{"references": ["A spatial model of the efficiency of T cell search in the influenza-infected lung L Drew, F Stephanie, B Soumya, C Candice, C Judy, M Melanie. Journal of Theoretical Biology 398 (7), 52-63", "Banerjee, S., Guedj, J., Ribeiro, R. M., Moses, M., & Perelson, A. S. 2016. Estimating biologically relevant parameters under uncertainty for experimental within-host murine West Nile virus infection. Journal of the Royal Society Interface, 13(117), 20160130-.http://doi.org/10.1098/rsif.2016.0130", "Science and technology consortia in US biomedical research: A paradigm shift in response to unsustainable academic growth TWC Curt Balch, Hugo Arias-Pulido, Soumya Banerjee, Alex K. Lancaster. BioEssays 37 (2), 119-122", "Soumya Banerjee and Joshua Hecker. A Multi-Agent System Approach to Load-Balancing and Resource Allocation for Distributed Computing, arXiv preprint arXiv:1509.06420, 2015", "Soumya Banerjee and Melanie Moses. Immune System Inspired Strategies for Distributed Systems. arXiv preprint arXiv:1008.2799, 2010", "Soumya Banerjee and Melanie Moses. Scale Invariance of Immune System Response Rates and Times: Perspectives on Immune System Architecture and Implications for Artificial Immune Systems. Swarm Intelligence 4, 301\u2013318 (2010). URL http://www.springerlink.com/content/w67714j72448633l/", "Soumya Banerjee, A Roadmap for a Computational Theory of the Value of Information in Origin of Life Questions, Interdisciplinary Description of Complex Systems, 2016", "Soumya Banerjee, Jeremie Guedj, Ruy Ribeiro, Melanie Moses, Alan Perelson (2016). Estimating biologically relevant parameters under uncertainty for experimental within-host murine West Nile virus infection. Journal of the Royal Society Interface, 13(117), 20160130-. http://doi.org/10.1098/rsif.2016.0130", "Soumya Banerjee. 2009. An Immune System Inspired Approach to Automated Program Verification, arXiv preprint arXiv:0905.2649, 2009", "Soumya Banerjee. 2013. Scaling in the immune system, PhD Thesis, University of New Mexico (2013) Soumya Banerjee. A Biologically Inspired Model of Distributed Online Communication Supporting Efficient Search and Diffusion of Innovation. Interdisciplinary Description of Complex Systems 14 (1), 10-22", "Soumya Banerjee. A computational technique to estimate within-host productively infected cell lifetimes in emerging viral infections. PeerJ Preprints 4 (e2621v2) 2017", "Soumya Banerjee. An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing. PeerJ Preprints 5 (e2690v1) 2017", "Soumya Banerjee. An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing. PeerJ Preprints 5 (e2690v1) 2017", "Soumya Banerjee. An Immune System Inspired Theory for Crime and Violence in Cities. Interdisciplinary Description of Complex Systems, 15(2):133-143, 2017", "Soumya Banerjee. Analysis of a Planetary Scale Scientific Collaboration Dataset Reveals Novel Patterns. arXiv preprint arXiv:1509.07313, 2015", "Soumya Banerjee. Optimal strategies for virus propagation. arXiv preprint arXiv:1512.00844, 2015"]}

How different is the immune system in a human from that of a mouse? Do pathogens replicate at the same rate in different species? Answers to these questions have impact on human health since multi-host pathogens that jump from animals to humans affect millions worldwide. It is not known how rates of immune response and viral dynamics vary from species to species and how they depend on species body size. Metabolic scaling theory predicts that intracellular processes will be slower in larger animals since cellular metabolic rates are slower. We test how rates of pathogenesis and immune system response rates depend on species body size. We hypothesize that immune response rates are invariant with body size. Our work suggests how the physical architecture of the immune system and chemical signals within it may lead to nearly scale-invariant immune search and response. We fit mathematical models to experimental West Nile Virus (WNV, a multi-host pathogen) infection data and investigate how model parameters characterizing the pathogen and the immune response change with respect to animal mass. Phylogeny also affects pathogenesis and immune response. We use a hierarchical Bayesian model, that incorporates phylogeny, to test hypotheses about the role of mass and phylogeny on pathogen replication and immune response. We observe that: 1. Hierarchical models (informed by phylogeny) make more accurate predictions of experimental data and more realistic estimates of biologically relevant parameters characterizing WNV infection. 2. Rates of WNV production decline with species body mass, modified by a phylogenetic influence. Our work is the first to systematically explore the role of host body mass in pathogenesis using mathematical models and empirical data. We investigate the complex interplay between the physical structure of the immune system and host body mass in determining immune response. The modeling strategies and tools outlined here are likely to be applicable to modeling of other multi-host pathogens. This work could also be extended to understand how drug and vaccine efficacy in humans may systematically differ from that in model organisms like mice, in which most initial experimental studies are conducted.