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Inferring Social Networks from Outbreaks [chapter]

Dana Angluin, James Aspnes, Lev Reyzin
2010 Lecture Notes in Computer Science  
We consider the problem of inferring the most likely social network given connectivity constraints imposed by observations of outbreaks within the network.  ...  Given such constraints, the problem would then be to find a maximum likelihood social network from the disease data.  ...  Here, we consider inferring the structure of social networks by observing phenomena that give us information about their connectivity.  ... 
doi:10.1007/978-3-642-16108-7_12 fatcat:4x2swpz7jnft5h63j5govwyray

Integrating molecular epidemiology and social network analysis to study infectious diseases: Towards a socio-molecular era for public health

Tetyana I. Vasylyeva, Samuel R. Friedman, Dimitrios Paraskevis, Gkikas Magiorkinis
2016 Infection, Genetics and Evolution  
Thus, social network data include more detailed picture of a network and can improve inferences made from molecular data.  ...  The main differences between the two data sources are that, firstly, social network data include uninfected individuals unlike the molecular data sampled only from infected network members.  ...  be inferred from this phylogenetic tree.  ... 
doi:10.1016/j.meegid.2016.05.042 pmid:27262354 pmcid:PMC5135626 fatcat:qv5y4pw2ind6robgm2v7jdos4m

Network inference from multimodal data: A review of approaches from infectious disease transmission

Bisakha Ray, Elodie Ghedin, Rumi Chunara
2016 Journal of Biomedical Informatics  
Multi-domain data can now be used to improve the robustness and reliability of recovered networks from unimodal data.  ...  Novel pieces of linked information in the form of spatial, temporal, and other covariates including high-throughput sequence data, clinical visits, social network information, pharmaceutical prescriptions  ...  from genomics to social network analysis [43] .  ... 
doi:10.1016/j.jbi.2016.09.004 pmid:27612975 pmcid:PMC7106161 fatcat:tpsn75h7lnf3td6xplygemx3ca

SOPHIE: viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework [article]

Pavel Skums, Fatemeh Mohebbi, Vyacheslav Tsyvina, Pelin Icer Baykal, Alina Nemira, Sumathi Ramachandran, Yury Khudyakov
2022 bioRxiv   pre-print
It infers transmission networks from viral phylogenies and expected properties of inter-host social networks modelled as random graphs with given expected degree distributions.  ...  SOPHIE is scalable, accounts for intra-host diversity and accurately infers transmissions without case-specific epidemiological data.  ...  The output from SOPHIE was used to estimate key epidemiological parameters directly from the inferred transmission networks.  ... 
doi:10.1101/2022.05.05.490757 fatcat:vl7t3e6yz5cntkhylioqq7vgma

Epidemic models on social networks—With inference

Tom Britton
2020 Statistica neerlandica (Print)  
K E Y W O R D S control measures, epidemic models, incidence data, random networks, sequence data, statistical inference This is an open access article under the terms of the Creative Commons Attribution  ...  Some common network models and transmission models are defined and large population properties of them are presented.  ...  , but also to improve inference procedures for data from network epidemics.  ... 
doi:10.1111/stan.12203 fatcat:cwhcsaaq4ral3df4kw52kg7p7a

Epidemiological and Viral Genomic Sequence Analysis of the 2014 Ebola Outbreak Reveals Clustered Transmission

Samuel V. Scarpino, Atila Iamarino, Chad Wells, Dan Yamin, Martial Ndeffo-Mbah, Natasha S. Wenzel, Spencer J. Fox, Tolbert Nyenswah, Frederick L. Altice, Alison P. Galvani, Lauren Ancel Meyers, Jeffrey P. Townsend
2014 Clinical Infectious Diseases  
Using Ebolavirus genomic and epidemiological data, we conducted the first joint analysis in which both data types were used to fit dynamic transmission models for an ongoing outbreak.  ...  For example, we estimated a clustering coefficient of ϕ = 0.21 (95% CI, .196-.223) from empirical contact tracing data obtained from the Liberian Ministry of Health and Social Welfare.  ...  The agreement of our empirical, network, and genomic analyses supports a conclusion of significant social clustering, a conclusion that is robust to likely underreporting.  ... 
doi:10.1093/cid/ciu1131 pmid:25516185 pmcid:PMC4375398 fatcat:vpobrdqeerhopohfbgmx2gadoy

Causal Inference in Disease Spread across a Heterogeneous Social System [article]

Minkyoung Kim, Dean Paini, Raja Jurdak
2018 arXiv   pre-print
From our causal inference, outbreaks are more likely driven by statewide global diffusion over time, leading to complex behavior of disease spread.  ...  We infer causal relationships between infections and quantify the reflexivity of a meta-population, the level of feedback on event occurrences by its internal dynamics (likelihood of a regional outbreak  ...  We would like to express our gratitude to Cassie Jansen and Fiona May at Queensland Health for providing dengue outbreak data and for valuable discussions and to Tourism Research Australia for providing  ... 
arXiv:1801.08133v1 fatcat:rsdemo5tcbcpzanb27htflgxry

Inferring Social Network Structure from Bacterial Sequence Data

Mateusz M. Pluciński, Richard Starfield, Rodrigo P. P. Almeida, Petter Holme
2011 PLoS ONE  
Using DNA sequence data from pathogens to infer transmission networks has traditionally been done in the context of epidemics and outbreaks.  ...  circulating in an endemic equilibrium could be used to infer information about host contact networks.  ...  If global network properties can be inferred from MLST data then it is also plausible that some of the local network structure can also be gleaned from the same data.  ... 
doi:10.1371/journal.pone.0022685 pmid:21829645 pmcid:PMC3148245 fatcat:zcznsqc7m5f23jckowdfvh4bvm

Infectious disease transmission and contact networks in wildlife and livestock

M. E. Craft
2015 Philosophical Transactions of the Royal Society of London. Biological Sciences  
Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade  ...  This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or  ...  structure from outbreak data.  ... 
doi:10.1098/rstb.2014.0107 pmid:25870393 pmcid:PMC4410373 fatcat:djvzgotkv5h7zao7rn4reihumi

CovidSens: A Vision on Reliable Social Sensing for COVID-19 [article]

Md Tahmid Rashid, Dong Wang
2020 arXiv   pre-print
In this paper, we propose CovidSens, a vision of social sensing based risk alert systems to spontaneously obtain and analyze social data to infer COVID-19 propagation.  ...  Due to the ubiquity of Internet connectivity and smart devices, social sensing is emerging as a dynamic AI-driven sensing paradigm to extract real-time observations from online users.  ...  An ensemble of solutions employing natural language processing (NLP) [114] , deep neural networks (DNNs), and social network analysis can be built to accurately infer the location information from the  ... 
arXiv:2004.04565v3 fatcat:wo7mgcydzjbnvif7mdehqmhspm

Effectiveness of network interdiction strategies to limit contagion during a pandemic

Satyaki Roy, Preetom Biswas, Preetam Ghosh
2021 IEEE Access  
Despite initial success in curbing the spread of diseases through a lockdown and rapid vaccine development, human lives are threatened by sudden outbreaks from new strains of the virus.  ...  In this work, we present three interdiction rules that employ machine learning-based network inference on daily infected cases to infer the influence of contagion between neighboring zones.  ...  at any given time t with social network G t .  ... 
doi:10.1109/access.2021.3095252 fatcat:tyldzb6ybrhuzpw6l5mw5zenna

Detailed Transmission Network Analysis of a Large Opiate-Driven Outbreak of HIV Infection in the United States

Ellsworth M Campbell, Hongwei Jia, Anupama Shankar, Debra Hanson, Wei Luo, Silvina Masciotra, S Michele Owen, Alexandra M Oster, Romeo R Galang, Michael W Spiller, Sara J Blosser, Erika Chapman (+11 others)
2017 Journal of Infectious Diseases  
Sample collection dates and recency assay results were used to infer dates of infection. Epidemiologic and laboratory data each generated large and dense networks.  ...  In January 2015, an outbreak of undiagnosed human immunodeficiency virus (HIV) infections among persons who inject drugs (PWID) was recognized in rural Indiana.  ...  Inferred Transmission Network The inferred transmission network, constructed from both the contact tracing and MST networks, consisted of 176 nodes connected by 303 potential transmission events, 52.3%  ... 
doi:10.1093/infdis/jix307 pmid:29029156 fatcat:324iwc4dvbgmjjcgyow3pzcmpq

CovidSens: a vision on reliable social sensing for COVID-19

Md Tahmid Rashid, Dong Wang
2020 Artificial Intelligence Review  
In this paper, we propose CovidSens, a vision of social sensing-based risk alert systems to spontaneously obtain and analyze social data to infer the state of the COVID-19 propagation.  ...  Due to the ubiquity of Internet connectivity and smart devices, social sensing is emerging as a dynamic AI-driven sensing paradigm to extract real-time observations from online users.  ...  Compared to traditional social sensing applications, CovidSens not only requires an inference of the data veracity but also how the COVID-19 outbreak can progress across regions based on indications from  ... 
doi:10.1007/s10462-020-09852-3 pmid:32836651 pmcid:PMC7291936 fatcat:b4fycdhby5gw5honu7li6w4dcy

Situation awareness in crowdsensing for disease surveillance in crisis situations

Peter Haddawy, Lutz Frommberger, Tomi Kauppinen, Giorgio De Felice, Prae Charkratpahu, Sirawaratt Saengpao, Phanumas Kanchanakitsakul
2015 Proceedings of the Seventh International Conference on Information and Communication Technologies and Development - ICTD '15  
mobile4D smartphone-based disaster reporting and alerting system with a situation awareness data interpretation and integration layer and demonstrate its application to the problem of tracking cholera outbreaks  ...  Using the output from algorithms for temporal data anomaly detection, their Bayes nets infer the probability of occurrence of disease outbreaks.  ...  Links in this network and in the outbreak projection network are quantified with conditional probabilities. Probabilities were obtained from published statistical studies, e.g [6, 8] .  ... 
doi:10.1145/2737856.2737879 dblp:conf/ictd/HaddawyFKFCSK15 fatcat:rfffnx475nevhcjlqhhzwgzata

A Social Network Platform Architecture Based on Markov Logic and Transformer Based Neuron Translation

Bokai Xu, Zhuoyu Li
2022 Zenodo  
In this work we seek to realize a new kind of social network platform which could automatically make large scale and concrete inference of underlying truth of social issues on social network platform.  ...  To accomplish this, we introduced the Jianfeng Social Network: a new kind of social network platform architecture based on Markov Logic and Transformer based neuron translation.  ...  The outbreak of New Coronavirus Pandemic in late 2019 and early 2020 attracted some attention on social networks when the outbreak was in its nascent stage, but due to algorithmic flaws in today's social  ... 
doi:10.5281/zenodo.5879115 fatcat:kpt7juho5raillj6nsjeuwgyji
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