Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability.

The emerging coronavirus SARS-CoV-2 has caused a COVID-19 pandemic. SARS-CoV-2 causes a generally mild, but sometimes severe and even life-threatening infection, known as COVID-19. Currently, there exist no effective vaccines or drugs and, as such, global public authorities have so far relied upon non pharmaceutical interventions (NPIs). Since COVID-19 symptoms are aspecific and may resemble a common cold, if it should come back with a seasonal pattern and coincide with the influenza season, this would be particularly challenging, overwhelming and straining the healthcare systems, particularly in resource-limited contexts, and would increase the likelihood of nosocomial transmission. In the present study, we devised a mathematical model focusing on the treatment of people complaining of influenza-like-illness (ILI) symptoms, potentially at risk of contracting COVID-19 or other emerging/re-emerging respiratory infectious agents during their admission at the health-care setting, who will occupy the detection kits causing a severe shortage of testing resources. The model is used to assess the effect of mass influenza vaccination on the spread of COVID-19 and other respiratory pathogens in the case of a coincidence of the outbreak with the influenza season. Here, we show that increasing influenza vaccine uptake or enhancing the public health interventions would facilitate the management of respiratory outbreaks coinciding with the peak flu season, especially, compensate the shortage of the detection resources. However, how to increase influenza vaccination coverage rate remains challenging. Public health decision- and policy-makers should adopt evidence-informed strategies to improve influenza vaccine uptake.