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How Interactions during Viral-Viral Coinfection Can Shape Infection Kinetics.

Lubna Pinky1, Joseph R DeAguero2, Christopher H Remien3

  • 1Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.

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Summary
This summary is machine-generated.

Viral coinfections can worsen or reduce disease severity through complex interactions. Mathematical modeling revealed that virus-specific cell clearance rates significantly influence outcomes in coinfections like influenza A virus with RSV or SARS-CoV-2.

Keywords:
RSVSARS-CoV-2influenzamathematical modelingrhinovirusviral coinfectionviral dynamics

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Area of Science:

  • Virology and Mathematical Biology
  • Respiratory viral infections
  • Viral-viral interactions

Background:

  • Respiratory viral infections are a major global health concern, with coinfections being common.
  • The impact of viral coinfections on disease severity is variable, ranging from reduced to increased pathogenicity.
  • Mechanisms underlying these divergent outcomes in viral coinfections are not fully understood.

Purpose of the Study:

  • To investigate the mechanisms driving distinct disease outcomes in viral coinfections.
  • To predict potential dynamics of viral-viral interactions using mathematical modeling.
  • To explore how different infection orders, timings, and viral pairings affect disease severity.

Main Methods:

  • Mathematical models were fitted to viral load data from ferrets infected with respiratory syncytial virus (RSV) and influenza A virus (IAV).
  • Model simulations explored unexamined coinfection scenarios, including different infection orders and viral pairings (e.g., IAV with rhinovirus (RV) or SARS-CoV-2 (CoV2)).
  • Human viral load data and murine weight-loss data from single and coinfections were used to interpret model results.

Main Results:

  • In RSV-IAV coinfection, IAV reduced RSV production, and RSV slowed IAV-infected cell clearance.
  • Coinfection with IAV and RV or CoV2 in mice showed increased severity, likely due to slower IAV-infected cell clearance.
  • When IAV followed RV, improved outcomes correlated with IAV reducing RV-infected cell clearance rates.

Conclusions:

  • Mathematical modeling of viral coinfections provides insights into how viral-viral interactions regulate disease severity.
  • Virus-specific infected cell clearance rates are key determinants of coinfection outcomes.
  • The study generates testable hypotheses for experimental evaluation of viral coinfection dynamics.