The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development
Abstract Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and its role in preparedness and responses, ra...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Molecular Biomedicine |
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| Online Access: | https://doi.org/10.1186/s43556-024-00238-3 |
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| author | Mayur Suresh Gawande Nikita Zade Praveen Kumar Swapnil Gundewar Induni Nayodhara Weerarathna Prateek Verma |
| author_facet | Mayur Suresh Gawande Nikita Zade Praveen Kumar Swapnil Gundewar Induni Nayodhara Weerarathna Prateek Verma |
| author_sort | Mayur Suresh Gawande |
| collection | DOAJ |
| description | Abstract Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and its role in preparedness and responses, ranging from enhanced epidemiological modelling to the acceleration of vaccine development. The confluence of AI technologies has guided us in a new era of data-driven decision-making, revolutionizing our ability to anticipate, mitigate, and treat infectious illnesses. The review begins by discussing the impact of a pandemic on emerging countries worldwide, elaborating on the critical significance of AI in epidemiological modelling, bringing data-driven decision-making, and enabling forecasting, mitigation and response to the pandemic. In epidemiology, AI-driven epidemiological models like SIR (Susceptible-Infectious-Recovered) and SIS (Susceptible-Infectious-Susceptible) are applied to predict the spread of disease, preventing outbreaks and optimising vaccine distribution. The review also demonstrates how Machine Learning (ML) algorithms and predictive analytics improve our knowledge of disease propagation patterns. The collaborative aspect of AI in vaccine discovery and clinical trials of various vaccines is emphasised, focusing on constructing AI-powered surveillance networks. Conclusively, the review presents a comprehensive assessment of how AI impacts epidemiological modelling, builds AI-enabled dynamic models by collaborating ML and Deep Learning (DL) techniques, and develops and implements vaccines and clinical trials. The review also focuses on screening, forecasting, contact tracing and monitoring the virus-causing pandemic. It advocates for sustained research, real-world implications, ethical application and strategic integration of AI technologies to strengthen our collective ability to face and alleviate the effects of global health issues. |
| format | Article |
| id | doaj-art-23ee960162864adb8c7cba797cd64f3f |
| institution | Kabale University |
| issn | 2662-8651 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Molecular Biomedicine |
| spelling | doaj-art-23ee960162864adb8c7cba797cd64f3f2025-01-05T12:05:08ZengSpringerMolecular Biomedicine2662-86512025-01-016112510.1186/s43556-024-00238-3The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine developmentMayur Suresh Gawande0Nikita Zade1Praveen Kumar2Swapnil Gundewar3Induni Nayodhara Weerarathna4Prateek Verma5Department of Artificial Intelligence and Data Science, Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (Deemed to Be University), Sawangi (Meghe)Department of Artificial Intelligence and Data Science, Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (Deemed to Be University), Sawangi (Meghe)Department of Computer Science and Medical Engineering, Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (Deemed to Be University), Sawangi (Meghe)Department of Artificial Intelligence and Machine Learning, Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (Deemed to Be University)Department of Biomedical Sciences, School of Allied Health Sciences, Datta Meghe Institute of Higher Education and Research (Deemed to Be University)Department of Artificial Intelligence and Machine Learning, Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (Deemed to Be University)Abstract Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and its role in preparedness and responses, ranging from enhanced epidemiological modelling to the acceleration of vaccine development. The confluence of AI technologies has guided us in a new era of data-driven decision-making, revolutionizing our ability to anticipate, mitigate, and treat infectious illnesses. The review begins by discussing the impact of a pandemic on emerging countries worldwide, elaborating on the critical significance of AI in epidemiological modelling, bringing data-driven decision-making, and enabling forecasting, mitigation and response to the pandemic. In epidemiology, AI-driven epidemiological models like SIR (Susceptible-Infectious-Recovered) and SIS (Susceptible-Infectious-Susceptible) are applied to predict the spread of disease, preventing outbreaks and optimising vaccine distribution. The review also demonstrates how Machine Learning (ML) algorithms and predictive analytics improve our knowledge of disease propagation patterns. The collaborative aspect of AI in vaccine discovery and clinical trials of various vaccines is emphasised, focusing on constructing AI-powered surveillance networks. Conclusively, the review presents a comprehensive assessment of how AI impacts epidemiological modelling, builds AI-enabled dynamic models by collaborating ML and Deep Learning (DL) techniques, and develops and implements vaccines and clinical trials. The review also focuses on screening, forecasting, contact tracing and monitoring the virus-causing pandemic. It advocates for sustained research, real-world implications, ethical application and strategic integration of AI technologies to strengthen our collective ability to face and alleviate the effects of global health issues.https://doi.org/10.1186/s43556-024-00238-3Artificial intelligenceCOVID-19Global healthEpidemiological modellingMachine learning algorithmsVaccine development |
| spellingShingle | Mayur Suresh Gawande Nikita Zade Praveen Kumar Swapnil Gundewar Induni Nayodhara Weerarathna Prateek Verma The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development Molecular Biomedicine Artificial intelligence COVID-19 Global health Epidemiological modelling Machine learning algorithms Vaccine development |
| title | The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development |
| title_full | The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development |
| title_fullStr | The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development |
| title_full_unstemmed | The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development |
| title_short | The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development |
| title_sort | role of artificial intelligence in pandemic responses from epidemiological modeling to vaccine development |
| topic | Artificial intelligence COVID-19 Global health Epidemiological modelling Machine learning algorithms Vaccine development |
| url | https://doi.org/10.1186/s43556-024-00238-3 |
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