Browsing by Author "Webb CT"

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    Decision-making for foot-and-mouth disease control: Objectives matter.
    (2016-06) Probert WJM; Shea K; Fonnesbeck CJ; Runge MC; Carpenter TE; Dürr S; Garner MG; Harvey N; Stevenson MA; Webb CT; Werkman M; Tildesley MJ; Ferrari MJ
    Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.
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    Ectoparasite and bacterial population genetics and community structure indicate extent of bat movement across an island chain.
    (Cambridge University Press, 2024-05-24) McKee CD; Peel AJ; Hayman DTS; Suu-Ire R; Ntiamoa-Baidu Y; Cunningham AA; Wood JLN; Webb CT; Kosoy MY
    Few studies have examined the genetic population structure of vector-borne microparasites in wildlife, making it unclear how much these systems can reveal about the movement of their associated hosts. This study examined the complex host-vector-microbe interactions in a system of bats, wingless ectoparasitic bat flies (Nycteribiidae), vector-borne microparasitic bacteria (Bartonella), and bacterial endosymbionts of flies (Enterobacterales) across an island chain in the Gulf of Guinea, West Africa. Limited population structure was found in bat flies and Enterobacterales symbionts compared to that of their hosts. Significant isolation by distance was observed in the dissimilarity of Bartonella communities detected in flies from sampled populations of Eidolon helvum bats. These patterns indicate that, while genetic dispersal of bats between islands is limited, some nonreproductive movements may lead to the dispersal of ectoparasites and associated microbes. This study deepens our knowledge of the phylogeography of African fruit bats, their ectoparasites, and associated bacteria. The results presented could inform models of pathogen transmission in these bat populations and increase our theoretical understanding of community ecology in host-microbe systems.
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    Utility of mosquito surveillance data for spatial prioritization of vector control against dengue viruses in three Brazilian cities
    (BioMed Central, 2015-12) Pepin KM; Leach CB; Marques-Toledo C; Laass KH; Paixao KS; Luis AD; Hayman DTS; Johnson NG; Buhnerkempe MG; Carver S; Grear DA; Tsao K; Eiras AE; Webb CT
    BACKGROUND: Vector control remains the primary defense against dengue fever. Its success relies on the assumption that vector density is related to disease transmission. Two operational issues include the amount by which mosquito density should be reduced to minimize transmission and the spatio-temporal allotment of resources needed to reduce mosquito density in a cost-effective manner. Recently, a novel technology, MI-Dengue, was implemented city-wide in several Brazilian cities to provide real-time mosquito surveillance data for spatial prioritization of vector control resources. We sought to understand the role of city-wide mosquito density data in predicting disease incidence in order to provide guidance for prioritization of vector control work. METHODS: We used hierarchical Bayesian regression modeling to examine the role of city-wide vector surveillance data in predicting human cases of dengue fever in space and time. We used four years of weekly surveillance data from Vitoria city, Brazil, to identify the best model structure. We tested effects of vector density, lagged case data and spatial connectivity. We investigated the generality of the best model using an additional year of data from Vitoria and two years of data from other Brazilian cities: Governador Valadares and Sete Lagoas. RESULTS: We found that city-wide, neighborhood-level averages of household vector density were a poor predictor of dengue-fever cases in the absence of accounting for interactions with human cases. Effects of city-wide spatial patterns were stronger than within-neighborhood or nearest-neighborhood effects. Readily available proxies of spatial relationships between human cases, such as economic status, population density or between-neighborhood roadway distance, did not explain spatial patterns in cases better than unweighted global effects. CONCLUSIONS: For spatial prioritization of vector controls, city-wide spatial effects should be given more weight than within-neighborhood or nearest-neighborhood connections, in order to minimize city-wide cases of dengue fever. More research is needed to determine which data could best inform city-wide connectivity. Once these data become available, MI-dengue may be even more effective if vector control is spatially prioritized by considering city-wide connectivity between cases together with information on the location of mosquito density and infected mosquitos.