  COVID-19 Prevention, which combines the soft approaches and best practices
for public health safety, is the only recommended solution from the health
science and management society side considering the pandemic era. In an attempt
to evaluate the validity of such claims in a conflict and COVID-19-affected
country like Afghanistan, we conducted a large-scale digital social experiment
using conversational AI and social platforms from an info-epidemiology and an
infoveillance perspective. This served as a means to uncover an underling
truth, give large-scale facilitation support, extend the soft impact of
discussion to multiple sites, collect, diverge, converge and evaluate a large
amount of opinions and concerns from health experts, patients and local people,
deliberate on the data collected and explore collective prevention approaches
of COVID-19. Finally, this paper shows that deciding a prevention measure that
maximizes the probability of finding the ground truth is intrinsically
difficult without utilizing the support of an AI-enabled discussion systems.
