Can treatment increase the epidemic size?

Area of Science:

• Epidemiology
• Mathematical Biology
• Pharmacology

Background:

• Antiviral treatments are crucial for infectious disease control, especially when vaccines are unavailable.
• Drug resistance evolution and spread significantly hinder epidemic containment efforts.
• Previous models suggest an optimal treatment rate exists to minimize epidemic size, but conditions were unknown.

Purpose of the Study:

• To determine the conditions for an optimal antiviral treatment rate that minimizes epidemic final size.
• To investigate the combined effects of treatment and drug-resistant strain transmissibility on epidemic outcomes.
• To derive novel final size relations for epidemic models with drug-sensitive and drug-resistant strains.

Main Methods:

• Mathematical modeling of infectious disease dynamics incorporating drug resistance.
• Derivation of analytical conditions for the existence of an optimal treatment rate.
• Analysis of a two-strain pathogen model (drug-sensitive and drug-resistant).
• Numerical simulations to illustrate theoretical findings and explore de novo resistance emergence.

Main Results:

• Conditions for the existence of an optimal treatment rate were established for a class of epidemic models.
• The interplay between treatment rate and drug-resistant strain transmissibility was analyzed concerning epidemic final size.
• Novel final size relations were derived for a two-strain epidemic model, accounting for drug resistance.

Conclusions:

• Optimal antiviral treatment strategies are essential for minimizing epidemic spread, considering drug resistance.
• Understanding the conditions for optimal treatment rates can improve public health interventions.
• This research provides a theoretical framework for managing infectious diseases in the presence of antiviral drug resistance.