Related Experiment Video
Updated: Dec 22, 2025

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
Published on: April 9, 2021
Using the contact network model and Metropolis-Hastings sampling to reconstruct the COVID-19 spread on the "Diamond
Feng Liu1, Xin Li2, Gaofeng Zhu3
1Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
Abstract:
Traditional compartmental models such as SIR (susceptible, infected, recovered) assume that the epidemic transmits in a homogeneous population, but the real contact patterns in epidemics are heterogeneous. Employing a more realistic model that considers heterogeneous contact is consequently necessary. Here, we use a contact network to reconstruct unprotected, protected contact, and airborne spread to simulate the two-stages outbreak of COVID-19 (coronavirus disease 2019) on the "Diamond Princess" cruise ship. We employ Bayesian inference and Metropolis-Hastings sampling to estimate the model parameters and quantify the uncertainties by the ensemble simulation technique. During the early epidemic with intensive social contacts, the results reveal that the average transmissibility was 0.026 and the basic reproductive number was 6.94, triple that in the WHO report, indicating that all people would be infected in one month. The and decreased to 0.0007 and 0.2 when quarantine was implemented. The reconstruction suggests that diluting the airborne virus concentration in closed settings is useful in addition to isolation, and high-risk susceptible should follow rigorous prevention measures in case exposed. This study can provide useful implications for control and prevention measures for the other cruise ships and closed settings.
More Related Videos
Related Concept Videos
Steps in Outbreak Investigation
Causality in Epidemiology
Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...

