Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Urban-adapted mammal species have more known pathogens

Nature Ecology & Evolution volume 6, pages 794–801 (2022)Cite this article

Subjects

Abstract

The world is rapidly urbanizing, inviting mounting concern that urban environments will experience increased zoonotic disease risk. Urban animals could have more frequent contact with humans, therefore transmitting more zoonotic parasites; however, this relationship is complicated by sampling bias and phenotypic confounders. Here we test whether urban mammal species host more zoonotic parasites, investigating the underlying drivers alongside a suite of phenotypic, taxonomic and geographic predictors. We found that urban-adapted mammals have more documented parasites and more zoonotic parasites: despite comprising only 6% of investigated species, urban mammals provided 39% of known host–parasite combinations. However, contrary to predictions, much of the observed effect was attributable to parasite discovery and research effort rather than to urban adaptation status, and urban-adapted species in fact hosted fewer zoonotic parasites than expected on the basis of their total parasite richness. We conclude that extended historical contact with humans has had a limited impact on zoonotic parasite richness in urban-adapted mammals; instead, their greater observed zoonotic richness probably reflects sampling bias arising from proximity to humans, supporting a near-universal conflation between zoonotic risk, research effort and synanthropy. These findings underscore the need to resolve the mechanisms linking anthropogenic change, sampling bias and observed wildlife disease dynamics.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Urban-adapted mammals have more known parasites and zoonoses specifically.
Fig. 2: Citation numbers are higher in urban species and drive observed parasite and zoonotic parasite richness.
Fig. 3: Path analysis revealed that urban-adapted mammals do not have more zoonoses than expected on the basis of their overall parasite diversity.
Fig. 4: Model fixed-effect estimates and spatial effects on overall and zoonotic parasite richness.

Data availability

The CLOVER dataset is available at https://github.com/viralemergence/clover. The VIRION dataset is available at https://github.com/viralemergence/virion. All other ancillary data are available at https://github.com/viralemergence/UrbanOutputters.

Code availability

The code used here is available at https://github.com/viralemergence/UrbanOutputters.

References

  1. Morse, S. S. et al. Prediction and prevention of the next pandemic zoonosis. Lancet 380, 1956–1965 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Jones, K. E. et al. Global trends in emerging infectious diseases. Nature 451, 990–993 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Keesing, F. et al. Impacts of biodiversity on the emergence and transmission of infectious diseases. Nature 468, 647–652 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Carlson, C. J. et al. Climate change will drive novel cross-species viral transmission. Preprint at bioRxiv https://doi.org/10.1101/2020.01.24.918755 (2020).

  5. Gibb, R. et al. Zoonotic host diversity increases in human-dominated ecosystems. Nature https://doi.org/10.1038/s41586-020-2562-8 (2020).

  6. Loh, E. H. et al. Targeting transmission pathways for emerging zoonotic disease surveillance and control. Vector Borne Zoonotic Dis. 15, 432–437 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Hassell, J. M., Begon, M., Ward, M. J. & Fèvre, E. M. Urbanization and disease emergence: dynamics at the wildlife–livestock–human interface. Trends Ecol. Evol. 32, 55–67 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Cohen, J. M., Sauer, E. L., Santiago, O., Spencer, S. & Rohr, J. R. Divergent impacts of warming weather on wildlife disease risk across climates. Science 370, eabb1702 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Murray, M. H. et al. City sicker? A meta-analysis of wildlife health and urbanization. Front. Ecol. Environ. 17, 575–583 (2019).

    Article  Google Scholar 

  10. Becker, D. J., Hall, R. J., Forbes, K. M., Plowright, R. K. & Altizer, S. Anthropogenic resource subsidies and host–parasite dynamics in wildlife. Phil. Trans. R. Soc. B 373, 20170086 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Werner, C. S. & Nunn, C. L. Effect of urban habitat use on parasitism in mammals: a meta-analysis. Proc. Biol. Sci. 287, 20200397 (2020).

    PubMed  PubMed Central  Google Scholar 

  12. Becker, D. J., Streicker, D. G. & Altizer, S. Linking anthropogenic resources to wildlife–pathogen dynamics: a review and meta-analysis. Ecol. Lett. 18, 483–495 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Becker, D. J. et al. Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defense. J. Anim. Ecol. 89, 972–995 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Albery, G. F. & Becker, D. J. Fast-lived hosts and zoonotic risk. Trends Parasitol. https://doi.org/10.1016/j.pt.2020.10.012 (2021).

  15. Seto, K. C., Güneralp, B. & Hutyra, L. R. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc. Natl Acad. Sci. USA 109, 16083–16088 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Chen, G. et al. Global projections of future urban land expansion under shared socioeconomic pathways. Nat. Commun. 11, 537 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Gao, J. & O’Neill, B. C. Mapping global urban land for the twenty-first century with data-driven simulations and shared socioeconomic pathways. Nat. Commun. 11, 2302 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Santini, L. et al. One strategy does not fit all: determinants of urban adaptation in mammals. Ecol. Lett. 22, 365–376 (2019).

    Article  PubMed  Google Scholar 

  19. Ostfeld, R. S. et al. Life history and demographic drivers of reservoir competence for three tick-borne zoonotic pathogens. PLoS ONE 9, e107387 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Olival, K. J. et al. Host and viral traits predict zoonotic spillover from mammals. Nature 546, 646–650 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Mollentze, N. & Streicker, D. G. Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts. Proc. Natl Acad. Sci. USA 117, 9423–9430 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Gutiérrez, J. S., Piersma, T. & Thieltges, D. W. Micro- and macroparasite species richness in birds: the role of host life history and ecology. J. Anim. Ecol. 88, 1226–1239 (2019).

    Article  PubMed  Google Scholar 

  23. Teitelbaum, C. S. et al. A comparison of diversity estimators applied to a database of host–parasite associations. Ecography 43, 1316–1328 (2019).

    Article  Google Scholar 

  24. Jorge, F. & Poulin, R. Poor geographical match between the distributions of host diversity and parasite discovery effort. Proc. R. Soc. B 285, 20180072 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Allen, T. et al. Global hotspots and correlates of emerging zoonotic diseases. Nat. Commun. 8, 1124 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Gibb, R. et al. Mammal virus diversity estimates are unstable due to accelerating discovery effort. Biol. Lett. https://doi.org/10.1098/rsbl.2021.0427 (2022).

  27. Hughes, A. et al. Sampling biases shape our view of the natural world. Ecography 44, 1259–1269 (2021).

    Article  Google Scholar 

  28. Estes, L. et al. The spatial and temporal domains of modern ecology. Nat. Ecol. Evol. 2, 819–826 (2018).

    Article  PubMed  Google Scholar 

  29. Titley, M. A., Snaddon, J. L. & Turner, E. C. Scientific research on animal biodiversity is systematically biased towards vertebrates and temperate regions. PLoS ONE 12, e0189577 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Lloyd-Smith, J. O. et al. Should we expect population thresholds for wildlife disease? Trends Ecol. Evol. 20, 511–519 (2005).

    Article  PubMed  Google Scholar 

  31. Cummings, C. R. et al. Foraging in urban environments increases bactericidal capacity in plasma and decreases corticosterone concentrations in white ibises. Front. Ecol. Evol. 8, 575980 (2020).

    Article  Google Scholar 

  32. Hwang, J. et al. Anthropogenic food provisioning and immune phenotype: association among supplemental food, body condition, and immunological parameters in urban environments. Ecol. Evol. 8, 3037–3046 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Strandin, T., Babayan, S. A. & Forbes, K. M. Reviewing the effects of food provisioning on wildlife immunity. Phil. Trans. R. Soc. B 373, 20170088 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Downs, C. J., Dochtermann, N. A., Ball, R., Klasing, K. C. & Martin, L. B. The effects of body mass on immune cell concentrations of mammals. Am. Nat. 195, 107–114 (2020).

    Article  PubMed  Google Scholar 

  35. Downs, C. J. et al. Extreme hyperallometry of mammalian antibacterial defenses. Preprint at bioRxiv https://doi.org/10.1101/2020.09.04.242107 (2020).

  36. Becker, D. J., Seifert, S. N. & Carlson, C. J. Beyond infection: integrating competence into reservoir host prediction. Trends Ecol. Evol. 35, 1062–1065 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Hanson, D. A., Britten, H. B., Restani, M. & Washburn, L. R. High prevalence of Yersinia pestis in black-tailed prairie dog colonies during an apparent enzootic phase of sylvatic plague. Conserv. Genet. 8, 789–795 (2007).

    Article  CAS  Google Scholar 

  38. Gecchele, L. V., Pedersen, A. B. & Bell, M. Fine-scale variation within urban landscapes affects marking patterns and gastrointestinal parasite diversity in red foxes. Ecol. Evol. 10, 13796–13809 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Albery, G. F., Sweeny, A. R., Becker, D. J. & Bansal, S. Fine-scale spatial patterns of wildlife disease are common and understudied. Funct. Ecol. https://doi.org/10.1111/1365-2435.13942 (2021).

  40. Jones, K. E. et al. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90, 2648–2648 (2009).

    Article  Google Scholar 

  41. Fritz, S. A., Bininda-Emonds, O. R. P. & Purvis, A. Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics. Ecol. Lett. 12, 538–549 (2009).

    Article  PubMed  Google Scholar 

  42. Albery, G. F., Eskew, E. A., Ross, N. & Olival, K. J. Predicting the global mammalian viral sharing network using phylogeography. Nat. Commun. https://doi.org/10.1038/s41467-020-16153-4 (2020).

  43. IUCN Red List of Threatened Species Version 2019-2 (IUCN, 2019); https://www.iucnredlist.org

  44. Becker, D. J. et al. Optimising predictive models to prioritise viral discovery in zoonotic reservoirs. Lancet Microbe https://doi.org/10.1016/S2666-5247(21)00245-7 (2022).

  45. Mason, P. Parasites of deer in New Zealand. N. Zeal. J. Zool. 21, 39–47 (1994).

    Article  Google Scholar 

  46. Wilman, H. et al. EltonTraits 1.0: species-level foraging attributes of the world’s birds and mammals. Ecology 95, 2027 (2014).

    Article  Google Scholar 

  47. Plourde, B. T. et al. Are disease reservoirs special? Taxonomic and life history characteristics. PLoS ONE 12, e0180716 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Gibb, R. et al. Data proliferation, reconciliation, and synthesis in viral ecology. Bioscience https://doi.org/10.1101/2021.01.14.426572 (2021).

  49. Stephens, P. R. et al. Global mammal parasite database version 2.0. Ecology 98, 1476 (2017).

    Article  PubMed  Google Scholar 

  50. Wardeh, M., Risley, C., Mcintyre, M. K., Setzkorn, C. & Baylis, M. Database of host–pathogen and related species interactions, and their global distribution. Sci. Data 2, 150049 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Shaw, L. P. et al. The phylogenetic range of bacterial and viral pathogens of vertebrates. Mol. Ecol. 29, 3361–3379 (2020).

    Article  PubMed  Google Scholar 

  52. Chamberlain, S. A. & Szöcs, E. taxize: taxonomic search and retrieval in R. F1000Res https://doi.org/10.12688/f1000research.2-191.v2 (2013).

  53. Carlson, C. J. et al. The Global Virome in One Network (VIRION): an atlas of vertebrate–virus associations. mBio 13, e0298521 (2022).

    Article  PubMed  Google Scholar 

  54. Lindgren, F. & Rue, H. Bayesian spatial modelling with R-INLA. J. Stat. Softw. 63, 1–25 (2015).

    Article  Google Scholar 

  55. Lindgren, F., Rue, H. & Lindstrom, J. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. J. R. Stat. Soc. B 73, 423–498 (2011).

    Article  Google Scholar 

  56. Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1–22 (2010).

    Article  Google Scholar 

  57. Winter, D. J. rentrez: an R package for the NCBI eUtils API. R J. 9, 520–526 (2017).

    Article  Google Scholar 

  58. Shipley, B. Confirmatory path analysis in a generalized multilevel context. Ecology 90, 363–368 (2009).

    Article  PubMed  Google Scholar 

  59. Carlson, C. J., Dallas, T. A., Alexander, L. W., Phelan, A. L. & Phillips, A. J. What would it take to describe the global diversity of parasites? Proc. R. Soc. B 287, 20201841 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by funding to the Viral Emergence Research Initiative (VERENA) consortium, including National Science Foundation grant BII 2021909.

Author information

Authors and Affiliations

  1. Department of Biology, Georgetown University, Washington, DC, USA

    Gregory F. Albery

  2. Center for Global Health Science and Security, Georgetown University Medical Center, Washington, DC, USA

    Colin J. Carlson

  3. Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC, USA

    Colin J. Carlson

  4. Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Lily E. Cohen

  5. Department of Biology, Pacific Lutheran University, Tacoma, WA, USA

    Evan A. Eskew

  6. Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK

    Rory Gibb

  7. Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK

    Rory Gibb

  8. Quantitative Disease Ecology and Conservation (QDEC) Lab Group, Department of Geography, University of Florida, Gainesville, FL, USA

    Sadie J. Ryan

  9. Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA

    Sadie J. Ryan

  10. School of Life Sciences, University of KwaZulu-Natal, Durban, South Africa

    Sadie J. Ryan

  11. University of Edinburgh, Ashworth Laboratories, Edinburgh, Scotland

    Amy R. Sweeny

  12. Department of Biology, University of Oklahoma, Norman, OK, USA

    Daniel J. Becker

Authors
  1. Gregory F. Albery
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Colin J. Carlson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lily E. Cohen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Evan A. Eskew
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rory Gibb
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sadie J. Ryan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Amy R. Sweeny
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Daniel J. Becker
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.F.A. and D.J.B. conceived the study, and G.F.A. analysed the data and wrote the manuscript. C.J.C., L.E.C., E.A.E., R.G., S.J.R., A.R.S. and D.J.B. offered thoughts on the analysis and commented on the manuscript.

Corresponding author

Correspondence to Gregory F. Albery.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Ecology & Evolution thanks Luis Escobar, James Hassell and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Albery, G.F., Carlson, C.J., Cohen, L.E. et al. Urban-adapted mammal species have more known pathogens. Nat Ecol Evol 6, 794–801 (2022). https://doi.org/10.1038/s41559-022-01723-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41559-022-01723-0

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing