COVID-19 or Influenza, or Both? A Comparison and Algorithmic Approach to Management

Abstract

Context: First cases of Coronavirus disease 2019 (COVID-19) were reported in December 2019. With more than 100 million confirmed cases 14 months later, the disease has become the worst public-health dilemma of the century. The rapid global spread of COVID-19 has resulted in an international health emergency, threatening to overwhelm health care systems in many parts of the world, especially poor resource countries. Evidence Acquisition: Influenza and COVID-19 have similar clinical symptoms, and both cause a respiratory illness that may vary from mild to severe. Both diseases have the same mode of transmission and require similar public health guidelines to prevent their spread, but their treatment strategies are different. In this study, an algorithmic method is proposed for managing patients according to their symptoms for each of these infections. Results: In fall and winter, infections with seasonal influenza and other respiratory viruses become common. As influenza also causes significant morbidity and mortality, especially at the two extremes of age and in those with compromised immunity, it is of major importance to know the similarities and dissimilarities between COVID-19 and seasonal influenza and plan appropriate public health measures to deal with each of these illnesses. Conclusions: Will there be a devastating combined epidemic of COVID-19 and influenza (COV-Flu) during the 2020 - 2021 season? Does co-infection increase the risk of severe illness or amplify virus shedding? Actually, we do not yet know the answers to these questions; so, in this article, first, we attempt to define the similarities and differences between COV-Flu. Then, we will have a brief discussion on how to manage patients presenting with symptoms suggestive of both diseases. However, as COVID-19 has been recognized as a pandemic since December 2019, the management of this emerging disease is rapidly evolving as new information is collected from different parts of the world.