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Estimating individuals' genetic and non-genetic effects underlying infectious disease transmission from temporal epidemic data

Christopher M. Pooley, Glenn Marion, Stephen C. Bishop, Richard I. Bailey, Andrea B. Doeschl-Wilson, James Lloyd-Smith
2020 PLoS Computational Biology  
SIRE represents a new tool for analysing a wide range of experimental and field disease data with the aim of discovering and validating SNPs and other factors controlling infectious disease transmission  ...  Different genetic and non-genetic regulations and data scenarios (representing realistic recording schemes) were simulated to validate SIRE and to assess their impact on the precision, accuracy and bias  ...  disease transmission, from temporal epidemic data.  ... 
doi:10.1371/journal.pcbi.1008447 pmid:33347459 fatcat:j7vkgy2tnjf2jnuasa7qw3wxuu

Genomic analysis of emerging pathogens: methods, application and future trends

Lucy M Li, Nicholas C Grassly, Christophe Fraser
2014 Genome Biology  
In this review, we evaluate methods that exploit pathogen sequences and the contribution of genomic analysis to understand the epidemiology of recently emerged infectious diseases.  ...  The number of emerging infectious diseases is increasing. Characterizing novel or re-emerging infections is aided by the availability of pathogen genomes.  ...  Role of genetics in studying infectious diseases Over the last two decades, sequence data have increased in quality, length and volume due to improvements in the underlying technology and decreasing costs  ... 
doi:10.1186/s13059-014-0541-9 pmid:25418281 pmcid:PMC4283782 fatcat:hr6bmd7wsnfshffok5l7eb523y

Estimating genetic and non-genetic effects for host susceptibility, infectivity and recoverability using temporal epidemic data [article]

Christopher M Pooley, Stephen C Bishop, Andrea B Doeschl-Wilson, Glenn Marion
2019 biorxiv/medrxiv   pre-print
SIRE represents a new tool for analysing a wide range of experimental and field disease data with the aim of discovering and validating SNPs and other factors controlling infectious disease transmission  ...  SIRE implements a Bayesian algorithm which makes use of temporal data (consisting of any combination of recorded individual infection times, recovery times or disease status measurements) from multiple  ...  disease transmission, from temporal epidemic data.  ... 
doi:10.1101/618363 fatcat:e33u3p5fxjbsfoxl6znx2jj2f4

Molecular epidemiology of infectious diseases

Sana Eybpoosh, Ali Akbar Haghdoost, Ehsan Mostafavi, Abbas Bahrampour, Kayhan Azadmanesh, Farzaneh Zolala
2017 Electronic Physician  
In this paper, the authors try to discuss the ways that molecular epidemiology studies identify infectious diseases' causation and pathogenesis, and unravel infectious agents' sources, reservoirs, circulation  ...  pattern, transmission pattern, transmission probability, and transmission order.  ...  Acknowledgments: This article is part of a PhD thesis and was supported by Kerman University of Medical Sciences (Grant number: grant 92-10-8-29690), Pasteur Institute of Iran, and UNAIDS Country office  ... 
doi:10.19082/5149 pmid:28979755 pmcid:PMC5614305 fatcat:jgxrvkt44jhdpklwdu6hhr7dxm

Assessing biases in phylodynamic inferences in the presence of super-spreaders

Arata Hidano, M. Carolyn Gates
2019 Veterinary Research  
Genetic sequences were sampled serially over the epidemic, which were then used to estimate the epidemic starting date using Extended Bayesian Coalescent Skyline plot (EBSP) and Birth-death skyline plot  ...  We simulated 100 epidemics of a hypothetical pathogen (fast evolving foot and mouth disease virus-like) over a real livestock movement network allowing the genetic mutations in pathogen sequence.  ...  from Massey University, SoVS Strategic Fund, University of Auckland, and Kathleen Spragg Agricultural Research Trust.  ... 
doi:10.1186/s13567-019-0692-5 pmid:31558163 pmcid:PMC6764146 fatcat:hxxjs5qbw5ghhomaes2u7tf32y

Genetic differences in host infectivity affect disease spread and survival in epidemics

Osvaldo Anacleto, Santiago Cabaleiro, Beatriz Villanueva, María Saura, Ross D. Houston, John A. Woolliams, Andrea B. Doeschl-Wilson
2019 Scientific Reports  
undergoing an epidemic are also affected by endurance (the propensity of diseased individual to survive the infection) and infectivity (i.e. the propensity of an infected individual to transmit disease  ...  Here we propose an experimental design and statistical models for estimating genetic diversity in all three host traits.  ...  Temporal epidemic data generated by applying our experimental design in an infectious disease model using family-structured fish allowed to dissect the different sources of genetic variation on disease  ... 
doi:10.1038/s41598-019-40567-w pmid:30894567 pmcid:PMC6426847 fatcat:6krndnlcmzagjf5rm7pnuqdkw4

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  
Currently, molecular epidemiology methods are used in a variety of settings: from infectious disease surveillance systems to the description of disease transmission pathways.  ...  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.  ...  Acknowledgements TV is supported by the Clarendon Fund and Hertford College of the University of Oxford, SF is supported by the NIH NIDA (Grant number DP1DA034989), GM is supported by the MRC Clinician  ... 
doi:10.1016/j.meegid.2016.05.042 pmid:27262354 pmcid:PMC5135626 fatcat:qv5y4pw2ind6robgm2v7jdos4m

Inferring Epidemic Network Topology from Surveillance Data

Xiang Wan, Jiming Liu, William K. Cheung, Tiejun Tong, Alessandro Vespignani
2014 PLoS ONE  
We apply our model on the surveillance data from the 2009 H1N1 pandemic in Hong Kong. The inferred epidemic network displays significant effect on the propagation of infectious diseases.  ...  The accumulated surveillance data including temporal, spatial, clinical, and demographic information, can provide valuable information with which to infer the underlying epidemic networks.  ...  Acknowledgments We thank the editor and two anonymous reviewers for their constructive comments, which helped us to improve the manuscript. Author Contributions  ... 
doi:10.1371/journal.pone.0100661 pmid:24979215 pmcid:PMC4076216 fatcat:r6ygo6cqj5h33g4sna7hlvoqou

Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data

Finlay Campbell, Anne Cori, Neil Ferguson, Thibaut Jombart, Virginia E. Pitzer
2019 PLoS Computational Biology  
There exists significant interest in developing statistical and computational tools for inferring 'who infected whom' in an infectious disease outbreak from densely sampled case data, with most recent  ...  on the coverage of the contact tracing effort and the amount of non-infectious mixing between cases.  ...  Acknowledgments We are thankful to Github (https://github.com), CRAN (http://cran.r-project.org) and the wider R community for providing great resources for the development and hosting of outbreaker2.  ... 
doi:10.1371/journal.pcbi.1006930 pmid:30925168 pmcid:PMC6457559 fatcat:7wixfnjrgbfr3la46is6h43gyy

Tuberculosis outbreak investigation using phylodynamic analysis

Denise Kühnert, Mireia Coscolla, Daniela Brites, David Stucki, John Metcalfe, Lukas Fenner, Sebastien Gagneux, Tanja Stadler
2018 Epidemics  
Specifically, we (i) test if the outbreak data sets contain enough genetic variation to estimate short-term evolutionary rates and (ii) reconstruct epidemiological parameters such as the effective reproduction  ...  There is little temporal signal in the Bern data set and moderate temporal signal in the WTK data set.  ...  The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
doi:10.1016/j.epidem.2018.05.004 pmid:29880306 pmcid:PMC6227250 fatcat:od4gjke7dbbe5n4klq3g7f6cfa

Phylogenetic and epidemic modeling of rapidly evolving infectious diseases

Denise Kühnert, Chieh-Hsi Wu, Alexei J. Drummond
2011 Infection, Genetics and Evolution  
Epidemic modeling of infectious diseases has a long history in both theoretical and empirical research.  ...  However the recent explosion of genetic data has revealed the rapid rate of evolution that many populations of infectious agents undergo and has underscored the need to consider both evolutionary and ecological  ...  Reconstructing the origins of an infectious disease When a new epidemic emerges, one of the first goals is to trace it back to its genetic and geographic origin.  ... 
doi:10.1016/j.meegid.2011.08.005 pmid:21906695 pmcid:PMC7106223 fatcat:yisqfpn3qzcl3hc4hy56eyfttq

Genetic differences in host infectivity affect disease spread and survival in epidemics: [article]

Osvaldo Anacleto, Santiago Cabaleiro, Beatriz Villanueva, Maria Saura, Ross Houston, John A Woolliams, Andrea B Doeschl-Wilson
2018 bioRxiv   pre-print
undergoing an epidemic are also affected by endurance (the propensity of diseased individual to survive the infection) and infectivity (i.e. the propensity of an infected individual to transmit disease  ...  Here we propose an experimental design and statistical models for estimating genetic diversity in all three host traits.  ...  Temporal epidemic data 257 generated by applying our experimental design in an infectious disease model using Figure 2) .  ... 
doi:10.1101/483602 fatcat:ncvz6zvzkfgflpe2evsb2eu3xy

Seasonal Population Movements and the Surveillance and Control of Infectious Diseases

Caroline O. Buckee, Andrew J. Tatem, C. Jessica E. Metcalf
2017 Trends in Parasitology  
National policies designed to control infectious diseases should allocate resources for interventions based on regional estimates of disease burden from surveillance systems.  ...  Two complementary and poorly described drivers of seasonal disease incidence are the mobility and aggregation of human populations, which spark outbreaks and sustain transmission, respectively, and may  ...  Dynamical models of infectious disease transmission, statistical methods for handling spatial data, and population genetic models, all struggle to incorporate temporal fluctuations.  ... 
doi:10.1016/j.pt.2016.10.006 pmid:27865741 pmcid:PMC5423408 fatcat:4nuftxfkdzdvjndjnnfobideza

Table of Contents

2015 Epidemics  
3: What are the mechanisms underlie the dilution effect, and when do they apply? 4: How to estimate cross-species transmission in field settings?  ...  for cross-species spillover transmission from general principles to specific, mechanistic frameworks integrating all relevant data types 3: Harness pathogen genetic data across the human-animal interface  ... 
doi:10.1016/s1755-4365(15)00033-x fatcat:q2gg4cfowjhvvnnooczyybhjly

Supersize me: how whole-genome sequencing and big data are transforming epidemiology

Rowland R. Kao, Daniel T. Haydon, Samantha J. Lycett, Pablo R. Murcia
2014 Trends in Microbiology  
has the potential to produce a paradigm shift in our understanding of infectious disease transmission and control.  ...  In epidemiology, the identification of 'who infected whom' allows us to quantify key characteristics such as incubation periods, heterogeneity in transmission rates, duration of infectiousness, and the  ...  An epidemiological model of disease progression in individuals is used to estimate possible dates of infection and the infectious period of the observed cases.  ... 
doi:10.1016/j.tim.2014.02.011 pmid:24661923 pmcid:PMC7125769 fatcat:nhs32qxdjzdwvoa5d3j72sgihm
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