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  1. Book ; Online ; E-Book: Population biology of vector-borne diseases

    Drake, John M. / Bonsall, Michael B. / Strand, Michael R.

    (Ecology and evolution of infectious diseases series)

    2021  

    Author's details edited by John M. Drake, Michael B. Bonsall, Michael R. Strand
    Series title Ecology and evolution of infectious diseases series
    Keywords Epidemiology & medical statistics ; Public health & preventive medicine ; Human biology ; Parasitology (non-medical) ; Virology (non-medical) ; Insects (entomology) ; Zoology: Invertebrates ; Microbiology (non-medical)
    Language English
    Size 1 Online-Ressource (viii, 293 Seiten), Illustrationen
    Publisher Oxford University Press
    Publishing place Oxford
    Publishing country Great Britain
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT020834162
    ISBN 978-0-19-259464-8 ; 9780198853244 ; 0-19-259464-8 ; 0198853246
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: How to publish a 'Method' article in Ecology Letters.

    Drake, John M

    Ecology letters

    2023  Volume 26, Issue 10, Page(s) 1645–1646

    MeSH term(s) Publishing ; Ecology
    Language English
    Publishing date 2023-11-27
    Publishing country England
    Document type Editorial ; Comment
    ZDB-ID 1441608-6
    ISSN 1461-0248 ; 1461-023X
    ISSN (online) 1461-0248
    ISSN 1461-023X
    DOI 10.1111/ele.14304
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  3. Article ; Online: How to publish a 'perspective' or 'synthesis' article in Ecology Letters.

    Drake, John M / Chase, Jonathan M

    Ecology letters

    2023  Volume 26, Issue 3, Page(s) 349–350

    Language English
    Publishing date 2023-02-18
    Publishing country England
    Document type Editorial
    ZDB-ID 1441608-6
    ISSN 1461-0248 ; 1461-023X
    ISSN (online) 1461-0248
    ISSN 1461-023X
    DOI 10.1111/ele.14165
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  4. Article ; Online: A Data-driven Horizon Scan of Bacterial Pathogens at the Wildlife-livestock Interface.

    Evans, Michelle V / Drake, John M

    EcoHealth

    2022  Volume 19, Issue 2, Page(s) 246–258

    Abstract: Many livestock diseases rely on wildlife for the transmission or maintenance of the pathogen, and the wildlife-livestock interface represents a potential site of disease emergence for novel pathogens in livestock. Predicting which pathogen species are ... ...

    Abstract Many livestock diseases rely on wildlife for the transmission or maintenance of the pathogen, and the wildlife-livestock interface represents a potential site of disease emergence for novel pathogens in livestock. Predicting which pathogen species are most likely to emerge in the future is an important challenge for infectious disease surveillance and intelligence. We used a machine learning approach to conduct a data-driven horizon scan of bacterial associations at the wildlife-livestock interface for cows, sheep, and pigs. Our model identified and ranked from 76 to 189 potential novel bacterial species that might associate with each livestock species. Wildlife reservoirs of known and novel bacteria were shared among all three species, suggesting that targeting surveillance and/or control efforts towards these reservoirs could contribute disproportionately to reducing spillover risk to livestock. By predicting pathogen-host associations at the wildlife-livestock interface, we demonstrate one way to plan for and prevent disease emergence in livestock.
    MeSH term(s) Animals ; Animals, Wild ; Bacteria ; Cattle ; Communicable Diseases/epidemiology ; Livestock ; Sheep ; Swine
    Language English
    Publishing date 2022-06-06
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2164327-1
    ISSN 1612-9210 ; 1612-9202
    ISSN (online) 1612-9210
    ISSN 1612-9202
    DOI 10.1007/s10393-022-01599-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Untangling the evolution of dengue viruses.

    Rohani, Pejman / Drake, John M

    Science (New York, N.Y.)

    2021  Volume 374, Issue 6570, Page(s) 941–942

    Abstract: The push and pull of dengue virus serotype evolution influences epidemic potential. ...

    Abstract The push and pull of dengue virus serotype evolution influences epidemic potential.
    MeSH term(s) Dengue ; Dengue Virus/genetics ; Humans
    Language English
    Publishing date 2021-11-18
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 128410-1
    ISSN 1095-9203 ; 0036-8075
    ISSN (online) 1095-9203
    ISSN 0036-8075
    DOI 10.1126/science.abm6812
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 27: 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 77: Show issues

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  6. Article: A Data-driven Horizon Scan of Bacterial Pathogens at the Wildlife–livestock Interface

    Evans, Michelle V. / Drake, John M.

    EcoHealth. 2022 June, v. 19, no. 2

    2022  

    Abstract: Many livestock diseases rely on wildlife for the transmission or maintenance of the pathogen, and the wildlife–livestock interface represents a potential site of disease emergence for novel pathogens in livestock. Predicting which pathogen species are ... ...

    Abstract Many livestock diseases rely on wildlife for the transmission or maintenance of the pathogen, and the wildlife–livestock interface represents a potential site of disease emergence for novel pathogens in livestock. Predicting which pathogen species are most likely to emerge in the future is an important challenge for infectious disease surveillance and intelligence. We used a machine learning approach to conduct a data-driven horizon scan of bacterial associations at the wildlife–livestock interface for cows, sheep, and pigs. Our model identified and ranked from 76 to 189 potential novel bacterial species that might associate with each livestock species. Wildlife reservoirs of known and novel bacteria were shared among all three species, suggesting that targeting surveillance and/or control efforts towards these reservoirs could contribute disproportionately to reducing spillover risk to livestock. By predicting pathogen-host associations at the wildlife–livestock interface, we demonstrate one way to plan for and prevent disease emergence in livestock.
    Keywords disease surveillance ; environmental health ; infectious diseases ; models ; monitoring ; pathogens ; risk ; sheep ; wildlife
    Language English
    Dates of publication 2022-06
    Size p. 246-258.
    Publishing place Springer US
    Document type Article
    ZDB-ID 2164327-1
    ISSN 1612-9210 ; 1612-9202
    ISSN (online) 1612-9210
    ISSN 1612-9202
    DOI 10.1007/s10393-022-01599-3
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    In stock of ZB MED Bonn / Germany

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  7. Article ; Online: A semi-parametric, state-space compartmental model with time-dependent parameters for forecasting COVID-19 cases, hospitalizations and deaths.

    O'Dea, Eamon B / Drake, John M

    Journal of the Royal Society, Interface

    2022  Volume 19, Issue 187, Page(s) 20210702

    Abstract: Short-term forecasts of the dynamics of coronavirus disease 2019 (COVID-19) in the period up to its decline following mass vaccination was a task that received much attention but proved difficult to do with high accuracy. However, the availability of ... ...

    Abstract Short-term forecasts of the dynamics of coronavirus disease 2019 (COVID-19) in the period up to its decline following mass vaccination was a task that received much attention but proved difficult to do with high accuracy. However, the availability of standardized forecasts and versioned datasets from this period allows for continued work in this area. Here, we introduce the Gaussian infection state space with time dependence (GISST) forecasting model. We evaluate its performance in one to four weeks ahead forecasts of COVID-19 cases, hospital admissions and deaths in the state of California made with official reports of COVID-19, Google's mobility reports and vaccination data available each week. Evaluation of these forecasts with a weighted interval score shows them to consistently outperform a naive baseline forecast and often score closer to or better than a high-performing ensemble forecaster. The GISST model also provides parameter estimates for a compartmental model of COVID-19 dynamics, includes a regression submodel for the transmission rate and allows for parameters to vary over time according to a random walk. GISST provides a novel, balanced combination of computational efficiency, model interpretability and applicability to large multivariate datasets that may prove useful in improving the accuracy of infectious disease forecasts.
    MeSH term(s) COVID-19 ; Epidemiological Models ; Forecasting ; Hospitalization ; Humans ; SARS-CoV-2
    Language English
    Publishing date 2022-02-16
    Publishing country England
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2156283-0
    ISSN 1742-5662 ; 1742-5689
    ISSN (online) 1742-5662
    ISSN 1742-5689
    DOI 10.1098/rsif.2021.0702
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: An open-access database of infectious disease transmission trees to explore superspreader epidemiology.

    Taube, Juliana C / Miller, Paige B / Drake, John M

    PLoS biology

    2022  Volume 20, Issue 6, Page(s) e3001685

    Abstract: Historically, emerging and reemerging infectious diseases have caused large, deadly, and expensive multinational outbreaks. Often outbreak investigations aim to identify who infected whom by reconstructing the outbreak transmission tree, which visualizes ...

    Abstract Historically, emerging and reemerging infectious diseases have caused large, deadly, and expensive multinational outbreaks. Often outbreak investigations aim to identify who infected whom by reconstructing the outbreak transmission tree, which visualizes transmission between individuals as a network with nodes representing individuals and branches representing transmission from person to person. We compiled a database, called OutbreakTrees, of 382 published, standardized transmission trees consisting of 16 directly transmitted diseases ranging in size from 2 to 286 cases. For each tree and disease, we calculated several key statistics, such as tree size, average number of secondary infections, the dispersion parameter, and the proportion of cases considered superspreaders, and examined how these statistics varied over the course of each outbreak and under different assumptions about the completeness of outbreak investigations. We demonstrated the potential utility of the database through 2 short analyses addressing questions about superspreader epidemiology for a variety of diseases, including Coronavirus Disease 2019 (COVID-19). First, we found that our transmission trees were consistent with theory predicting that intermediate dispersion parameters give rise to the highest proportion of cases causing superspreading events. Additionally, we investigated patterns in how superspreaders are infected. Across trees with more than 1 superspreader, we found preliminary support for the theory that superspreaders generate other superspreaders. In sum, our findings put the role of superspreading in COVID-19 transmission in perspective with that of other diseases and suggest an approach to further research regarding the generation of superspreaders. These data have been made openly available to encourage reuse and further scientific inquiry.
    MeSH term(s) COVID-19/epidemiology ; Decision Trees ; Disease Outbreaks ; Disease Transmission, Infectious ; Humans
    Language English
    Publishing date 2022-06-22
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2126776-5
    ISSN 1545-7885 ; 1544-9173
    ISSN (online) 1545-7885
    ISSN 1544-9173
    DOI 10.1371/journal.pbio.3001685
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    Zs.A 6193: Show issues Location:
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  9. Article ; Online: Season and prey identity mediate the effect of predators on parasites in rodents: a test of the healthy herds hypothesis

    Richards, Robert L. / Conner, L. Mike / Morris, Gail / Drake, John M. / Ezenwa, Vanessa O.

    Oecologia. 2023 Jan., v. 201, no. 1 p.107-118

    2023  

    Abstract: The healthy herds hypothesis (HHH) suggests that predators decrease parasitism in their prey. Repeated tests of this hypothesis across a range of taxa and ecosystems have revealed significant variation in the effect of predators on parasites in prey. ... ...

    Abstract The healthy herds hypothesis (HHH) suggests that predators decrease parasitism in their prey. Repeated tests of this hypothesis across a range of taxa and ecosystems have revealed significant variation in the effect of predators on parasites in prey. Differences in the response to predators (1) between prey taxa, (2) between seasons, and (3) before and after catastrophic disturbance are common in natural systems, but typically ignored in empirical tests of the HHH. We used a predator exclusion experiment to measure the effect of these heterogeneities on the tri-trophic interaction among predators, parasites and prey. We experimentally excluded mammalian predators from the habitats of hispid cotton rats (Sigmodon hispidus) and cotton mice (Peromyscus gossypinus) and measured the effect of exclusion on gastrointestinal parasites in these rodents. Our experiment spanned multiple seasons and before and after a prescribed burn. We found that the exclusion of the same predators had opposite effects on the parasites of small mammal prey species. Additionally, we found that the effect of mammal exclusion on parasitism differed before versus after fire disturbance. Finally, we saw that the effect of predator exclusion was highly dependent on prey capture season. Significant effects of exclusion emerged primarily in the fall and winter months. The presence of so many different effects in one relatively simple system suggests that predator effects on parasites in prey are highly context dependent.
    Keywords Peromyscus gossypinus ; Sigmodon hispidus ; cotton ; gastrointestinal system ; parasitism ; prescribed burning ; prey species ; small mammals ; tritrophic interactions
    Language English
    Dates of publication 2023-01
    Size p. 107-118.
    Publishing place Springer Berlin Heidelberg
    Document type Article ; Online
    ZDB-ID 123369-5
    ISSN 1432-1939 ; 0029-8549
    ISSN (online) 1432-1939
    ISSN 0029-8549
    DOI 10.1007/s00442-022-05284-8
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  10. Article ; Online: Protective population behavior change in outbreaks of emerging infectious disease.

    Lodge, Evans K / Schatz, Annakate M / Drake, John M

    BMC infectious diseases

    2021  Volume 21, Issue 1, Page(s) 577

    Abstract: Background: During outbreaks of emerging and re-emerging infections, the lack of effective drugs and vaccines increases reliance on non-pharmacologic public health interventions and behavior change to limit human-to-human transmission. Interventions ... ...

    Abstract Background: During outbreaks of emerging and re-emerging infections, the lack of effective drugs and vaccines increases reliance on non-pharmacologic public health interventions and behavior change to limit human-to-human transmission. Interventions that increase the speed with which infected individuals remove themselves from the susceptible population are paramount, particularly isolation and hospitalization. Ebola virus disease (EVD), Severe Acute Respiratory Syndrome (SARS), and Middle East Respiratory Syndrome (MERS) are zoonotic viruses that have caused significant recent outbreaks with sustained human-to-human transmission.
    Methods: This investigation quantified changing mean removal rates (MRR) and days from symptom onset to hospitalization (DSOH) of infected individuals from the population in seven different outbreaks of EVD, SARS, and MERS, to test for statistically significant differences in these metrics between outbreaks.
    Results: We found that epidemic week and viral serial interval were correlated with the speed with which populations developed and maintained health behaviors in each outbreak.
    Conclusions: These findings highlight intrinsic population-level changes in isolation rates in multiple epidemics of three zoonotic infections with established human-to-human transmission and significant morbidity and mortality. These data are particularly useful for disease modelers seeking to forecast the spread of emerging pathogens.
    MeSH term(s) Animals ; Communicable Disease Control/methods ; Communicable Diseases, Emerging/epidemiology ; Communicable Diseases, Emerging/prevention & control ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Disease Outbreaks ; Epidemics/prevention & control ; Forecasting ; Health Behavior ; Hemorrhagic Fever, Ebola/epidemiology ; Hemorrhagic Fever, Ebola/prevention & control ; Humans ; Public Health ; Severe Acute Respiratory Syndrome/epidemiology ; Severe Acute Respiratory Syndrome/prevention & control ; Zoonoses/epidemiology ; Zoonoses/prevention & control
    Language English
    Publishing date 2021-06-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041550-3
    ISSN 1471-2334 ; 1471-2334
    ISSN (online) 1471-2334
    ISSN 1471-2334
    DOI 10.1186/s12879-021-06299-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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