Optimal vaccination policy to prevent endemicity: a stochastic model

Area of Science:

• Epidemiology
• Mathematical Biology
• Immunology

Background:

• Waning immunity and recurrent vaccination are critical factors in maintaining endemic disease states.
• Understanding the dynamics of immunity loss and booster dose timing is essential for effective public health strategies.

Purpose of the Study:

• To investigate the impact of waning immunity and vaccination schedules on the establishment of endemic equilibrium.
• To determine criteria for endemic equilibrium existence based on immunity loss and booster dose distribution.
• To evaluate the effectiveness of different vaccination policies, including booster spacing and access equity.

Main Methods:

• Development of an individual-based model incorporating memory effects for transmission and immunity.
• Stochasticity at the individual level considered.
• Derivation of large-scale epidemic behavior equations by taking the population size to infinity.

Main Results:

• A criterion for endemic equilibrium existence was identified, dependent on immunity loss rate and booster dose timing.
• Evenly spaced booster shots are more effective than irregular ones in preventing disease spread.
• A critical vaccination coverage threshold for disease eradication was derived, similar to imperfect vaccine outbreak prevention.

Conclusions:

• Vaccination policy outcomes are influenced by vaccine efficacy and booster dose distribution.
• Fair vaccine allocation is optimal for preventing endemicity.
• Regular, evenly spaced booster vaccinations are key to controlling endemic diseases.