  Currently, the world seeks to find appropriate mitigation techniques to
control and prevent the spread of the new SARS-CoV-2. In our paper herein, we
present a peculiar Multi-Task Learning framework that jointly predicts the
effect of SARS-CoV-2 as well as Personal-Protective-Equipment consumption in
Community Health Centres for a given populace. Predicting the effect of the
virus (SARS-CoV-2), via studies and analyses, enables us to understand the
nature of SARS-CoV- 2 with reference to factors that promote its growth and
spread. Therefore, these foster widespread awareness; and the populace can
become more proactive and cautious so as to mitigate the spread of Corona Virus
Disease 2019 (COVID- 19). Furthermore, understanding and predicting the demand
for Personal Protective Equipment promotes the efficiency and safety of
healthcare workers in Community Health Centres. Owing to the novel nature and
strains of SARS-CoV-2, relatively few literature and research exist in this
regard. These existing literature have attempted to solve the problem
statement(s) using either Agent-based Models, Machine Learning Models, or
Mathematical Models. In view of this, our work herein adds to existing
literature via modeling our problem statements as Multi- Task Learning
problems. Results from our research indicate that government actions and human
factors are the most significant determinants that influence the spread of
SARS-CoV-2.
