scholarly journals Toward epidemic thresholds on temporal networks: a review and open questions

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Jack Leitch ◽  
Kathleen A. Alexander ◽  
Srijan Sengupta

AbstractEpidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Sergei P. Sidorov ◽  
Sergei V. Mironov ◽  
Alexey A. Grigoriev

AbstractMany empirical studies have shown that in social, citation, collaboration, and other types of networks in real world, the degree of almost every node is less than the average degree of its neighbors. This imbalance is well known in sociology as the friendship paradox and states that your friends are more popular than you on average. If we introduce a value equal to the ratio of the average degree of the neighbors for a certain node to the degree of this node (which is called the ‘friendship index’, FI), then the FI value of more than 1 for most nodes indicates the presence of the friendship paradox in the network. In this paper, we study the behavior of the FI over time for networks generated by growth network models. We will focus our analysis on two models based on the use of the preferential attachment mechanism: the Barabási–Albert model and the triadic closure model. Using the mean-field approach, we obtain differential equations describing the dynamics of changes in the FI over time, and accordingly, after obtaining their solutions, we find the expected values of this index over iterations. The results show that the values of FI are decreasing over time for all nodes in both models. However, for networks constructed in accordance with the triadic closure model, this decrease occurs at a much slower rate than for the Barabási–Albert graphs. In addition, we analyze several real-world networks and show that their FI distributions follow a power law. We show that both the Barabási–Albert and the triadic closure networks exhibit the same behavior. However, for networks based on the triadic closure model, the distributions of FI are more heavy-tailed and, in this sense, are closer to the distributions for real networks.


2020 ◽  
Vol 7 (5) ◽  
pp. 929-937 ◽  
Author(s):  
Disheng Tang ◽  
Wenbo Du ◽  
Louis Shekhtman ◽  
Yijie Wang ◽  
Shlomo Havlin ◽  
...  

Abstract Links in most real networks often change over time. Such temporality of links encodes the ordering and causality of interactions between nodes and has a profound effect on network dynamics and function. Empirical evidence has shown that the temporal nature of links in many real-world networks is not random. Nonetheless, it is challenging to predict temporal link patterns while considering the entanglement between topological and temporal link patterns. Here, we propose an entropy-rate-based framework, based on combined topological–temporal regularities, for quantifying the predictability of any temporal network. We apply our framework on various model networks, demonstrating that it indeed captures the intrinsic topological–temporal regularities whereas previous methods considered only temporal aspects. We also apply our framework on 18 real networks of different types and determine their predictability. Interestingly, we find that, for most real temporal networks, despite the greater complexity of predictability brought by the increase in dimension, the combined topological–temporal predictability is higher than the temporal predictability. Our results demonstrate the necessity for incorporating both temporal and topological aspects of networks in order to improve predictions of dynamical processes.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Yao ◽  
Bingsheng Chen ◽  
Tim S. Evans ◽  
Kim Christensen

AbstractWe study the evolution of networks through ‘triplets’—three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.


2021 ◽  
Vol 10 (9) ◽  
pp. 1890
Author(s):  
Gabriele Pesarini ◽  
Gabriele Venturi ◽  
Domenico Tavella ◽  
Leonardo Gottin ◽  
Mattia Lunardi ◽  
...  

Background: The aim of this research is to describe the performance over time of transcatheter aortic valve implantations (TAVIs) in a high-volume center with a contemporary, real-world population. Methods: Patients referred for TAVIs at the University Hospital of Verona were prospectively enrolled. By cumulative sum failures analysis (CUSUM), procedural-control curves for standardized combined endpoints—as defined by the Valve Academic Research Consortium-2 (VARC-2)—were calculated and analyzed over time. Acceptable and unacceptable limits were derived from recent studies on TAVI in intermediate and low-risk patients to fit the higher required standards for current indications. Results: A total of 910 patients were included. Baseline risk scores significantly reduced over time. Complete procedural control was obtained after approximately 125 and 190 cases for device success and early safety standardized combined endpoints, respectively. High risk patients (STS ≥ 8) had poorer outcomes, especially in terms of VARC-2 clinical efficacy, and required a higher case load to maintain in-control and proficient procedures. Clinically relevant single endpoints were all influenced by operator’s experience as well. Conclusions: Quality-control analysis for contemporary TAVI interventions based on standardized endpoints suggests the need for relevant operator’s experience to achieve and maintain optimal clinical results, especially in higher-risk subjects.


2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S191-S192
Author(s):  
Nupur Gupta ◽  
Adit B Sanghvi ◽  
John Mellors ◽  
Rima Abdel-Massih

Abstract Background Telemedicine (TM) has emerged as a viable solution to extend infectious disease (ID) expertise to communities without access to this specialty.1 TM allows clinicians in rural settings to connect with specialists at distant sites and provide the best care for their patients, often eliminating the need for hospital transfers. Here, we describe the experience from one of the longest standing inpatient Tele-ID consult services using live audio-video (AV) visits with the assistance of a telepresenter. Methods Longitudinal data were collected from a 126-bed rural hospital in Pennsylvania that had no access to ID consultation before 2014. Live AV consults during business hours began in 2014 and telephonic physician to physician consults were made available 24/7. All ID consult data were extracted from the hospital electronic health record between 2014 to 2019. Key outcomes assessed included the number of consult encounters, total hospital length of stay (LOS), discharges to home, transfer to tertiary care centers, and readmission rates at 30 days. Results Most consulted patients were Caucasians, and females with an average age of 64.7 years (Table 1). The number of unique consult encounters increased annually from 111 in 2014 to 469 in 2019 (Table 1). The Charlson Comorbidity Score and Elixhauser Comorbidity Index also increased each year beginning in 2016 (Table 1). By contrast, LOS decreased each year as did the 30-day readmission rate (Table 2). Most patients were not transferred (average 89.4% over 6 years) to tertiary care centers and more than half were discharged to home each year (Table 2). Conclusion This longitudinal 6-year observation study of an inpatient TM ID service at a rural hospital showed remarkable annual growth in consult encounters (total growth >400%). Despite increasing patient acuity, overall hospital LOS decreased over time (10.2 to 8.2 days). Patient transfers to tertiary care centers remained low (average 10.5% over 6 years) as did 30-day readmissions (average 16.3% over 6 years). The majority of patients were discharged to home (average 61.3% over 6 years). These findings show that a rural inpatient TM ID consult service can expand over time and is an effective alternative for hospitals without access to ID expertise. Disclosures John Mellors, MD, Abound Bio (Shareholder)Accelevir Diagnostics (Consultant)Co-Crystal Pharmaceuticals (Shareholder)Gilead (Consultant, Grant/Research Support)Merck (Consultant) Rima Abdel-Massih, MD, Infectious Disease Connect (Shareholder, Other Financial or Material Support, Chief Medical Officer)


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 547.1-547
Author(s):  
C. Deakin ◽  
G. Littlejohn ◽  
H. Griffiths ◽  
T. Smith ◽  
C. Osullivan ◽  
...  

Background:The availability of biosimilars as non-proprietary versions of established biologic disease-modifying anti-rheumatic drugs (bDMARDs) is enabling greater access for patients with rheumatic diseases to effective medications at a lower cost. Since April 2017 both the originator and a biosimilar for etanercept (trade names Enbrel and Brenzys, respectively) have been available for use in Australia.Objectives:[1]To model effectiveness of etanercept originator or biosimilar in reducing Disease Activity Score 28-joint count C reactive protein (DAS28CRP) in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) or ankylosing spondylitis (AS) treated with either drug as first-line bDMARD[2]To describe persistence on etanercept originator or biosimilar as first-line bDMARD in patients with RA, PsA or ASMethods:Clinical data were obtained from the Optimising Patient outcomes in Australian rheumatoLogy (OPAL) dataset, derived from electronic medical records. Eligible patients with RA, PsA or AS who initiated etanercept originator (n=856) or biosimilar (n=477) as first-line bDMARD between 1 April 2017 and 31 December 2020 were identified. Propensity score matching was performed to select patients on originator (n=230) or biosimilar (n=136) with similar characteristics in terms of diagnosis, disease duration, joint count, age, sex and concomitant medications. Data on clinical outcomes were recorded at 3 months after baseline, and then at 6-monthly intervals. Outcomes data that were missing at a recorded visit were imputed.Effectiveness of the originator, relative to the biosimilar, for reducing DAS28CRP over time was modelled in the matched population using linear mixed models with both random intercepts and slopes to allow for individual heterogeneity, and weighting of individuals by inverse probability of treatment weights to ensure comparability between treatment groups. Time was modelled as a combination of linear, quadratic and cubic continuous variables.Persistence on the originator or biosimilar was analysed using survival analysis (log-rank test).Results:Reduction in DAS28CRP was associated with both time and etanercept originator treatment (Table 1). The conditional R-squared for the model was 0.31. The average predicted DAS28CRP at baseline, 3 months, 6 months, 9 months and 12 months were 4.0 and 4.4, 3.1 and 3.4, 2.6 and 2.8, 2.3 and 2.6, and 2.2 and 2.4 for the originator and biosimilar, respectively, indicating a clinically meaningful effect of time for patients on either drug and an additional modest improvement for patients on the originator.Median time to 50% of patients stopping treatment was 25.5 months for the originator and 24.1 months for the biosimilar (p=0.53). An adverse event was the reason for discontinuing treatment in 33 patients (14.5%) on the originator and 18 patients (12.9%) on the biosimilar.Conclusion:Analysis using a large national real-world dataset showed treatment with either the etanercept originator or the biosimilar was associated with a reduction in DAS28CRP over time, with the originator being associated with a further modest reduction in DAS28CRP that was not clinically significant. Persistence on treatment was not different between the two drugs.Table 1.Respondent characteristics.Fixed EffectEstimate95% Confidence Intervalp-valueTime (linear)0.900.89, 0.911.5e-63Time (quadratic)1.011.00, 1.011.3e-33Time (cubic)1.001.00, 1.007.1e-23Originator0.910.86, 0.960.0013Acknowledgements:The authors acknowledge the members of OPAL Rheumatology Ltd and their patients for providing clinical data for this study, and Software4Specialists Pty Ltd for providing the Audit4 platform.Supported in part by a research grant from Investigator-Initiated Studies Program of Merck & Co Inc, Kenilworth, NJ, USA. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck & Co Inc, Kenilworth, NJ, USA.Disclosure of Interests:Claire Deakin: None declared, Geoff Littlejohn Consultant of: Over the last 5 years Geoffrey Littlejohn has received educational grants and consulting fees from AbbVie, Bristol Myers Squibb, Eli Lilly, Gilead, Novartis, Pfizer, Janssen, Sandoz, Sanofi and Seqirus., Hedley Griffiths Consultant of: AbbVie, Gilead, Novartis and Lilly., Tegan Smith: None declared, Catherine OSullivan: None declared, Paul Bird Speakers bureau: Eli Lilly, abbvie, pfizer, BMS, UCB, Gilead, Novartis


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Naomi A. Arnold ◽  
Raul J. Mondragón ◽  
Richard G. Clegg

AbstractDiscriminating between competing explanatory models as to which is more likely responsible for the growth of a network is a problem of fundamental importance for network science. The rules governing this growth are attributed to mechanisms such as preferential attachment and triangle closure, with a wealth of explanatory models based on these. These models are deliberately simple, commonly with the network growing according to a constant mechanism for its lifetime, to allow for analytical results. We use a likelihood-based framework on artificial data where the network model changes at a known point in time and demonstrate that we can recover the change point from analysis of the network. We then use real datasets and demonstrate how our framework can show the changing importance of network growth mechanisms over time.


2016 ◽  
Vol 3 (7) ◽  
pp. 160131 ◽  
Author(s):  
Daniel Smith ◽  
Mark Dyble ◽  
James Thompson ◽  
Katie Major ◽  
Abigail E. Page ◽  
...  

Humans regularly cooperate with non-kin, which has been theorized to require reciprocity between repeatedly interacting and trusting individuals. However, the role of repeated interactions has not previously been demonstrated in explaining real-world patterns of hunter–gatherer cooperation. Here we explore cooperation among the Agta, a population of Filipino hunter–gatherers, using data from both actual resource transfers and two experimental games across multiple camps. Patterns of cooperation vary greatly between camps and depend on socio-ecological context. Stable camps (with fewer changes in membership over time) were associated with greater reciprocal sharing, indicating that an increased likelihood of future interactions facilitates reciprocity. This is the first study reporting an association between reciprocal cooperation and hunter–gatherer band stability. Under conditions of low camp stability individuals still acquire resources from others, but do so via demand sharing (taking from others), rather than based on reciprocal considerations. Hunter–gatherer cooperation may either be characterized as reciprocity or demand sharing depending on socio-ecological conditions.


2016 ◽  
Vol 2016 (1) ◽  
pp. 4-19 ◽  
Author(s):  
Andreas Kurtz ◽  
Hugo Gascon ◽  
Tobias Becker ◽  
Konrad Rieck ◽  
Felix Freiling

Abstract Recently, Apple removed access to various device hardware identifiers that were frequently misused by iOS third-party apps to track users. We are, therefore, now studying the extent to which users of smartphones can still be uniquely identified simply through their personalized device configurations. Using Apple’s iOS as an example, we show how a device fingerprint can be computed using 29 different configuration features. These features can be queried from arbitrary thirdparty apps via the official SDK. Experimental evaluations based on almost 13,000 fingerprints from approximately 8,000 different real-world devices show that (1) all fingerprints are unique and distinguishable; and (2) utilizing a supervised learning approach allows returning users or their devices to be recognized with a total accuracy of 97% over time


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