@article{acebes-doria_agnello_alston_andrews_beers_bergh_bessin_blaauw_buntin_burkness_et al._2020, title={Season-Long Monitoring of the Brown Marmorated Stink Bug (Hemiptera: Pentatomidae) Throughout the United States Using Commercially Available Traps and Lures}, volume={113}, ISSN={["1938-291X"]}, DOI={10.1093/jee/toz240}, abstractNote={Abstract Reliable monitoring of the invasive Halyomorpha halys abundance, phenology and geographic distribution is critical for its management. Halyomorpha halys adult and nymphal captures on clear sticky traps and in black pyramid traps were compared in 18 states across the Great Lakes, Mid-Atlantic, Southeast, Pacific Northwest and Western regions of the United States. Traps were baited with commercial lures containing the H. halys pheromone and synergist, and deployed at field sites bordering agricultural or urban locations with H. halys host plants. Nymphal and adult captures in pyramid traps were greater than those on sticky traps, but captures were positively correlated between the two trap types within each region and during the early-, mid- and late season across all sites. Sites were further classified as having a low, moderate or high relative H. halys density and again showed positive correlations between captures for the two trap types for nymphs and adults. Among regions, the greatest adult captures were recorded in the Southeast and Mid-Atlantic on pyramid and sticky traps, respectively, with lowest captures recorded in the West. Nymphal captures, while lower than adult captures, were greatest in the Southeast and lowest in the West. Nymphal and adult captures were, generally, greatest during July–August and September–October, respectively. Trapping data were compared with available phenological models showing comparable population peaks at most locations. Results demonstrated that sticky traps offer a simpler alternative to pyramid traps, but both can be reliable tools to monitor H. halys in different geographical locations with varying population densities throughout the season.}, number={1}, journal={JOURNAL OF ECONOMIC ENTOMOLOGY}, author={Acebes-Doria, Angelita L. and Agnello, Arthur M. and Alston, Diane G. and Andrews, Heather and Beers, Elizabeth H. and Bergh, J. Christopher and Bessin, Ric and Blaauw, Brett R. and Buntin, G. David and Burkness, Eric C. and et al.}, year={2020}, month={Feb}, pages={159–171} }
 @article{chen_lanzas_lee_zenarosa_arif_dulin_2019, title={Metapopulation Model from Pathogen's Perspective: A Versatile Framework to Quantify Pathogen Transfer and Circulation between Environment and Hosts}, volume={9}, ISSN={["2045-2322"]}, DOI={10.1038/s41598-018-37938-0}, abstractNote={Metapopulation models have been primarily explored in infectious disease epidemiology to study host subpopulation movements and between-host contact structures. They also have the potential to investigate environmental pathogen transferring. In this study, we demonstrate that metapopulation models serve as an ideal modeling framework to characterize and quantify pathogen transfer between environment and hosts. It therefore unifies host, pathogen, and environment, collectively known as the epidemiological triad, a fundamental concept in epidemiology. We develop a customizable and generalized pathogen-transferring model where pathogens dwell in and transferring (via contact) between environment and hosts. We analyze three specific case studies: pure pathogen transferring without pathogen demography, source-sink dynamics, and pathogen control via external disinfection. We demonstrate how pathogens circulate in the system between environment and hosts, as well as evaluate different controlling efforts for healthcare-associated infections (HAIs). For pure pathogen transferring, system equilibria can be derived analytically to explicitly quantify long-term pathogen distribution in the system. For source-sink dynamics and pathogen control via disinfection, we demonstrate that complete eradication of pathogens can be achieved, but the rates of converging to system equilibria differ based on specific model parameterization. Direct host-host pathogen transferring and within-host dynamics can be future directions of this modeling framework by adding specific modules.}, journal={SCIENTIFIC REPORTS}, author={Chen, Shi and Lanzas, Cristina and Lee, Chihoon and Zenarosa, Gabriel L. and Arif, Ahmed A. and Dulin, Michael}, year={2019}, month={Feb} }
 @article{dawson_keung_napoles_vella_chen_sanderson_lanzas_2018, title={Investigating behavioral drivers of seasonal Shiga-Toxigenic Escherichia Coli (STEC) patterns in grazing cattle using an agent-based model}, volume={13}, ISSN={["1932-6203"]}, url={http://europepmc.org/articles/PMC6179278}, DOI={10.1371/journal.pone.0205418}, abstractNote={The causes of seasonal variability in pathogen transmission are not well understood, and have not been comprehensively investigated. In an example for enteric pathogens, incidence of Escherichia coli O157 (STEC) colonization in cattle is consistently higher during warmer months compared to cooler months in various cattle production systems. However, actual mechanisms for this seasonality remain elusive. In addition, the influence of host (cattle) behavior on this pattern has not been thoroughly considered. To that end, we constructed a spatially explicit agent-based model that accounted for the effect of temperature fluctuations on cattle behavior (direct contact among cattle and indirect between cattle and environment), as well as its effect on pathogen survival in the environment. We then simulated the model in a factorial approach to evaluate the hypothesis that temperature fluctuations can lead to seasonal STEC transmission dynamics by influencing cattle aggregation, grazing, and drinking behaviors. Simulation results showed that higher temperatures increased the frequency at which cattle aggregated under shade in pasture, resulting in increased direct contact and transmission of STEC between individual cattle, and hence higher incidence over model simulations in the warm season. In contrast, increased drinking behavior during warm season was not an important transmission pathway. Although sensitivity analyses suggested that the relative importance of direct vs. indirect (environmental) pathways depend to upon model parameterization, model simulations indicated that factors influencing cattle aggregation, such as temperature, were likely strong drivers of transmission dynamics of enteric pathogens.}, number={10}, journal={PLOS ONE}, author={Dawson, Daniel E. and Keung, Jocelyn H. and Napoles, Monica G. and Vella, Michael R. and Chen, Shi and Sanderson, Michael W. and Lanzas, Cristina}, year={2018}, month={Oct} }
 @article{chen_lenhart_day_lee_dulin_lanzas_2018, title={Pathogen transfer through environment-host contact: an agent-based queueing theoretic framework}, volume={35}, ISSN={["1477-8602"]}, url={https://doi.org/10.1093/imammb/dqx014}, DOI={10.1093/imammb/dqx014}, abstractNote={Queueing theory studies the properties of waiting queues and has been applied to investigate direct host-to-host transmitted disease dynamics, but its potential in modelling environmentally transmitted pathogens has not been fully explored. In this study, we provide a flexible and customizable queueing theory modelling framework with three major subroutines to study the in-hospital contact processes between environments and hosts and potential nosocomial pathogen transfer, where environments are servers and hosts are customers. Two types of servers with different parameters but the same utilization are investigated. We consider various forms of transfer functions that map contact duration to the amount of pathogen transfer based on existing literature. We propose a case study of simulated in-hospital contact processes and apply stochastic queues to analyse the amount of pathogen transfer under different transfer functions, and assume that pathogen amount decreases during the inter-arrival time. Different host behaviour (feedback and non-feedback) as well as initial pathogen distribution (whether in environment and/or in hosts) are also considered and simulated. We assess pathogen transfer and circulation under these various conditions and highlight the importance of the nonlinear interactions among contact processes, transfer functions and pathogen demography during the contact process. Our modelling framework can be readily extended to more complicated queueing networks to simulate more realistic situations by adjusting parameters such as the number and type of servers and customers, and adding extra subroutines.}, number={3}, journal={MATHEMATICAL MEDICINE AND BIOLOGY-A JOURNAL OF THE IMA}, author={Chen, Shi and Lenhart, Suzanne and Day, Judy D. and Lee, Chihoon and Dulin, Michael and Lanzas, Cristina}, year={2018}, month={Sep}, pages={409–425} }
 @article{nielsen_chen_fleischer_2017, title={Coupling developmental physiology, photoperiod, and temperature to model phenology and dynamics of an invasive Heteropteran, Halyomorpha halys (vol 7, 2016)}, volume={8}, journal={Frontiers in Physiology}, author={Nielsen, A. L. and Chen, S. and Fleischer, S. J.}, year={2017} }
 @article{chen_sanderson_lee_cernicchiaro_renter_lanzas_2016, title={Basic Reproduction Number and Transmission Dynamics of Common Serogroups of Enterohemorrhagic Escherichia coli}, volume={82}, ISSN={["1098-5336"]}, DOI={10.1128/aem.00815-16}, abstractNote={ABSTRACT Understanding the transmission dynamics of pathogens is essential to determine the epidemiology, ecology, and ways of controlling enterohemorrhagic Escherichia coli (EHEC) in animals and their environments. Our objective was to estimate the epidemiological fitness of common EHEC strains in cattle populations. For that purpose, we developed a Markov chain model to characterize the dynamics of 7 serogroups of enterohemorrhagic Escherichia coli (O26, O45, O103, O111, O121, O145, and O157) in cattle production environments based on a set of cross-sectional data on infection prevalence in 2 years in two U.S. states. The basic reproduction number (R 0) was estimated using a Bayesian framework for each serogroup based on two criteria (using serogroup alone [the O-group data] and using O serogroup, Shiga toxin gene[s], and intimin [eae] gene together [the EHEC data]). In addition, correlations between external covariates (e.g., location, ambient temperature, dietary, and probiotic usage) and prevalence/R 0 were quantified. R 0 estimates varied substantially among different EHEC serogroups, with EHEC O157 having an R 0 of >1 (∼1.5) and all six other EHEC serogroups having an R 0 of less than 1. Using the O-group data substantially increased R 0 estimates for the O26, O45, and O103 serogroups (R 0 > 1) but not for the others. Different covariates had distinct influences on different serogroups: the coefficients for each covariate were different among serogroups. Our modeling and analysis of this system can be readily expanded to other pathogen systems in order to estimate the pathogen and external factors that influence spread of infectious agents. IMPORTANCE In this paper we describe a Bayesian modeling framework to estimate basic reproduction numbers of multiple serotypes of Shiga toxin-producing Escherichia coli according to a cross-sectional study. We then coupled a compartmental model to reconstruct the infection dynamics of these serotypes and quantify their risk in the population. We incorporated different sensitivity levels of detecting different serotypes and evaluated their potential influence on the estimation of basic reproduction numbers.}, number={18}, journal={APPLIED AND ENVIRONMENTAL MICROBIOLOGY}, author={Chen, Shi and Sanderson, Michael W. and Lee, Chihoon and Cernicchiaro, Natalia and Renter, David G. and Lanzas, Cristina}, year={2016}, month={Sep}, pages={5612–5620} }
 @article{nielsen_chen_fleischer_2016, title={Coupling developmental physiology, photoperiod, and temperature to model phenology and dynamics of an invasive heteropteran, Halyomorpha halys}, volume={7}, journal={Frontiers in Physiology}, author={Nielsen, A. L. and Chen, S. and Fleischer, S. J.}, year={2016} }
 @article{lanzas_chen_2016, title={Mathematical modeling tools to study preharvest food safety}, volume={4}, number={4}, journal={Microbiology Spectrum}, author={Lanzas, C. and Chen, S.}, year={2016} }
 @article{chen_bao_2015, title={Linking body size and energetics with predation strategies: A game theoretic modeling framework}, volume={316}, journal={Ecological Modelling}, author={Chen, S. and Bao, F. S.}, year={2015}, pages={81–86} }
 @article{chen_ilany_white_sanderson_lanzas_2015, title={Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?}, volume={10}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84939158760&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0129253}, abstractNote={Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.}, number={6}, journal={PLOS ONE}, author={Chen, Shi and Ilany, Amiyaal and White, Brad J. and Sanderson, Michael W. and Lanzas, Cristina}, year={2015}, month={Jun} }
 @article{chen_fleischer_saunders_thomas_2015, title={The influence of diurnal temperature variation on degree-day accumulation and insect life history}, volume={10}, number={3}, journal={PLoS One}, author={Chen, S. and Fleischer, S. J. and Saunders, M. C. and Thomas, M. B.}, year={2015} }