On the numerical computation of $R_0$ in periodic environments
By: Dimitri Breda, Simone De Reggi, Jordi Ripoll
Potential Business Impact:
Predicts disease spread faster and easier.
We propose a novel approach to approximate the basic reproduction number $R_0$ as spectral radius of the Next-Generation Operator in time-periodic population models by characterizing the latter via evolution semigroups. Once birth/infection and transition operators are identified, we discretize them via either Fourier or Chebyshev collocation methods. Then $R_0$ is obtained by solving a generalized matrix eigenvalue problem. The order of convergence of the approximating reproduction numbers to the true one is shown to depend on the regularity of the model coefficients, and spectral accuracy is proved. We validate the theoretical results by discussing applications to epidemiology, viz. a large-size multi-group epidemic model with periodic contact rates, and a vector-borne disease model with seasonal vector recruitment. We illustrate how the method facilitates implementation compared to existing approaches and how it can be easily adapted to also compute type-reproduction numbers.
Similar Papers
The signal is not flushed away: Inferring the effective reproduction number from wastewater data in small populations
Methodology
Tracks disease spread better to predict outbreaks.
Reproduction Number and Spatial Connectivity Structure Estimation via Graph Sparsity-Promoting Penalized Functional
Signal Processing
Tracks how fast sickness spreads, even with bad data.
Higher-order spacings in the superposed spectra of random matrices with comparison to spacing ratios and application to complex systems
Data Analysis, Statistics and Probability
Finds hidden patterns in complex systems.