Modeling Disease Vector Occurrence When Detection Is Imperfect II: Drivers of Site-Occupancy by Synanthropic Triatoma brasiliensis in the Brazilian Northeast
Carolina Valença-Barbosa,
Marli M Lima,
Otília Sarquis,
Claudia M Bezerra and
Fernando Abad-Franch
PLOS Neglected Tropical Diseases, 2014, vol. 8, issue 5, 1-12
Abstract:
Background: Understanding the drivers of habitat selection by insect disease vectors is instrumental to the design and operation of rational control-surveillance systems. One pervasive yet often overlooked drawback of vector studies is that detection failures result in some sites being misclassified as uninfested; naïve infestation indices are therefore biased, and this can confound our view of vector habitat preferences. Here, we present an initial attempt at applying methods that explicitly account for imperfect detection to investigate the ecology of Chagas disease vectors in man-made environments. Methodology: We combined triplicate-sampling of individual ecotopes (n = 203) and site-occupancy models (SOMs) to test a suite of pre-specified hypotheses about habitat selection by Triatoma brasiliensis. SOM results were compared with those of standard generalized linear models (GLMs) that assume perfect detection even with single bug-searches. Principal Findings: Triatoma brasiliensis was strongly associated with key hosts (native rodents, goats/sheep and, to a lesser extent, fowl) in peridomestic environments; ecotope structure had, in comparison, small to negligible effects, although wooden ecotopes were slightly preferred. We found evidence of dwelling-level aggregation of infestation foci; when there was one such focus, same-dwelling ecotopes, whether houses or peridomestic structures, were more likely to become infested too. GLMs yielded negatively-biased covariate effect estimates and standard errors; both were, on average, about four times smaller than those derived from SOMs. Conclusions/Significance: Our results confirm substantial population-level ecological heterogeneity in T. brasiliensis. They also suggest that, at least in some sites, control of this species may benefit from peridomestic rodent control and changes in goat/sheep husbandry practices. Finally, our comparative analyses highlight the importance of accounting for the various sources of uncertainty inherent to vector studies, including imperfect detection. We anticipate that future research on infectious disease ecology will increasingly rely on approaches akin to those described here. Author Summary: Chagas disease prevention depends on the control of its insect vectors — large blood-sucking bugs called triatomines. One commonly neglected problem of vector studies is imperfect detection, whereby some sites are mistakenly classified as uninfested. We address this drawback by combining repeated sampling of ‘ecotopes’ (houses, fowl-houses, corrals, woodpiles, etc.) with models that accommodate detection failures to study habitat selection by a major vector, Triatoma brasiliensis. Triatoma brasiliensis was strongly associated with peridomestic rodents and goats/sheep. We found little support to the conventional view that T. brasiliensis prefers stone-like habitats; at least in our study setting, host availability was much more important than ecotope structure, and, overall, wooden habitats (timber piles or wood-fenced corrals) were slightly favored. The risk of infestation in any individual ecotope increased when another ecotope in the same dwelling was also infested; this increase was the same for houses and for peridomestic structures. These findings suggest that management of peridomestic animals, and especially rodents and goats, could help mitigate the risk of dwelling and house infestation by T. brasiliensis. In sum, our study demonstrates how relatively simple but sound sampling and analytical approaches can critically enhance our understanding of disease ecology by explicitly accounting for imperfect detection.
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pntd00:0002861
DOI: 10.1371/journal.pntd.0002861
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