Introduction
As of the beginning of April, over a million people acrossthe globe have
been tested positive for the novel severe acute respiratory syndrome
corona virus 2 (SARS-CoV-2) infection1. Having begun
in Wuhan,China, the epicentre of this pandemic has shifted to the USA
over the past three months. Parallel large scale outbreaks have occurred
in Italy and Spain with a majority of countries struggling to contain
its spread.Cancer patients are believed to be one of the most vulnerable
populations due to the immune compromised state caused by both the
disease and its treatment.2
India has one of the largest incidence of oral cacner in the world. With
the mounting evidence on COVID-19,there are no systematic reports of
cancer patients with COVID-19, let alone oral cancer. Patients with
these cancers are more likely to succumb to COVID-19 than the cancer
itself. It is believed that the SARS-COV-2 would accelerate cell death
in a relatively short span of time, especially in patients receiving
chemotherapeutic agents where the underlying immunity level is
substantially low. Most healthcare administrators are deferring early
stage diseases to be attended to after the situation subsides. The
biggest brunt is being borne by the advanced stage oral cancer patietns,
especially stage IV. Almost all of these tumors will progress to an
unresectable stage by the time the pandemic is contained.Hence,planning
of intervention and an adequate support strategy is required for the
best service to be established.3
We present a simulation model using a multistate approach with
transition-specific hazard functions that would predict the outcomes
ofstage IV oral cancer patients thatreceive cancer directed treatment
and get infected with SARS-CoV-2, and the same patients if they do not
receive any cancer directed treatment and do not get infected with
SARS-CoV-2during the pandemic.This model will provide a unique approach
for setting suitable strategiestaking into account the current complex
scenario of social distancing, human physiology and heterogeneity of the
patients’ disease status.