Researchers at the University of South Florida (USF) are leveraging artificial intelligence to transform mosquito surveillance in a groundbreaking effort to combat malaria in Africa. Spearheaded by Ryan Carney, an associate professor of integrative biology, and Sriram Chellappan, a professor in the department of computer science and engineering, this interdisciplinary initiative aims to develop real-time solutions for targeting malaria-infected mosquitoes.
Funded by a $3.6 million grant from the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), the project, known as EMERGENTS (Enhancing Malaria Epidemiology Research through Genomics and Translational Systems), will establish a new International Center for Excellence for Malaria Research in west-central Africa, involving expertise from Nigeria and Cameroon. According to the World Health Organization (WHO), there were 249 million new malaria cases globally in 2022, resulting in 608,000 deaths, with Africa bearing 95% of these fatalities.
Objectives and Scope of EMERGENTS
Over the next five years, the center will focus on evidence-based strategies for malaria eradication and elimination. This includes training a new generation of African scientists, enhancing the understanding of insecticide resistance, and investigating the spread of Anopheles stephensi, an urban malaria vector that has recently invaded Africa. The gathered data will contribute to the global management of malaria. While Africa is the primary focus, the developed technology and methodologies have significant implications for the United States, particularly in Florida, a state vulnerable to mosquito-borne illnesses due to its climate and high international travel rate.
Advanced Mosquito Surveillance Technology
Carney and Chellappan will lead efforts in image-driven mosquito surveillance, training local scientists to utilize citizen science through mosquitodashboard.org. This global mosquito-tracking dashboard, created by Carney and Chellappan in 2022 with National Science Foundation funding, integrates hundreds of thousands of mosquito observations from various platforms into an interactive, real-time data portal using photos uploaded by the public from their smartphones.
Chellappan is also developing an AI-enabled smart trap to lure, capture, and monitor Anopheles stephensi. This patent-pending smart trap will be deployed across west-central Africa during the project to automate the identification of Anopheles stephensi in real-time.
Innovative AI Algorithms
“Our team is uniquely capable of using anatomy-based classification from a single photo to identify mosquitoes,” Chellappan stated. “Our algorithm automatically identifies specific anatomical components such as the head, thorax, abdomen, wings, and legs, using these to determine the mosquito species—such as the wings for Anopheles stephensi.”
The dashboard and smart traps provide real-time data to researchers and mosquito-control personnel, aiding in the early detection of invasive and disease-carrying mosquitoes. Carney and Chellappan’s previous studies, in collaboration with the Centers for Disease Control and Prevention (CDC), have successfully piloted these tools in countries like Ethiopia and Madagascar since 2022. The additional funding will refine these algorithms and include more species, focusing primarily on Anopheles stephensi.
“Anopheles stephensi is a highly efficient malaria vector, adapted to human environments,” Carney explained. “It can cause significant epidemics in urban centers, as we’ve begun to see in Africa. While this species hasn’t been detected in the U.S. yet, our citizen science infrastructure and identification technologies ensure we’re prepared for such threats.”
Future Prospects and Collaboration
Chellappan hopes that as technology advances, these smart traps can be sold at an affordable price, enhancing community-led mosquito surveillance and control locally and internationally.
This global interdisciplinary project includes collaborators from the University of Florida, African Centre of Excellence for Genomics of Infectious Diseases, Centre for Research in Infectious Diseases, University of North Carolina at Chapel Hill, Africa CDC, Brown University, Centre Pasteur du Cameroun, CERMEL Gabon, DELGEME Plus Mali, Naval Medical Research Unit-3 Italy, and the University of Dschang in Cameroon.
USF’s participation is funded under NIAID grant number U19AI181594 to the University of Florida. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Cite this article as (APA format):
AR Managing Editor (2024). USF Researchers Use AI for Advanced Mosquito Surveillance to Combat Malaria in Africa. Retrieved from https://www.africanresearchers.org/usf-researchers-use-ai-for-advanced-mosquito-surveillance-to-combat-malaria-in-africa/
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