Measuring Infection Transmission in a Stochastic SIV Model with Infection Reintroduction and Imperfect Vaccine

Area of Science:

• Epidemiology
• Mathematical Biology
• Public Health

Background:

• Stochastic epidemic models are crucial for understanding disease spread.
• The basic reproduction number (R0) is a key metric for herd immunity but may overestimate transmission with imperfect vaccines.
• Existing models often do not fully account for vaccinated populations or vaccine efficacy.

Purpose of the Study:

• To incorporate a vaccinated compartment into a SIS stochastic epidemic model.
• To define and evaluate alternative transmission measures beyond R0 for imperfect vaccines.
• To analyze the impact of initial vaccination coverage and vaccine efficacy on epidemic dynamics.

Main Methods:

• Utilized a continuous-time Markov chain to model disease spread.
• Introduced a vaccinated compartment into the SIS model framework.
• Defined and analyzed alternative epidemiological metrics to R0.

Main Results:

• The basic reproduction number can overestimate secondary infections in models with vaccinated individuals.
• Alternative measures provide a more accurate assessment of transmission potential with imperfect vaccines.
• Initial vaccination coverage and vaccine efficacy significantly influence epidemic spread.

Conclusions:

• The study highlights limitations of R0 for imperfect vaccination strategies.
• Proposed alternative measures offer improved insights for public health interventions.
• Optimizing immunization coverage requires considering vaccine efficacy and model refinements.