Abstract
Correct identification of triatomine bugs is crucial for Chagas disease surveillance, yet available taxonomic keys are outdated, incomplete, or both. Here we present TriatoDex, an Android app-based pictorial, annotated, polytomous key to the Triatominae. TriatoDex was developed using Android Studio and tested by 27 Brazilian users. Each user received a box with pinned, number-labeled, adult triatomines (33 species in total) and was asked to identify each bug to the species level. We used generalized linear mixed models (with user- and species-ID random effects) and information-theoretic model evaluation/averaging to investigate TriatoDex performance. TriatoDex encompasses 79 questions and 554 images of the 150 triatomine-bug species described worldwide up to 2017. TriatoDex-based identification was correct in 78.9% of 824 tasks. TriatoDex performed better in the hands of trained taxonomists (93.3% vs. 72.7% correct identifications; model-averaged, adjusted odds ratio 5.96, 95% confidence interval [CI] 3.09-11.48). In contrast, user age, gender, primary job (including academic research/teaching or disease surveillance), workplace (including universities, a reference laboratory for triatomine-bug taxonomy, or disease-surveillance units), and basic training (from high school to biology) all had negligible effects on TriatoDex performance. Our analyses also suggest that, as TriatoDex results accrue to cover more taxa, they may help pinpoint triatomine-bug species that are consistently harder (than average) to identify. In a pilot comparison with a standard, printed key (370 tasks by seven users), TriatoDex performed similarly (84.5% correct assignments, CI 68.9-94.0%), but identification was 32.8% (CI 24.7-40.1%) faster on average-for a mean absolute saving of ~2.3 minutes per bug-identification task. TriatoDex holds much promise as a handy, flexible, and reliable tool for triatomine-bug identification; an updated iOS/Android version is under development. We expect that, with continuous refinement derived from evolving knowledge and user feedback, TriatoDex will substantially help strengthen both entomological surveillance and research on Chagas disease vectors.
Highlights
The correct identification of pathogen vectors is critical both for understanding disease dynamics and for effective disease control and surveillance
Female a Users who received specific training in triatomine-bug taxonomy. b Users working at a national reference laboratory for triatomine-bug taxonomy. c In our main analyses, we focused on getting estimates of TRIATODEX performance for users primarily involved in health surveillance (‘Surveillance’ vs. the rest) and primarily involved in academic research/teaching (‘Researcher’ plus ‘Graduate student’ vs. the rest). d Users who participated in the comparison of TRIATODEX with a standard printed key
In its current version (August 2020), which is the one we used in performance trials, TRIATODEX covers the 150 triatomine-bug species described up to 2017 (S1 Table); for each species but T. gomeznunezi, the app features a dorsal picture of an adult specimen and a coarse distribution map
Summary
The correct identification of pathogen vectors is critical both for understanding disease dynamics and for effective disease control and surveillance. Vector identification has traditionally relied on printed dichotomous keys based on morphological characters (e.g., [1,2,3]). Standard printed keys are being superseded by electronic alternatives [4]. TriatoKey [10] is an electronic key to 42 triatomine-bug species recorded in Brazil; it was developed to support identification by nonspecialist disease-surveillance and community-health technicians [10]. Electronic keys based on smartphone technology should be especially helpful for identifying vectors in the field. This may help enhance surveillance by professional staff and is opening disease-vector surveillance to citizen science [11,12,13]
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