CovidSim

CovidSim simulates COVID-19 transmission dynamics using a SEIR (Susceptible, Exposed, Infectious, Recovered) model to evaluate the impact of intervention strategies on epidemiological outcomes in a hypothetical European country with a population of 10 million.

Key Features:

• SEIR Model Implementation: Uses a compartmental SEIR model that categorizes individuals as Susceptible (S), Exposed (E), Infectious (I), and Recovered (R).
• Intervention Analysis: Allows variation of contact-reduction parameters to represent social distancing, lockdowns, and other public health measures and assess their effects on transmission.
• Outcome Prediction: Produces quantitative predictions of population-level outcomes, estimating 22%–63% infection prevalence, 0.2%–0.6% hospitalizations, and 0.07%–0.28% mortality under different scenarios.
• Scenario Planning: Simulates multiple control strategies to compare timing and magnitude of epidemic peaks and to assess intervention timing relative to vaccine availability.

Scientific Applications:

• Intervention impact evaluation: Quantifies how varying levels of contact reduction alter epidemic peak timing and magnitude.
• Burden estimation: Estimates population-level infection prevalence, hospitalization needs, and mortality under alternative intervention scenarios.
• Scenario comparison: Compares prospective control strategies to inform timing of interventions relative to vaccine rollout or other resource planning.

Methodology:

Simulates a compartmental SEIR model (S, E, I, R) with parameter adjustments for contact reduction (e.g., social distancing, lockdowns) and runs scenario simulations to generate quantitative estimates of infections, hospitalizations, and mortality.