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Modeling Virus Transmission & Evolution in Mixed Communities MODELING VIRUS TRANSMISSION & EVOLUTION IN MIXED COMMUNITIES MODELING VIRUS TRANSMISSION & EVOLUTION IN MIXED COMMUNITIES By MORGAN P. KAIN, B.S.,M.S. A Thesis Submitted to the School of Graduate Studies in Partial Fulfilment of the Requirements for the Degree Doctor of Philosophy McMaster University © Copyright by Morgan P. Kain, April 2019 PhD Thesis — Morgan P. Kain McMaster University — Biology McMaster University DOCTOR OF PHILOSOPHY (2019) Hamilton, Ontario (Biol- ogy) TITLE: Modeling virus transmission & evolution in mixed communities AUTHOR: Morgan P. Kain, B.S. (University of Pittsburgh), M.S. (East Carolina University) SUPERVISOR: Professor Benjamin M. Bolker NUMBER OF PAGES: ix, Main Text 134, Appendix 227. ii PhD Thesis — Morgan P. Kain McMaster University — Biology Lay Abstract In their work in the late 1970s and early 1980s, Anderson and May demonstrated that pathogen induced host harm and pathogen transmission ability are intimately linked. This work clearly showed that pathogens maximize their reproductive potential by causing some harm their hosts, contrary to the established belief that pathogens shouldn’t harm their hosts at all. I extend this work to study pathogen evolution and transmission in heterogeneous host populations, using two model host-pathogen systems: birds infected with West Nile virus, and European rabbits infected with the myxoma virus, as well as a general model for the evolution of poorly adapted pathogens in small host populations. I show that pathogen transmission in heterogeneous host populations can be estimated using citizen science data, that pathogen transmission is lower in heterogeneous populations, and that pathogens invading naive host populations may experience short-term evolution to higher-than-optimal virulence, increasing infection burden. iii PhD Thesis — Morgan P. Kain McMaster University — Biology Abstract In the early 1980s Anderson and May showed that parasite virulence (host mortality rate when infected) and parasite transmission are positively correlated because of their joint dependence on host exploitation (e.g. replication rate). This correlation often results in maximum parasite fitness at intermediate virulence, which has important implications for both parasite evolution and transmission. Anderson and May’s observation has led to nearly four decades of work on the ecology and evolution of host-parasite interactions, which focuses on making either general predictions for a range of simplified host-parasite systems or detailed predictions for a single host-parasite system. Yet, despite decades of research, we know comparatively little about parasite evolution and transmission in heterogeneous and/or small host populations. Additionally, much previous work has distanced itself from empirical data, either by outpacing the collection of data or under-utilizing available data. My work focuses on the evolution and transmission of parasites in heterogeneous host populations; I rely on tradeoff theory, but adopt a case-study approach to maximize the use of empirical data. Using West Nile virus infections of birds I show that a continent-wide strain displacement event cannot be explained by current data (Chapter 2), and that transmission in heterogeneous host communities can be estimated using data from citizen scientists, laboratory experiments, and phylogenetic comparative analysis (Chapter 3). Using Myxoma virus infection of European rabbits, I show that tradeoff theory can help us to understand parasite evolution in host populations with heterogeneous secondary infection burden (Chapter 4). In Chapter 5 I show that poorly evolved parasites invading new host populations experience transient evolution away from optimal virulence. In addition to my biological focus, I emphasize clarity and rigor in statistical analyses, including the importance of appropriate uncertainty propagation, as well as reproducible science. iv PhD Thesis — Morgan P. Kain McMaster University — Biology Acknowledgements First and foremost I would like to thank my supervisor Ben Bolker for his support throughout my journey. Thank you for your patience as I entered a new field of study and first attempted to cobble together epidemiological models. Your continued enthusiasm helped to keep me excited about my work and to push through what I found to be the doldrums of model exploration in the absence of any data. I thank my committee member Jonathan Dushoff for his deep insight and for helping me through small roadblocks on nearly a weekly basis. I also thank my committee member Ian Dworkin for a perspective outside of my subfield, which helped me to relay my science to a broader audience. I thank my advisor Ben Bolker and both of my committee members for feedback on each of my thesis chapters, as well as my external examiner for comments and feedback on the complete thesis. I would also like to thank Jonathan Dushoff and Evan Twomey for inviting me to collaborate on exciting side projects, and my advisor Ben Bolker, my committee members, and the members of the Bolker, Dushoff, Earn, and Kolasa labs for broader scientific discussions. Thank you for sharing both your depth and breadth of knowledge. It is hard to imagine leaving a PhD program with exposure to a greater breadth of scientific ideas than I was exposed to here. Finally, I would not have been able to complete this thesis without the love and support of my family and Jo Werba. Thank you for keeping me sane! v PhD Thesis — Morgan P. Kain McMaster University — Biology Contents 1 Introduction ................................... 1 2 Can existing data on West Nile virus infection in birds and mosquitos explain strain replacement? ......................... 11 3 Predicting West Nile virus transmission in North American bird communities using phylogenetic mixed effects models and eBird citizen science data .............................. 30 4 The evolutionary response of virulence to host heterogeneity: a general model with application to myxomatosis in rabbits co-infected with intestinal helminths ........................... 77 5 The evolution of parasites constrained by a virulence-transmission tradeoff and compensatory virulence factor “tuning” .........100 6 Concluding Remarks ............................. 127 Appendix A: Additional figures for Chapter 2 ...............135 Appendix B: Citation information for the data used in Chapter 2 ... 161 Appendix C: Additional methods and results for Chapter 3 .......183 Appendix D: Details on code used in Chapter 3 ..............202 Appendix E: A general model exploration for Chapter 4 .........204 Appendix F: Additional results for Chapter 5 ...............220 vi PhD Thesis — Morgan P. Kain McMaster University — Biology List of Figures and Tables Chapter 2 Figure 1: WNV life cycle . .14 Figure 2: Bird titer profiles . 20 Figure 3: Bird survival . 21 Figure 4: Bird-to-mosquito transmission probability . 21 Figure 5: Mosquito-to-bird transmission probability . 22 Figure 6: WNV R0 .............................................................23 Table 1: Parameters from the literature . 17 Table 2: Ratio of NY99 R0 to WN02 R0 ........................................22 Table 3: WNV R0 estimates . 25 Chapter 3 Figure 1: WNV R0 estimates between months and among Texas counties . .53 Figure 2: Spatio-temporal GAM model parameter estimates . 54 Figure 3: Keystone species . 56 Table 1: Sub-model details for our multi-faceted ecological model for WNV R0 . 37 Table 2: Details about each source of uncertainty . .50 Table 3: Capability of simplified models to estimate WNV R0 in Texas . 52 Chapter 4 Figure 1: Parasite virulence-transmission tradeoff curves . 82 Figure 2: MYXV virulence evolution model schematic . 84 Figure 3: MYXV ESS relative virulence . 89 Figure 4: MYXV virulence in Scotland and Australia . .90 Chapter 5 Figure 1: Parasite evolution with efficiency scale = 30 . .111 Figure 2: Parasite evolution with efficiency scale = 10 . .112 Figure 3: Parasite evolution with efficiency scale = 50 . .113 Figure 4: Discrete time stochastic simulation results . .116 Figure 5: Parasite virulence evolution in stochastic and deterministic models . 117 Table 1: Parameter values used in all simulations . 109 Table 2: Discrete time stochastic simulation results . .115 vii PhD Thesis — Morgan P. Kain McMaster University — Biology List of Abbreviations and Symbols α Parasite virulence β Parasite transmission rate R0 Parasite intrinsic reproductive number AD Adaptive Dynamics BBS Breeding Bird Survey CBC Christmas Bird Count DTS Discrete Time Stochastic eBird Cornell Laboratory of Ornithology citizen science database ESS Evolutionary Stable Strategy GAM Generalized Additive Model GLMM Generalized Linear Mixed Effects Model LMM Linear Mixed Effects Model MYXV Myxoma virus NEON National Ecological Observation Network NY02 Lineage I strain of West Nile virus isolated in 1999 in North America RD Reaction Diffusion USA United States of America WN02 Lineage I strain of West Nile virus isolated in 2002 in North America WNV West Nile virus viii PhD Thesis — Morgan P. Kain McMaster University — Biology Declaration of Academic Achievement This sandwich thesis contains an introduction (Chapter 1), two published works (Chapter 2, Chapter 4), a manuscript in a third round of review (Chapter 3), a draft of a manuscript in the early stages of preparation for publication (Chapter 5), and a conclusion (Chapter 6). Preambles to Chapters 2-5 describe authors’ and committee members’ contributions. Chapters 1 and 6 were written by me. ix PhD Thesis — Morgan P. Kain McMaster
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