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  1. Artikel: Accurately summarizing an outbreak using epidemiological models takes time.

    Case, B K M / Young, Jean-Gabriel / Hébert-Dufresne, Laurent

    Royal Society open science

    2023  Band 10, Heft 9, Seite(n) 230634

    Abstract: Recent outbreaks of Mpox and Ebola, and worrying waves of COVID-19, influenza and respiratory syncytial virus, have all led to a sharp increase in the use of epidemiological models to estimate key epidemiological parameters. The feasibility of this ... ...

    Abstract Recent outbreaks of Mpox and Ebola, and worrying waves of COVID-19, influenza and respiratory syncytial virus, have all led to a sharp increase in the use of epidemiological models to estimate key epidemiological parameters. The feasibility of this estimation task is known as the practical identifiability (PI) problem. Here, we investigate the PI of eight commonly reported statistics of the classic susceptible-infectious-recovered model using a new measure that shows how much a researcher can expect to learn in a model-based Bayesian analysis of prevalence data. Our findings show that the basic reproductive number and final outbreak size are often poorly identified, with learning exceeding that of individual model parameters only in the early stages of an outbreak. The peak intensity, peak timing and initial growth rate are better identified, being in expectation over 20 times more probable having seen the data by the time the underlying outbreak peaks. We then test PI for a variety of true parameter combinations and find that PI is especially problematic in slow-growing or less-severe outbreaks. These results add to the growing body of literature questioning the reliability of inferences from epidemiological models when limited data are available.
    Sprache Englisch
    Erscheinungsdatum 2023-09-27
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2787755-3
    ISSN 2054-5703
    ISSN 2054-5703
    DOI 10.1098/rsos.230634
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: Adapting vector surveillance using Bayesian experimental design: An application to an ongoing tick monitoring program in the southeastern United States.

    Case, B K M / Dye-Braumuller, Kyndall C / Evans, Chris / Li, Huixuan / Rustin, Lauren / Nolan, Melissa S

    Ticks and tick-borne diseases

    2024  Band 15, Heft 3, Seite(n) 102329

    Abstract: Maps of the distribution of medically-important ticks throughout the US remain lacking in spatial and temporal resolution in many areas, leading to holes in our understanding of where and when people are at risk of tick encounters, an important baseline ... ...

    Abstract Maps of the distribution of medically-important ticks throughout the US remain lacking in spatial and temporal resolution in many areas, leading to holes in our understanding of where and when people are at risk of tick encounters, an important baseline for informing public health response. In this work, we demonstrate the use of Bayesian Experimental Design (BED) in planning spatiotemporal surveillance of disease vectors. We frame survey planning as an optimization problem with the objective of identifying a calendar of sampling locations that maximizes the expected information regarding some goal. Here we consider the goals of understanding associations between environmental factors and tick presence and minimizing uncertainty in high risk areas. We illustrate our proposed BED workflow using an ongoing tick surveillance study in South Carolina parks. Following a model comparison study based on two years of initial data, several techniques for finding optimal surveys were compared to random sampling. Two optimization algorithms found surveys better than all replications of random sampling, while a space-filling heuristic performed favorably as well. Further, optimal surveys of just 20 visits were more effective than repeating the schedule of 111 visits used in 2021. We conclude that BED shows promise as a flexible and rigorous means of survey design for vector control, and could help alleviate pressure on local agencies by limiting the resources necessary for accurate information on arthropod distributions. We have made the code for our BED workflow publicly available on Zenodo to help promote the application of these methods to future surveillance efforts.
    Mesh-Begriff(e) Animals ; Humans ; United States ; Ticks ; Bayes Theorem ; Southeastern United States/epidemiology
    Sprache Englisch
    Erscheinungsdatum 2024-03-13
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ZDB-ID 2541872-5
    ISSN 1877-9603 ; 1877-959X
    ISSN (online) 1877-9603
    ISSN 1877-959X
    DOI 10.1016/j.ttbdis.2024.102329
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Buch ; Online: Accurately summarizing an outbreak using epidemiological models takes time

    Case, B. K. M. / Young, Jean-Gabriel / Hébert-Dufresne, Laurent

    2023  

    Abstract: Recent outbreaks of monkeypox and Ebola, and worrying waves of COVID-19, influenza and respiratory syncytial virus, have all led to a sharp increase in the use of epidemiological models to estimate key epidemiological parameters. The feasibility of this ... ...

    Abstract Recent outbreaks of monkeypox and Ebola, and worrying waves of COVID-19, influenza and respiratory syncytial virus, have all led to a sharp increase in the use of epidemiological models to estimate key epidemiological parameters. The feasibility of this estimation task is known as the practical identifiability (PI) problem. Here, we investigate the PI of eight commonly reported statistics of the classic Susceptible-Infectious-Recovered model using a new measure that shows how much a researcher can expect to learn in a model-based Bayesian analysis of prevalence data. Our findings show that the basic reproductive number and final outbreak size are often poorly identified, with learning exceeding that of individual model parameters only in the early stages of an outbreak. The peak intensity, peak timing, and initial growth rate are better identified, being in expectation over 20 times more probable having seen the data by the time the underlying outbreak peaks. We then test PI for a variety of true parameter combinations, and find that PI is especially problematic in slow-growing or less-severe outbreaks. These results add to the growing body of literature questioning the reliability of inferences from epidemiological models when limited data are available.

    Comment: 7 pages, 4 figures
    Schlagwörter Quantitative Biology - Populations and Evolution ; Mathematics - Dynamical Systems ; Physics - Data Analysis ; Statistics and Probability ; Physics - Physics and Society ; Statistics - Methodology
    Thema/Rubrik (Code) 310
    Erscheinungsdatum 2023-01-20
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: The unintended consequences of inconsistent closure policies and mobility restrictions during epidemics.

    Althouse, Benjamin M / Wallace, Brendan / Case, B K M / Scarpino, Samuel V / Allard, Antoine / Berdahl, Andrew M / White, Easton R / Hébert-Dufresne, Laurent

    BMC global and public health

    2023  Band 1, Heft 1, Seite(n) 28

    Abstract: Background: Controlling the spread of infectious diseases-even when safe, transmission-blocking vaccines are available-may require the effective use of non-pharmaceutical interventions (NPIs), e.g., mask wearing, testing, limits on group sizes, venue ... ...

    Abstract Background: Controlling the spread of infectious diseases-even when safe, transmission-blocking vaccines are available-may require the effective use of non-pharmaceutical interventions (NPIs), e.g., mask wearing, testing, limits on group sizes, venue closure. During the SARS-CoV-2 pandemic, many countries implemented NPIs inconsistently in space and time. This inconsistency was especially pronounced for policies in the United States of America (US) related to venue closure.
    Methods: Here, we investigate the impact of inconsistent policies associated with venue closure using mathematical modeling and high-resolution human mobility, Google search, and county-level SARS-CoV-2 incidence data from the USA. Specifically, we look at high-resolution location data and perform a US-county-level analysis of nearly 8 million SARS-CoV-2 cases and 150 million location visits, including 120 million church visitors across 184,677 churches, 14 million grocery visitors across 7662 grocery stores, and 13.5 million gym visitors across 5483 gyms.
    Results: Analyzing the interaction between venue closure and changing mobility using a mathematical model shows that, across a broad range of model parameters, inconsistent or partial closure can be worse in terms of disease transmission as compared to scenarios with no closures at all. Importantly, changes in mobility patterns due to epidemic control measures can lead to increase in the future number of cases. In the most severe cases, individuals traveling to neighboring jurisdictions with different closure policies can result in an outbreak that would otherwise have been contained. To motivate our mathematical models, we turn to mobility data and find that while stay-at-home orders and closures decreased contacts in most areas of the USA, some specific activities and venues saw an increase in attendance and an increase in the distance visitors traveled to attend. We support this finding using search query data, which clearly shows a shift in information seeking behavior concurrent with the changing mobility patterns.
    Conclusions: While coarse-grained observations are not sufficient to validate our models, taken together, they highlight the potential unintended consequences of inconsistent epidemic control policies related to venue closure and stress the importance of balancing the societal needs of a population with the risk of an outbreak growing into a large epidemic.
    Supplementary information: The online version contains supplementary material available at 10.1186/s44263-023-00028-z.
    Sprache Englisch
    Erscheinungsdatum 2023-12-04
    Erscheinungsland England
    Dokumenttyp Journal Article
    ISSN 2731-913X
    ISSN (online) 2731-913X
    DOI 10.1186/s44263-023-00028-z
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel ; Online: Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata.

    Case, B K M / Young, Jean-Gabriel / Penados, Daniel / Monroy, Carlota / Hébert-Dufresne, Laurent / Stevens, Lori

    PLoS neglected tropical diseases

    2022  Band 16, Heft 6, Seite(n) e0010436

    Abstract: Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an ... ...

    Abstract Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an approach emphasizing community feedback and housing improvements has been shown to yield lasting results. However, the additional resources and personnel required by such an intervention likely hinders its widespread adoption. One solution to this problem would be to target only a subset of houses in a community while still eliminating enough infestations to interrupt disease transfer. Here we develop a sequential sampling framework that adapts to information specific to a community as more houses are visited, thereby allowing us to efficiently find homes with domiciliary vectors while minimizing sampling bias. The method fits Bayesian geostatistical models to make spatially informed predictions, while gradually transitioning from prioritizing houses based on prediction uncertainty to targeting houses with a high risk of infestation. A key feature of the method is the use of a single exploration parameter, α, to control the rate of transition between these two design targets. In a simulation study using empirical data from five villages in southeastern Guatemala, we test our method using a range of values for α, and find it can consistently select fewer homes than random sampling, while still bringing the village infestation rate below a given threshold. We further find that when additional socioeconomic information is available, much larger savings are possible, but that meeting the target infestation rate is less consistent, particularly among the less exploratory strategies. Our results suggest new options for implementing long-term T. dimidiata control.
    Mesh-Begriff(e) Animals ; Bayes Theorem ; Chagas Disease/epidemiology ; Chagas Disease/prevention & control ; Disease Vectors ; Insecticides ; Triatoma
    Chemische Substanzen Insecticides
    Sprache Englisch
    Erscheinungsdatum 2022-06-02
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2429704-5
    ISSN 1935-2735 ; 1935-2735
    ISSN (online) 1935-2735
    ISSN 1935-2735
    DOI 10.1371/journal.pntd.0010436
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Buch ; Online: Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata

    Case, B. K. M. / Young, Jean-Gabriel / Penados, Daniel / Monroy, Carlota / Hébert-Dufresne, Laurent / Stevens, Lori

    2021  

    Abstract: Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an ... ...

    Abstract Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an approach emphasizing community feedback and housing improvements has been shown to yield lasting results. However, the additional resources and personnel required by such an intervention likely hinders its widespread adoption. One solution to this problem would be to target only a subset of houses in a community while still eliminating enough infestations to interrupt disease transfer. Here we develop a sequential sampling framework that adapts to information specific to a community as more houses are visited, thereby allowing us to efficiently find homes with domiciliary vectors while minimizing sampling bias. The method fits Bayesian geostatistical models to make spatially informed predictions, while gradually transitioning from prioritizing houses based on prediction uncertainty to targeting houses with a high risk of infestation. A key feature of the method is the use of a single exploration parameter, $\alpha$, to control the rate of transition between these two design targets. In a simulation study using empirical data from five villages in southeastern Guatemala, we test our method using a range of values for $\alpha$, and find it can consistently select fewer homes than random sampling, while still bringing the village infestation rate below a given threshold. We further find that when additional socioeconomic information is available, much larger savings are possible, but that meeting the target infestation rate is less consistent, particularly among the less exploratory strategies. Our results suggest new options for implementing long-term T. dimidiata control.
    Schlagwörter Statistics - Applications ; Quantitative Biology - Populations and Evolution ; Quantitative Biology - Quantitative Methods ; Statistics - Methodology
    Thema/Rubrik (Code) 310
    Erscheinungsdatum 2021-11-10
    Erscheinungsland us
    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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