Bloodborne HIV: Don't Get Stuck!

Protect yourself from bloodborne HIV during healthcare and cosmetic services

Time to let go of sexual fantasies about Africa’s HIV epidemics


For decades, too many experts in health agencies and universities have said most HIV in Africa comes from sex. Some does, of course. But most does not. Blaming sex never fit facts – many, many HIV-positive Africans knew and said they did NOT have any sexual risk. Too many experts didn’t believe them.

Finally, we have new evidence to challenge experts’ sexual fantasies. This new evidence comes from looking at each person’s HIV. It does not[!] depend on what anyone says about their sexual behavior.

Sequencing to see who infected whom

Each HIV is made of small pieces (nucleotides) in a particular order, which is called its “sequence.” HIV sequences change bit-by-bit over time. Comparing HIV sequences from two or more people can show how closely their infections are related. If sequences are very similar, one person likely infected the other.

To see how HIV infections have been moving through a community, researchers can take HIV from lots of people in the community, sequence the HIV they collect, and then look to see who has similar sequences. Similar sequences may be in pairs or in larger groups (clusters) of three or more sequences.

Here’s where it gets interesting for Africa: When a study has sequenced a lot of HIV from a community, those sequences can show how many people got HIV from known sex partners, and how many got HIV from other unidentified risks (sex or blood).

What percentage of HIV infections in Africa come from known sex partners

From 2013-2022, five studies sequenced HIV from hundreds to thousands of people in communities in Africa and said how many pairs of similar sequences came from known sex partners. Across these five studies, the percentages of HIV infections explained by known sex partners ranged from 0.3% to 6.6% (see Figure 1, below). All known sex partners were spouses or steady partners (I include suspected partners living together in these percentages).

Studies no doubt missed some spouses who were not at home or did not want to give a blood sample. And studies did not have information on who was a short-term sex partner. But if sex was responsible for even 1/3rd of HIV infections in these communities, missing spouses and short-term partners would have to infect many times more people than identified steady partners.          

Here’s are some details about what these five studies report (Figure 1, and paragraphs following the figure).

Evidence from Mochudi, Botswana

During 2010-13, researchers collected HIV from more than 1,200 adults in Mochudi, a town north of Gaborone, the capital. They sequenced about 2/3rds of the HIV they collected. Two reports give similar but slightly different information about numbers of infections explained by sex:

  • (a) One study, using 785 sequences from Mochudi, found 191 sequences to be similar to one or more others, including 4 pairs from men and women living together.[1] The study does not say they were sex partners. But assuming they were, the study identified sexual links to explain 4 infections: In each pair, one person likely infected the other, but the study cannot say how the first person in each pair got HIV. Hence, the study identified a sexual source for 0.5% (=4/785) of HIV sampled and sequenced from Mochudi.
  • (b) A second study, using 833 sequences from Mochudi, found 322 to be similar to one or more others, including 15 pairs from men and women living together.[2] The study does not say if they were sex partners. Assuming they were, the study found a sexual source for 15 infections, or 1.8% (=15/833) of HIV sampled and sequenced.

Evidence from KwaZulu-Natal, South Africa

In 2011-14, a study collected HIV samples from more than 5,000 adults in a community in uMkhanyakude, KwaZulu-Natal, South Africa.[3] The study sequenced 1,222 HIV from people with known addresses. Among these 1,222 sequences, the study found 333 that were similar to one or more other sequences. Similar sequences included 4 pairs from men and women living together who were not more than five years apart in age. The study does not say if they were sex partners. Assuming they were, the 4 pairs provide a sexual explanation for 4 infections, or 0.3% (=4/1,222) of HIV sequenced and with information on residence.

Evidence from Rakai, Uganda

Two studies sequenced HIV collected in long-term study communities in Rakai District, Uganda. The two studies collected HIV in different years from some of the same but also some different communities. Here’s what they report about sequences and sex partners:

  • One study sequenced 1,099 HIV collected in 2008-9.[4] The study found 209 sequences to be similar to one or more others, including 51 pairs from known couples (married or stable partners). These 51 pairs provided a sexual explanation for 51 infections, or 4.6% (=51/1,099) of infections with sequenced HIV.
  • The second study sequenced 2,652 HIV collected in 2011-15. The study found 1,334 sequences in clusters (that is, similar to one or more others), including 176 pairs from couples.[5] This provides a sexual explanation for 176 infections, or 6.6% (=176/2,652) of HIV sequenced.

Let go of sexual fantasies! What next?

For years, experts denied evidence – saying HIV-positive African who said they were virgins or had one HIV-negative lifetime partner were lying about their sexual behavior . But as Figure 1 shows, only small minorities of HIV infections can traced to known sex partners with similar HIV sequences. This evidence cannot be rejected by saying people lied about their sexual behavior.

It’s time to let go of sexual fantasies. And It’s LONG past time to get serious about finding and stopping HIV transmission from careless and unsafe skin-piercing procedures in health care and cosmetic services. How? Investigate unexplained infections (see menu on the right).

References

1. Novitsky V, Bussmann H, Logan A, et al. Phylogenetic relatedness of circulating HIV-1C variants in Mochudi, Botswana. PLoS One. 2013; b: e8059, DOI:10.1371/journal.pone.0080589. Available at: https://www.ncbi.nlm.nih.gov/pubmed/24349005 (accessed 24 July 2017).

2. Novitsky V, Bussmann H, Okui L, et al. Estimated age and gender profile of individuals missed by a home-based HIV testing and counseling campaign in a Botswana community. J Int AIDS Soc 2015; 18: 19918. Available at: https://dash.harvard.edu/bitstream/handle/1/17295521/4450241.pdf?sequence=1&isAllowed=y (accessed 30 May 2022).

3. Cuadros DF, de Oliveira T, Graf T, et al. The role of high-risk geographies in the perpetuation of the HIV epidemic in rural South Africa: A spatial molecular epidemiology study. PLOS Glob Pub Health [internet] 22 Feb 2022 https://doi.org/10.1371/journal.pgph.0000105 Available at: https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0000105#sec017 (accessed 13 May 2022).

4. Grabowski MK, Lessler J, Redd AD, et al. The role of viral introductions in sustaining community-based HIV epidemics in rural Uganda: evidence from spatial clustering, phylogenetics, and egocentric transmission models. PLoS 2014; 11: e1001610. Available at: https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001610 (accessed 4 June 2022).

2. Ratmann O, Grabowski MK, Hall M, et al. Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis. Nat Commun 2019; 10: 1411. Available at: https://www.nature.com/articles/s41467-019-09139-4.pdf (accessed 4 June 2022).


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