Showing posts with label epidemiology. Show all posts
Showing posts with label epidemiology. Show all posts

Thursday, December 30, 2021

"Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks"

Another paper of mine has just been published in final form. (Technically, one could say that it's almost in final form; the issue number has been determined, but its stamp is not yet on the .pdf file as I write this blog entry because some other articles from the same issue haven't yet been published.) Here are some details.

Title: "Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks"

Authors: Qinyi Chen and Mason A. Porter

Abstract: In the study of infectious diseases on networks, researchers calculate epidemic thresholds to help forecast whether or not a disease will eventually infect a large fraction of a population. Because network structure typically changes with time, which fundamentally influences the dynamics of spreading processes and in turn affects epidemic thresholds for disease propagation, it is important to examine epidemic thresholds in models of disease spread on temporal networks. Most existing studies of epidemic thresholds in temporal networks have focused on models in discrete time, but most real-world networked systems evolve continuously with time. In our work, we encode the continuous time-dependence of networks in the evaluation of the epidemic threshold of a susceptible–infected–susceptible (SIS) process by studying an SIS model on tie-decay networks. We derive the epidemic-threshold condition of this model, and we perform numerical experiments to verify it. We also examine how different factors—the decay coefficients of the tie strengths in a network, the frequency of the interactions between the nodes in the network, and the sparsity of the underlying social network on which interactions occur—lead to decreases or increases of the critical values of the threshold and hence contribute to facilitating or impeding the spread of a disease. We thereby demonstrate how the features of tie-decay networks alter the outcome of disease spread.

Tuesday, December 17, 2019

"A Two-Patch Epidemic Model with Nonlinear Relapse"

Another of my papers came out in final form today. Here are some details.

Title: A Two-Patch Epidemic Model with Nonlinear Relapse

Authors: Juan G. Calvo, Alberto Hernández, Mason A. Porter, and Fabio Sanchez

Abstract (English version): The propagation of infectious diseases and its impact on individuals play a major role in disease dynamics, and it is important to incorporate population heterogeneity into efforts to study diseases. As a simplistic but illustrative example, we examine interactions between urban and rural populations on the dynamics of disease spreading. Using a compartmental framework of susceptible–infected–susceptible (SIŜ) dynamics with some level of immunity, we formulate a model that allows nonlinear reinfection. We investigate the effects of population movement in a simple scenario: a case with two patches, which allows us to model population movement between urban and rural areas. To study the dynamics of the system, we compute a basic reproduction number for each population (urban and rural). We also compute steady states, determine the local stability of the disease-free steady state, and identify conditions for the existence of endemic steady states. From our analysis and computational experiments, we illustrate that population movement plays an important role in disease dynamics. In some cases, it can be rather beneficial, as it can enlarge the region of stability of a disease-free steady state.

Note: The published paper also has a Spanish version of the abstract.

Saturday, January 19, 2019

What Happens in San José Stays in San José (2019 Edition)

I'll soon be going to San José, Costa Rica for the third time to work on a collaboration on dengue dynamics and control. I'll also be participating in a spiffy panel discussion, where I'll get to meet one of my coauthors in person for the first time.

Wednesday, December 19, 2018

Tales from the ArXiv: Motto: "Somebody has to Study this Shit!"

Motto: Somebody has to study this shit!

And I mean this literally: the title of the paper is "An Agent-Based Model for Bovine Viral Diarrhea".

Update: Normally, I hate it when papers are full of bullshit. However, I may need to make an exception in this case.