Surveillance of vector-borne pathogens under imperfect detection: lessons from Chagas disease risk (mis)measurement
| Autor: | Rodrigo Gurgel-Gonçalves, César Augusto Cuba Cuba, Camila Santana, Thaís Tâmara Castro Minuzzi-Souza, Mariana Hecht, Tamires Vital, Marcelo Santalucia, Monique Knox, Marcelle Ribeiro, Fernando Abad-Franch, Luciana Hagström, Nadjar Nitz, Marcos Takashi Obara |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Chagas disease medicine.medical_specialty Pathogen detection 030231 tropical medicine lcsh:Medicine Article 03 medical and health sciences Human health 0302 clinical medicine Epidemiology parasitic diseases medicine lcsh:Science Trypanosoma cruzi Disease surveillance Multidisciplinary biology business.industry lcsh:R medicine.disease biology.organism_classification Virology 030104 developmental biology Vector (epidemiology) lcsh:Q Disease prevention business |
| Zdroj: | Scientific Reports Scientific Reports, Vol 8, Iss 1, Pp 1-10 (2018) |
| ISSN: | 2045-2322 |
| Popis: | Vector-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 identified T. cruzi in Giemsa-stained slides. qPCR was >99% sensitive and specific, whereas cPCR was ~100% specific 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|