scholarly journals Individual space–time activity-based modelling of infectious disease transmission within a city

2007 ◽  
Vol 5 (24) ◽  
pp. 759-772 ◽  
Author(s):  
Yong Yang ◽  
Peter Atkinson ◽  
Dick Ettema

This paper provides an example of the application of an individual space–time activity-based model (ISTAM) to the simulation of the transmission of infectious disease in Eemnes, a city in The Netherlands. Four questions were addressed: (i) how to build the whole population at the city level, (ii) how to build the structure of the activity bundles for the city, (iii) how to assign daily activity patterns to each individual, and (iv) how to simulate within-AB transmission. The model was calibrated and examples of simulation results such as dynamics of the population during a whole day, infection distribution and network analysis are presented.

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

Author(s):  
Gregory Gutin ◽  
Tomohiro Hirano ◽  
Sung-Ha Hwang ◽  
Philip R. Neary ◽  
Alexis Akira Toda

AbstractHow does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a susceptible–infected–removed with social distancing model. The key feature of the model is that individuals are limited in the number of acquaintances that they can interact with, thereby constraining disease transmission to an infectious subnetwork of the original social network. While increased social distancing typically reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the network, indicating the need for policies that are network dependent. Our results also reveal the importance of coordinating policies at the ‘global’ level. In particular, the public health benefits from social distancing to a group (e.g. a country) may be completely undone if that group maintains connections with outside groups that are not following suit.


2008 ◽  
Vol 6 (6) ◽  
pp. 477-487 ◽  
Author(s):  
Nicholas C. Grassly ◽  
Christophe Fraser

2012 ◽  
Vol 54 (1-2) ◽  
pp. 23-36 ◽  
Author(s):  
E. K. WATERS ◽  
H. S. SIDHU ◽  
G. N. MERCER

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.


2019 ◽  
Vol 34 (4) ◽  
Author(s):  
Amy Moran-Thomas

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.


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