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Artificial intelligence (AI): a new window to revamp the vector-borne disease control

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Abstract

Artificial intelligence (AI) facilitates scientists to devise intelligent machines that work and behave like humans to resolve difficulties and problems by utilizing minimal resources. The Healthcare sector has benefited due to this. Mosquito-transmitted diseases pose a significant health risk. Despite all advances, present strategies for curbing these diseases still depend largely on controlling the mosquito vectors. This strategy demands an army of entomology experts for thorough monitoring, determining, and finally eradicating the targeted mosquito population. Deep learning (DL) algorithms may substitute such unmanageable processes. The current review focuses on how AI, with particular emphasis on deep learning, demonstrates effectiveness in quick detection, identification, monitoring, and finally controlling the target mosquito populations with minimal resources. It accelerates the pace of operation and data exploration on ongoing evolutionary status, tendency to feed blood, and age grading of mosquitoes. The successful combination of computer and biological sciences will provide practical insight and generate a new research niche in this study area.

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Acknowledgements

The first author would like to thank University Grants Commission, Government of India for financial support. Further, authors are thankful to the Head, Post Graduate Department of Zoology, Berhampur University, Berhampur, Odisha, for providing necessary facilities and encouragement.

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Authors and Affiliations

  1. P.G. Department of Zoology, Berhampur University, Bhanjabihar-760007, Odisha, India

    Basudev Nayak, Laxman Kumar Murmu & Tapan Kumar Barik

  2. PG Department of Computer Science, Berhampur University, Bhanjabihar-760007, Odisha, India

    Bonomali Khuntia

  3. P.G. Department of Biotechnology and Bioinformatics, Sambalpur University, JyotiVihar-768019, Odisha, India

    Bijayalaxmi Sahu

  4. Integrated Disease Surveillance Programme (IDSP), State Surveillance Unit, Dte. of Public Health, Odisha-751 001, Odisha, India

    Rabi Sankar Pandit

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  1. Basudev Nayak
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Basudev Nayak performed the literature search and drafted the article. Bonomali Khuntia drafted the article.Laxman Kumar Murmu did literature search and drafted the article. Bijayalaxmi Sahu performed literature search. Rabi Sankar Pandit drafted the article and Tapan Kumar Barik conceptualized and drafted the article.

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Correspondence to Tapan Kumar Barik.

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Nayak, B., Khuntia, B., Murmu, L.K. et al. Artificial intelligence (AI): a new window to revamp the vector-borne disease control. Parasitol Res 122, 369–379 (2023). https://doi.org/10.1007/s00436-022-07752-9

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