Dataset Information

Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

ABSTRACT: Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. Three models based on measures of vegetation, habitat patch characteristics, and herbaceous landcover emerged as effective predictors of observed disease and vector distribution. An ensemble model containing these three models improved precision and predictive ability over individual models. A priori assessment of qualitative model characteristics effectively identified models that subsequently emerged as better predictors in quantitative analysis. Both a methodology for quantitative model comparison and a checklist for qualitative assessment of candidate models for extrapolation are provided; both tools aim to improve collaboration between those producing models and those interested in applying them to new areas and research questions.

SUBMITTER: Lorenz A

PROVIDER: S-EPMC4114569 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

Lorenz Alyson A Dhingra Radhika R Chang Howard H HH Bisanzio Donal D Liu Yang Y Remais Justin V JV

PloS one 20140729 7

Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted coun ...[more]

PMID: 25072884

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Project description:After a request from the European Commission, EFSA's Panel on Animal Health and Welfare summarised the main characteristics of 36 vector-borne diseases (VBDs) in https://efsa.maps.arcgis.com/apps/PublicGallery/index.html?appid=dfbeac92aea944599ed1eb754aa5e6d1. The risk of introduction in the EU through movement of livestock or pets was assessed for each of the 36 VBDs individually, using a semiquantitative Method to INTegrate all relevant RISK aspects (MINTRISK model), which was further modified to a European scale into the http://www3.lei.wur.nl/mintrisk/ModelMgt.aspx. Only eight of the 36 VBD-agents had an overall rate of introduction in the EU (being the combination of the rate of entry, vector transmission and establishment) which was estimated to be above 0.001 introductions per year. These were Crimean-Congo haemorrhagic fever virus, bluetongue virus, West Nile virus, Schmallenberg virus, Hepatozoon canis, Leishmania infantum, Bunyamwera virus and Highlands J. virus. For these eight diseases, the annual extent of spread was assessed, assuming the implementation of available, authorised prevention and control measures in the EU. Further, the probability of overwintering was assessed, as well as the possible impact of the VBDs on public health, animal health and farm production. For the other 28 VBD-agents for which the rate of introduction was estimated to be very low, no further assessments were made. Due to the uncertainty related to some parameters used for the risk assessment or the instable or unpredictability disease situation in some of the source regions, it is recommended to update the assessment when new information becomes available. Since this risk assessment was carried out for large regions in the EU for many VBD-agents, it should be considered as a first screening. If a more detailed risk assessment for a specific VBD is wished for on a national or subnational level, the EFSA-VBD-RISK-model is freely available for this purpose.

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Project description:BackgroundTriatomine bugs transmit Chagas disease across Latin America, where vector control-surveillance is increasingly decentralized. Locally run systems often deal with highly diverse native-vector faunas-plus, in some areas, domestic populations of non-native species. Flexible entomological-risk indicators that cover native and non-native vectors and can support local decision-making are therefore needed.MethodsWe present a local-scale entomological-risk score ("TriatoScore") that leverages and builds upon information on the ecology-behavior and distribution-biogeography of individual triatomine bug species. We illustrate our approach by calculating TriatoScores for the 417 municipalities of Bahia state, Brazil. For this, we (i) listed all triatomine bug species recorded statewide; (ii) derived a "species relevance score" reflecting whether each species is native/non-native and, if native, whether/how often it invades/colonizes dwellings; (iii) mapped each species' presence by municipality; (iv) for native vectors, weighted presence by the proportion of municipal territory within ecoregions occupied by each species; (v) multiplied "species relevance score" × "weighted presence" to get species-specific "weighted scores"; and (vi) summed "weighted scores" across species to get municipal TriatoScores. Using standardized TriatoScores, we then grouped municipalities into high/moderate/low entomological-risk strata.ResultsTriatoScores were higher in municipalities dominated by dry-to-semiarid ecoregions than in those dominated by savanna-grassland or, especially, moist-forest ecoregions. Bahia's native triatomines can maintain high to moderate risk of vector-borne Chagas disease in 318 (76.3%) municipalities. Historical elimination of Triatoma infestans from 125 municipalities reduced TriatoScores by ~ 27% (range, 20-44%); eight municipalities reported T. infestans since Bahia was certified free of Trypanosoma cruzi transmission by this non-native species. Entomological-risk strata based on TriatoScores agreed well with Bahia's official disease-risk strata, but TriatoScores suggest that the official classification likely underestimates risk in 42 municipalities. Of 152 municipalities failing to report triatomines in 2006-2019, two and 71 had TriatoScores corresponding to, respectively, high and moderate entomological risk.ConclusionsTriatoScore can help control-surveillance managers to flexibly assess and stratify the entomological risk of Chagas disease at operationally relevant scales. Integrating eco-epidemiological, demographic, socioeconomic, or operational data (on, e.g., local-scale dwelling-infestation or vector-infection frequencies, land-use change and urbanization, housing conditions, poverty, or the functioning of control-surveillance systems) is also straightforward. TriatoScore may thus become a useful addition to the triatomine bug control-surveillance toolbox.

Dataset Information

Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

Publications

Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

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