Background Viral load (VL) testing of patients on antiretroviral therapy (ART) is critical to suppressing HIV. Timely transport of VL samples from health facilities to the laboratory for testing is often problematic in Turkana County, Kenya, and transportation barriers cause delays that can negatively impact the health of ART patients. Unmanned Aerial Vehicles (UAVs), or drones, are being promoted as a potential, novel way to reduce transportation times for laboratory samples and medical commodities. Our study models the use of UAVs in a remote area of Kenya to estimate costs and feasibility of their application for the Afya Nyota ya Bonde project, a large HIV service delivery program. Methods We gathered data from 12 Afya-supported facilities on VL sample transportation and turnaround time, ART drug transportation, and transportation practices and costs. The annual cost and average turnaround time for the transportation of VL samples and ART drugs was calculated using baseline data from the program to establish a comparison for scenarios that use a UAV. We then designed and costed four transportation scenarios that used UAVs to pick up VL samples and deliver ART drugs through a logistics company that will be adding UAV services. Results The modeled scenarios demonstrate that UAVs could transport nearly 100% of VL samples to the lab within the three-day goal compared to the 3% that are transported under the current system. Additionally, using UAVs could reduce the burden on health workers who must personally transport the samples, reducing opportunity costs resulting from facility closures due to provider absence. However, the UAV scenario cost more than three times the current costs (US$ 56,350/Kenyan Shillings (KSh) 5,635,000 per year compared to between US$ 172,878/Ksh 17,287,800 and US$ 200,208/Ksh 20,020,800), and the consolidation of VL testing days required to accommodate the UAV may be problematic for ART patients. Conclusions As the cost of UAV transport declines, this technology could be an important tool for optimizing the transport of lab samples and medications.
