| Year |
Citation |
Score |
| 2024 |
Rahul CR, Deardon R. Behavioural Change Piecewise Constant Spatial Epidemic Models. Infectious Disease Modelling. 10: 302-324. PMID 39634020 DOI: 10.1016/j.idm.2024.10.006 |
0.316 |
|
| 2024 |
Akter T, Deardon R. Conditional logistic individual-level models of spatial infectious disease dynamics. Infectious Disease Modelling. 10: 268-286. PMID 39624232 DOI: 10.1016/j.idm.2024.10.008 |
0.358 |
|
| 2024 |
Hodzic-Santor E, Deardon R. Edge effects in spatial infectious disease models. Spatial and Spatio-Temporal Epidemiology. 50: 100673. PMID 39181608 DOI: 10.1016/j.sste.2024.100673 |
0.32 |
|
| 2024 |
Rahul CR, Deardon R. Individual-level models of disease transmission incorporating piecewise spatial risk functions. Spatial and Spatio-Temporal Epidemiology. 50: 100664. PMID 39181603 DOI: 10.1016/j.sste.2024.100664 |
0.357 |
|
| 2023 |
Akter T, Deardon R. Variable screening methods in spatial infectious disease transmission models. Spatial and Spatio-Temporal Epidemiology. 47: 100622. PMID 38042533 DOI: 10.1016/j.sste.2023.100622 |
0.325 |
|
| 2023 |
Biesheuvel MM, Ward C, Penterman P, van Engelen E, van Schaik G, Deardon R, Barkema HW. Within-herd transmission of Mycoplasma bovis infections after initial detection in dairy cows. Journal of Dairy Science. PMID 37709017 DOI: 10.3168/jds.2023-23407 |
0.426 |
|
| 2023 |
Amiri L, Torabi M, Deardon R. Analyzing COVID-19 data in the Canadian province of Manitoba: A new approach. Spatial Statistics. 55: 100729. PMID 37089455 DOI: 10.1016/j.spasta.2023.100729 |
0.32 |
|
| 2022 |
Ward MA, Deeth LE, Deardon R. Computationally efficient parameter estimation for spatial individual-level models of infectious disease transmission. Spatial and Spatio-Temporal Epidemiology. 41: 100497. PMID 35691654 DOI: 10.1016/j.sste.2022.100497 |
0.331 |
|
| 2021 |
Singh BB, Ward MP, Lowerison M, Lewinson RT, Vallerand IA, Deardon R, Gill JPS, Singh B, Barkema HW. Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities. One Health (Amsterdam, Netherlands). 13: 100283. PMID 34222606 DOI: 10.1016/j.onehlt.2021.100283 |
0.443 |
|
| 2021 |
Angevaare J, Feng Z, Deardon R. Inference of latent event times and transmission networks in individual level infectious disease models. Spatial and Spatio-Temporal Epidemiology. 37: 100410. PMID 33980405 DOI: 10.1016/j.sste.2021.100410 |
0.302 |
|
| 2021 |
Amiri L, Torabi M, Deardon R, Pickles M. Spatial modeling of individual-level infectious disease transmission: Tuberculosis data in Manitoba, Canada. Statistics in Medicine. PMID 33469942 DOI: 10.1002/sim.8863 |
0.301 |
|
| 2020 |
Singh BB, Lowerison M, Lewinson RT, Vallerand IA, Deardon R, Gill JP, Singh B, Barkema HW. Public health interventions slowed but did not halt the spread of COVID-19 in India. Transboundary and Emerging Diseases. PMID 33012088 DOI: 10.1111/tbed.13868 |
0.391 |
|
| 2020 |
Nobrega DB, Naqvi SA, Dufour S, Deardon R, Kastelic JP, De Buck J, Barkema HW. Critically important antimicrobials are generally not needed to treat nonsevere clinical mastitis in lactating dairy cows: Results from a network meta-analysis. Journal of Dairy Science. PMID 32896405 DOI: 10.3168/Jds.2020-18365 |
0.479 |
|
| 2020 |
Mahsin MD, Deardon R, Brown P. Geographically dependent individual-level models for infectious diseases transmission. Biostatistics (Oxford, England). PMID 32118253 DOI: 10.1093/Biostatistics/Kxaa009 |
0.468 |
|
| 2020 |
V. V, Almutiry W, Deardon R. Individual-Level Modelling of Infectious Disease Data: EpiILM The R Journal. 12: 87. DOI: 10.32614/rj-2020-020 |
0.315 |
|
| 2019 |
Almutiry W, Deardon R. Incorporating Contact Network Uncertainty in Individual Level Models of Infectious Disease using Approximate Bayesian Computation. The International Journal of Biostatistics. PMID 31812945 DOI: 10.1515/Ijb-2017-0092 |
0.423 |
|
| 2019 |
Lowerison MW, Josephson CB, Jetté N, Sajobi TT, Patten S, Williamson T, Deardon R, Barkema HW, Wiebe S. Association of Levels of Specialized Care With Risk of Premature Mortality in Patients With Epilepsy. Jama Neurology. PMID 31380987 DOI: 10.1001/Jamaneurol.2019.2268 |
0.407 |
|
| 2019 |
Augusta C, Deardon R, Taylor G. Deep learning for supervised classification of spatial epidemics. Spatial and Spatio-Temporal Epidemiology. 29: 187-198. PMID 31128628 DOI: 10.1016/J.Sste.2018.08.002 |
0.327 |
|
| 2019 |
Augusta C, Taylor GW, Deardon R. Dynamic contact networks of swine movement in Manitoba, Canada: characterization and implications for infectious disease spread. Transboundary and Emerging Diseases. PMID 31059200 DOI: 10.1111/Tbed.13220 |
0.341 |
|
| 2019 |
Coward S, Clement F, Benchimol EI, Bernstein CN, Avina-Zubieta JA, Bitton A, Carroll MW, Hazlewood G, Jacobson K, Jelinski S, Deardon R, Jones JL, Kuenzig ME, Leddin D, McBrien KA, et al. Past and Future Burden of Inflammatory Bowel Diseases Based on Modeling of Population-based Data. Gastroenterology. PMID 30639677 DOI: 10.1053/J.Gastro.2019.01.002 |
0.324 |
|
| 2019 |
Kwong GPS, Deardon R, Hunt S, Guerin MT. Bayesian Design of Agricultural Disease Transmission Experiments for Individual Level Models Statistical Communications in Infectious Diseases. DOI: 10.1515/Scid-2018-0005 |
0.375 |
|
| 2019 |
Romanescu RG, Deardon R. Implementation of Power Law Network Models of Epidemic Surveillance Data for Better Evaluation of Outbreak Detection Alarms Statistical Communications in Infectious Diseases. DOI: 10.1515/Scid-2018-0004 |
0.309 |
|
| 2018 |
Petukhova T, Ojkic D, McEwen B, Deardon R, Poljak Z. Assessment of autoregressive integrated moving average (ARIMA), generalized linear autoregressive moving average (GLARMA), and random forest (RF) time series regression models for predicting influenza A virus frequency in swine in Ontario, Canada. Plos One. 13: e0198313. PMID 29856881 DOI: 10.1371/Journal.Pone.0198313 |
0.371 |
|
| 2018 |
Pokharel G, Deardon R. Spatially Informed Back-Calculation for Spatio-Temporal Infectious Disease Models Statistical Communications in Infectious Diseases. 10. DOI: 10.1515/Scid-2017-0001 |
0.413 |
|
| 2017 |
Romanescu RG, Deardon R. Fast Inference for Network Models of Infectious Disease Spread Scandinavian Journal of Statistics. 44: 666-683. DOI: 10.1111/Sjos.12270 |
0.386 |
|
| 2016 |
Deeth LE, Deardon R. Spatial data aggregation for spatio-temporal individual-level models of infectious disease transmission. Spatial and Spatio-Temporal Epidemiology. 17: 95-104. PMID 27246276 DOI: 10.1016/J.Sste.2016.04.013 |
0.42 |
|
| 2016 |
Malik R, Deardon R, Kwong GP. Parameterizing Spatial Models of Infectious Disease Transmission that Incorporate Infection Time Uncertainty Using Sampling-Based Likelihood Approximations. Plos One. 11: e0146253. PMID 26731666 DOI: 10.1371/Journal.Pone.0146253 |
0.453 |
|
| 2016 |
Romanescu R, Deardon R. Modeling two strains of disease via aggregate-level infectivity curves. Journal of Mathematical Biology. 72: 1195-224. PMID 26084408 DOI: 10.1007/S00285-015-0910-3 |
0.455 |
|
| 2016 |
Pokharel G, Deardon R. Gaussian process emulators for spatial individual-level models of infectious disease Canadian Journal of Statistics. 44: 480-501. DOI: 10.1002/Cjs.11304 |
0.416 |
|
| 2015 |
Deeth LE, Deardon R, Gillis DJ. Model Choice Using the Deviance Information Criterion for Latent Conditional Individual-Level Models of Infectious Disease Spread Epidemiologic Methods. 4. DOI: 10.1515/em-2014-0001 |
0.334 |
|
| 2014 |
Pokharel G, Deardon R. Supervised learning and prediction of spatial epidemics. Spatial and Spatio-Temporal Epidemiology. 11: 59-77. PMID 25457597 DOI: 10.1016/J.Sste.2014.08.003 |
0.438 |
|
| 2014 |
Malik R, Deardon R, Kwong GP, Cowling BJ. Individual-level modeling of the spread of influenza within households Journal of Applied Statistics. 41: 1578-1592. DOI: 10.1080/02664763.2014.881787 |
0.443 |
|
| 2014 |
McKinley TJ, Ross JV, Deardon R, Cook AR. Simulation-based Bayesian inference for epidemic models Computational Statistics and Data Analysis. 71: 434-447. DOI: 10.1016/J.Csda.2012.12.012 |
0.35 |
|
| 2013 |
Bifolchi N, Deardon R, Feng Z. Spatial approximations of network-based individual level infectious disease models. Spatial and Spatio-Temporal Epidemiology. 6: 59-70. PMID 23973181 DOI: 10.1016/J.Sste.2013.07.001 |
0.436 |
|
| 2013 |
Deeth LE, Deardon R. Latent conditional individual-level models for infectious disease modeling. The International Journal of Biostatistics. 9. PMID 23917477 DOI: 10.1515/Ijb-2013-0026 |
0.433 |
|
| 2013 |
Kwong GP, Poljak Z, Deardon R, Dewey CE. Bayesian analysis of risk factors for infection with a genotype of porcine reproductive and respiratory syndrome virus in Ontario swine herds using monitoring data. Preventive Veterinary Medicine. 110: 405-17. PMID 23416041 DOI: 10.1016/J.Prevetmed.2013.01.004 |
0.409 |
|
| 2012 |
Bottoms K, Poljak Z, Dewey C, Deardon R, Holtkamp D, Friendship R. Investigation of strategies for the introduction and transportation of replacement gilts on southern Ontario sow farms. Bmc Veterinary Research. 8: 217. PMID 23140357 DOI: 10.1186/1746-6148-8-217 |
0.308 |
|
| 2012 |
Kwong GP, Deardon R. Linearized forms of individual-level models for large-scale spatial infectious disease systems. Bulletin of Mathematical Biology. 74: 1912-37. PMID 22718395 DOI: 10.1007/S11538-012-9739-8 |
0.424 |
|
| 2012 |
Le H, Poljak Z, Deardon R, Dewey CE. Clustering of and Risk Factors for the Porcine High Fever Disease in a Region of Vietnam Transboundary and Emerging Diseases. 59: 49-61. PMID 21722329 DOI: 10.1111/J.1865-1682.2011.01239.X |
0.338 |
|
| 2012 |
Vrbik I, Deardon R, Feng Z, Gardner A, Braun J. Using Individual-Level Models for Infectious Disease Spread to Model Spatio-Temporal Combustion Dynamics Bayesian Analysis. 7: 615-638. DOI: 10.1214/12-Ba721 |
0.406 |
|
| 2012 |
Deardon R, Habibzadeh B, Chung HY. Spatial measurement error in infectious disease models Journal of Applied Statistics. 39: 1139-1150. DOI: 10.1080/02664763.2011.644522 |
0.451 |
|
| 2012 |
Hosseinkashi Y, Chenouri S, Small CG, Deardon R. A stochastic graph process for epidemic modelling Canadian Journal of Statistics. 40: 55-67. DOI: 10.1002/Cjs.10142 |
0.338 |
|
| 2011 |
Gardner A, Deardon R, Darlington G. Goodness-of-fit measures for individual-level models of infectious disease in a Bayesian framework. Spatial and Spatio-Temporal Epidemiology. 2: 273-81. PMID 22748225 DOI: 10.1016/J.Sste.2011.07.012 |
0.387 |
|
| 2010 |
Deardon R, Brooks SP, Grenfell BT, Keeling MJ, Tildesley MJ, Savill NJ, Shaw DJ, Woolhouse ME. INFERENCE FOR INDIVIDUAL-LEVEL MODELS OF INFECTIOUS DISEASES IN LARGE POPULATIONS. Statistica Sinica. 20: 239-261. PMID 26405426 |
0.353 |
|
| 2010 |
Habibzadeh B, Deardon R. The Effect of Misspecifying Latent and Infectious Periods in Space-Time Epidemic Models Statistical Communications in Infectious Diseases. 2. DOI: 10.2202/1948-4690.1006 |
0.314 |
|
| 2008 |
Tildesley MJ, Deardon R, Savill NJ, Bessell PR, Brooks SP, Woolhouse ME, Grenfell BT, Keeling MJ. Accuracy of models for the 2001 foot-and-mouth epidemic. Proceedings. Biological Sciences / the Royal Society. 275: 1459-68. PMID 18364313 DOI: 10.1098/Rspb.2008.0006 |
0.416 |
|
| 2007 |
Savill NJ, Shaw DJ, Deardon R, Tildesley MJ, Keeling MJ, Woolhouse ME, Brooks SP, Grenfell BT. Effect of data quality on estimates of farm infectiousness trends in the UK 2001 foot-and-mouth disease epidemic. Journal of the Royal Society, Interface / the Royal Society. 4: 235-41. PMID 17251150 DOI: 10.1098/Rsif.2006.0178 |
0.408 |
|
| 2006 |
Savill NJ, Shaw DJ, Deardon R, Tildesley MJ, Keeling MJ, Woolhouse ME, Brooks SP, Grenfell BT. Topographic determinants of foot and mouth disease transmission in the UK 2001 epidemic. Bmc Veterinary Research. 2: 3. PMID 16412245 DOI: 10.1186/1746-6148-2-3 |
0.386 |
|
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