title: Modeling disease vector occurrence when detection is imperfect II: Drivers of site-occupancy by synanthropic Triatoma brasiliensis in the Brazilian northeast.
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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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
  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.
authors.affiliation: Chagas Disease Eco-epidemiology Laboratory, Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil.
authors.forename: Carolina
authors.initials: C
authors.lastname: Valença-Barbosa
authors.affiliation: Chagas Disease Eco-epidemiology Laboratory, Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil.
authors.forename: Marli M
authors.initials: MM
authors.lastname: Lima
authors.affiliation: Chagas Disease Eco-epidemiology Laboratory, Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil.
authors.forename: Otília
authors.initials: O
authors.lastname: Sarquis
authors.affiliation: Secretaria Estadual de Saúde do Ceará, Fortaleza, Brazil.
authors.forename: Claudia M
authors.initials: CM
authors.lastname: Bezerra
authors.affiliation: Infectious Disease Ecology Laboratory, Instituto Leônidas e Maria Deane - Fiocruz, Manaus, Brazil.
authors.forename: Fernando
authors.initials: F
authors.lastname: Abad-Franch
mesh_terms: D000818:Animals; D001938:Brazil; D014355:Chagas Disease / Q000635:transmission; D017753:Ecosystem; D007303:Insect Vectors / Q000502:physiology*; D016014:Linear Models; D008954:Models, Biological; D012377:Rodentia; D012418:Ruminants; D014224:Triatoma / Q000502:physiology*