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.