Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Shahzamal,; Jurdak, Raja; Mans, Bernard; Shoghri, Ahmad El; Hoog, Frank de

doi:10.1007/978-3-030-04503-6_5

Cited by 6 publications

(10 citation statements)

References 17 publications

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“…While disease transmission is possible through direct encounters (i.e. the infected and the susceptible individual are present in the same place at the same time), pathogens can remain in the environment for an extended period of time [1] [7]. Therefore, an infectious person can infect susceptible individuals without a direct encounter.…”

Section: Related Workmentioning

confidence: 99%

“…Human mobility continues to play a vital role in spreading infectious diseases within a population [1] [2]. Ongoing population growth and the high reliance of individuals on public transport services in highly populated cities provide a suitable platform for contagious diseases, such as measles, the recently emerged coronavirus and influenza, to spread widely and rapidly [3][4] [5].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, some pathogens may remain in the environment (e.g. a bus) for a prolonged period and can infect susceptible individuals after the infectious person has left the area [1] [7]. Furthermore, transport services shorten distances and times and strongly connect different suburbs, potentially exposing communities to a high infection risk [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identifying Highly Influential Travellers for Spreading Disease on a Public Transport System

Shoghri

Liebig

Jurdak

et al. 2020

2020 IEEE 21st International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

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The recent outbreak of a novel coronavirus and its rapid spread underlines the importance of understanding human mobility. Enclosed spaces, such as public transport vehicles (e.g. buses and trains), offer a suitable environment for infections to spread widely and quickly. Investigating the movement patterns and the physical encounters of individuals on public transit systems is thus critical to understand the drivers of infectious disease outbreaks. For instance, previous work has explored the impact of recurring patterns inherent in human mobility on disease spread, but has not considered other dimensions such as the distance travelled or the number of encounters. Here, we consider multiple mobility dimensions simultaneously to uncover critical information for the design of effective intervention strategies. We use one month of citywide smart card travel data collected in Sydney, Australia to classify bus passengers along three dimensions, namely the degree of exploration, the distance travelled and the number of encounters. Additionally, we simulate disease spread on the transport network and trace the infection paths. We investigate in detail the transmissions between the classified groups while varying the infection probability and the suspension time of pathogens. Our results show that characterizing individuals along multiple dimensions simultaneously uncovers a complex infection interplay between the different groups of passengers, that would remain hidden when considering only a single dimension. We also identify groups that are more influential than others given specific disease characteristics, which can guide containment and vaccination efforts.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identifying Highly Influential Travellers for Spreading Disease on a Public Transport System

Shoghri

Liebig

Jurdak

et al. 2020

2020 IEEE 21st International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

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“…Another limitation of current contact-based vaccination strategies is that they only focus on direct contacts between individuals. Our recent work [17][18][19][20] introduced the concept of indirect transmission, where disease can transmit through indirect interaction (in addition to direct interactions), which is representative of many infectious diseases. For example, a acknowledge the Distributed Sensing System Group, Data61, CSIRO for providing research facilities for this research.…”

Section: Introductionmentioning

confidence: 99%

Vaccination strategies on dynamic networks with indirect transmission links and limited contact information

et al. 2020

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Infectious diseases are still a major global burden for modern society causing 13 million deaths annually. One way to reduce the morbidity and mortality rates from infectious diseases is through pre-emptive or targeted vaccinations. Current theoretical vaccination strategies based on contact networks, however, rely on highly specific individual contact information which is difficult and costly to obtain, in order to identify influential spreading individuals. Current approaches also focus only on direct contacts between individuals for spreading, and disregard indirect transmission where a pathogen can spread between one infected individual and one susceptible individual who visit the same location within a short time-frame without meeting. This paper presents a novel vaccination strategy which relies on coarse-grained contact information, both direct and indirect, that can be easily and efficiently collected. Rather than tracking exact contact degrees of individuals, our strategy uses the types of places people visit to estimate a range of contact degrees for individuals, considering both direct and indirect contacts. We conduct extensive computer simulations to evaluate the performance of our strategy in comparison to state-of-the-art vaccination strategies. Results show that, when considering indirect links, our lower cost vaccination strategy achieves comparable performance to the contact-degree based approach and outperforms other existing strategies without requiring over-detailed information.

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“…The SPDT model captures transmission events occurring simultaneously at multiple locations by an infected individual (transmission at the current location due to the direct interaction, and transmissions at the previous locations due to indirect interactions). In this diffusion model, the link infectivity, which is the probability of causing infection by a SPDT link which is created for direct and/or indirect interactions, depends on various factors such as the presence of infected and susceptible individuals at the interaction location, decay rates of infectious items and environmental conditions etc [5,12,17,18]. The current SPST models cannot account for these features as the inclusion of indirect interactions can significantly affect a diffusion process.…”

Section: Introductionmentioning

confidence: 99%

Indirect interactions influence contact network structure and diffusion dynamics

et al. 2019

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Interaction patterns at the individual level influence the behaviour of diffusion over contact networks. Most of the current diffusion models only consider direct interactions, capable of transferring infectious items among individuals, to build transmission networks of diffusion. However, delayed indirect interactions, where a susceptible individual interacts with infectious items after the infected individual has left the interaction space, can also cause transmission events. We define a diffusion model called the same place different time transmission (SPDT)-based diffusion that considers transmission links for these indirect interactions. Our SPDT model changes the network dynamics where the connectivity among individuals varies with the decay rates of link infectivity. We investigate SPDT diffusion behaviours by simulating airborne disease spreading on data-driven contact networks. The SPDT model significantly increases diffusion dynamics with a high rate of disease transmission. By making the underlying connectivity denser and stronger due to the inclusion of indirect transmissions, SPDT models are more realistic than same place same time transmission (SPST)-based models for the study of various airborne disease outbreaks. Importantly, we also find that the diffusion dynamics including indirect links are not reproducible by the current SPST models based on direct links, even if both SPDT and SPST networks assume the same underlying connectivity. This is because the transmission dynamics of indirect links are different from those of direct links. These outcomes highlight the importance of the indirect links for predicting outbreaks of airborne diseases.

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Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Cited by 6 publications

References 17 publications

Identifying Highly Influential Travellers for Spreading Disease on a Public Transport System

Identifying Highly Influential Travellers for Spreading Disease on a Public Transport System

Vaccination strategies on dynamic networks with indirect transmission links and limited contact information

Indirect interactions influence contact network structure and diffusion dynamics

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