Surveillance of vector-borne pathogens under imperfect detection: lessons from Chagas disease risk (mis)measurement

dc.creatorSouza, Thaís Tâmara Castro Minuzzi
dc.creatorNitz, Nadjar
dc.creatorCuba, César Augusto Cuba
dc.creatorHagström, Luciana
dc.creatorHecht, Mariana Machado
dc.creatorSantana, Camila
dc.creatorRibeiro, Marcelle
dc.creatorVital, Tamires Emanuele
dc.creatorSantalucia, Marcelo
dc.creatorKnox, Monique
dc.creatorObara, Marcos Takashi
dc.creatorFranch, Fernando Abad
dc.creatorGonçalves, Rodrigo Gurgel
dc.date2018-03-05T13:20:37Z
dc.date2018-03-05T13:20:37Z
dc.date2018
dc.date.accessioned2023-09-26T20:22:42Z
dc.date.available2023-09-26T20:22:42Z
dc.identifierSOUZA, Thaís Tâmara Castro Minuzzi et al. Surveillance of vector-borne pathogens under imperfect detection: lessons from Chagas disease risk (mis)measurement. Sci Rep., v. 8, n. 1, art. 151, 2018.
dc.identifier2045-2322
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/25050
dc.identifier10.1038/s41598-017-18532-2
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8855543
dc.descriptionVector-borne pathogens threaten human health worldwide. Despite their critical role in disease prevention, routine surveillance systems often rely on low-complexity pathogen detection tests of uncertain accuracy. In Chagas disease surveillance, optical microscopy (OM) is routinely used for detecting Trypanosoma cruzi in its vectors. Here, we use replicate T. cruzi detection data and hierarchical site-occupancy models to assess the reliability of OM-based T. cruzi surveillance while explicitly accounting for false-negative and false-positive results. We investigated 841 triatomines with OM slides (1194 fresh, 1192 Giemsa-stained) plus conventional (cPCR, 841 assays) and quantitative PCR (qPCR, 1682 assays). Detections were considered unambiguous only when parasitologists unmistakably identifed T. cruzi in Giemsa-stained slides. qPCR was >99% sensitive and specifc, whereas cPCR was ~100% specifc but only ~55% sensitive. In routine surveillance, examination of a single OM slide per vector missed ~50–75% of infections and wrongly scored as infected ~7% of the bugs. qPCR-based and model-based infection frequency estimates were nearly three times higher, on average, than OM-based indices. We conclude that the risk of vector-borne Chagas disease may be substantially higher than routine surveillance data suggest. The hierarchical modelling approach we illustrate can help enhance vector-borne disease surveillance systems when pathogen detection is imperfect
dc.description2023-01-01
dc.formatapplication/pdf
dc.languageeng
dc.publisherNature
dc.rightsrestricted access
dc.subjectDoença de Chagas
dc.subjectT. cruzi
dc.subjectChagas disease
dc.subjectVector-borne
dc.titleSurveillance of vector-borne pathogens under imperfect detection: lessons from Chagas disease risk (mis)measurement
dc.typeArticle


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