A team of Columbian researchers are working to develop a machine-learning based imaging and sorting solution that allows for the sorting of male and female tsetse flies. Pioneered by Zelda Moran, the scientists aim to eradicate the tsetse population in Africa.
The tsetse fly is found in sub-Saharan African countries where the population depends mainly on agriculture, fishing, animal husbandry or hunting. The insect is a major limitation to economic development in this region because it threatens livestock and human life through the transmission of a parasitic disease which is deadly to both animal (nagana) and human (sleeping sickness).
Up to 70 million people in 20 sub-African countries are at risk from the disease. The disease develops in areas ranging from a single village to an entire region. Within an infected area, the intensity of the disease can vary from one village to the next. Accumulated contributions find that African countries have suffered several epidemics over the last century. One between 1896 and 1906, one in 1920 and the most recent epidemic was between 1970 and the late 1990s. Each outbreak was controlled by experts and the World Health Organization (WHO), which drove the mortality rate down by a significant percentage.
However, instead of waiting until an epidemic occurs before taking action, researchers have been concentrated on the factors that control the distribution and abundance of these vectors and the means by which their numbers can be reduced. To this end, findings reveal that the female tsetse flies only mates once in a lifetime. A female that mates with a sterile male will not reproduce. This means that if a deliberate arrangement is made for enough of such matings to occur, the result will be fewer tsetse flies and surely less sleeping sickness.
Bearing this in mind researchers discovered sustainable control techniques to help reduce the production of tsetse thereby eliminating its population in Africa. In 2018 Senegal reported a 98 percent drop in tsetse population, five years after its control campaign technique of sterilising male tsetse. However, Columbian tsetse researchers seek to facilitate the process of sterilising the male tsetse flies, with the aim to eradicate the tsetse population in Africa.
While working as an intern at the International Atomic Energy Agency (IAEA) in 2014, Moran first used near-infrared light to peer inside the pupae of tsetse flies. She placed the pupae under a microscope and used the near-infrared light to photograph them, allowing her to discern if the developing flies were male or female. She designed this novel sorting technique to support the Sterile Insect Technique, which the IAEA has used to eradicate tsetse populations in Zanzibar and other countries. The sterilizing technique uses irradiation to render large numbers of male flies infertile. The flies are then released into breeding grounds, where they mate with female flies.
This innovative research project suggests a more simplified and time-saving method to fight the tsetse population, as opposed to the manual technique used by fly-production labs such as the one in Senegal. Once the project is completed, the production of sterile male tsetse will increase and the unfertilized mating will drastically reduce the tsetse population which will help eliminate the spread of the disease. Eliminating tsetse flies will, in fact, change the lives of farmers in sub-Saharan African countries especially. Livestock production will no longer be at risk, rural living will be conducive and inhabitants will have the right conditions to go about their commercial activities. Furthermore, this will create an enabling environment for people to explore economic activities, which will not only improve their immediate living conditions but also contribute to the growth of Africa’s economy.
The team consists of three other scientists with a common goal to find solutions to public-health problems. They include: Szabolcs Marka; an astrophysicist with an expertise in biophysics, Zsuzsa Marka; an experimental physicist, John Wright; an electrical engineer who does high-dimensional data analysis and develops algorithms to solve imaging problems – in this case, the pupae images.
Szabolcs Marka and Zsuzsa Marka had previously collaborated on insect behavior research, including how to mitigate malaria mosquitoes and fruit flies. If sex-sorting by machine learning could be applied to insects like mosquitoes, perhaps illnesses such as malaria and dengue fever might also come under tighter control.
