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Global pandemics cause strong negative impacts on global health, economies, education, socialisation, and recreation. The COVID-19 global pandemic has challenged government policymakers and business decision-makers to make efficient, effective, and ethical decisions to mitigate its damages. In this research, we evaluate how ‘Analytics Decision Support Systems (DSS)’ are supporting decision making in public health with descriptive, predictive, and prescriptive analytics. We use the WHO-INTEGRATE Evidence-to-Decision (EtD) Framework and selectively evaluate recent research in Analytics DSS published in the Analytics and Public Health domains. Our findings reveal concentration in the utilization of predictive analytics and the focusing only on two of the six core criteria: balance of health benefits/harms and societal implications. We suggest that future research address the other four areas: human rights and socio-cultural acceptability; health equity, equality, and non-discrimination; financial and economic considerations; feasibility and health system considerations, and the integration of big data advanced technologies.

Evaluating analytics DSS for the COVID-19 pandemic through WHO-INTEGRATE EtD for health policy