Abstract

Understanding host interactions that lead to pathogen transmission is fundamental to the prediction and control of epidemics1,2,3,4,5. Although the majority of transmissions often occurs within social groups6,7,8,9, the contribution of connections that bridge groups and species to pathogen dynamics is poorly understood10,11,12. These cryptic connections—which are often indirect or infrequent—provide transmission routes between otherwise disconnected individuals and may have a key role in large-scale outbreaks that span multiple populations or species. Here we quantify the importance of cryptic connections in disease dynamics by simultaneously characterizing social networks and tracing transmission dynamics of surrogate-pathogen epidemics through eight communities of bats. We then compared these data to the invasion of the fungal pathogen that causes white-nose syndrome, a recently emerged disease that is devastating North American bat populations13,14,15. We found that cryptic connections increased links between individuals and between species by an order of magnitude. Individuals were connected, on average, to less than two per cent of the population through direct contact and to only six per cent through shared groups. However, tracing surrogate-pathogen dynamics showed that each individual was connected to nearly fifteen per cent of the population, and revealed widespread transmission between solitarily roosting individuals as well as extensive contacts among species. Connections estimated from surrogate-pathogen epidemics, which include cryptic connections, explained three times as much variation in the transmission of the fungus that causes white-nose syndrome as did connections based on shared groups. These findings show how cryptic connections facilitate the community-wide spread of pathogens and can lead to explosive epidemics.

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All raw data points are contained within the main-text Figs. and Extended Data Figs. All other data are available from the corresponding author upon reasonable request.

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Acknowledgements

Financial support was provided by the NSF (grants DGE-0741448, DEB-1115895 and EF-0914866), USFWS and Bat Conservation International. E. McMaster provided support and site access; B. Lyon, J. Nicol, L. Childs and E. Palsson provided comments on analyses or the manuscript; and M. Hee, H. Guedi, S. Yamada, K. George, G. Auteri, J. Bailey and N. Tran aided in the laboratory or field.

Reviewer information

Nature thanks B. Fenton, J. Lloyd-Smith and D. Reeder for their contribution to the peer review of this work.

Author information

Affiliations

  1. Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, USA

    • Joseph R. Hoyt
    • , Winifred F. Frick
    •  & A. Marm Kilpatrick
  2. Department of Biological Sciences, Virginia Polytechnic Institute, Blacksburg, VA, USA

    • Joseph R. Hoyt
    •  & Kate E. Langwig
  3. Wisconsin Department of Natural Resources, Bureau of Natural Heritage Conservation, Madison, WI, USA

    • J. Paul White
    • , Heather M. Kaarakka
    •  & Jennifer A. Redell
  4. Department of Biology, Eastern Michigan University, Ypsilanti, MI, USA

    • Allen Kurta
  5. Michigan Department of Natural Resources, Baraga, MI, USA

    • John E. DePue
  6. Michigan Department of Natural Resources, Norway, MI, USA

    • William H. Scullon
  7. Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, Durham, NH, USA

    • Katy L. Parise
    •  & Jeffrey T. Foster
  8. Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA

    • Katy L. Parise
    •  & Jeffrey T. Foster
  9. Bat Conservation International, Austin, TX, USA

    • Winifred F. Frick

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Contributions

J.R.H., K.E.L. and A.M.K. conceptualized the project, analysed the data and wrote the paper with input from all authors. J.R.H., K.E.L., J.P.W., H.M.K., J.A.R., A.K., J.E.D., W.H.S., W.F.F. and A.M.K. designed, organized and performed the field study. J.R.H., K.L.P. and J.T.F. performed laboratory testing.

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The authors declare no competing interests.

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Correspondence to Joseph R. Hoyt.

Extended data figures and tables

  1. Extended Data Fig. 1 Application and re-sighting of UVF dust on bats and in the environment.

    a, Applying UVF dust to P. subflavus. b, A dusted P. subflavus shortly after release. c, M. septentrionalis after UVF-dust application. d, A group of eight M. lucifugus roosting together in March. Each bat in the group had UVF dust. e, A dusted M. lucifugus in a group of three bats during March. At least three of the bats in the photo can be seen with UVF dust. f, Location in the environment with patches of UVF dust in March next to a hibernating P. subflavus.

  2. Extended Data Fig. 2 Trends of population counts and timing of UVF-dust and disease data collection.

    The grey bar shows the winter period when the UVF-dust study was conducted and the red bar shows the year the P. destructans arrived. Temporal patterns of social group size are provided in Extended Data Fig. 6a.

  3. Extended Data Fig. 3 Social and epidemic networks for four additional communities of hibernating bats.

    ah, Each row shows two networks (physical contact and UVF dust) for each of four sites (WI-ST, WI-SB, MI-TM and MI-GA). Each circle (node) represents an individual bat, with colour indicating species; larger numbered circles (1–7) are bats that were dusted with UVF dust with unique colours in November at each site. Lines (edges) between nodes indicate physical contact among bats in social networks (a–d) or UVF dust that originated from the UVF-dusted bat (large circle) in epidemic networks (e–h). Each UVF-dust epidemic network in e–h shows seven replicate epidemics, with each epidemic originating from a single, numbered UVF-dusted bat. Locations of nodes (bats) in the two networks are identical, so the spread of UVF dust within and between groups of touching bats can be visualized in the UVF-dust network.

  4. Extended Data Fig. 4 Comparison of observed data from late-winter and total shared-group connections including group rearrangements.

    The y axes show the percentage of individuals of each species at each site observed in direct physical contact, in shared groups or with UVF dust originating from a single focal individual. a, M. lucifugus. b, M. septentrionalis. c, P. subflavus. Small points show the observed (grey) data and augmented (coloured) connections, including group rearrangements. The black open points show the mean late winter estimate of direct contact and social-group connections based on a single time point of the populations without group switching (Fig. 1, Extended Data Fig. 3; left panels). The large coloured points (means in Fig. 2) show the mean number of connections from simulations in which bats rearranged during six arousals over the winter (also shown in Fig. 2). Where the large coloured points are within the black open points, there were no differences between the observed and augmented data including group rearrangements. The connections observed in UVF-dust epidemics are shown for comparison, but do not differ.

  5. Extended Data Fig. 5 Shared-group (cluster) size for four species of hibernating bats.

    Different letters above bars indicate mean group sizes that differ significantly; generalized linear model with negative binomial distribution with site as a random effect and species as a fixed effect (E. fuscus, n = 202 observed groups, intercept: 0.020 ± 0.11; M. lucifugus, n = 1,011 observed groups, coefficient 0.450 ± 0.08; M. septentrionalis, n = 151 observed groups, coefficient: −0.03 ± 0.12; P. subflavus, n = 263 observed groups, coefficient, −0.058 ± 0.11). The lower and upper hinges of the box plot show the first and third quartiles. The upper and lower whiskers extend to the largest and smallest value 1.5 times the interquartile range.

  6. Extended Data Fig. 6 Distributions of shared-group sizes for four species of hibernating bats in early (November) and late (March) winter and during the collection of UVF-dust and fungal infection data.

    a, Across all species, there was no significant change in social-group size over the winter using season (early versus late winter) as a fixed effect, and site and species as random effects (early winter, intercept: 0.38 ± 0.21; late winter, coefficient: 0.01 ± 0.03, P = 0.716, n = 1,956 bat groupings). We also investigated changes in social-group size for M. lucifugus, using an identical model but dropping species as a random effect. Again, we found no significant change in social group size over the winter (early winter, intercept: 0.84 ± 0.17, n = 457; late winter, coefficient: −0.008 ± 0.04, n = 528, P = 0.84). Neither model was significantly better than a null-intercept model. For E. fuscus, shared-group sizes increased slightly over the winter (early winter, intercept: 0.11 ± 0.11, n = 79; late winter, coefficient: 0.28 ± 0.14, n = 100, P = 0.040). b, We compared social-group size (n = 1,328) between the disease-arrival year and the dust-study year using a generalized linear mixed-effects model with a Poisson distribution and a log link. We found no significant difference in social-group sizes among years using study year as a categorical fixed effect (dust or disease) and site and species as random effects (disease study, intercept: 0.32 ± 0.16; UVF-dust study, coefficient: −0.04 ± 0.04, P = 0.33).

  7. Extended Data Fig. 7 Environmental contamination and spatial overlap of UVF-dusted individuals.

    a, Total surface area of the hibernacula walls and ceilings with UVF dust originating from different species (n = 51 measurements). Small black points show the summed total surface area with each colour of dust. Large points show the mean and 95% confidence intervals of the three species that were originally dusted in November (generalized linear mixed-effects model with site as a random effect and species as a fixed effect; M. lucifugus, intercept: 2.71 ± 0.15; M. septentrionalis, coefficient: 0.14 ± 0.17, t = 0.79; P. subflavus, coefficient: −0.21 ± 0.18, t = −1.16; species effect, P = 0.30). b, Percentage overlap of hibernacula areas used by individual bats compared to areas used by other individuals (n = 172 individual overlap estimates). The home range was calculated for each individual UVF-dust colour based on locations in the environment at which bats deposited their unique colour of UVF dust (see Methods). The points show an overlap estimate for each individual dusted bat compared to another dusted bat at that same site with larger points showing the mean and 95% confidence intervals for each species (generalized linear mixed-effects model with site as a random effect and species as a fixed effect; M. lucifugus, intercept: 0.88 ± 0.05; M. septentrionalis, coefficient: −0.03 ± 0.05, t = −0.50; P. subflavus, coefficient: −0.21 ± 0.07, t = −2.86; species effect, P = 0.02). Points are jittered in b to show overlapping data.

  8. Extended Data Fig. 8 The probability of an individual being re-sighted with UVF dust by group size.

    a, The probability of M. lucifugus (n = 1,697 individuals re-sighted for all dust colours) individuals having UVF dust that originated from another M. lucifugus increased with group size (generalized linear mixed-effects model with site and individual bat as random effects, and group size as a fixed effect; group size, coefficient: 0.017 ± 0.005; intercept, −0.596 ± 0.201, P = 0.0015). b, The probability of M. lucifugus (n = 4,164 individuals re-sighted for all dust colours) having UVF dust that originated from dusted M. septentrionalis decreased with M. lucifugus group size (group size coefficient, −0.013 ± 0.004; intercept, −1.973 ± 0.221, P = 0.0003). This suggests that M. septentrionalis were more likely to contact M. lucifugus roosting solitarily than in groups, whereas M. lucifugus roosting in groups were more likely to be contacted by other M. lucifugus than were M. lucifugus individuals that roosted solitarily.

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