Dynamics of epidemic diseases without guaranteed immunity

Area of Science:

• Epidemiology
• Statistical Physics
• Infectious Disease Dynamics

Background:

• The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic highlighted novel disease spread dynamics.
• Understanding agent recovery and immunity development is crucial for disease control.

Purpose of the Study:

• To investigate disease spread dynamics where immunity requires prolonged infection.
• To characterize disease phases using statistical field theory.
• To propose effective control strategies based on disease dynamics.

Main Methods:

• Development of a statistical field theory model for disease spread.
• Analysis of disease phases: pandemic and response regimes.
• Quantitative testing of the model using an idealized disease network.

Main Results:

• The statistical field theory accurately bounds the peak infection rate.
• The model effectively describes the SARS-CoV-2 outbreak in Wuhan, China.
• Only 30% of recovered agents developed immunity.

Conclusions:

• Disease dynamics can be characterized by phases within a statistical field theory framework.
• Maintaining the 'response regime' is key to preventing a 'second wave' or pandemic.
• The model provides insights into SARS-CoV-2 immunity and epidemic control.