Skip to main content

Twice as many Kenyan truck drivers test for HIV following text alerts about self-testing

Caitlin Mahon

21 January 2021

The hardest to reach truck drivers benefitted from text announcements about self-testing availability, but the vast majority still did not test – how can we reach them?

People travelling down a dirt track in a truck
Photos are used for illustrative purposes. They do not imply health status or behaviour. Credit: iStock/pierivb

Text messages announcing the availability of HIV self-testing more than doubled the number of Kenyan truckers testing for HIV compared to those who received a standard of care model – but this still left a staggering 96% of this population untested for HIV.

Mobile populations, including truck drivers, are a high-risk group for HIV around the world. The nature of their work means that they spend much of their time away from their families and on the road, meaning they may have multiple sexual partners, which may include sex workers and other people living along transport routes. They are also highly unlikely to ever engage in health services unless they are specifically targeted.

While research for this group is generally lacking, a 2015 study revealed that 56% of Kenyan truckers had paid for sex in the last six months and 47% had a regular partner along their trucking route in addition to a wife or girlfriend at home. Just 14% of this sample reported always using a condom in the last six months. Research among truck drivers in other countries in the region also report high HIV prevalence. For example, in South Africa, 26% of truck drivers are thought to be living with HIV. Even fewer studies exist about HIV testing, but research again from South Africa in 2004 revealed that just 38.2% had ever been tested for HIV.

In this randomized control trial, 2,262 male truck drivers who did not test regularly for HIV and were on the electronic health record system of the North Star Alliance were allocated into three arms. The North Star Alliance brings health services to mobile populations across East and Southern Africa through roadside clinics, among other services.

In the intervention arm, three text messages were sent to periodically alert truck drivers about the availability of self-testing at all eight of the North Star Alliance clinics in Kenya. A second arm delivered an enhanced standard of care (SOC) model with truck drivers being alerted about the availability of just HIV testing at all North Star Clinics, sent three times. In the third group, the standard of care arm, a text message was sent just once alerting drivers about HIV testing.

Overall, HIV testing rates were very low. In the SOC model and enhanced SOC model, just 1.3% of the truckers came forward for testing – this increased to 3.5% for those in the intervention arm. The authors note that part of the reason why these numbers were so low was that the study was purposely designed to elicit drivers who do not, or may have never, tested.

Of those who tested in the intervention arm, 64.5% chose to self-test while 35.5% chose a standard provider-based blood test. Of those who chose to self-test, 70% chose to self-test in the clinic under supervision while the rest decided to take the test home. The authors note the diversity of ways the truckers tested, underscoring the importance of testing choices for the target group.

But how can we reach more of the hardest-to-reach? In their discussion, the authors postulate that they may have reached more truckers if they had distributed the self-test kits directly to the truckers, instead of via a clinic. Other studies have told us that it is often the action of getting physically to the clinic that is another major barrier to testing for the hardest-to-reach – either because they can’t make a clinic, or because they don’t want to. In this case, direct distribution coupled with clinic pick-up could be a future option. North Star Alliance already do outreach at truck stops and could consider self-testing distribution here, say the authors.

“Future studies might explore different combinations of test choices, such as provider-administered oral tests and self-administered blood tests, to try to determine which tests are the most popular and what the array of testing choices should be in order to maximize testing uptake.”

Share this page

Did you find this page useful?
See what data we collect and why