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Patients as Patches: Ecology and Epidemiology in Healthcare Environments

Published online by Cambridge University Press:  20 October 2016

Eric T. Lofgren
Affiliation:
Paul G. Allen School for Global Animal Health, Washington State University, Pullman, Washington Community Health Analytics Initiative, Washington State University, Pullman, Washington The Command, Control and Interoperability Center for Advanced Data Analysis (CCICADA), Piscataway, New Jersey
Andrea M. Egizi
Affiliation:
Tick-Borne Disease Laboratory, Monmouth County Mosquito Control Division, Tinton Falls, New Jersey Center for Vector Biology, Department of Entomology, Rutgers University, New Brunswick, New Jersey
Nina H. Fefferman*
Affiliation:
The Command, Control and Interoperability Center for Advanced Data Analysis (CCICADA), Piscataway, New Jersey Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee
*
Address correspondence to Nina H. Fefferman, Department of Ecology and Evolutionary Biology, 569 Dabney Hall, Knoxville, TN 37996-1610 (feffermn@dimacs.rutgers.edu).
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Abstract

The modern healthcare system involves complex interactions among microbes, patients, providers, and the built environment. It represents a unique and challenging setting for control of the emergence and spread of infectious diseases. We examine an extension of the perspectives and methods from ecology (and especially urban ecology) to address these unique issues, and we outline 3 examples: (1) viewing patients as individual microbial ecosystems; (2) the altered ecology of infectious diseases specifically within hospitals; and (3) ecosystem management perspectives for infection surveillance and control. In each of these cases, we explore the accuracy and relevance of analogies to existing urban ecological perspectives, and we demonstrate a few of the potential direct uses of this perspective for altering research into the control of healthcare-associated infections.

Infect Control Hosp Epidemiol. 2016;1507–1512

Type
Commentaries
Copyright
© 2016 by The Society for Healthcare Epidemiology of America. All rights reserved 

BACKGROUND

Systematic investigation into the effects of urbanization on ecological processes began in earnest after World War II.Reference McDonnell 1 In the past few decades, the study of how urban environments yield different types of ecosystems from those favored by undisturbed or rural environments has blossomed into its own field: urban ecology. By framing research questions using urbanization, this field has been able to provide insights that might otherwise have remained case-by-case results within ecological research.

Thus far, the field has focused on 3 areas of urban impact: the built environment; the byproducts and processes of human urban life as they affect resources and/or habitats for animals and plants; and the resulting biodiversity of the urban ecosystem.Reference Grimm, Faeth and Golubiewski 2 These foci have identified knowledge and data gaps in the understanding of urban ecological processes, have suggested novel hypotheses for scientific investigation, and have enabled concrete and empirically informed planning for more sustainable urban development.

While the complexity of urban ecosystems differs from natural environments,Reference Alberti 3 and this difference can largely be attributed to human-related factors, the main populations and communities studied in cities have been plants and animals (eg, McKinneyReference McKinney 4 ). However, there remains a gigantic yet vastly under-studied realm of the ecology of human urban environments: the urban microbiome.Reference King 5

Here, we consider the healthcare environment as one in which an ecological perspective may be beneficial in improving clinical care and in which the focuses of urban ecology in particular lend themselves to new methods of addressing healthcare-associated infections. While not all healthcare settings are located in what might be considered urban areas, even rural hospitals often feature relatively intense development, a high density of human beings in the same place, and a structurally modified environment. All of these factors are commonly associated with the perspectives and tools of urban ecology.

Applying Urban Microbiome Ecology to Hospital Epidemiology

The healthcare environment represents a complex and medically and economically important environment for pathogens and other human-dependent microbes. Healthcare-associated infections are among the leading causes of death in the United States and have a substantial economic cost.Reference Calfee 6 The built environment within the hospital is awash with (1) microbes only infrequently encountered outside the healthcare environment, (2) disinfectants, and (3) an array of antimicrobial agents ranging from drugs used in patient treatment to surfaces designed to be resistant to bacterial colonization. Urban settings in particular, because of their size and population density, have greater numbers of emergency care facilities, and academic medical centers, and they offer more specialized resources for treating complicated conditions.Reference Galea and Vlahov 7 Thus, patients may go to several providers simultaneously or in sequence. This diffuses accountability for infections so there is no single obvious “point of failure,” but rather a network of institutions struggling to address their infection control problems.Reference Lee, Bartsch and Wong 8 Conversely, denser urban settings also support larger institutions with increasing numbers of patients under care, meaning that facilities failing to control hospital-acquired infections may affect a larger number of people.

Viewing hospital settings in an ecological context (Table 1) can yield insights into pathogen dynamics, transmission, and control. An approachable analogy to other ecological disciplines is to view not only the hospital environment as an ecosystem but also each patient as a free-standing ecosystem. This type of thinking is implicit in many current areas of hospital epidemiology research, from the decolonization of patients with chlorhexidine gluconate to manipulating their intestinal microflora to prevent C. difficile recurrence. Each patient can be thought of as a “patch,” a term denoting a small, self-contained ecosystem that is functionally remote from other habitats, such as an island or an isolated area of green space.Reference Pickett and White 9 The routes of transmission between patients, whether direct contact through the contaminated hands of healthcare workers or contact with a contaminated environment, then become the ecological corridorsReference Hilty, Lidicker and Merenlender 10 along which pathogens move from one patch to another. This group of habitat patches is analogous to a metapopulation, where migration between patches and asynchrony in patch dynamics (ie, not all people become infected or recover, at the same time) allow the population to persist over time.Reference Jesse, Ezanno, Davis and Heesterbeek 11 Urban ecologists are often interested in whether building dispersal corridors will counteract the effects of habitat fragmentation.Reference Gilbert-Norton, Wilson, Stevens and Beard 12 By contrast, infection preventionists attempt to intentionally fragment pathogen habitats and disrupt migration between patients, preventing pathogens from persisting over time. Unique to hospital epidemiology is the fact that some of these corridors, such as the hands of healthcare workers, are themselves also microbial habitats and thus could be patches as well. The level of abstraction for using ecological reasoning will depend on the problem in question. For example, while a patient-centric intervention may regard healthcare workers purely as the means by which patients are exposed, a new hand sanitization protocol might focus on the microbial environment of a worker’s hands.

TABLE 1 Outline of a Framework for Interpreting Ecological Dynamics in an Urban Hospital Environment

Each of these patient environments, by the very fact that they are in a hospital, also undergo significant environmental alterations. These include the direct targeting of a particular pathogen with a pharmaceutical intervention (most commonly an antibiotic or antiviral) as well as the unintended effect of these therapies on other microbes in the patient environment (eg, the impact of broad-spectrum antibiotics on the majority of normal intestinal flora, or a drastic reduction of particular non-target microbial speciesReference Sullivan, Edlund and Nord 13 , Reference Dethlefsen, Huse, Sogin and Relman 14 ). Such shifts in the patient environment can, in turn, alter immune functionReference Jarchum and Pamer 15 and open niches for colonization by microbes acquired post-hospitalization, leading to further changes in community composition.Reference Lloyd-Smith 16 These interactions may yield novel patterns in interpathogen competition and/or commensalism due to the numerous unusual and overlapping selective pressures that exist not only at the level of the patient but among patients as well. For example, the use of proton pump inhibitors may alter a patient’s intestinal flora, leaving them susceptible to C. difficile infection. In turn, the treatment of this infection with vancomycin may promote the proliferation of vancomycin-resistant Enterococci.Reference Al-Nassir, Sethi, Li, Pultz, Riggs and Donskey 17 This complex network of infection risks is borne out of the patient’s own microbiome, the hospital’s microbial environment, and the interactions between them through treatment.

Above the level of an individual patient, the temporal dynamics of urban life in humans can also impact the ecology of pathogens on the level of both host and hospital. For example, many diseases exhibit inherent pathogen-specific seasonality,Reference Lofgren, Fefferman, Naumov, Gorski and Naumova 18 Reference Lal, Hales, French and Baker 20 thereby periodically (re)introducing novel microbial competitors into the healthcare environment. Similarly, periodic influxes of cohorts of newly trained doctors, nurses, and other healthcare personnel may lead to a short-term increase in medical errors,Reference O’Brien-Pallas, Murphy, Shamian, Li and Hayes 21 , Reference Phillips and Barker 22 compromising the deliberate habitat fragmentation caused by infection control policies and allowing ecological corridors between patients to form. This is, in essence, a fluctuating level of habitat heterogeneity, involving anything from relatively mundane daily oscillations in hospital occupancy and the resulting effect on patient care,Reference Weissman, Rothschild and Bendavid 23 all the way up to social or political events, such as emergencies, natural disasters, or labor disputes.Reference Hirshberg, Scott, Granchi, Wall, Mattox and Stein 24 , Reference Abir, Choi, Cooke, Wang and Davis 25 These events can then cascade, altering the microbial environment and competitive landscape in unplanned ways. For example, the use of nurses from different departments to alleviate a temporary staffing shortage may result in combining several infection control cultures and compromising existing protocols.

The dynamics of disease transmission are also different between the healthcare environment and other urban environments, even those entirely created by humans. The near destruction of one’s intestinal flora due to antibiotics is a relatively frequent event within hospitals,Reference Magill, Edwards and Beldavs 26 and while surface-mediated transmission (ie, one individual infects another by way of their shared physical environment) undoubtedly exists in the normal course of urban life, it both occurs at a higher frequency and takes on greater seriousness within the context of the healthcare environment.Reference Weber, Rutala, Miller, Huslage and Sickbert-Bennett 27 , Reference Otter, Yezli and French 28

Ecological Implications of the Patient Environment

As in wildlife ecology, urban patterns of hosts-as-habitats can have considerable impact. Potentially different social conventions regarding intimate contact and sexual partnership in urban settings might alter the success of K-selected pathogens (ie, those that are transmitted rarely or require repeated exposure for successful transmission and therefore must survive within a single host for long periods of time, as is the case with many sexually transmitted infectionsReference O’Keefe 29 ). The dense patterns of contact among larger numbers of incidentally collocated people might easily be described as favoring r-selected pathogens (ie, ones that transmit quickly to new hosts, investing few resources in surviving within any single host for very long) up to a point, but past that point would be expected to shift into boom–bust dynamics wherein periodic large-scale outbreaks sweep through a majority of the population but then die out.Reference King, Shrestha, Harvill and Bjørnstad 30 Furthermore, as is known from population genetics and metapopulation ecology, increased numbers of potential hosts in regions that can, but do not frequently, interact allow rare neutral mutations to become established more frequently than in fully panmictic populations.

These perspectives are also directly relevant within a healthcare environment, with the associated array of intensive selective pressures. The prevalence of pharmaceutical interventions, disinfection and sterilization products, as well as their varied mechanisms of action and an ever-shifting microbial community, can alter the relative fitness of r- versus K- selected species as competitors. This perspective is of immediate practical use, relying on the very well-developed literature about which conditions favor r- versus K-selected species (eg, Resnick et alReference Reznick, Bryant and Bashey 31 and Phillips et alReference Phillips, Brown and Shine 32 ) and thereby generating practical and testable hypotheses about which pathogens are likeliest to become established as HAIs due to their relative evolutionary fitness among ambient pathogens. For example, r-selected species that are characterized by very high rates of reproduction and rapid, explosive growth (eg, norovirus) may be favored in many hospital environments, which, from a microbial perspective, are relatively unstable due to high amounts of environmental disinfection. In contrast, environments with more stable environments and populations, such as long-term care facilities, may favor, or at least be conducive to, the transmission of more K-selected pathogens, such as fungal infections or tuberculosis.

An Ecological Perspective on Infection Surveillance and Control

Understanding the principles of urban ecology that apply to healthcare environments has the potential to inform infection control policy and to improve existing infection surveillance and control programs. Advances in sequencing technology have made the study of infection control problems from a community ecology perspective a technical reality,Reference Lax and Gilbert 33 but this potential has not yet been fully realized. Methodological difficulties arise given the levels of asymptomatic carriageReference Jombart, Cori, Didelot, Cauchemez, Fraser and Ferguson 34 commonly seen in many pathogens important to hospital epidemiology, such as S. aureus or C. difficile. Despite these hurdles, these technologies are invaluable for quantifying what pathogens exist within a healthcare environment—the first step toward understanding its ecology.

An ecological perspective can help evaluate the relative impacts and unforeseen consequences of vertical infection control programs that combat a single pathogen (eg, targeted screening for CRE colonization when a patient is admitted) versus horizontal infection control programs that target a wide swath of pathogens through a single mechanism (eg, improved hand hygiene compliance).Reference Lofgren, Moehring, Anderson, Weber and Fefferman 35 Reference Edmond and Munoz-Price 37 Each of these types of programs, or several programs of each type within a hospital, impacts the community dynamics of the pathogens within the hospital and, by extension, within the patient-level environment as well. Understanding these dynamics, such as the potential of one infection control program to increase the prevalence of another type of microbe (ie, through competitive release)Reference Lloyd-Smith 16 allows for more well-controlled programs and may provide explanations for otherwise unanticipated or inexplicable changes in infection rates. The most common example confronting healthcare settings is the epidemiology of C. difficile. Treatment protocols that suggest the use of broad-spectrum antibiotics disrupt the normal ecology of the gut, opening up a large niche into which C. difficile may then proliferate and cause disease.

Similarly, infection risk analysis and mitigation may also be improved by incorporating urban ecological understanding about how to use observed biodiversity as an indicator of disturbance. Most current patient screening techniques, diagnostic tests, environmental contamination surveys, etc, operate based on the determination of presence/absence, ignoring other community properties, such as relative abundance. However, in ecology, species richness alone is typically an insufficient indicator of ecosystem processes, and the relative abundance of species, or evenness, is also extremely important.Reference Hillebrand, Bennett and Cadotte 38 For example, urban environments tend to display less evenness as a result of overrepresentation by invasive species and human commensals.Reference Shochat, Lerman, Anderies, Warren, Faeth and Nilon 39 These findings align perfectly with Clostridium difficile infection, which is driven not necessarily by the presence of the pathogen but rather by the pathogen’s relative abundance compared to other organisms within the patient’s microbiome.Reference Chang, Antonopoulos and Kalra 40 , Reference Buffie, Jarchum and Equinda 41 Interventions meant to alter microbial abundance, such as the use of fecal microbiota transplantation, are therefore direct means of altering the community ecology of the patient environment.Reference Lemon, Armitage, Relman and Fischbach 42 There is no reason that C. difficile should be unique in this respect, and save for infections stemming from the introduction of pathogens into an environment where they should not be (eg, central-line–associated bloodstream infections), the ecologically informed inclusion of abundance as part of biodiversity in surveillance and risk analysis may provide better understanding and improved potential for control.

Another aspect of biodiversity, functional diversity, may also be incredibly important from the standpoint of diagnosing and controlling diseases. In urban ecology, function refers to the processes and services performed by ecosystems (eg, nutrient cycling, primary productivity) and is sometimes, but not always, related to the presence or abundance of certain species.Reference Alberti 3 , Reference Hooper, Chapin and Ewel 43 However, groups of species performing similar functions can lead to functional redundancy, whereby species composition can change without compromising ecosystem processes.Reference Cadotte, Carscadden and Mirotchnick 44 Increasing evidence of functional redundancy in the human microbiomeReference Kurokawa, Itoh and Kuwahara 45 , Reference Turnbaugh, Hamady and Yatsunenko 46 calls for a broadening of epidemiological focus from the presence or abundance of a particular microbe toward consideration of functionally similar microbes or even specific microbial transcripts (eg, resistance genes).Reference Weinstock 47 This concept is already being explored through the use of bacterial interference as either a direct treatmentReference Gerding, Meyer and Lee 48 , Reference Deasy, Guccione and Dale 49 or as a potential source for new therapeutic agents.Reference Zipperer, Konnerth and Laux 50

In addition to impacts on ecosystem function, the various components of biodiversity discussed above can influence a community’s response to disturbance and invasion. While several authors have considered the implications of ecological resistance and resilience for human-associated microbial communities,Reference Robinson, Bohannan and Young 51 Reference Relman 53 further insights are uniquely applicable to the healthcare environment. Studies like the Hospital Microbiome ProjectReference Smith, Alverdy and An 54 may ultimately inspire efforts to cultivate surface-associated communities within hospitals that are resistant to pathogen establishment. For example, a recent study found that more diverse microbial communities occur in hospital rooms with windows that open, suggesting the potential for building features to affect microbial community composition, and perhaps indirectly, the movement of pathogens.Reference Kembel, Jones and Kline 55

Using Urban Ecology to Predict Hospital Epidemiology

With the examples outlined above, we can begin to see how concepts from urban ecology can inform research questions and recommendations in medical ecosystems. Urban ecology has a deep literature base regarding on the impact of urban settings on biodiversity. In general, these studies predict (in temperate regions) that species commonly transported into the urban center by humans (eg, invasives with high propagule pressure) will increase while native species richness declines, although some native species that can adapt to the changes associated with urbanization may increase.Reference McKinney 4 , Reference Shochat, Lerman, Anderies, Warren, Faeth and Nilon 39 , Reference McKinney 56 This framework can be applied in medical settings to consider epidemiological outcomes observed already, but with a unifying and explanatory theory by which to predict and describe pathogen dynamics. For example, there should be increasing numbers of outbreaks of rare but often introduced pathogens, such as MRSA when it is endemic in the community, even if it is controlled within a hospital. The incidence of infections that can be easily and effectively treated should decrease (as with the general decline in many infectious diseases in the twentieth century), and correspondingly there should be an increase in diseases that are becoming more difficult to treat, such as antimicrobial-resistant infections. The incidence of infections for which medical treatment increases the host’s ability to circulate among the rest of the population while still infectious should increase. Here, this can be the result of treatment suppressing symptoms but not shedding, or as the result of frequent patient transfers within or between hospitals.Reference Lee, Bartsch and Wong 8 Likewise, each of the analogies mentioned throughout this review can lead to specific predictions about disease dynamics in healthcare settings.

CONCLUSIONS

Although we have conducted only a surface-level overview of the potential application of ecological perspectives on hospital epidemiology, we believe an increased use of this type of analysis and thinking has immediate potential in helping combat healthcare-associated infections. These infections are directly analogous examples for many of the concepts developed within and between traditional and urban ecological research efforts (eg, invasive species). This perspective on hospital epidemiology puts forth clear and important questions for which existing theory in these disciplines can offer more general solutions, rather than the current case-by-case basis used for disease-specific epidemiological research. We can already see how to apply this perspective to an astounding diversity of issues confronting infection preventionists: (1) understanding/predicting the likely relative frequencies for different types of pathogens; (2) suggesting critical “corridors” for transmission of pathogens such that surveillance efforts in these locations or populations would be most effective in early detection of outbreaks; (3) informing public health interventions to trade off short-term against long-term outbreak management goals (ie, hospitalizing patients when staffing and resources are already strained during a public health emergency, prioritizing patient treatment and survival at the cost of increased risk for secondary infections, analogous to control strategies studied in population viability analysis); and (4) altering microbial management in healthcare facilities based on understandings of microbial community competition and commensalism dynamics, among others.

Over the past decade, the understanding that the ecology of infectious diseases can help to inform epidemiological research has led to some deep and beautiful insights.Reference Smith, Rubinstein, Park, Kelly and Klepac-Ceraj 57 , Reference Johnson, de Roode and Fenton 58 By taking this understanding a step further, borrowing also from research into the distinct ecological processes that occur in urban settings and how they differ from other environments, we believe we can leverage a greater depth of insight into urban microbial dynamics in direct application to everything from basic epidemiological science to clinical practice. This insight then has the potential to lead to better interventions and improved patient outcomes. Interested researchers may find surprisingly relevant concepts in foundational textbooks in urban ecologyReference Gaston 59 , Reference Adler and Tanner 60 or through discussions with colleagues in the ecological sciences.

ACKNOWLEDGMENTS

Financial support: We thank the Command, Control, and Interoperability Center for Advanced Data Analysis (CCICADA) for support to E.T.L. and N.H.F.

Potential conflicts of interest: All authors report no conflicts of interest relevant to this article.

References

REFERENCES

1. McDonnell, MJ. The history of urban ecology: an ecologist’s perspective. In: Niemelä J, Breuste JH, Elmqvist T, Guntenspergen PJ, McIntyre NE, eds. Urban Ecology: Patterns, Processes, and Applications. Oxford, UK: Oxford University Press; 2011:513.Google Scholar
2. Grimm, NB, Faeth, SH, Golubiewski, NE, et al. Global change and the ecology of cities. Science 2008;319:756760.Google Scholar
3. Alberti, M. The effects of urban patterns on ecosystem function. Int Reg Sci Rev 2005;28:168192.CrossRefGoogle Scholar
4. McKinney, M. Effects of urbanization on species richness: a review of plants and animals. Urban Ecosys 2008;11:161176.Google Scholar
5. King, G. Urban microbiomes and urban ecology: How do microbes in the built environment affect human sustainability in cities? J Microbiol 2014;52:721728.Google Scholar
6. Calfee, DP. Crisis in hospital-acquired, healthcare-associated infections. Ann Rev Med 2012;63:359371.Google Scholar
7. Galea, S, Vlahov, D. Urban health: evidence, challenges, and directions. Annu Rev Public Health 2005;26:341365.Google Scholar
8. Lee, BY, Bartsch, SM, Wong, KF, et al. The importance of nursing homes in the spread of methicillin-resistant Staphylococcus aureus (MRSA) among hospitals. Med Care 2013;51:205215.Google Scholar
9. Pickett, STA, White, PS. eds. The Ecology of Natural Disturbance and Patch Dynamics. San Diego, CA: Academic Press; 1985.Google Scholar
10. Hilty, JA, Lidicker, WZ Jr, Merenlender, AM. Corridor Ecology: The Science and Practice of Linking Landscapes for Biodiversity Conservation. Washington, DC: Island Press; 2006.Google Scholar
11. Jesse, M, Ezanno, P, Davis, S, Heesterbeek, JAP. A fully coupled, mechanistic model for infectious disease dynamics in a metapopulation: movement and epidemic duration. J Theoret Biol 2008;254:331338.Google Scholar
12. Gilbert-Norton, L, Wilson, R, Stevens, JR, Beard, KH. A meta-analytic review of corridor effectiveness—una revisión meta-analítica de la efectividad de los corredores. Conserv Biol 2010;24:660668.Google Scholar
13. Sullivan, A, Edlund, C, Nord, CE. Effect of antimicrobial agents on the ecological balance of human microflora. Lancet Infect Dis 2001;1:101114.Google Scholar
14. Dethlefsen, L, Huse, S, Sogin, ML, Relman, DA. The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing. PLoS Biol 2008;6:e280.CrossRefGoogle Scholar
15. Jarchum, I, Pamer, EG. Regulation of innate and adaptive immunity by the commensal microbiota. Curr Opin Immunol 2011;23:353360.Google Scholar
16. Lloyd-Smith, JO. Vacated niches, competitive release and the community ecology of pathogen eradication. Phil Trans Royal Soc B 2013;368.Google Scholar
17. Al-Nassir, WN, Sethi, AK, Li, Y, Pultz, MJ, Riggs, MM, Donskey, CJ. Both oral metronidazole and oral vancomycin promote persistent overgrowth of vancomycin-resistant Enterococci during treatment of Clostridium difficile-associated disease. Antimicrob Agents Chemother 2008;52:24032406.Google Scholar
18. Lofgren, E, Fefferman, NH, Naumov, YN, Gorski, J, Naumova, EN. Influenza seasonality: underlying causes and modeling theories. J Virol 2007;81:54295436.Google Scholar
19. Fisman, D. Seasonality of viral infections: mechanisms and unknowns. Clin Microbiol Infect 2013;18:946954.Google Scholar
20. Lal, A, Hales, S, French, N, Baker, MG. Seasonality in human zoonotic enteric diseases: a systematic review. PLoS One 2013;7:e31883.Google Scholar
21. O’Brien-Pallas, L, Murphy, GT, Shamian, J, Li, X, Hayes, LJ. Impact and determinants of nurse turnover: a pan-Canadian study. J Nurs Manag 2010;18:10731086.Google Scholar
22. Phillips, D, Barker, GC. A July spike in fatal medication errors: a possible effect of new medical residents. J Gen Intern Med 2010;25:774779.Google Scholar
23. Weissman, JS, Rothschild, JM, Bendavid, E, et al. Hospital workload and adverse events. Med Care 2007;45:448455.Google Scholar
24. Hirshberg, A, Scott, BG, Granchi, T, Wall, MJ Jr, Mattox, KL, Stein, M. How does casualty load affect trauma care in urban bombing incidents? A quantitative analysis. J Trauma Acute Care Surg 2005;58.Google Scholar
25. Abir, M, Choi, H, Cooke, CR, Wang, SC, Davis, MM. Effect of a mass casualty incident: clinical outcomes and hospital charges for casualty patients versus concurrent inpatients. Acad Emerg Med 2012;19:280286.Google Scholar
26. Magill, SS, Edwards, JR, Beldavs, ZG, et al. Prevalence of antimicrobial use in US acute care hospitals, May–September 2011. JAMA 2014;312:14381446.Google Scholar
27. Weber, DJ, Rutala, WA, Miller, MB, Huslage, K, Sickbert-Bennett, E. Role of hospital surfaces in the transmission of emerging health care-associated pathogens: norovirus, Clostridium difficile, and Acinetobacter species. Am J Infect Control 2010;38:S25S33.Google Scholar
28. Otter, JA, Yezli, S, French, GL. The role played by contaminated surfaces in the transmission of nosocomial pathogens. Infect Control Hosp Epidemiol 2011;32:687699.Google Scholar
29. O’Keefe, KJ. The evolution of virulence in pathogens with frequency-dependent transmission. J Theoret Biol 2005;233:5564.Google Scholar
30. King, AA, Shrestha, S, Harvill, ET, Bjørnstad, ON. Evolution of acute infections and the invasion-persistence trade-off. Amer Naturalist 2009;173:446455.Google Scholar
31. Reznick, D, Bryant, MJ, Bashey, F. r- and K-selection revisited: the role of population regulation in life-history evolution. Ecology 2002;83:15091520.Google Scholar
32. Phillips, BL, Brown, GP, Shine, R. Life-history evolution in range-shifting populations. Ecology 2010;91:16171627.Google Scholar
33. Lax, S, Gilbert, JA. Hospital-associated microbiota and implications for nosocomial infections. Trends Molec Med 2015;21:427432.Google Scholar
34. Jombart, T, Cori, A, Didelot, X, Cauchemez, S, Fraser, C, Ferguson, N. Bayesian reconstruction of disease outbreaks by combining epidemiologic and genomic data. PLoS Comput Biol 2014;10:e1003457.Google Scholar
35. Lofgren, ET, Moehring, RW, Anderson, DJ, Weber, DJ, Fefferman, NH. A mathematical model to evaluate the routine use of fecal microbiota transplantation to prevent incident and recurrent Clostridium difficile infection. Infect Control 2014;35:1827.Google Scholar
36. Septimus, E, Weinstein, RA, Perl, TM, Goldmann, DA, Yokoe, DS. Approaches for preventing healthcare-associated infections: go long or go wide? Infect Control Hosp Epidemiol 2014;35:797801.Google Scholar
37. Edmond, M, Munoz-Price, S. Surveillance cultures for carbapenem-resistant Gram-negatives: to do or not to do. Paper presented at: SHEA conference, May 14, 2015; Orlando, FL.Google Scholar
38. Hillebrand, H, Bennett, DM, Cadotte, MW. Consequences of dominance: a review of evenness effects on local and regional ecosystem processes. Ecology 2008;89:15101520.Google Scholar
39. Shochat, E, Lerman, SB, Anderies, JM, Warren, PS, Faeth, SH, Nilon, CH. Invasion, competition, and biodiversity loss in urban ecosystems. BioScience 2010;60:199208.Google Scholar
40. Chang, JY, Antonopoulos, DA, Kalra, A, et al. Decreased diversity of the fecal microbiome in recurrent Clostridium difficile-associated diarrhea. J Infect Dis 2008;197:435438.Google Scholar
41. Buffie, CG, Jarchum, I, Equinda, M, et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect Immun 2012;80:6273.Google Scholar
42. Lemon, KP, Armitage, GC, Relman, DA, Fischbach, MA. Microbiota-targeted therapies: an ecological perspective. Sci Transl Med 2012;4:137rv135137rv135.Google Scholar
43. Hooper, DU, Chapin, FS, Ewel, JJ, et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol Monogr 2005;75:335.Google Scholar
44. Cadotte, MW, Carscadden, K, Mirotchnick, N. Beyond species: functional diversity and the maintenance of ecological processes and services. J Appl Ecol 2011;48:10791087.Google Scholar
45. Kurokawa, K, Itoh, T, Kuwahara, T, et al. Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes. DNA Res 2007;14:169181.Google Scholar
46. Turnbaugh, PJ, Hamady, M, Yatsunenko, T, et al. A core gut microbiome in obese and lean twins. Nature 2009;457:480484.Google Scholar
47. Weinstock, GM. Genomic approaches to studying the human microbiota. Nature 2012;489:250256.Google Scholar
48. Gerding, DN, Meyer, T, Lee, C, et al. Administration of spores of nontoxigenic Clostridium difficile strain M3 for prevention of recurrent C. difficile infection. JAMA 2015;313:17191727.Google Scholar
49. Deasy, AM, Guccione, E, Dale, AP, et al. Nasal inoculation of the commensal Niseria lactamica inhibits carriage of Neisseria meningitides by young adults: a controlled human infection study. Clin Infect Dis 2015;60:15121520.Google Scholar
50. Zipperer, A, Konnerth, MC, Laux, C, et al. Human commensals producing a novel antibiotic impair pathogen colonization. Nature 2016;535:511516.Google Scholar
51. Robinson, CJ, Bohannan, BJ, Young, VB. From structure to function: the ecology of host-associated microbial communities. Microbiol Mol Biol Rev 2010;74:453476.Google Scholar
52. Costello, EK, Stagaman, K, Dethlefsen, L, Bohannan, BJ, Relman, DA. The application of ecological theory toward an understanding of the human microbiome. Science 2012;336:12551262.Google Scholar
53. Relman, DA. The human microbiome: ecosystem resilience and health. Nutr Rev 2012;70:S2S9.Google Scholar
54. Smith, D, Alverdy, J, An, G, et al. The hospital microbiome project: meeting report for the 1st hospital microbiome project workshop on sampling design and building science measurements, Chicago, IL, June 7–8, 2012. Stand Genomic Sci 2013;8:112117.Google Scholar
55. Kembel, SW, Jones, E, Kline, J, et al. Architectural design influences the diversity and structure of the built environment microbiome. ISME J 2012;6:14691479.Google Scholar
56. McKinney, ML. Urbanization as a major cause of biotic homogenization. Biol Conserv 2006;127:247260.Google Scholar
57. Smith, VH, Rubinstein, RJ, Park, S, Kelly, L, Klepac-Ceraj, V. Microbiology and ecology are vitally important to premedical curricula. Evol Med Pub Health 2015;179192.Google Scholar
58. Johnson, PTJ, de Roode, JC, Fenton, A. Why infectious disease research needs community ecology. Science 2015;349:1069.Google Scholar
59. Gaston, KJ. ed. Urban Ecology. Cambridge University Press: Cambridge, UK; 2010.Google Scholar
60. Adler, FR, Tanner, CJ. Urban Ecosystems: Ecological Principles for the Built Environment. Cambridge University Press: Cambridge, UK; 2013.Google Scholar
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TABLE 1 Outline of a Framework for Interpreting Ecological Dynamics in an Urban Hospital Environment