20-29 had the smallest proportional increase (1.5%), even though they had the same number of additional new infections.
- This is why it is important to address both groups, as the same number of infections can have a very different impact on the total.
- Adults aged 30-39 had the largest increase in the total number of cases (99 new infections).
- Among people over 50, both the number of cases and the proportion of the total new infections they represent has been on the rise since 2012.
Sex/Gender Distribution
Note: The gender binary was assumed in much of the data given. In some charts there was a third option, but it lumped together sex not reported, transsexual and transgender (see this chart on gender data)
- Since 2012, the proportion of people newly diagnosed with HIV who identify as female has remained steady at around 22-24%.
Exposure category distribution
Although there has been an increase in the number and proportion of new HIV infections attributable to people who use injection drugs, this category is not the only one increasing, and is not the largest or most steady increase of the last five years. Other exposure categories have also been increasing, including heterosexual sex among people not from a country where HIV is endemic, which has been increasing in both number of new infections and the proportion of the total. If we focus only on harms from the opioid epidemic, then we risk leaving people behind who may mistakenly assume they are not at risk.
Selected Raw Data
Number of reported HIV Cases, 1996-2016
Data on the number of cases and rate per 100,000 people is taken from Bourgeois et al 2017, Figure 1; rates of change are calculated based on that information.
Year | # of cases | % change from previous year | rate per 100,000 | % change from previous year |
1996 | 2712 | 9.1 | ||
1997 | 2444 | -9.9% | 8.1 | -11.0% |
1998 | 2262 | -7.4% | 7.5 | -7.4% |
1999 | 2176 | -3.8% | 7.1 | -5.3% |
2000 | 2062 | -5.2% | 6.7 | -5.6% |
2001 | 2195 | 6.5% | 7.1 | 6.0% |
2002 | 2436 | 11.0% | 7.7 | 8.5% |
2003 | 2441 | 0.2% | 7.7 | 0.0% |
2004 | 2493 | 2.1% | 7.8 | 1.3% |
2005 | 2455 | -1.5% | 7.6 | -2.6% |
2006 | 2509 | 2.2% | 7.7 | 1.3% |
2007 | 2403 | -4.2% | 7.3 | -5.2% |
2008 | 2599 | 8.2% | 7.8 | 6.8% |
2009 | 2364 | -9.0% | 7 | -10.3% |
2010 | 2300 | -2.7% | 6.7 | -4.3% |
2011 | 2276 | -1.0% | 6.6 | -1.5% |
2012 | 2073 | -8.9% | 5.9 | -10.6% |
2013 | 2060 | -0.6% | 5.8 | -1.7% |
2014 | 2053 | -0.3% | 5.8 | 0.0% |
2015 | 2100 | 2.3% | 5.8 | 0.0% |
2016 | 2344 | 11.6% | 6.4 | 10.3% |
Sex/Gender data given
Number of cases data taken from Supplementary Table 5, percentages calculated.
Males | Females | Sex not reported/ transsexual/transgender | Total | ||||
Cases | % | Cases | % | Cases | % | Cases | |
2006 | 1,793 | 72.2% | 683 | 27.5% | 6 | 0.2% | 2,482 |
2007 | 1,776 | 74.9% | 589 | 24.8% | 7 | 0.3% | 2,372 |
2008 | 1,903 | 74.2% | 658 | 25.7% | 4 | 0.2% | 2,565 |
2009 | 1,740 | 74.4% | 593 | 25.4% | 6 | 0.3% | 2,339 |
2010 | 1,747 | 76.8% | 516 | 22.7% | 11 | 0.5% | 2,274 |
2011 | 1,713 | 76.1% | 527 | 23.4% | 11 | 0.5% | 2,251 |
2012 | 1,574 | 76.6% | 476 | 23.2% | 5 | 0.2% | 2,055 |
2013 | 1,591 | 78.2% | 435 | 21.4% | 9 | 0.4% | 2,035 |
2014 | 1,543 | 75.6% | 491 | 24.1% | 7 | 0.3% | 2,041 |
2015 | 1,584 | 75.9% | 498 | 23.9% | 4 | 0.2% | 2,086 |
2016 | 1,781 | 76.5% | 540 | 23.2% | 7 | 0.3% | 2,328 |