• Abhari, N., Colijn, C., Mooers, A., & Tupper, P. (2024). Capturing Diversity: Split Systems and Circular Approximations for Conservation. Journal of Theoretical Biology, 578:111689 https://doi.org/10.1016/j.jtbi.2023.111689

  • Are, E.B., Card, K.G. & Colijn, C. (2024). The role of vaccine status homophily in the COVID-19 pandemic: a cross-sectional survey with modelling, BMC Public Health, 24(1), 472. https://doi.org/10.1186/s12889-024-17957-5

  • Otto, S.P., MacPherson, A., & Colijn, C. (2024) Endemic does not mean constant as SARS-CoV-2 continues to evolve. Evolution,; qpae041, https://doi.org/10.1093/evolut/qpae041


  • Mulberry N, Rutherford AR, Colijn C. (2023). Pneumococcal population dynamics: Investigating vaccine-induced changes through multiscale modelling. PLOS Computational Biology. 2023;19: e1011755 doi:10.1371/journal.pcbi.1011755
  • Are EB, Stockdale J, Colijn C. (2023) Long-Term Dynamics of COVID-19 in a Multi-strain Model. Book Chapter: David, J., Wu, J. (eds) Mathematics of Public Health. Fields Institute Communications, vol 88. Springer, Cham. 295-317. https://doi.org/10.1007/978-3-031-40805-2_11
  • Walter KS, Cohen T, Mathema B, Colijn C, Sobkowiak B, Comas I, Goig GA, Croda J, Andrews JR. (2023). Signatures of transmission in within-hose M. tuberculosis variation [Preprint]. medRxiv. 2023(12), 28.23300451
  • Are, E. B., Song, Y., Stockdale, J. E., Tupper, P., & Colijn, C. (2023). COVID-19 endgame: From pandemic to endemic? Vaccination, reopening and evolution in low- and high-vaccinated populations. Journal of Theoretical Biology, 559, 111368. https://doi.org/10.1016/j.jtbi.2022.111368
  • Barton, A., & Colijn, C. (2023). Genomic, clinical and immunity data join forces for public health. Nature Reviews. Microbiology, 21(10), 639–639. https://doi.org/10.1038/s41579-023-00965-4
  • Chitwood, M. H., Colijn, C., Yang, C., Crudu, V., Ciobanu, N., Codreanu, A., Kim, J., Rancu, I., Rhee, K., Cohen, T., & Sobkowiak, B. (2023). The recent rapid expansion of multidrug resistant strains of Mycobacterium tuberculosis Ural lineage 4.2 in the Republic of Moldova [Preprint]. Epidemiology. https://doi.org/10.1101/2023.11.10.23298377
  • Colijn, C., Halloran, M. E., O’Neill, P., & Trapman, P. (2023). Design and Analysis of Infectious Disease Studies. Oberwolfach Reports, 20(1), 487–435. https://doi.org/10.4171/OWR/2023/8
  • Hayati, M., Sobkowiak, B., Stockdale, J. E., & Colijn, C. (2023). Phylogenetic identification of influenza virus candidates for seasonal vaccines. Science Advances, 9(44), eabp9185. https://doi.org/10.1126/sciadv.abp9185
  • Lewis, M. A., Brown, P., Colijn, C., Cowen, L., Cotton, C., Day, T., Deardon, R., Earn, D., Haskell, D., Heffernan, J., Leighton, P., Murty, K., Otto, S., Rafferty, E., Tuohy, C. H., Wu, J., & Zhu, H. (2023). Charting a future for emerging infectious disease modelling in Canada. University of Victoria. http://hdl.handle.net/1828/15042
  • Otto, S. P., MacPherson, A., & Colijn, C. (2023). Endemic means change as SARS-CoV-2 evolves [Preprint]. Epidemiology. https://doi.org/10.1101/2023.09.28.23296264
  • Shaver, N., Katz, M., Darko Asamoah, G., Linkins, L.-A., Abdelkader, W., Beck, A., Bennett, A., Hughes, S. E., Smith, M., Begin, M., Coyle, D., Piggott, T., Kagina, B. M., Welch, V., Colijn, C., Earn, D. J. D., El Emam, K., Heffernan, J., O’Brien, S. F., … Little, J. (2023). Protocol for a living evidence synthesis on variants of concern and COVID-19 vaccine effectiveness. Vaccine, 41(43), 6411–6418. https://doi.org/10.1016/j.vaccine.2023.09.012
  • Sobkowiak, B., Haghmaram, P., Prystajecky, N., Zlosnik, J. E. A., Tyson, J., Hoang, L. M. N., & Colijn, C. (2023). The utility of SARS-CoV-2 genomic data for informative clustering under different epidemiological scenarios and sampling. Infection Genetics and Evolution, 113, 105484.
  • Stockdale, J. E., Susvitasari, K., Tupper, P., Sobkowiak, B., Mulberry, N., Gonçalves Da Silva, A., Watt, A. E., Sherry, N. L., Minko, C., Howden, B. P., Lane, C. R., & Colijn, C. (2023). Genomic epidemiology offers high resolution estimates of serial intervals for COVID-19. Nature Communications, 14(1), 4830. https://doi.org/10.1038/s41467-023-40544-y
  • Susvitasari, K., Tupper, P. F., Cancino-Muños, I., Lòpez, M. G., Comas, I., & Colijn, C. (2023). Epidemiological cluster identification using multiple data sources: An approach using logistic regression. Microbial Genomics, 9(3). https://doi.org/10.1099/mgen.0.000929
  • Susvitasari, K., Tupper, P., Stockdale, J. E., & Colijn, C. (2023). A method to estimate the serial interval distribution under partially-sampled data. Epidemics, 45, 100733. https://doi.org/10.1016/j.epidem.2023.100733
  • Wang, S., Ge, S., Sobkowiak, B., Wang, L., Grandjean, L., Colijn, C., & Elliott, L. T. (2023). Genome-Wide Association with Uncertainty in the Genetic Similarity Matrix. Journal of Computational Biology, 30(2), 189–203.
  • Warren, J. L., Chitwood, M. H., Sobkowiak, B., Colijn, C., & Cohen, T. (2023). Spatial modeling of Mycobacterium tuberculosis transmission with dyadic genetic relatedness data. Biometrics. Journal of the International Biometric Society, biom.13836. https://doi.org/10.1111/biom.13836
  • Yerlanov, M., Agarwal, P., Colijn, C., & Stockdale, J. E. (2023). Effective population size in simple infectious disease models. Journal of Mathematical Biology, 87(6), 80. https://doi.org/10.1007/s00285-023-02016-1
  • Zhang, L., Abhari, N., Colijn, C., & Wu, Y. (2023). A fast and scalable method for inferring phylogenetic networks from trees by aligning lineage taxon strings. Genome Research, 33(7), 1053–1060.


  • Cancino-Muñoz, I., López, M. G., Torres-Puente, M., Villamayor, L. M., Borrás, R., Borrás-Máñez, M., Bosque, M., Camarena, J. J., Colijn, C., Colomer-Roig, E., Colomina, J., Escribano, I., Esparcia-Rodríguez, O., García-García, F., Gil-Brusola, A., Gimeno, C., Gimeno-Gascón, A., Gomila-Sard, B., Gónzales-Granda, D., … Comas, I. (2022). Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics. eLife, 11, e76605. https://doi.org/10.7554/eLife.76605
  • Colijn, C., Earn, D. J., Dushoff, J., Ogden, N. H., Li, M., Knox, N., Van Domselaar, G., Franklin, K., Jolly, G., & Otto, S. P. (2022). La nécessité d’une surveillance génomique liée du SRAS-CoV-2. RMTC, 48(4), 147–155. https://doi.org/10.14745/ccdr.v48i04a03f
  • Colijn, C., Earn, D. J., Dushoff, J., Ogden, N. H., Li, M., Knox, N., Van Domselaar, G., Franklin, K., Jolly, G., & Otto, S. P. (2022). The need for linked genomic surveillance of SARS-CoV-2. Canada Communicable Disease Report, 48(4), 131–139.
  • Fibke, C. D., Joffres, Y., Tyson, J. R., Colijn, C., Janjua, N. Z., Fjell, C., Prystajecky, N., Jassem, A., & Sbihi, H. (2022). Spike Mutation Profiles Associated With SARS-CoV-2 Breakthrough Infections in Delta Emerging and Predominant Time Periods in British Columbia, Canada. Frontiers in Public Health, 10, 915363. https://doi.org/10.3389/fpubh.2022.915363
  • Grandjean, L., Saso, A., Torres Ortiz, A., Lam, T., Hatcher, J., Thistlethwayte, R., Harris, M., Best, T., Johnson, M., Wagstaffe, H., Ralph, E., Mai, A., Colijn, C., Breuer, J., Buckland, M., Gilmour, K., Goldblatt, D., & COVID-19 Staff Testing of Antibody Responses Study (Co-Stars) team. (2022). Long-Term Persistence of Spike Protein Antibody and Predictive Modeling of Antibody Dynamics After Infection With Severe Acute Respiratory Syndrome Coronavirus 2. Clinical Infectious Diseases, 74(7), 1220–1229.
  • Hayati, M., Chindelevitch, L., Aanensen, D., & Colijn, C. (2022). Deep clustering of bacterial tree images. Philosophical Transactions of the Royal Society B: Biological Sciences, 377(1861), 20210231. https://doi.org/10.1098/rstb.2021.0231
  • Iyaniwura, S. A., Falcão, R. C., Ringa, N., Adu, P. A., Spencer, M., Taylor, M., Colijn, C., Coombs, D., Janjua, N. Z., Irvine, M. A., & Otterstatter, M. (2022). Mathematical modeling of COVID-19 in British Columbia: An age-structured model with time-dependent contact rates. Epidemics, 39, 100559. https://doi.org/10.1016/j.epidem.2022.100559
  • Liu, P., Biller, P., Gould, M., & Colijn, C. (2022). Analyzing Phylogenetic Trees with a Tree Lattice Coordinate System and a Graph Polynomial. Systematic Biology, 71(6), 1378–1390. https://doi.org/10.1093/sysbio/syac008
  • Liu, P., Song, Y., Colijn, C., & MacPherson, A. (2022). The impact of sampling bias on viral phylogeographic reconstruction. PLOS Glob Public Health, 2(9), e0000577. https://doi.org/10.1371/journal.pgph.0000577
  • Sobkowiak, B., & Colijn, C. (2022). Characterising indel diversity in a large Mycobacterium tuberculosis outbreak – implications for transmission reconstruction [Preprint]. Genomics. https://doi.org/10.1101/2022.10.26.513840
  • Sobkowiak, B., Kamelian, K., Zlosnik, J. E. A., Tyson, J., Silva, A. G. D., Hoang, L. M. N., Prystajecky, N., & Colijn, C. (2022). Cov2clusters: Genomic clustering of SARS-CoV-2 sequences. BMC Genomics, 23(1), 710. https://doi.org/10.1186/s12864-022-08936-4
  • Stockdale, J. E., Anderson, S. C., Edwards, A. M., Iyaniwura, S. A., Mulberry, N., Otterstatter, M. C., Janjua, N. Z., Coombs, D., Colijn, C., & Irvine, M. A. (2022). Quantifying transmissibility of SARS-CoV-2 and impact of intervention within long-term healthcare facilities. Royal Society Open Science, 9(1), 211710.
  • Stockdale, J. E., Liu, P., & Colijn, C. (2022). The potential of genomics for infectious disease forecasting. Nature Microbiology, 7(11), 1736–1743. https://doi.org/10.1038/s41564-022-01233-6
  • Tupper, P., Pai, S., COVID Schools Canada, & Colijn, C. (2022). COVID-19 cluster size and transmission rates in schools from crowdsourced case reports. eLife, 11, e76174. https://doi.org/10.7554/eLife.76174
  • Walter, K. S., Pereira Dos Santos, P. C., Gonçalves, T. O., Da Silva, B. O., Santos, A. D. S., Leite, A. D. C., Da Silva, A. M., Moreira, F. M. F., De Oliveira, R. D., Lemos, E. F., Cunha, E., Liu, Y. E., Ko, A. I., Colijn, C., Cohen, T., Mathema, B., Croda, J., & Andrews, J. R. (2022). The role of prisons in disseminating tuberculosis in Brazil: A genomic epidemiology study. The Lancet Regional Health - Americas, 9, 100186. https://doi.org/10.1016/j.lana.2022.100186
  • Wang, L., Min, J., Doig, R., Elliott, L. T., & Colijn, C. (2022). Estimation of SARS‐CoV‐2 antibody prevalence through serological uncertainty and daily incidence. Can J Statistics, 50(3), 734–750. https://doi.org/10.1002/cjs.11722
  • Yang, C., Sobkowiak, B., Naidu, V., Codreanu, A., Ciobanu, N., Gunasekera, K. S., Chitwood, M. H., Alexandru, S., Bivol, S., Russi, M., Havumaki, J., Cudahy, P., Fosburgh, H., Allender, C. J., Centner, H., Engelthaler, D. M., Menzies, N. A., Warren, J. L., Crudu, V., … Cohen, T. (2022). Phylogeography and transmission of M. tuberculosis in Moldova: A prospective genomic analysis. PLoS Medicine, 19(2), e1003933. https://doi.org/10.1371/journal.pmed.1003933


  • Anderson, S. C., Mulberry, N., Edwards, A. M., Stockdale, J. E., Iyaniwura, S. A., Falcao, R. C., Otterstatter, M. C., Janjua, N. Z., Coombs, D., & Colijn, C. (2021). How much leeway is there to relax COVID-19 control measures? Epidemics, 35, 100453. https://doi.org/10.1016/j.epidem.2021.100453
  • Are, E. B., & Colijn, C. (2021). Projected spread of COVID-19’s second wave in South Africa under different levels of lockdown [Preprint]. Epidemiology. https://doi.org/10.1101/2021.01.22.21250308
  • Brown, T. S., Eldholm, V., Brynildsrud, O., Osnes, M., Levy, N., Stimson, J., Colijn, C., Alexandru, S., Noroc, E., Ciobanu, N., Crudu, V., Cohen, T., & Mathema, B. (2021). Evolution and emergence of multidrug-resistant Mycobacterium tuberculosis in Chisinau, Moldova. Microbial Genomics, 7(8). https://doi.org/10.1099/mgen.0.000620
  • Chindelevitch, L., Hayati, M., Poon, A. F. Y., & Colijn, C. (2021). Network science inspires novel tree shape statistics. PLoS ONE, 16(12), e0259877. https://doi.org/10.1371/journal.pone.0259877
  • Dushoff, J., Colijn, C., Earn, D. J. D., & Bolker, B. M. (2021). Transmission dynamics are crucial to COVID-19 vaccination policy. Proceedings of the National Academy of Sciences of the United States of America, 118(29), e2105878118. https://doi.org/10.1073/pnas.2105878118
  • Harrow, G. L., Lees, J. A., Hanage, W. P., Lipsitch, M., Corander, J., Colijn, C., & Croucher, N. J. (2021). Negative frequency-dependent selection and asymmetrical transformation stabilise multi-strain bacterial population structures. The ISME Journal, 15(5), 1523–1538. https://doi.org/10.1038/s41396-020-00867-w
  • Liu, P., McQuarrie, L., Song, Y., & Colijn, C. (2021). Modelling the impact of household size distribution on the transmission dynamics of COVID-19. Journal of The Royal Society Interface, 18(177), rsif.2021.0036, 20210036. https://doi.org/10.1098/rsif.2021.0036
  • Mulberry, N., Tupper, P., Kirwin, E., McCabe, C., & Colijn, C. (2021). Vaccine rollout strategies: The case for vaccinating essential workers early. PLOS Glob Public Health, 1(10), e0000020. https://doi.org/10.1371/journal.pgph.0000020
  • Otto, S. P., Day, T., Arino, J., Colijn, C., Dushoff, J., Li, M., Mechai, S., Van Domselaar, G., Wu, J., Earn, D. J. D., & Ogden, N. H. (2021). The origins and potential future of SARS-CoV-2 variants of concern in the evolving COVID-19 pandemic. Current Biology, 31(14), R918–R929. https://doi.org/10.1016/j.cub.2021.06.049
  • Quan, A. M. L., Mah, C., Krebs, E., Zang, X., Chen, S., Althoff, K., Armstrong, W., Behrends, C. N., Dombrowski, J. C., Enns, E., Feaster, D. J., Gebo, K. A., Goedel, W. C., Golden, M., Marshall, B. D. L., Mehta, S. H., Pandya, A., Schackman, B. R., Strathdee, S. A., … Weiner, J. (2021). Improving health equity and ending the HIV epidemic in the USA: A distributional cost-effectiveness analysis in six cities. The Lancet HIV, 8(9), e581–e590. https://doi.org/10.1016/S2352-3018(21)00147-8
  • Sadarangani, M., Abu Raya, B., Conway, J. M., Iyaniwura, S. A., Falcao, R. C., Colijn, C., Coombs, D., & Gantt, S. (2021). Importance of COVID-19 vaccine efficacy in older age groups. Vaccine, 39(15), 2020–2023. https://doi.org/10.1016/j.vaccine.2021.03.020
  • Stockdale, J. E., Doig, R., Min, J., Mulberry, N., Wang, L., Elliott, L. T., & Colijn, C. (2021). Long time frames to detect the impact of changing COVID-19 measures, Canada, March to July 2020. Eurosurveillance, 26(40). https://doi.org/10.2807/1560-7917.ES.2021.26.40.2001204
  • Tupper, P., & Colijn, C. (2021). COVID-19 in schools: Mitigating classroom clusters in the context of variable transmission. PLoS Computational Biology, 17(7), e1009120. https://doi.org/10.1371/journal.pcbi.1009120
  • Tupper, P., Otto, S. P., & Colijn, C. (2021). Fundamental limitations of contact tracing for COVID-19. FACETS, 6, 1993–2001. https://doi.org/10.1139/facets-2021-0016
  • Wang, S., Ge, S., Colijn, C., Biller, P., Wang, L., & Elliott, L. T. (2021). Estimating Genetic Similarity Matrices Using Phylogenies. Journal of Computational Biology, 28(6), 587–600. https://doi.org/10.1089/cmb.2020.0375
  • Warren, J. L., Chitwood, M. H., Sobkowiak, B., Crudu, V., Colijn, C., & Cohen, T. (2021). Spatial modeling of dyadic genetic relatedness data: Identifying factors associated with M. tuberculosis transmission in Moldova. https://doi.org/10.48550/arXiv.2109.14003


  • Anderson, S. C., Edwards, A. M., Yerlanov, M., Mulberry, N., Stockdale, J. E., Iyaniwura, S. A., Falcao, R. C., Otterstatter, M. C., Irvine, M. A., Janjua, N. Z., Coombs, D., & Colijn, C. (2020). Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing. PLoS Computational Biology, 16(12), e1008274. https://doi.org/10.1371/journal.pcbi.1008274
  • Colijn, C., Corander, J., & Croucher, N. J. (2020). Designing ecologically optimized pneumococcal vaccines using population genomics. Nature Microbiology, 5(3), 473–485. https://doi.org/10.1038/s41564-019-0651-y
  • Hayati, M., Biller, P., & Colijn, C. (2020). Predicting the short-term success of human influenza virus variants with machine learning. Proceedings of the Royal Society Biology, 287(1924), 20200319. https://doi.org/10.1098/rspb.2020.0319
  • Metzig, C., & Colijn, C. (2020). A Maximum Entropy Method for the Prediction of Size Distributions. Entropy. An International and Interdisciplinary Journal of Entropy and Information Studies, 22(3).
  • Metzig, C., Gould, M., Noronha, R., Abbey, R., Sandler, M., & Colijn, C. (2020). Classification of origin with feature selection and network construction for folk tunes. Pattern Recognition Letters, 133, 356–364. https://doi.org/10.1016/j.patrec.2020.03.023
  • Tindale, L. C., Stockdale, J. E., Coombe, M., Garlock, E. S., Lau, W. Y. V., Saraswat, M., Zhang, L., Chen, D., Wallinga, J., & Colijn, C. (2020). Evidence for transmission of COVID-19 prior to symptom onset. eLife, 9, e57149. https://doi.org/10.7554/eLife.57149
  • Tupper, P., Boury, H., Yerlanov, M., & Colijn, C. (2020). Event-specific interventions to minimize COVID-19 transmission. Proceedings of the National Academy of Sciences of the United States of America, 117(50), 32038–32045. https://doi.org/10.1073/pnas.2019324117
  • Walter, K. S., Colijn, C., Cohen, T., Mathema, B., Liu, Q., Bowers, J., Engelthaler, D. M., Narechania, A., Lemmer, D., Croda, J., & Andrews, J. R. (2020). Genomic variant-identification methods may alter Mycobacterium tuberculosis transmission inferences. Microbial Genomics, 6(8). https://doi.org/10.1099/mgen.0.000418
  • Xu, Y., Stockdale, J. E., Naidu, V., Hatherell, H., Stimson, J., Stagg, H. R., Abubakar, I., & Colijn, C. (2020). Transmission analysis of a large tuberculosis outbreak in London: A mathematical modelling study using genomic data. Microbial Genomics, 6(11). https://doi.org/10.1099/mgen.0.000450
  • Mulberry, N., Rutherford, A., & Colijn, C. (2020). Systematic comparison of coexistence in models of drug-sensitive and drug-resistant pathogen strains. Theoretical Population Biology, 202(133), 150–158. https://doi.org/10.1016/j.tpb.2019.12.001


  • Hall, M. D., & Colijn, C. (2019). Transmission Trees on a Known Pathogen Phylogeny: Enumeration and Sampling. Molecular Biology and Evolution, 36(6), 1333–1343. https://doi.org/10.1093/molbev/msz058
  • Knight, G. M., Davies, N. G., Colijn, C., Coll, F., Donker, T., Gifford, D. R., Glover, R. E., Jit, M., Klemm, E., Lehtinen, S., Lindsay, J. A., Lipsitch, M., Llewelyn, M. J., Mateus, A. L. P., Robotham, J. V., Sharland, M., Stekel, D., Yakob, L., & Atkins, K. E. (2019). Mathematical modelling for antibiotic resistance control policy: Do we know enough? BMC Infectious Diseases, 19(1), 1011. https://doi.org/10.1186/s12879-019-4630-y
  • Mabud, T. S., De Lourdes Delgado Alves, M., Ko, A. I., Basu, S., Walter, K. S., Cohen, T., Mathema, B., Colijn, C., Lemos, E., Croda, J., & Andrews, J. R. (2019). Correction: Evaluating strategies for control of tuberculosis in prisons and prevention of spillover into communities: An observational and modeling study from Brazil. PLoS Medicine, 16(3), e1002764. https://doi.org/10.1371/journal.pmed.1002764
  • Mabud, T. S., De Lourdes Delgado Alves, M., Ko, A. I., Basu, S., Walter, K. S., Cohen, T., Mathema, B., Colijn, C., Lemos, E., Croda, J., & Andrews, J. R. (2019). Evaluating strategies for control of tuberculosis in prisons and prevention of spillover into communities: An observational and modeling study from Brazil. PLoS Medicine, 16(1), e1002737. https://doi.org/10.1371/journal.pmed.1002737
  • Metzig, C., Ratmann, O., Bezemer, D., & Colijn, C. (2019). Phylogenies from dynamic networks. PLoS Computational Biology, 15(2), e1006761. https://doi.org/10.1371/journal.pcbi.1006761
  • Stimson, J., Gardy, J., Mathema, B., Crudu, V., Cohen, T., & Colijn, C. (2019). Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions. Molecular Biology and Evolution, 36(3), 587–603. https://doi.org/10.1093/molbev/msy242
  • Xu, Y., Cancino-Muñoz, I., Torres-Puente, M., Villamayor, L. M., Borrás, R., Borrás-Máñez, M., Bosque, M., Camarena, J. J., Colomer-Roig, E., Colomina, J., Escribano, I., Esparcia-Rodríguez, O., Gil-Brusola, A., Gimeno, C., Gimeno-Gascón, A., Gomila-Sard, B., González-Granda, D., Gonzalo-Jiménez, N., Guna-Serrano, M. R., … Comas, I. (2019). High-resolution mapping of tuberculosis transmission: Whole genome sequencing and phylogenetic modelling of a cohort from Valencia Region, Spain. PLoS Medicine, 16(10), e1002961. https://doi.org/10.1371/journal.pmed.1002961
  • Xu, Y., Topliffe, H., Stimson, J., Stagg, H.R., Abubakar, I., & Colijn, C. (2019) Transmission analysis of a large TB outbreak in London: mathematical modelling study using genomic data. bioRxiv. 761411. doi: 10.1101/761411


  • Ayabina, D., Ronning, J. O., Alfsnes, K., Debech, N., Brynildsrud, O. B., Arnesen, T., Norheim, G., Mengshoel, A.-T., Rykkvin, R., Dahle, U. R., Colijn, C., & Eldholm, V. (2018). Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population. Microbial Genomics, 4(10). https://doi.org/10.1099/mgen.0.000219
  • Colijn, C., & Plazzotta, G. (2018). A Metric on Phylogenetic Tree Shapes. Systematic Biology, 67(1), 113–126. https://doi.org/10.1093/sysbio/syx046
  • Kendall, M., Ayabina, D., & Colijn, C. (2018). Estimating transmission from genetic and epidemiological data: A metric to compare transmission trees. Statistical Science, 33(1), 70–85. https://doi.org/10.1214/17-STS637
  • Kendall, M., Eldholm, V., & Colijn, C. (2018). Comparing phylogenetic trees according to tip label categories [Preprint]. Evolutionary Biology. https://doi.org/10.1101/251710
  • Lees, J. A., Kendall, M., Parkhill, J., Colijn, C., Bentley, S. D., & Harris, S. R. (2018). Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: A simulation based study. Wellcome Open Research, 3, 33. https://doi.org/10.12688/wellcomeopenres.14265.1
  • Ratmann, O., Camacho, A., Hu, S., & Colijn, C. (2018). Informed choices: How to calibrate ABC with hypothesis testing. In Handbook of approximate bayesian computation (1st ed.). Chapman and Hall. https://www.routledgehandbooks.com/doi/10.1201/9781315117195-11
  • Yaesoubi, R., Trotter, C., Colijn, C., Yaesoubi, M., Colombini, A., Resch, S., Kristiansen, P. A., LaForce, F. M., & Cohen, T. (2018). The cost-effectiveness of alternative vaccination strategies for polyvalent meningococcal vaccines in Burkina Faso: A transmission dynamic modeling study. PLoS Medicine, 15(1), e1002495. https://doi.org/10.1371/journal.pmed.1002495
  • Yang, C., Lu, L., Warren, J. L., Wu, J., Jiang, Q., Zuo, T., Gan, M., Liu, M., Liu, Q., DeRiemer, K., Hong, J., Shen, X., Colijn, C., Guo, X., Gao, Q., & Cohen, T. (2018). Internal migration and transmission dynamics of tuberculosis in Shanghai, China: An epidemiological, spatial, genomic analysis. The Lancet Infectious Diseases, 18(7), 788–795. https://doi.org/10.1016/S1473-3099(18)30218-4
  • Metzig, C., & Colijn, C. (2018) Preferential attachment in systems and networks of constant size [Preprint]. arXiv. 10:e22030312.


  • Cobey, S., Baskerville, E. B., Colijn, C., Hanage, W., Fraser, C., & Lipsitch, M. (2017). Host population structure and treatment frequency maintain balancing selection on drug resistance. Journal of The Royal Society Interface, 14(133), 20170295. https://doi.org/10.1098/rsif.2017.0295
  • Colijn, C., Jones, N., Johnston, I. G., Yaliraki, S., & Barahona, M. (2017). Toward Precision Healthcare: Context and Mathematical Challenges. Frontiers in Physiology, 8. https://doi.org/10.3389/fphys.2017.00136
  • Didelot, X., Fraser, C., Gardy, J., & Colijn, C. (2017). Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks. Molecular Biology and Evolution, msw075. https://doi.org/10.1093/molbev/msw275
  • Fyson, N., Kim, M. K., Lun, D. S., & Colijn, C. (2017). Gene-centric constraint of metabolic models [Preprint]. Biochemistry. https://doi.org/10.1101/116558
  • Fyson, N., King, J., Belcher, T., Preston, A., & Colijn, C. (2017). A curated genome-scale metabolic model of Bordetella pertussis metabolism. Plos Computational Biology, 13(7), e1005639.
  • Grandjean, L., Gilman, R. H., Iwamoto, T., Köser, C. U., Coronel, J., Zimic, M., Török, M. E., Ayabina, D., Kendall, M., Fraser, C., Harris, S., Parkhill, J., Peacock, S. J., Moore, D. A. J., & Colijn, C. (2017). Convergent evolution and topologically disruptive polymorphisms among multidrug-resistant tuberculosis in Peru. PLoS ONE, 12(12), e0189838. https://doi.org/10.1371/journal.pone.0189838
  • Jombart, T., Kendall, M., Almagro‐Garcia, J., & Colijn, C. (2017). treespace: Statistical exploration of landscapes of phylogenetic trees. Molecular Ecology Resources, 17(6), 1385–1392. https://doi.org/10.1111/1755-0998.12676
  • Klinkenberg, D., Backer, J. A., Didelot, X., Colijn, C., & Wallinga, J. (2017). Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks. PLoS Computational Biology, 13(5), e1005495. https://doi.org/10.1371/journal.pcbi.1005495
  • Ratmann, O., Hodcroft, E. B., Pickles, M., Cori, A., Hall, M., Lycett, S., Colijn, C., Dearlove, B., Didelot, X., Frost, S., Hossain, A. S. M. M., Joy, J. B., Kendall, M., Kühnert, D., Leventhal, G. E., Liang, R., Plazzotta, G., Poon, A. F. Y., Rasmussen, D. A., … on behalf of the PANGEA-HIV Consortium. (2017). Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison. Molecular Biology and Evolution, 34(1), 185–203. https://doi.org/10.1093/molbev/msw217
  • Ratmann, O., Wymant, C., Colijn, C., Danaviah, S., Essex, M., Frost, S., Gall, A., Gaseitsiwe, S., Grabowski, M. K., Gray, R., Guindon, S., Von Haeseler, A., Kaleebu, P., Kendall, M., Kozlov, A., Manasa, J., Minh, B. Q., Moyo, S., Novitsky, V., … On Behalf Of The Pangea-Hiv Consort. (2017). HIV-1 Full-Genome Phylogenetics of Generalized Epidemics in Sub-Saharan Africa: Impact of Missing Nucleotide Characters in Next-Generation Sequences. AIDS Research and Human Retroviruses, 33(11), 1083–1098. https://doi.org/10.1089/aid.2017.0061
  • Plazzotta, G., & Colijn, C. (2017). Phylodynamics without trees: estimating R0 directly from pathogen sequences [Preprint]. bioRxiv. 102061. doi:10.1101/1020612017


  • Aanensen, D. M., Feil, E. J., Holden, M. T. G., Dordel, J., Yeats, C. A., Fedosejev, A., Goater, R., Castillo-Ramírez, S., Corander, J., Colijn, C., Chlebowicz, M. A., Schouls, L., Heck, M., Pluister, G., Ruimy, R., Kahlmeter, G., Åhman, J., Matuschek, E., Friedrich, A. W., … Kearns, A. (2016). Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: A Population Snapshot of Invasive Staphylococcus aureus in Europe. American Society for Microbiology, 7(3), e00444-16.
  • Ayabina, D., Hendon-Dunn, C., Bacon, J., & Colijn, C. (2016). Diverse drug-resistant subpopulations of Mycobacterium tuberculosis are sustained in continuous culture. Journal of The Royal Society Interface, 13(124), 20160745. https://doi.org/10.1098/rsif.2016.0745
  • Chindelevitch, L., Colijn, C., Moodley, P., Wilson, D., & Cohen, T. (2016). ClassTR: Classifying Within-Host Heterogeneity Based on Tandem Repeats with Application to Mycobacterium tuberculosis Infections. PLoS Computational Biology, 12(2), e1004475. https://doi.org/10.1371/journal.pcbi.1004475
  • Colijn, C., & Cohen, T. (2016). Whole-genome sequencing of Mycobacterium tuberculosis for rapid diagnostics and beyond. The Lancet Respiratory Medicine, 4(1), 6–8. https://doi.org/10.1016/S2213-2600(15)00510-X
  • Hatherell, H. A., Colijn, C., Stagg, H. R., Jackson, C., Winter, J. R., & Abubakar, I. (2016). Interpreting whole genome sequencing for investigating tuberculosis transmission: A systematic review. BMC Medicine, 14(1), 21. https://doi.org/10.1186/s12916-016-0566-x
  • Hatherell, H.A., Didelot, X., Pollock, S. L., Tang, P., Crisan, A., Johnston, J. C., Colijn, C., & Gardy, J. L. (2016). Declaring a tuberculosis outbreak over with genomic epidemiology. Microbial Genomics, 2(5). https://doi.org/10.1099/mgen.0.000060
  • Kendall, M., & Colijn, C. (2016). Mapping Phylogenetic Trees to Reveal Distinct Patterns of Evolution. Molecular Biology and Evolution, 33(10), 2735–2743. https://doi.org/10.1093/molbev/msw124
  • Klinkenberg, D., Backer, J., Didelot, X., Colijn, C., & Wallinga, J. (2016). New method to reconstruct phylogenetic and transmission trees with sequence data from infectious disease outbreaks [Preprint]. Epidemiology. https://doi.org/10.1101/069195
  • Plazzotta, G., & Colijn, C. (2016). Asymptotic frequency of shapes in supercritical branching trees. Journal of Applied Probability, 53(4), 1143–1155. https://doi.org/10.1017/jpr.2016.70
  • Plazzotta, G., Kwan, C., Boyd, M., & Colijn, C. (2016). Effects of memory on the shapes of simple outbreak trees. Scientific Reports, 6(1), 21159. https://doi.org/10.1038/srep21159
  • Sartelli, M., Weber, D. G., Ruppé, E., Bassetti, M., Wright, B. J., Ansaloni, L., Catena, F., Coccolini, F., Abu-Zidan, F. M., Coimbra, R., Moore, E. E., Moore, F. A., Maier, R. V., De Waele, J. J., Kirkpatrick, A. W., Griffiths, E. A., Eckmann, C., Brink, A. J., Mazuski, J. E., … Viale, P. (2016). Antimicrobials: A global alliance for optimizing their rational use in intra-abdominal infections (AGORA). World Journal of Emergency Surgery : WJES, 11(1), 33. https://doi.org/10.1186/s13017-016-0089-y


  • Colijn, C., & Cohen, T. (2015). How competition governs whether moderate or aggressive treatment minimizes antibiotic resistance. eLife, 4, e10559. https://doi.org/10.7554/eLife.10559
  • Crisan, A., Wong, H. Y., Johnston, J. C., Tang, P., Colijn, C., Otterstatter, M., Hiscoe, L., Parker, R., Pollock, S. L., & Gardy, J. L. (2015). Spatio-temporal analysis of tuberculous infection risk among clients of a homeless shelter during an outbreak. The International Journal of Tuberculosis and Lung Disease : The Official Journal of the International Union against Tuberculosis and Lung Disease, 19(9), 1033–1038. https://doi.org/10.5588/ijtld.14.0957
  • Knight, G. M., Colijn, C., Shrestha, S., Fofana, M., Cobelens, F., White, R. G., Dowdy, D. W., & Cohen, T. (2015). The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis. Clin Infect Dis., 61(suppl 3), S147–S154. https://doi.org/10.1093/cid/civ579
  • Kunkel, A., Colijn, C., Lipsitch, M., & Cohen, T. (2015). How could preventive therapy affect the prevalence of drug resistance? Causes and consequences. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1670), 20140306. https://doi.org/10.1098/rstb.2014.0306
  • Nicoli, E. J., Ayabina, D., Trotter, C. L., Turner, K. M. E., & Colijn, C. (2015). Competition, coinfection and strain replacement in models of Bordetella pertussis. Theoretical Population Biology, 103, 84–92. https://doi.org/10.1016/j.tpb.2015.05.003
  • Plazzotta, G., Cohen, T., & Colijn, C. (2015). Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection. Journal of Theoretical Biology, 368, 67–73. https://doi.org/10.1016/j.jtbi.2014.12.009
  • Kendall, M., & Colijn, C. (2015). A tree metric using structure and length to capture distinct phylogenetic signals. arXiv:1507.05211v3 [q-bio.PE].


  • Didelot, X., Gardy, J., & Colijn, C. (2014). Bayesian Inference of Infectious Disease Transmission from Whole-Genome Sequence Data. Molecular Biology and Evolution, 31(7), 1869–1879. https://doi.org/10.1093/molbev/msu121
  • Farhat, M. R., Shapiro, B. J., Sheppard, S. K., Colijn, C., & Murray, M. (2014). A phylogeny-based sampling strategy and power calculator informs genome-wide associations study design for microbial pathogens. Genome Medicine, 6(11), 101. https://doi.org/10.1186/s13073-014-0101-7
  • Jombart, T., Aanensen, D. M., Baguelin, M., Birrell, P., Cauchemez, S., Camacho, A., Colijn, C., Collins, C., Cori, A., Didelot, X., Fraser, C., Frost, S., Hens, N., Hugues, J., Höhle, M., Opatowski, L., Rambaut, A., Ratmann, O., Soubeyrand, S., … Ferguson, N. (2014). OutbreakTools: A new platform for disease outbreak analysis using the R software. Epidemics, 7, 28–34. https://doi.org/10.1016/j.epidem.2014.04.003
  • Mills, H. L., Johnson, S., Hickman, M., Jones, N. S., & Colijn, C. (2014). Errors in reported degrees and respondent driven sampling: Implications for bias. Drug and Alcohol Dependence, 142, 120–126. https://doi.org/10.1016/j.drugalcdep.2014.06.015
  • Colijn, C., & Gardy, J. (2014). Phylogenetic tree shapes resolve disease transmission patterns. Evol Med Public Health, 2014(1), 96–108. doi:10.1093/emph/eou018
  • Aanensen, D.M., Baguelin, M., Birrell, P., Cauchemez, S., Camacho, A., Colijn, C., et al. (2014). OutbreakTools: a new platform for disease outbreak analysis using the R software. Epidemics, 7, 28-34. doi:10.1016/j.epidem.2014.04.003


  • Mills, H. L., Cohen, T., & Colijn, C. (2013). Community-wide isoniazid preventive therapy drives drug-resistant tuberculosis: A model-based analysis. Science Translational Medicine, 5(180), 180ra49. https://doi.org/10.1126/scitranslmed.3005260
  • Mills, H. L., Ganesh, A., & Colijn, C. (2013). Pathogen spread on coupled networks: Effect of host and network properties on transmission thresholds. Journal of Theoretical Biology, 320, 47–57. https://doi.org/10.1016/j.jtbi.2012.12.006
  • Mills, H. L., White, E., Colijn, C., Vickerman, P., & Heimer, R. (2013). HIV transmission from drug injectors to partners who do not inject, and beyond: Modelling the potential for a generalized heterosexual epidemic in St. Petersburg, Russia. Drug and Alcohol Dependence, 133(1), 242–247. https://doi.org/10.1016/j.drugalcdep.2013.04.028
  • Nicoli, E. J., Trotter, C. L., Turner, K. M. E., Colijn, C., Waight, P., & Miller, E. (2013). Influenza and RSV make a modest contribution to invasive pneumococcal disease incidence in the UK. Journal of Infection, 66(6), 512–520. https://doi.org/10.1016/j.jinf.2013.02.007
  • Robinson, K., Fyson, N., Cohen, T., Fraser, C., & Colijn, C. (2013). How the Dynamics and Structure of Sexual Contact Networks Shape Pathogen Phylogenies. PLoS Computational Biology, 9(6), e1003105. https://doi.org/10.1371/journal.pcbi.1003105


  • Brandes, A., Lun, D. S., Ip, K., Zucker, J., Colijn, C., Weiner, B., & Galagan, J. E. (2012). Inferring Carbon Sources from Gene Expression Profiles Using Metabolic Flux Models. PLoS ONE, 7(5), e36947. https://doi.org/10.1371/journal.pone.0036947
  • Cohen, T., Van Helden, P. D., Wilson, D., Colijn, C., McLaughlin, M. M., Abubakar, I., & Warren, R. M. (2012). Mixed-Strain Mycobacterium tuberculosis Infections and the Implications for Tuberculosis Treatment and Control. Clinical Microbiology Reviews, 25(4), 708–719. https://doi.org/10.1128/CMR.00021-12
  • Irving, T. J., Blyuss, K. B., Colijn, C., & Trotter, C. L. (2012). Modelling meningococcal meningitis in the African meningitis belt. Epidemiology and Infection, 140(5), 897–905. https://doi.org/10.1017/S0950268811001385
  • Mills, H. L., Colijn, C., Vickerman, P., Leslie, D., Hope, V., & Hickman, M. (2012). Respondent driven sampling and community structure in a population of injecting drug users, Bristol, UK. Drug and Alcohol Dependence, 126(3), 324–332. https://doi.org/10.1016/j.drugalcdep.2012.05.036
  • Robinson, K., Cohen, T., & Colijn, C. (2012). The dynamics of sexual contact networks: Effects on disease spread and control. Theoretical Population Biology, 81(2), 89–96. https://doi.org/10.1016/j.tpb.2011.12.009
  • Sergeev, R., Colijn, C., Murray, M., & Cohen, T. (2012). Modeling the Dynamic Relationship Between HIV and the Risk of Drug-Resistant Tuberculosis. Science Translational Medicine, 4(135), 135ra67. https://doi.org/10.1126/scitranslmed.3003815


  • Colijn, C., Cohen, T., Ganesh, A., & Murray, M. (2011). Spontaneous Emergence of Multiple Drug Resistance in Tuberculosis before and during Therapy. PLoS ONE, 6(3), e18327. https://doi.org/10.1371/journal.pone.0018327
  • Ip, K., Colijn, C., & Lun, D. S. (2011). Analysis of complex metabolic behavior through pathway decomposition. BMC Systems Biology, 5(1), 91. https://doi.org/10.1186/1752-0509-5-91
  • Mills, H. L., Cohen, T., & Colijn, C. (2011). Modelling the performance of isoniazid preventive therapy for reducing tuberculosis in HIV endemic settings: The effects of network structure. Journal of The Royal Society Interface, 8(63), 1510–1520. https://doi.org/10.1098/rsif.2011.0160
  • Sergeev, R., Colijn, C., & Cohen, T. (2011). Models to understand the population-level impact of mixed strain M. tuberculosis infections. Journal of Theoretical Biology, 280(1), 88–100. https://doi.org/10.1016/j.jtbi.2011.04.011


  • Colijn, C., Cohen, T., Fraser, C., Hanage, W., Goldstein, E., Givon-Lavi, N., Dagan, R., & Lipsitch, M. (2010). What is the mechanism for persistent coexistence of drug-susceptible and drug-resistant strains of Streptococcus pneumoniae ? Journal of The Royal Society Interface, 7(47), 905–919. https://doi.org/10.1098/rsif.2009.0400


  • Cohen, T., Colijn, C., Wright, A., Zignol, M., Pym, A., & Murray, M. (2009). Does Current Drug Resistance Surveillance Provide Useful Information in Tuberculosis? American Journal of Respiratory and Critical Care Medicine, 179(1), 82–83. https://doi.org/10.1164/ajrccm.179.1.82a
  • Cohen, T., Dye, C., Colijn, C., Williams, B., & Murray, M. (2009). Mathematical models of the epidemiology and control of drug-resistant TB. Expert Review of Respiratory Medicine, 3(1), 67–79. https://doi.org/10.1586/17476348.3.1.67
  • Colijn, C. (2009). Propagation through dynamic networks: Degree distribution and the spread of disease. 2009 IEEE Information Theory Workshop, 594–598. https://doi.org/10.1109/ITW.2009.5351503
  • Colijn, C., Brandes, A., Zucker, J., Lun, D. S., Weiner, B., Farhat, M. R., Cheng, T.-Y., Moody, D. B., Murray, M., & Galagan, J. E. (2009). Interpreting Expression Data with Metabolic Flux Models: Predicting Mycobacterium tuberculosis Mycolic Acid Production. PLoS Computational Biology, 5(8), e1000489. https://doi.org/10.1371/journal.pcbi.1000489
  • Colijn, C., Cohen, T., & Murray, M. (2009). Latent Coinfection and the Maintenance of Strain Diversity. Bulletin of Mathematical Biology, 71(1), 247–263. https://doi.org/10.1007/s11538-008-9361-y
  • Lipsitch, M., Colijn, C., Cohen, T., Hanage, W. P., & Fraser, C. (2009). No coexistence for free: Neutral null models for multistrain pathogens. Epidemics, 1(1), 2–13. https://doi.org/10.1016/j.epidem.2008.07.001 Cohen T, Colijn C, Wright A, Zignol M, Pym A, Murray M. (2009). Reply-Does Current Drug Resistance Surveillance Provide Useful Information in Tuberculosis?. American Journal of Respiratory and Critical Care Medicine, 179(1), 80.


  • Cohen, T., Colijn, C., Finklea, B., Wright, A., Zignol, M., Pym, A., & Murray, M. (2008). Are survey-based estimates of the burden of drug resistant TB too low? Insight from a simulation study. PLoS One, 3(6), e2363.
  • Cohen, T., Colijn, C., & Murray, M. (2008). Mathematical Modeling of Tuberculosis Transmission Dynamics. In S. H. E. Kaufmann, E. Rubin, W. J. Britton, & P. Helden (Eds.), Handbook of Tuberculosis (1st ed., pp. 227–243). Wiley. https://doi.org/10.1002/9783527611614.ch44
  • Cohen, T., Colijn, C., & Murray, M. (2008). Modeling the effects of strain diversity and mechanisms of strain competition on the potential performance of new tuberculosis vaccines. Proceedings of the National Academy of Sciences of the United States of America, 105(42), 16302–16307. https://doi.org/10.1073/pnas.0808746105
  • Cohen, T., Colijn, C., Wright, A., Zignol, M., Pym, A., & Murray, M. (2008). Challenges in Estimating the Total Burden of Drug-resistant Tuberculosis. American Journal of Respiratory and Critical Care Medicine, 177(12), 1302–1306. https://doi.org/10.1164/rccm.200801-175PP
  • Lin, H.-H., Murray, M., Cohen, T., Colijn, C., & Ezzati, M. (2008). Effects of smoking and solid-fuel use on COPD, lung cancer, and tuberculosis in China: A time-based, multiple risk factor, modelling study. The Lancet, 372(9648), 1473–1483. https://doi.org/10.1016/S0140-6736(08)61345-8
  • Yang, G.H., Zhong, N.S., Lin, H.H., Murray, M., Cohen, T., Colijn, C., & Ezzati, M. (2008). Effects of smoking and solid-fuel use on COPD, lung cancer, and tuberculosis in China: A time-based, multiple risk factor, modelling study. Commentary. Lancet, London, 372(9648), 445–1446, 1473-1483 [13 p.].


  • Cohen, T., Colijn, C., Finklea, B., & Murray, M. (2007). Exogenous re-infection and the dynamics of tuberculosis epidemics: Local effects in a network model of transmission. Journal of The Royal Society Interface, 4(14), 523–531. https://doi.org/10.1098/rsif.2006.0193
  • Colijn, C., Cohen, T., & Murray, M. (2007). Emergent heterogeneity in declining tuberculosis epidemics. Journal of Theoretical Biology, 247(4), 765–774. https://doi.org/10.1016/j.jtbi.2007.04.015
  • Colijn, C., Cohen, T., & Murray, M. (2007). Mathematical Models of Tuberculosis: Accomplishments and future challenges. BIOMAT 2006, 123–148. https://doi.org/10.1142/9789812708779_0008
  • Colijn, C., Foley, C., & Mackey, M. C. (2007). G-CSF treatment of canine cyclical neutropenia: A comprehensive mathematical model. Experimental Hematology, 35(6), 898–907. https://doi.org/10.1016/j.exphem.2007.02.015
  • Colijn, C., & Mackey, M. C. (2007). Bifurcation and Bistability in a Model of Hematopoietic Regulation. Siam Journal On Applied Dynamical Systems, 6(2), 378–394. https://doi.org/10.1137/050640072


  • Colijn, C., Dale, D. C., Foley, C., & Mackey, M. C. (2006). Observations on the Pathophysiology and Mechanisms for Cyclic Neutropenia. Mathematical Modelling of Natural Phenomena, 1(2), 45–69. https://doi.org/10.1051/mmnp:2008004
  • Colijn, C., Fowler, A. C., & Mackey, M. C. (2006). High frequency spikes in long period blood cell oscillations. Journal of Mathematical Biology, 53(4), 499–519. https://doi.org/10.1007/s00285-006-0027-9




  • Colijn, C. (2003). The de Broglie-Bohm Causal Interpretation of Quantum Mechanics and its Application to some Simple Systems [Phd]. University of Waterloo.
  • Colijn, C., & Vrscay, E. R. (2003). Erratum to: “Spin-dependent Bohm trajectories for hydrogen eigenstates”. Physics Letters A, 316(6), 424. https://doi.org/10.1016/S0375-9601(03)01032-6
  • Colijn, C., & Vrscay, E. R. (2003). Spin-dependent Bohm trajectories associated with an electronic transition in hydrogen. Journal of Physics A: Mathematical and General, 36(16), 4689–4702. https://doi.org/10.1088/0305-4470/36/16/317
  • Colijn, C., & Vrscay, E. R. (2003). Spin-Dependent Bohm Trajectories for Pauli and Dirac Eigenstates of Hydrogen. Foundations of Physics Letters, 16(4), 303–323. https://doi.org/10.1023/A:1025344924499



  • Colijn, C. (1999). Addressing Complexity: Exploring Social Change Through Chaos and Complexity Theory. York University.