Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases

Abstract

Artificial intelligence (AI) represents a valuable tool that could be widely used to inform clinical and public health decision-making to effectively manage the impacts of a pandemic. The objective of this scoping review was to identify the key use cases for involving AI for pandemic preparedness and response from the peer-reviewed, preprint, and grey literature. The data synthesis had two parts: an in-depth review of studies that leveraged machine learning (ML) techniques and a limited review of studies that applied traditional modeling approaches. ML applications from the in-depth review were categorized into use cases related to public health and clinical practice, and narratively synthesized. One hundred eighty-three articles met the inclusion criteria for the in-depth review. Six key use cases were identified: forecasting infectious disease dynamics and effects of interventions; surveillance and outbreak detection; real-time monitoring of adherence to public health recommendations; real-time detection of influenza-like illness; triage and timely diagnosis of infections; and prognosis of illness and response to treatment. Data sources and types of ML that were useful varied by use case. The search identified 1167 articles that reported on traditional modeling approaches, which highlighted additional areas where ML could be leveraged for improving the accuracy of estimations or projections. Important ML-based solutions have been developed in response to pandemics, and particularly for COVID-19 but few were optimized for practical application early in the pandemic. These findings can support policymakers, clinicians, and other stakeholders in prioritizing research and development to support operationalization of AI for future pandemics.

Rigorous Policy-Making Amid COVID-19 and Beyond: Literature Review and Critical Insights

“…artificial intelligence (AI)-powered: incorporating intelligent and automatic decision-making mechanisms to ensure the policies are developed based on the most updated evidence [ 83 , 94 , 95 , 96 , 97 , 98 ];…”

“…AI can be understood as machine programs or algorithms that are “able to mimic human intelligence” [ 124 ]. The AI-powered component of the PADS model emphasizes the importance of incorporating intelligent and automatic decision-making mechanisms to ensure the policies are developed based on the most updated and comprehensive evidence robustly analyzed [ 83 , 94 , 95 , 96 , 97 , 98 ]. Advanced AI systems can help policymakers to make more informed policies that are both reactive (retrospectively analyzing data to develop intelligent solutions) and proactive (predictive decision-making insights based on advanced modelling) in nature [ 125 , 126 , 127 ].…”

Application of Artificial Intelligence in COVID-19 Diagnosis and Therapeutics

“…It serves as a framework for considering people as a group and aids in the development of measures from the town to city level and, possibly, at national level [ 95 ]. When new epidemics occur in the era of information technology, a new approach to public health that consists of “collective, coordinated, and organized activities to continuously improve the health imbalance of the local population” has been proposed [ 96 ].…”

Google earth engine based computational system for the earth and environment monitoring applications during the COVID-19 pandemic using thresholding technique on SAR datasets

“…Moreover, visualizing the problem, spatially segregating the inundated areas, resilient spatial information, and accurate results with validation. As a result, it provides efficient results to support decision-makers with quick responses for flood monitoring, formulating measures and maintaining social distancing norms during COVID-19 ( Khan and Ramsahai, 2021 ; Shahid et al, 2021 ; Syrowatka et al, 2021 ). Automation is required for an efficient approach to map and deliver robust accurate water maps; avoid expensive and time-consuming manual processing.…”