Fluid dynamics and epidemiology: Seasonality and transmission dynamics

Area of Science:

• Epidemiology
• Environmental Science
• Fluid Dynamics

Background:

• Epidemic models often overlook climate's impact on virus transmission dynamics.
• Understanding seasonal influences on airborne pathogens is crucial for pandemic preparedness.

Purpose of the Study:

• To investigate the relationship between weather seasonality, airborne virus transmission, and pandemic outbreaks.
• To develop a new index quantifying airborne infection risk based on climate factors.

Main Methods:

• Utilized high-fidelity multi-phase fluid dynamics simulations to model virus particle concentration.
• Derived a novel Airborne Infection Rate (AIR) index from simulation data.
• Integrated the AIR index with a susceptible-infected-recovered (SIR) epidemiological model.

Main Results:

• Demonstrated that weather seasonality drives two distinct pandemic outbreaks annually.
• Showcased the correlation between temperature, humidity, wind speed, and viral transmission rates.
• Presented case numbers and transmission data for New York, Paris, and Rio de Janeiro.

Conclusions:

• Two pandemic outbreaks per year are an inevitable consequence of weather seasonality.
• The proposed AIR index offers a method to incorporate climate effects into epidemiological models.
• Epidemiological models require climate considerations for accurate pandemic forecasting.