Mass Testing and Proactiveness Affect Epidemic Spreading

Abstract

The detection and management of diseases become quite
complicated when pathogens contain asymptomatic phenotypes
amongst their ranks, as evident during the recent COVID-19 pandemic.
Spreading of diseases has been studied extensively under the paradigm
of susceptible–infected–recovered–deceased (SIRD) dynamics. Various
game-theoretic approaches have also addressed disease spread, many
of which consider S , I , R , and D as strategies rather than as states.
Remarkably, most studies from the above approaches do not account
for the distinction between the symptomatic or asymptomatic aspect of
the disease. It is well-known that precautionary measures like washing
hands, wearing masks and social distancing significantly mitigate the
spread of many contagious diseases. Herein, we consider the adoption
of such precautions as strategies and treat S , I , R , and D as states.
We also attempt to capture the differences in epidemic spreading arising
from symptomatic and asymptomatic diseases on various network topologies.
Through extensive computer simulations, we examine that the cost
of maintaining precautionary measures as well as the extent of mass testing
in a population affects the final fraction of socially responsible individuals.
We observe that the lack of mass testing could potentially lead
to a pandemic in case of asymptomatic diseases. Network topology also
seems to play an important role. We further observe that the final fraction
of proactive individuals depends on the initial fraction of both infected as
well as proactive individuals. Additionally, edge density can significantly
influence the overall outcome. Our findings are in broad agreement with
the lessons learnt from the ongoing COVID-19 pandemic.