Branching process models to identify risk factors for infectious disease transmission

2021 ◽  
pp. 1-29
Author(s):  
Shannon K. Gallagher ◽  
Dean Follmann
Keyword(s):  
Infectious Disease ◽  
Risk Factors ◽  
Disease Transmission ◽  
Branching Process ◽  
Process Models ◽  
Infectious Disease Transmission

Travel Connectivity and Infectious Disease Transmission Risks in Oceania

2020 ◽  
Author(s):  
Angela Maria Cadavid Restrepo ◽  
Luis Furuya-Kanamori ◽  
Helen Mayfield ◽  
Eric J. Nilles ◽  
Colleen L. Lau
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Infectious Disease Transmission

scholarly journals Mathematical models of infectious disease transmission

2008 ◽  
Vol 6 (6) ◽  
pp. 477-487 ◽  
Author(s):  
Nicholas C. Grassly ◽  
Christophe Fraser
Keyword(s):  
Infectious Disease ◽  
Mathematical Models ◽  
Disease Transmission ◽  
Infectious Disease Transmission

scholarly journals SPATIAL HETEROGENEITY IN SIMPLE DETERMINISTIC SIR MODELS ASSESSED ECOLOGICALLY

2012 ◽  
Vol 54 (1-2) ◽  
pp. 23-36 ◽  
Author(s):  
E. K. WATERS ◽  
H. S. SIDHU ◽  
G. N. MERCER
Keyword(s):  
Infectious Disease ◽  
Spatial Heterogeneity ◽  
Disease Transmission ◽  
Herd Immunity ◽  
Epidemic Models ◽  
Final Size ◽  
Infectious Disease Transmission ◽  
Epidemic Dynamics ◽  
Mean Crowding ◽  
Rate Of Movement

AbstractPatchy or divided populations can be important to infectious disease transmission. We first show that Lloyd’s mean crowding index, an index of patchiness from ecology, appears as a term in simple deterministic epidemic models of the SIR type. Using these models, we demonstrate that the rate of movement between patches is crucial for epidemic dynamics. In particular, there is a relationship between epidemic final size and epidemic duration in patchy habitats: controlling inter-patch movement will reduce epidemic duration, but also final size. This suggests that a strategy of quarantining infected areas during the initial phases of a virulent epidemic might reduce epidemic duration, but leave the population vulnerable to future epidemics by inhibiting the development of herd immunity.

scholarly journals What is Communicable? Unaccounted Injuries and “Catching” Diabetes in an Illegible Epidemic

2019 ◽  
Vol 34 (4) ◽  
Author(s):  
Amy Moran-Thomas
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Disease Transmission ◽  
Communicable Disease ◽  
Treatment Access ◽  
Infectious Disease Transmission ◽  
The World ◽  
Historically Situated ◽  
Over Time ◽  
Non Communicable Disease

Long-accepted models of causality cast diseases into the binary of either “contagious” or “non-communicable,” typically with institutional resources focused primarily on interrupting infectious disease transmission. But in southern Belize, as in much of the world today, epidemic diabetes has become a leading cause of death and a notorious contributor to organ failure and amputated limbs. This ethnographic essay follows caregivers’ and families’ work to survive in-between public health categories, and asks what responses a bifurcated model of infectious versus non-communicable disease structures or incapacitates in practice. It proposes an alternative focus on diabetes as a “para-communicable” condition—materially transmitted as bodies and ecologies intimately shape each other over time, with unequal and compounding effects for historically situated groups of people. The article closes by querying how communicability relates to community, and why it matters to reframe narratives about contributing causalities in relation to struggles for treatment access.

scholarly journals A mathematical model of infectious disease transmission

2020 ◽  
Vol 34 ◽  
pp. 02002
Author(s):  
Aurelia Florea ◽  
Cristian Lăzureanu
Keyword(s):  
Infectious Disease ◽  
Mathematical Model ◽  
Nonlinear System ◽  
Numerical Simulations ◽  
Disease Transmission ◽  
Three Dimensional ◽  
Type System ◽  
Epidemic Disease ◽  
Infectious Disease Transmission ◽  
The Stability

In this paper we consider a three-dimensional nonlinear system which models the dynamics of a population during an epidemic disease. The considered model is a SIS-type system in which a recovered individual automatically becomes a susceptible one. We take into account the births and deaths, and we also consider that susceptible individuals are divided into two groups: non-vaccinated and vaccinated. In addition, we assume a medical scenario in which vaccinated people take a special measure to quarantine their newborns. We study the stability of the considered system. Numerical simulations point out the behavior of the considered population.

Schools as Vectors of Infectious Disease Transmission during the 1918 Influenza Pandemic

2021 ◽  
pp. e20200025
Author(s):  
Don Lafreniere ◽  
Timothy Stone ◽  
Rose Hildebrandt ◽  
Richard C. Sadler ◽  
Michael Madison ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Influenza Pandemic ◽  
Infectious Disease Transmission ◽  
1918 Influenza
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