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Dr. Kim Pepin

Contact information
Title: Quantitative Research Biologist
Address: 4101 Laporte Avenue, Fort Collins CO  80521-2154
Telephone: 970-266-6162
Fax: 970-266-6063

PhD, University of Idaho “Mechanisms of viral adaptation”, 2006 
BSc, University of British Columbia, Ecology, 1998

Areas of Expertise
Quantitative biology, Ecology, Evolutionary Biology, Disease dynamics, wildlife-livestock interface

Department of Biology, Colorado State University

International Experience  
China (avian influenza) 
Brazil (dengue fever)

Current Research
  • Science-based modeling tools for decision making in wildlife management
  • Quantitative tools for risk assessment of wildlife and disease management
  • Methods for analyzing surveillance data and predicting geographic spread of invasive species and diseases
  • Role of social dynamics, contact structure and movement in disease transmission and efficacy of wildlife management
  • Wildlife disease surveillance design
Dr. Pepin is a quantitative ecologist that develops models for assisting the implementation of wildlife management and disease surveillance/control strategies. The quantitative approaches used involves parameter estimation from data, prediction from statistical models, and mechanistic dynamical models developed from field data.

One primary research avenue Dr. Pepin pursues is to develop quantitative tools for guiding decision making in wildlife management – especially for controlling feral swine. Monitoring is important for most wildlife management programs but can be difficult to conduct well because resources are often prioritized for control rather than monitoring. Thus, she aims to develop methods and user-friendly tools for inferring management efficacy based on management data that are readily collected, and to identify strategies for collecting monitoring data which impose low burden on managers. She focuses on problems such as inferring population density or damage before and after management and determining when management goals have been achieved so that resource allocation can be optimized in space and time. Dr. Pepin also conducts studies to identify and understand key ecological processes that are essential for planning science-based management solutions and identifying the best targets for management.

Understanding and predicting disease dynamics in wildlife is challenging because demographic and ecological data are often sparse and disease signatures can be difficult to find. A second major focus of her research is to quantify processes that are important in wildlife disease transmission, such as contact structure and movement. She aims to understand the role of these processes in disease risk in wildlife populations at the wildlife-livestock interface and determine their effects on efficacy of interventions. This knowledge is applied to developing tools for predicting geographic spread of disease (and similar process such as species invasions), informing optimal resource allocation, designing surveillance systems, and determining effective control strategies. Dr. Pepin also develops improved methods for assessing disease risk in wildlife populations by accounting for disease-dynamic mechanisms and wildlife-specific ecology. Currently, she’s particularly interested in avian influenza, carnivore rabies, and important diseases of swine such as African swine fever.

Recent Publications

Davis, A.J., R. McCreary, J. Psiropoulos, G. Brennan, T. Cox, A. Partin, and K.M. Pepin. 2017. Quantifying site-level usage and certainty of absence for an invasive species through occupancy analysis of camera-trap data. Biological Invasions 20:877-890. doi: 10.1007/s10530-017-1579-x

VerCauteren, K., A. Daivs, and K. Pepin. 2018. Phase 2 Wildlife Management - Addressing invasive and overabundant Wildlife: The white-tailed deer continuum and invasive wild pig example. In: Proceedings of the 17th Wildlife Damage Management Conference 17:23-26.

Davis A.J., B. Leland, M. Bodenchuck, K.C. VerCauteren, and K.M. Pepin. 2017. Estimating population density for disease risk assessment: The importance of understanding the area of influence of traps using wild pigs as an example. Preventive Veterinary Medicine 141: 33-37.  doi: 10.1016/j.prevetmed.2017.04.004 

Kay, S.L., J.W. Fischer, A.J. Monaghan, J.C. Beasley, R. Boughton, T.A. Campbell, S.M. Cooper, S.S. Ditchkoff, S.B. Hartley, J.C. Kilgo, S.M. Wisely, A.C. Wyckoff, K.C. VerCauteren, and K.M. Pepin. 2017. Quantifying drivers of wild pig movement across multiple spatial and temporal scales.   Movement Ecology 5(1):14.  doi: 10.1186/s40462-017-0105-1

Keiter, D.A., A.J. Davis, O.E. Rhodes Jr., F.L. Cunningham, J.C. Kilgo, K.M. Pepin, and J.C. Beasley. 2017. Effects of scale of movement, detection probability, and true population density on common methods of estimating population density. Scientific Reports 7(1):9446. doi: 10.1038/s41598-017-09746-5 

Pepin, K.M., A.J. Davis, D.G. Strecker, J.W. Fischer, K.C. VerCauteren, and A.T. Gilbert. 2017. Predicting spatial spread of rabies in skunk populations using surveillance data reported by the public. PLoS Neglected Tropical Diseases 11(7): e0005822. doi: 10.1371/journal.pntd.0005822

Pepin, K.M., A.J. Davis, F.L. Cunningham, K.C. VerCauteren, and D.C. Eckery. 2017. Potential effects of incorporating fertility control into typical culling regimes in wild pig populations. PLoS ONE 12(8):e0183441. doi: 10.1371/journal.pone.0183441

Pepin, K.M., A.J. Davis, and K.C. VerCauteren. 2017. Efficiency of different spatial and temporal strategies for reducing vertebrate pest populations. Ecological Modeling 365:106-118. doi: 10.1016/j.ecolmodel.2017.10.005

Pepin, K.M., S.L. Kay, and A.J. Davis. 2017. Comment on: Blood does not buy goodwill:  Allowing culling increases poaching of large carnivore. Proceedings of the Royal Society B 284: 20161459.  doi: 10.1098/rspb.2016.1459

Pepin, K.M., S.L. Kay, B.D. Golas, S.S. Shriner, A.T. Gilbert, R.S. Miller, A.L. Graham, S. Riley, P.C. Cross, M.D. Samuel, M.B. Hooten, J.A. Hoeting, J.O. Lloyd-Smith, C.T. Webb, and M.G. Buhnerkempe. 2017.Inferring infection hazard in wildlife populations by linking data across individual and population scales. Ecology Letters.  doi: 10.1111/ele.12732

Pinsent, A., K.M. Pepin, H. Zhu, Y. Guan, M.T. white, and S. Riley. 2017. The persistence of multiple strains of avian influenza in live bird markets. Proceedings of the Royal Society B 284:20170715. doi: 10.1098/rspb.2017.0715   

Davis, A.J., M.B. Hooten, R.S. Miller, M.L. Farnsworth, J. Lewis, M. Moxcey, and K.M. Pepin. 2016. Inferring invasive species abundance using removal data from management actions. Ecological Applications 26(7):2339-2346.  doi: 10.1002/eap.1383 

Lavelle, M.J., S.L. Kay, K.M. Pepin, D.A. Grear, H. Campa III, and K.C. VerCauteren. 2016. Evaluating wildlife-cattle contact rates to improve the understanding of dynamics of bovine tuberculosis transmission in Michigan, USA. Preventive Veterinary Medicine 135:28-36.  doi: 10.1016/j.prevetmed.2016.10.009 

Pepin, K.M., A.J. Davis, J. Beasley, R. Boughton, T. Campbell, S.M. Cooper, W. Gaston, S. Hartley, J.C. Kilgo, S.M. Wisely, C. Wyckoff, and K.C. VerCauteren. 2016. Contact heterogeneities in feral swine: Implications for disease management and future research. Ecosphere 7(3):e01230.  doi: 10.1002/ecs2.1230   

Pepin, K.M. and K.C. VerCauteren. 2016. Disease-emergence dynamics and control in a socially-structured wildlife species. Scientific Reports 6:25150.  doi: 10.1038/srep25150

Walter, K.S., K.M. Pepin, C.T. Webb, H.D. Gaff, P.J. Krause, V.E. Pitzer, and M.A. Diuk-Wasser. 2016. Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes. Proceedings of the Royal Society B:  Biological Sciences 283(1832): 20160834.  doi: 10.1098/rspb.2016.0834     

Lavelle, M.J., C.I.I.I. Henry, K. LeDoux, P.J. Ryan, J.W. Fischer, K.M. Pepin, C.R. Blass, M.P. Glow, S.E. Hygnstrom, and K.C. VerCauteren. 2015. Deer response to exclusion from stored cattle feed in Michigan, USA. Preventive Veterinary Medicine 121(1-2):159-164. doi: 10.1016/j.prevetmed.2015.06.015

Pepin, K.M., C.B. Leach, C. Marques-Toledo, K.H. Laass, K.S. Paixao, A.D. Luis, D.T.S. Hayman, N.G. Johnson, M.G. Buhnerkempe, S. Carver, D.A. Grear, K. Tsao, A.E. Eiras, and C.T. Webb. 2015. Utility of mosquito surveillance data for spatial prioritization of vector control against dengue viruses in three Brazilian cities. Parasites & Vectors 8(98).  doi: 10.1186/s13701-015-0659-y


O'Dea, E.B., K.M. Pepin, B.A. Lopman, and C.O. Wilke. 2014. Fitting outbreak models to data from many small norovirus outbreaks. Epidemics 6:18-29.  doi: 10.1016/j.epidem.2013.12.0

Pepin, K.M., E. Spackman, J.D. Brown, K.L. Pabilonia, L.P. Garber, J.T. Weaver, D.A. Kennedy, K.A. Patyk, K.P. Huyvaert, R.S. Miller, A.B. Franklin, K. Pedersen, T.L. Bogich, P. Rohani, S.A. Shriner, C.T. Webb, and S. Riley. 2014. Using quantitative diseasedynamics as a tool for guiding response to avian influenza in poultry in theUnited States of AmericaPreventive Veterinary Medicine 113(4):376-397.  doi:10.1016/j.prevetmed.2013.11.011.

Russell, C.A., P.M. Kasson, R.O. Donis, S. Riley, J. Dunbar, A. Rambaut, J. Asher, S. Burke, C.T. Davis, R.J. Garten, S. Gnanakaran, S.I. Hay, S. Herfst, N.S. Lewis, J.O. Lloyd-Smith, C.A. Macken, S. Maurer-Stroh, E. Neuhaus, C.R. Parrish, K.M. Pepin,  D.R. Perez, S. Shepard, D.L. Smith, D.L. Suarez, S.C. Trock, M. Widdowson, D. George,  M. Lipsitch, and J.D. Bloom. 2014. Improving pandemic influenza risk assessment. eLife 3:e03883.  doi: 10.7554/eLife.03883

Pepin KM, Lloyd-Smith JO, Webb CT, Holcomb K, Huachen Z, Guan Y, Riley S. Minimizing the threat of pandemic emergence from avian influenza in poultry systems. BMC Infectious Diseases. 13:592.
George DB, Webb CT, Pepin KM, Savage LT, Antolin MF. Persistence of Prairie-Dog Populations Affected by Plague. Ecology 94:1572.
Pepin KM, Riley S, & Grenfell BT. Effects of influenza antivirals on individual and population immunity over many epidemic waves. Epidemiology & Infection 141:366-376.
Pepin KM, Wang J, Webb CT, Poss M, Hudson PJ, Hong W, Zhu H, Guan Y, Riley S. Anticipating the prevalence of avian influenza subtypes H9 and H5 in live-bird markets. PLoS One 8:e56157.
Pepin KM, Marques-Toledo C,  Scherer L, Morais MM, Ellis B, Eiras AE. Cost-effectiveness of a novel system of mosquito surveillance and control: MI-dengue. Emerging Infectious Diseases 19:542-550.
Pepin KM, Wang J, Webb CT, Smith GJ, Poss M, Hudson PJ, Hong W, Zhu H, Riley S, & Guan Y. Multiannual patterns of influenza A transmission in Chinese live-bird market systems. Influenza & Other Respiratory Viruses 7:97-107.
Abdo Z, Stein M, Wojtowicz A & Pepin KM. The ABC's of experimental evolution. ISRN Computational Biology Article ID: 467943.

Pepin KM, VanDalen KK, Mooers NL, Ellis JW, Sullivan HJ, Root JJ, Webb CT, Franklin AB, Shriner SA.. Quantification of heterosubtypic immunity between avian influenza subtypes H3N8 and H4N6 in multiple avian host species. Journal of General Virology 93:2575.

Pepin KM, Eisen RJ, Mead PS, Piesman J, Fish D, Hoen AG, Barbour AG, Hamer S, Diuk-Wasser MA.. Geographic variation in the relationship between human Lyme disease incidence and the density of infected host-seeking Ixodes scapularis nymphs in the Eastern US.American Journal of Tropical Medicine & Hygiene 86:1062.

Pepin KM, Lass S, Pulliam JRC , Read AF, & Lloyd-Smith JO. Identifying genetic markers of adaptation for surveillance of viral host jumps. Nature Reviews Microbiology 8: 802.

Pepin KM, Volkov I, Banavar JR, Wilke CO, & Grenfell BT. Phenotypic Differences in Viral Immune Escape Explained by Linking Within-Host Dynamics to Host-Population Immunity. Journal of Theoretical Biology 265: 501.

Steinmeyer S, Wilke CO, & Pepin KM. Methods of modeling viral disease dynamics across the within- and between-host scales: The impact of virus dose on host population immunity. Philisophical Transactions of the Royal Society B 365: 1931.

Volkov I, Pepin KM, Lloyd-Smith JO Banavar JR & Grenfell BT. Synthesizing within-host and population level selective pressures on viral populations: the impact of adaptive immunity on viral immune escape. Journal of the Royal Society Interface 7: 1311.

 Lloyd-Smith JO, George D, Pepin KM, Pitzer VE, Pulliam JRC, Dobson AP, Hudson PJ, & Grenfell BT. Epidemic dynamics at the human-animal interface. Science 326:1362-1367.
 Pepin KM, Domsic J & McKenna R. Genomic evolution in a virus under specific selection for host recognition. Infection, Genetics and Evolution 8: 825-834.
Pepin KM & Hanley KA. Density-dependent competitive suppression of sylvatic dengue virus by endemic dengue virus in cultured mosquito cells. Vector-Borne and Zoonotic Diseases 8: 821-828.
Pepin KM & Wichman HA. Experimental evolution and genome sequencing reveal variation in levels of clonal interference in large populations of bacteriophage fX174.  BMC Evolutionary Biology 8: 85.
Pepin KM, Lambeth K & Hanley KA. Asymmetric competitive suppression between strains of dengue virus. BMC Microbiology 8: 28.
 Pepin KM & Wichman HA. Variable epistatic effects between mutations at host recognition sites in fX174 bacteriophage. Evolution 61: 1710-1724.
Gomulkiewicz R, Drown DM, Dybdahl MF, Godsoe W, Nuismer SL, Pepin KM, Ridenhour BJ, Smith CI & Yoder JB. Do’s and Don’ts of testing the geographic mosaic theory of coeveolution. Heredity 98: 249-258.
 Pepin KM, Samuel MA, & Wichman HA. Variable pleiotropic effects from mutations at the same locus hamper prediction of fitness from a fitness component. Genetics 172: 2047-2056.
 Pepin K, Momose F, Ishida N, & Nagata K. Molecular cloning of horse Hsp90 cDNA and its comparative analysis with other vertebrate Hsp90 sequences. Journal of Veterinary Medical Science 63: 115-124.
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