Rates of HIV in female sex workers in Kenya decreased by two-thirds over a ten-year period

Phelister Abdalla, the National Coordinator of the Kenya Sex Workers Alliance (KESWA), speaking at AIDS 2018. Image by juno mac. Creative Commons licence.

Research from specialist HIV prevention and treatment clinics for female sex workers in Nairobi has found that the number testing positive for HIV dropped by more than two-thirds between 2008 and 2017. While no single intervention can be identified as to the underlying cause in the decreasing numbers, it suggests that increasing HIV awareness, testing and treatment in Kenya are reaching this population of women, despite the criminalisation of sex work. It is estimated that female sex workers in Kenya are almost ten times more likely to contract HIV than non-sex workers, so they are a key population to target.

The study published in the February issue of AIDS analysed anonymous data collected at seven different Sex Worker Outreach Programs in Nairobi from a total of 33,560 women. The clinics use peer support and outreach workers to recruit female sex workers. When signing up to use the clinic’s services, each woman was offered an HIV test, which was used to monitor rates of HIV. Further information was collected by analysing questionnaires that the women were asked to complete when attending. Only 78% of the women completed this information, as it was not mandatory for enrolment into the clinic.



In everyday language, a general movement upwards or downwards (e.g. every year there are more HIV infections). When discussing statistics, a trend often describes an apparent difference between results that is not statistically significant. 

sample size

A study has adequate statistical power if it can reliably detect a clinically important difference (i.e. between two treatments) if a difference actually exists. If a study is under-powered, there are not enough people taking part and the study may not tell us whether one treatment is better than the other.


Studies aim to give information that will be applicable to a large group of people (e.g. adults with diagnosed HIV in the UK). Because it is impractical to conduct a study with such a large group, only a sub-group (a sample) takes part in a study. This isn’t a problem as long as the characteristics of the sample are similar to those of the wider group (e.g. in terms of age, gender, CD4 count and years since diagnosis).


The result of a statistical test which tells us whether the results of a study are likely to be due to chance and would not be confirmed if the study was repeated. All p-values are between 0 and 1; the most reliable studies have p-values very close to 0. A p-value of 0.001 means that there is a 1 in 1000 probability that the results are due to chance and do not reflect a real difference. A p-value of 0.05 means there is a 1 in 20 probability that the results are due to chance. When a p-value is 0.05 or below, the result is considered to be ‘statistically significant’. Confidence intervals give similar information to p-values but are easier to interpret. 


In HIV, usually refers to legal jurisdictions which prosecute people living with HIV who have – or are believed to have – put others at risk of acquiring HIV (exposure to HIV). Other jurisdictions criminalise people who do not disclose their HIV status to sexual partners as well as actual cases of HIV transmission. 

The overall percentage of female sex workers who were positive for HIV decreased from 44% in 2008 to 12% in 2017 (p value < 0.0001), amounting to a 67% reduction in prevalence after adjustment for known demographic and behavioural factors that could influence the results. In all age groups there was a general trend downwards in most years. Prevalence in the under 25 year olds was used to estimate the number of new infections because previous national surveys suggest that this age group are responsible for the majority of new infections. In the under 25s, positive diagnosis at enrolment increased from 14% to peak at 19% in 2010 but then fell down to 5% by 2017, which could correlate to a decrease in the overall number of new HIV cases.

Two of the major strategies used for HIV prevention are HIV testing and condom use. In 2008 women who tested positive for HIV at the clinic had previously been tested in 50% of cases, compared to 95% in 2017. In women who tested negative there was also an increase from 77% to 98%, showing that more women had been getting tested for HIV. Condom use increased significantly with both regular and casual partners. For HIV-negative female sex workers with regular partners in 2008, only 11% reported condom use all the time but by 2017, this had risen to 75%. When looking at casual sex partners for this group, condom use every time was reported by 67% of women in 2008 but increased to 90% in 2017.

Rates of abnormal vaginal discharge and genital ulcers were used as markers for symptoms of sexually transmitted infections. For both symptoms there was a decrease over time. In female sex workers who tested positive for HIV, the rate of discharge fell from 68% to 50% and ulcers from 39% to 30%. In female sex workers who tested negative for HIV, reports of discharge decreased from 63% to 51% and ulcers from 24% to 23%.

However, the researchers did note some limitations to this study, as it is possible that more sex workers at higher risk of contracting HIV were enrolled earlier in the study, with sex workers at lower risk joining later. This may have occurred because of HIV-positive women seeking out these clinics in earlier years as a means to access treatment or because clinics strived to meet HIV treatment initiation targets in later years. This could account for part of the decrease seen.

"Increasing HIV awareness, testing and treatment in Kenya are reaching female sex workers."

While the overall sample size was robust, a large portion of data is also missing from the questionnaires, making the analysis of prevention strategies more limited. Even when using models to adjust for the reported changes in condom use and HIV testing, the lower rates of HIV were not fully accounted for, which suggests that other factors were also involved.

Some potentially important factors to explain the reduced prevalence were suggested by the researchers. The first is the improvement in HIV prevention messaging on a wide scale in Kenya for the entire population. The second factor could be higher rates of viral suppression in potential clients because of an increase in the use of antiretroviral therapy and the ‘treatment as prevention’ strategy. More specifically for female sex workers, the use of peer support to improve messaging to women not involved in clinics may also have contributed to the fall in HIV cases seen.

Given that the lifetime risk of HIV in female sex workers in Nairobi is still high despite these decreasing numbers, the researchers suggest that it is important to continue targeted interventions to further reduce infection rates of HIV.


Tago A et al. Declines in HIV prevalence in female sex workers accessing an HIV treatment and prevention programme in Nairobi, Kenya over a 10-year period. AIDS, 35: 317-324, 2021.

doi: 10.1097/QAD.0000000000002747

Full image credit: Phelister Abdalla (KESWA) presents learning from the SWAA, a groundbreaking learning programme led by and for sex workers from across Africa. Image by juno mac. Available at www.flickr.com/photos/166033858@N08/28810899427/ under Creative Commons licence CC BY-NC-ND 2.0.