  At the time of writing this paper, the world has around eleven million cases
of COVID-19, scientifically known as severe acute respiratory syndrome
corona-virus 2 (SARS-COV-2). One of the popular critical steps various health
organizations are advocating to prevent the spread of this contagious disease
is self-assessment of symptoms. Multiple organizations have already pioneered
mobile and web-based applications for self-assessment of COVID-19 to reduce
this global pandemic's spread. We propose an intelligent voice-based assistant
for COVID-19 self-assessment (IVACS). This interactive assistant has been built
to diagnose the symptoms related to COVID-19 using the guidelines provided by
the Centers for Disease Control and Prevention (CDC) and the World Health
Organization (WHO). The empirical testing of the application has been performed
with 22 human subjects, all volunteers, using the NASA Task Load Index (TLX),
and subjects performance accuracy has been measured. The results indicate that
the IVACS is beneficial to users. However, it still needs additional research
and development to promote its widespread application.
