Pandemic Mitigation: the Basic Reproduction Number
Abstract
PANDEMIC is a new, time-dependent simulation model treating the infectious spread of a disease in a complex, geographically varied region containing millions of people. In PANDEMIC, each person in the region interacts with others while moving from place to place to commute to work, attend meetings and school, shop and return to or stay at home. This model uses an NRL-developed algorithm called the Monotonic Lagrangian Grid (MLG) to determine who is close to whom during the peoples daily routines. PANDEMIC allows what if tests of different personal and societal public health behaviors and mitigation strategies to compare their impact and effectiveness. The goal of PANDEMIC is to predict the complex nonlinear interactions involved in mitigating the Covid-19 pandemic. This paper spotlights the basic reproduction number, R0, an often referenced public heath metric for evaluating epidemics and transmissible disease spread. R0(t), difficult to determine in the uncertainty of an evolving real world epidemic, is evaluated through detailed simulations tracking viral infection. The algorithm used to evaluate R0(t) is presented. Using a 52-week simulation of the first year of the Covid-19 pandemic, we discuss several issues in applying R0 as a public health metric. The time dependence of R0 is shown in three sets of idealized scenarios where environmental and behavioral parameters are held constant. However, real life scenarios have time-dependent behavior and mitigation responses which require a self-consistent treatment of the time span over which a metric like R0 is calculated. Our time dependent calculation of R0 successfully follows the evolution of the epidemic but it is not helpful in predicting a timely response during an ongoing epidemic. This simulation demonstrates definitively that R0 is not a metric intrinsic to the virus, measures, as was done in South Korea and Japan, showing what might have been achieved without testing or vaccines.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 26, 2021
- Accession Number
- AD1153857
Entities
People
- David R. Boris
- Jay Boris
- Keith Obenschain
Organizations
- United States Naval Research Laboratory