GENDER DISPARITIES IN HIV INFECTIONS AMONG ADOLOSCENTS IN SUB-SAHARAN AFRICA

As we step into the new year, full of hope and optimism, believing in the fact that things will change for the better, let us tackle a new dataset that looks at HIV infections among adolescents in the 10–19year age group in Sub-Saharan Africa from 1990–2019.

A multitude of inequities drives the HIV epidemic, but gender inequality is a major contributor to the continued spread of HIV globally.

Despite significant global progress in the work to reduce HIV infections and HIV/AIDS related deaths, women and girls continue to be disproportionately vulnerable to, and affected by HIV.

Early and forced marriage, gender-based violence, unequal access to information, including sexual health knowledge, and a lack of negotiating power and economic autonomy are among the factors that place women and adolescent girls at increased risk of HIV infection.

Sub-Saharan Africa is home to 88 per cent of the world’s children under 15 years of age living with HIV, and mothers2mothers, an NGO is actively working in 10 countries. This dataset tells the story of the extreme need and profound gender inequality that affects adolescent women and girls in these countries.

In 2019, around 130,000 adolescent girls between the ages of 10 and 19 were newly infected with HIV compared to 44,000 boys of the same age. Girls therefore accounted for 75 per cent of new HIV infections among adolescents, globally.

These new infections disproportionately affect girls in countries where the HIV epidemic is driven by transmission during heterosexual intercourse, or in places where transactional sex is common. This is the case in Eastern and Southern Africa, and in West and Central Africa (the geographies of focus in this dataset) where girls account for 83 per cent and 78 per cent, respectively, of new HIV infections among adolescents in the 10–19 age group.

However, there has been a fall in HIV incidence in many countries — a symptom of adolescents adopting safer sex practices — but this is not the case in sub-Saharan Africa. There, only 38% of girls and 52% of boys aged 15–19, who are sexually active with a non-regular partner, used a condom. Further to this, fewer than a third of adolescent girls and boys aged 15–19 have comprehensive knowledge of HIV. The negative impact of this high rate of adolescent HIV infection is long-term and even generational. With such high rates of transmission among adolescent girls, the prevention of imminent mother-to-child HIV transmission, becomes much harder.

This dataset is a subset of UNICEF’s ‘Key HIV epidemiology indicators for children and adolescents aged 10–19, 1990–2019.’ This UNICEF data is sourced from UNAIDS 2020 estimates, which provide ‘modeled estimates using the best available epidemiological and programmatic data to track the HIV epidemic’. Modeled estimates are used because counting the true numbers would require regularly testing entire populations for HIV, and investigating all deaths, which is logistically impossible and ethically problematic.

What worked for the visualization:

1. All key metrics are included namely: HIV related deaths per 100,000 people, new infections and incidence rates among adolescents.
2. Each metric has a chart explaining the trends.
3. The titles are precise and communicate the idea well.

What did not work for the visualization:

1. Color has been used separately for each metric. They do not work well together and seem to confuse rather than clearly explain the insights gathered.
2. An explanation behind axis titles is important. Since the audience is the general public without much knowledge of statistics, title definitions help in putting the point across.
3. The story that is presented does not seem to flow well.

My Interpretation:

1. I decided to include 2 separate views: 1990–2019 chart trend and the 2019 country breakdown.
2. Metrics, Views and Countries are represented as parameters giving the user the ability to interact with the dashboard and see insights for themselves.
3. I used a dot plot to show trends in metrics across time (1990–2019) between male and female adolescents highlighting disparities.
4. I used a scatter plot to show how different countries performed across the metrics in 2019.
5. What is interesting to note is that 1995–97 comes across as years with peak rates of annual HIV infections and new HIV infections per 1000 of the population.
6. The no of AIDS related deaths per 100k of the population and annual AIDS related deaths have declined over the years implying better intervention and precautions among the infected.
7. Females universally account for higher infections as compared to males across all relevant metrics highlighting the urgency of care and medical attention needed.
8. South Africa beats every other country in terms of no of people living with HIV, annual AIDS related deaths, annual HIV infections.

Although relevant work is being done in the affected regions, a lot more needs to be taken care of before we even start talking about gender equality.

Let me know what you think about it. Comments are most welcome.

Click here to view my visualization