The interactions of SARS-CoV-2 with cocirculating pathogens: Epidemiological implications and current knowledge gaps

Area of Science:

• Infectious Disease Epidemiology
• Virology
• Mathematical Modeling

Background:

• Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) persistence necessitates understanding coinfections and multiepidemics.
• Interactions between SARS-CoV-2 and other pathogens remain poorly defined, hindering effective forecasting and control.
• Multiepidemics, such as COVID-19 and influenza co-occurrence, may become more frequent.

Purpose of the Study:

• To review existing evidence on SARS-CoV-2 interactions with other pathogens.
• To develop a framework for systematically studying pathogen interactions.
• To inform models for predicting and managing risks associated with pathogen cocirculation.

Main Methods:

• Developed a general framework to characterize pathogen interactions (sign, strength, symmetry, duration, mechanism).
• Reviewed experimental evidence from animal models (ferrets, hamsters, mice) on SARS-CoV-2 coinfections.
• Analyzed epidemiological data from human populations to infer SARS-CoV-2 interaction patterns.
• Formulated transmission models for SARS-CoV-2 cocirculation with other pathogens.

Main Results:

• Animal studies generally showed increased disease severity in SARS-CoV-2 coinfections, particularly with influenza A viruses (IAVs), but viral load effects were inconsistent.
• Epidemiological data suggested potential protective effects of influenza and pneumococcal conjugate vaccinations against SARS-CoV-2 infection, though studies were prone to bias.
• The proposed framework can be integrated into transmission models to study pathogen interactions.

Conclusions:

• Coinfection with SARS-CoV-2 can exacerbate disease severity, highlighting the importance of understanding pathogen interactions.
• Further research, employing robust methodologies and multidisciplinary approaches, is needed to resolve uncertainties surrounding SARS-CoV-2 interactions.
• Transmission models incorporating a comprehensive interaction framework are valuable tools for public health preparedness.