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  1. Article ; Online: Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts

    Becker, Daniel J. / Eby, Peggy / Madden, Wyatt / Peel, Alison J. / Plowright, Raina K.

    Ecology Letters. 2023 Jan., v. 26, no. 1 p.23-36

    2023  

    Abstract: The ecological conditions experienced by wildlife reservoirs affect infection dynamics and thus the distribution of pathogen excreted into the environment. This spatial and temporal distribution of shed pathogen has been hypothesised to shape risks of ... ...

    Abstract The ecological conditions experienced by wildlife reservoirs affect infection dynamics and thus the distribution of pathogen excreted into the environment. This spatial and temporal distribution of shed pathogen has been hypothesised to shape risks of zoonotic spillover. However, few systems have data on both long‐term ecological conditions and pathogen excretion to advance mechanistic understanding and test environmental drivers of spillover risk. We here analyse three years of Hendra virus data from nine Australian flying fox roosts with covariates derived from long‐term studies of bat ecology. We show that the magnitude of winter pulses of viral excretion, previously considered idiosyncratic, are most pronounced after recent food shortages and in bat populations displaced to novel habitats. We further show that cumulative pathogen excretion over time is shaped by bat ecology and positively predicts spillover frequency. Our work emphasises the role of reservoir host ecology in shaping pathogen excretion and provides a new approach to estimate spillover risk.
    Keywords Chiroptera ; Hendra henipavirus ; ecology ; excretion ; foxes ; pathogens ; risk ; space and time ; wildlife
    Language English
    Dates of publication 2023-01
    Size p. 23-36.
    Publishing place John Wiley & Sons, Ltd
    Document type Article ; Online
    Note LETTER
    ZDB-ID 1441608-6
    ISSN 1461-0248 ; 1461-023X
    ISSN (online) 1461-0248
    ISSN 1461-023X
    DOI 10.1111/ele.14007
    Database NAL-Catalogue (AGRICOLA)

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  2. Article ; Online: Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts.

    Becker, Daniel J / Eby, Peggy / Madden, Wyatt / Peel, Alison J / Plowright, Raina K

    Ecology letters

    2022  

    Abstract: The ecological conditions experienced by wildlife reservoirs affect infection dynamics and thus the distribution of pathogen excreted into the environment. This spatial and temporal distribution of shed pathogen has been hypothesised to shape risks of ... ...

    Abstract The ecological conditions experienced by wildlife reservoirs affect infection dynamics and thus the distribution of pathogen excreted into the environment. This spatial and temporal distribution of shed pathogen has been hypothesised to shape risks of zoonotic spillover. However, few systems have data on both long-term ecological conditions and pathogen excretion to advance mechanistic understanding and test environmental drivers of spillover risk. We here analyse three years of Hendra virus data from nine Australian flying fox roosts with covariates derived from long-term studies of bat ecology. We show that the magnitude of winter pulses of viral excretion, previously considered idiosyncratic, are most pronounced after recent food shortages and in bat populations displaced to novel habitats. We further show that cumulative pathogen excretion over time is shaped by bat ecology and positively predicts spillover frequency. Our work emphasises the role of reservoir host ecology in shaping pathogen excretion and provides a new approach to estimate spillover risk.
    Language English
    Publishing date 2022-10-30
    Publishing country England
    Document type Letter
    ZDB-ID 1441608-6
    ISSN 1461-0248 ; 1461-023X
    ISSN (online) 1461-0248
    ISSN 1461-023X
    DOI 10.1111/ele.14007
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

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    In stock of ZB MED Bonn / Germany

    Z 2005/709: Show issues

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  3. Article ; Online: Comparing and linking machine learning and semi-mechanistic models for the predictability of endemic measles dynamics.

    Lau, Max S Y / Becker, Alex / Madden, Wyatt / Waller, Lance A / Metcalf, C Jessica E / Grenfell, Bryan T

    PLoS computational biology

    2022  Volume 18, Issue 9, Page(s) e1010251

    Abstract: Measles is one the best-documented and most-mechanistically-studied non-linear infectious disease dynamical systems. However, systematic investigation into the comparative performance of traditional mechanistic models and machine learning approaches in ... ...

    Abstract Measles is one the best-documented and most-mechanistically-studied non-linear infectious disease dynamical systems. However, systematic investigation into the comparative performance of traditional mechanistic models and machine learning approaches in forecasting the transmission dynamics of this pathogen are still rare. Here, we compare one of the most widely used semi-mechanistic models for measles (TSIR) with a commonly used machine learning approach (LASSO), comparing performance and limits in predicting short to long term outbreak trajectories and seasonality for both regular and less regular measles outbreaks in England and Wales (E&W) and the United States. First, our results indicate that the proposed LASSO model can efficiently use data from multiple major cities and achieve similar short-to-medium term forecasting performance to semi-mechanistic models for E&W epidemics. Second, interestingly, the LASSO model also captures annual to biennial bifurcation of measles epidemics in E&W caused by susceptible response to the late 1940s baby boom. LASSO may also outperform TSIR for predicting less-regular dynamics such as those observed in major cities in US between 1932-45. Although both approaches capture short-term forecasts, accuracy suffers for both methods as we attempt longer-term predictions in highly irregular, post-vaccination outbreaks in E&W. Finally, we illustrate that the LASSO model can both qualitatively and quantitatively reconstruct mechanistic assumptions, notably susceptible dynamics, in the TSIR model. Our results characterize the limits of predictability of infectious disease dynamics for strongly immunizing pathogens with both mechanistic and machine learning models, and identify connections between these two approaches.
    MeSH term(s) Communicable Diseases/epidemiology ; Disease Outbreaks ; Epidemics ; Humans ; Machine Learning ; Measles/epidemiology ; United States/epidemiology
    Language English
    Publishing date 2022-09-08
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1010251
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Pathogen spillover driven by rapid changes in bat ecology.

    Eby, Peggy / Peel, Alison J / Hoegh, Andrew / Madden, Wyatt / Giles, John R / Hudson, Peter J / Plowright, Raina K

    Nature

    2022  Volume 613, Issue 7943, Page(s) 340–344

    Abstract: During recent decades, pathogens that originated in bats have become an increasing public health concern. A major challenge is to identify how those pathogens spill over into human populations to generate a pandemic ... ...

    Abstract During recent decades, pathogens that originated in bats have become an increasing public health concern. A major challenge is to identify how those pathogens spill over into human populations to generate a pandemic threat
    MeSH term(s) Animals ; Humans ; Australia ; Bayes Theorem ; Chiroptera/virology ; Climate ; Ecosystem ; Horses/virology ; Public Health ; Hendra Virus/isolation & purification ; Natural Resources ; Agriculture ; Forests ; Ecology ; Food Supply ; Pandemics/prevention & control ; Pandemics/veterinary
    Language English
    Publishing date 2022-11-16
    Publishing country England
    Document type Journal Article ; Research Support, U.S. Gov't, P.H.S. ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 120714-3
    ISSN 1476-4687 ; 0028-0836
    ISSN (online) 1476-4687
    ISSN 0028-0836
    DOI 10.1038/s41586-022-05506-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 26: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MG 9: Show issues
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  5. Article: Estimating viral prevalence with data fusion for adaptive two-phase pooled sampling.

    Hoegh, Andrew / Peel, Alison J / Madden, Wyatt / Ruiz Aravena, Manuel / Morris, Aaron / Washburne, Alex / Plowright, Raina K

    Ecology and evolution

    2021  Volume 11, Issue 20, Page(s) 14012–14023

    Abstract: The COVID-19 pandemic has highlighted the importance of efficient sampling strategies and statistical methods for monitoring infection prevalence, both in humans and in reservoir hosts. Pooled testing can be an efficient tool for learning pathogen ... ...

    Abstract The COVID-19 pandemic has highlighted the importance of efficient sampling strategies and statistical methods for monitoring infection prevalence, both in humans and in reservoir hosts. Pooled testing can be an efficient tool for learning pathogen prevalence in a population. Typically, pooled testing requires a second-phase retesting procedure to identify infected individuals, but when the goal is solely to learn prevalence in a population, such as a reservoir host, there are more efficient methods for allocating the second-phase samples.To estimate pathogen prevalence in a population, this manuscript presents an approach for data fusion with two-phased testing of pooled samples that allows more efficient estimation of prevalence with less samples than traditional methods. The first phase uses pooled samples to estimate the population prevalence and inform efficient strategies for the second phase. To combine information from both phases, we introduce a Bayesian data fusion procedure that combines pooled samples with individual samples for joint inferences about the population prevalence.Data fusion procedures result in more efficient estimation of prevalence than traditional procedures that only use individual samples or a single phase of pooled sampling.The manuscript presents guidance on implementing the first-phase and second-phase sampling plans using data fusion. Such methods can be used to assess the risk of pathogen spillover from reservoir hosts to humans, or to track pathogens such as SARS-CoV-2 in populations.
    Language English
    Publishing date 2021-09-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 2635675-2
    ISSN 2045-7758
    ISSN 2045-7758
    DOI 10.1002/ece3.8107
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Severe Acute Respiratory Syndrome Coronavirus 2 Is Detected in the Gastrointestinal Tract of Asymptomatic Endoscopy Patients but Is Unlikely to Pose a Significant Risk to Healthcare Personnel.

    Cherne, Michelle D / Gentry, Andrew B / Nemudraia, Anna / Nemudryi, Artem / Hedges, Jodi F / Walk, Heather / Blackwell, Karlin / Snyder, Deann T / Jerome, Maria / Madden, Wyatt / Hashimi, Marziah / Sebrell, T Andrew / King, David B / Plowright, Raina K / Jutila, Mark A / Wiedenheft, Blake / Bimczok, Diane

    Gastro hep advances

    2022  Volume 1, Issue 5, Page(s) 844–852

    Abstract: Background and aims: Recent evidence suggests that the gut is an additional target for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, whether SARS-CoV-2 spreads via gastrointestinal secretions remains unclear. To ... ...

    Abstract Background and aims: Recent evidence suggests that the gut is an additional target for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, whether SARS-CoV-2 spreads via gastrointestinal secretions remains unclear. To determine the prevalence of gastrointestinal SARS-CoV-2 infection in asymptomatic subjects, we analyzed gastrointestinal biopsy and liquid samples from endoscopy patients for the presence of SARS-CoV-2.
    Methods: We enrolled 100 endoscopic patients without known SARS-CoV-2 infection (cohort A) and 12 patients with a previous COVID-19 diagnosis (cohort B) in a cohort study performed at a regional hospital. Gastrointestinal biopsies and fluids were screened for SARS-CoV-2 by polymerase chain reaction (PCR), immunohistochemistry, and virus isolation assay, and the stability of SARS-CoV-2 in gastrointestinal liquids in vitro was analyzed.
    Results: SARS-CoV-2 ribonucleic acid was detected by PCR in the colonic tissue of 1/100 patients in cohort A. In cohort B, 3 colonic liquid samples tested positive for SARS-CoV-2 by PCR and viral nucleocapsid protein was detected in the epithelium of the respective biopsy samples. However, no infectious virions were recovered from any samples. In vitro exposure of SARS-CoV-2 to colonic liquid led to a 4-log-fold reduction of infectious SARS-CoV-2 within 1 hour (
    Conclusion: Overall, the persistent detection of SARS-CoV-2 in endoscopy samples after resolution of COVID-19 points to the gut as a long-term reservoir for SARS-CoV-2. Since no infectious virions were recovered and SARS-CoV-2 was rapidly inactivated in the presence of colon liquids, it is unlikely that performing endoscopic procedures is associated with a significant infection risk due to undiagnosed asymptomatic or persistent gastrointestinal SARS-CoV-2 infections.
    Language English
    Publishing date 2022-06-24
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2772-5723
    ISSN (online) 2772-5723
    DOI 10.1016/j.gastha.2022.06.002
    Database MEDical Literature Analysis and Retrieval System OnLINE

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