Kenya is planning to use artificial intelligence (AI) to improve the tracking of mosquitoes that spread malaria, as health authorities seek to collect more information about the insects and the places where they are found.
The technology, known as VectorCam, is expected to be tested in October in partnership with the Kenya Medical Research Institute’s Centre for Global Health Research (Kemri-CGHR).
It will be used by community health promoters (CHPs) to collect and identify mosquitoes in large numbers of communities.VectorCam is an AI-powered smartphone device designed to rapidly identify mosquito species, sex, and feeding status in seconds.
Eric Ochomo, an entomologist at Kemri based at CGHR, says the technology is intended to widen the reach of existing mosquito monitoring efforts by speeding up identification.
“This would expand an existing surveillance system rather than replace it,” said Dr Ochomo.
Kenya has more than 107,000 CHPs working at the household and community levels. The Ministry of Health says they have helped to improve the early detection of malaria cases, referrals, adherence to treatment and the uptake of preventive interventions.
Under the proposed surveillance model, the CHPs will add mosquito collection and photography to their existing work at community level.
The VectorCam will use AI to identify the species, while taxonomists will analyse information from different locations to identify patterns in mosquito abundance, distribution and species composition.
Dr Ochomo says that Kenya could also draw on the skills of other health workers.Microscopists, for example, already examine specimens, and some have received entomology-related training through surveillance programmes. With additional training, they could undertake mosquito surveillance alongside their existing duties.
This approach would enable a relatively small group of specialists to oversee information from a much larger surveillance network. Kenya already has an established entomological surveillance system, in which teams collect and examine mosquitoes to determine their species, numbers, distribution, behaviour and susceptibility to insecticides, as well as whether they are carrying malaria parasites.
These findings help to inform mosquito control measures, including the use of insecticide-treated nets and indoor residual spraying.
However, the scope of this work is limited by the availability of specialists to carry it out. Dr Ochomo noted that skilled entomologists and taxonomists are expensive to train, which limits their availability.“
A well-trained entomologist is not cheap to find or fund, but the CHPs can help with surveillance, and we can work with data scientists to analyse the results,” he said.This shortage is important because Kenya has several species of mosquito that carry malaria, and they do not all live, feed, or rest in the same way and in the same place.
The main malaria vectors include Anopheles gambiae sensu stricto, Anopheles arabiensis and Anopheles funestus sensu stricto.
Anopheles merus contributes to transmission along parts of the coast, while Anopheles coustani is found in some inland areas. For example, Anopheles gambiae commonly breeds in temporary sunlit pools and puddles, and it has historically dominated parts of western Kenya’s highlands.
In some areas, it has accounted for over 80 percent of vector species.
By contrast, Anopheles funestus is more closely associated with permanent water bodies and can sustain transmission through drier periods. Anopheles arabiensis is often found around rice irrigation schemes.
“Knowing which species are present and where they are found can tell health workers more about how malaria is transmitted in a particular area and what mosquito control measures may be needed,” said Dr Ochomo.
A recent study in western Kenya found that Anopheles gambiae accounted for 71.4 percent of the female Anopheles mosquitoes collected, with Anopheles funestus accounting for 12.3 percent. However, the situation is changing as mosquito populations shift and new species emerge.
One example is Anopheles stephensi, an invasive malaria vector that was first detected in Kenya in 2022.
A study covering 18 counties between 2022 and 2024 confirmed the presence of 114 larval and 33 adult specimens across seven counties, with the majority of detections occurring along transportation routes. Unlike some of Kenya’s traditional malaria vectors, Anopheles stephensi can readily adapt to urban environments and breed in artificial water containers.
The detection of this species means that health authorities must now monitor it as they track how mosquito populations are changing and spreading. How VectorCam works, Sunny Patel, the co-founder of VectorCam, says the technology combines a smartphone, a small light box and artificial intelligence to identify mosquitoes in the field.
A mosquito collected during routine surveillance is placed in the device, where a macro lens magnifies it, and the phone takes a close-up photograph under controlled lighting.
The AI then studies the mosquito’s visible features and identifies its species, sex, and abdomen status.
“We’re essentially using the phone’s camera to take a picture of the mosquito, and then the AI looks at that picture and tells us what it is,” Mr Patel explained.
The technology is designed to make mosquito identification easier for health workers who may not have specialist entomology training.
“There’s a global shortage of entomologists,” he said.
Rather than every mosquito having to be examined by a specialist, trained field workers can use the device to identify mosquitoes closer to where they are collected.
This information can then be recorded and uploaded to a central surveillance system, providing malaria programmes with faster access to data on the presence of mosquitoes and their location. This technology has already been tested outside of Kenya. In Uganda, community health workers used VectorCam to identify more than 70,000 mosquitoes over the course of a 12-month randomised controlled trial.
The demand for detailed mosquito surveillance comes as Kenya continues to carry a substantial malaria burden despite a recent decline in reported cases.
According to the Ministry of Health, malaria incidence fell from 104 cases per 1,000 people in 2023 to 72 cases per 1,000 people in 2025.However, the national figure reveals significant differences between regions.
Some parts of the country continue to experience a much heavier malaria burden.
The World Health Organisation (WHO) estimates that Kenya records approximately 4.2 million malaria cases and 11,000 malaria-related deaths each year. The burden is concentrated in counties such as Siaya, Busia, Homa Bay, Turkana, Migori, Kakamega, Vihiga and Kisumu.
