AI to Help Combat Malaria in Africa

Researchers at the University of South Florida are revolutionizing mosquito monitoring with artificial intelligence to help fight malaria in Africa. Together with an interdisciplinary team of researchers, Ryan Carney, associate professor of integrative biology, and Sriram Chellappan, professor in the department of computer science and engineering, will advance the study of malaria and explore creative ways to target malaria-infected mosquitoes in real time.

AI to Help Combat Malaria in Africa
“Our algorithm automatically identifies the head, thorax, abdomen, wings, and legs from a mosquito image; then it uses specific anatomical components to identify the mosquito type – for example, the wing for Anopheles stephensi.” Image Credit: University of South Florida.

The National Institute of Allergy and Infectious Diseases, a division of the National Institutes of Health, provided $3.6 million in funding to support the initiative, which is a component of a multinational endeavor. A new International Center for Excellence for Malaria Research will be established in west-central Africa as part of the EMERGENTS (Enhancing Malaria Epidemiology Research through Genomics and Translational Systems) initiative.

The World Health Organization reports that there were 249 million new cases of malaria worldwide in 2022, with 608,000 cases ending in death. Africa bears a disproportionate burden of the disease, accounting for 95 % of global malaria fatalities in 2022.

Over the next five years, the international center will advance evidence-based malaria eradication and elimination strategies, such as training a new generation of African scientists, improving understanding of insecticide resistance, and tracking the geographic spread of Anopheles stephensi. This dangerous urban malaria vector has recently begun to invade Africa.

The information acquired at the facility will be utilized to manage malaria globally. While the EMERGENTS initiative's major focus is on Africa, the technologies and methodology produced via this project have important implications for the United States. With its favorable climate and high number of international visitors, Florida is an important hub for tracking mosquito-borne illnesses.

Carney and Chellappan will spearhead the project's image-driven mosquito monitoring activities by teaching local scientists how to use citizen science via, a worldwide mosquito-tracking dashboard they founded in 2022 with National Science Foundation support.

The online dashboard merges hundreds of thousands of mosquito observations from multiple platforms into an interactive, real-time dashboard and data gateway, utilizing images uploaded from smartphones.

Chellappan is developing an artificial intelligence-enabled smart trap to lure, catch, and monitor Anopheles stephensi, using some of the same unique techniques. During this project, various prototypes of the patent-pending smart trap will be deployed throughout west-central Africa to catch and automate the identification of Anopheles stephensi in real time.

We are the only team that we know of globally that can successfully enable anatomy-based classification from a single photo to identify mosquitoes. Our algorithm automatically identifies the head, thorax, abdomen, wings, and legs from a mosquito image; then, it uses specific anatomical components to identify the mosquito type–for example, the wing for Anopheles stephensi.

Sriram Chellappan, Professor, Department of Computer Science and Engineering, University of South Florida

The dashboard and smart trap are strong tools that offer researchers and mosquito control staff real-time data to detect invasive and disease-carrying mosquitos. Carney and Chellappan’s earlier investigations illustrate the efficacy of the dashboard and citizen science.

This technique has previously been tested in countries such as Ethiopia and Madagascar through citizen science activities as part of an ongoing campaign initiated in 2022 in conjunction with the Centers for Disease Control and Prevention. The additional funding from this new research will allow Carney and Chellappan to fine-tune their algorithms and add other species to automated identification, with Anopheles stephensi as the primary aim.

Anopheles stephensi is a very efficient vector of malaria, and something that has adapted itself to the human environment. Therefore, it can cause huge, unprecedented epidemics in urban centers, which we have already started to see unfolding in Africa. Florida is ground-zero for mosquito-borne diseases in the U.S., and although Anopheles stephensi has not yet been detected domestically, our citizen science infrastructure and species identification technologies ensure that we are prepared to fight this potential threat.

Ryan Carney, Associate Professor, Department of Integrative Biology, University of South Florida

Chellappan believes that as technology progresses during this project, the traps will be provided to individuals at a reasonable price, enhancing community-led mosquito surveillance and control both internationally and locally.

The University of Florida, the African Centre of Excellence for Genomics of Infectious Diseases, the Centre for Research in Infectious Diseases, the University of North Carolina at Chapel Hill, the Africa CDC, Brown University, the Centre Pasteur du Cameroun, CERMEL Gabon, DELGEME Plus Mali, the Naval Medical Research Unit-3 Italy, and the University of Dschang in Cameroon are just a few of the many international partners involved in this multidisciplinary global project.

USF received funds as a subaward under NIAID grant number U19AI181594 to the University of Florida.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.