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COVID-19 Prevention, which combines the soft approaches and best practicesfor public health safety, is the only recommended solution from the healthscience and management society side considering the pandemic era. In an attemptto evaluate the validity of such claims in a conflict and COVID-19-affectedcountry like Afghanistan, we conducted a large-scale digital social experimentusing conversational AI and social platforms from an info-epidemiology and aninfoveillance perspective. This served as a means to uncover an underlingtruth, give large-scale facilitation support, extend the soft impact ofdiscussion to multiple sites, collect, diverge, converge and evaluate a largeamount of opinions and concerns from health experts, patients and local people,deliberate on the data collected and explore collective prevention approachesof COVID-19. Finally, this paper shows that deciding a prevention measure thatmaximizes the probability of finding the ground truth is intrinsicallydifficult without utilizing the support of an AI-enabled discussion systems.

A Contribution to COVID-19 Prevention through Crowd Collaboration using Conversational AI & Social Platforms