Dataset Information

A new methodology for sampling blackflies for the entomological surveillance of onchocerciasis in Brazil.

ABSTRACT: The effectiveness of the MosqTent® trap was evaluated in endemic area to onchocerciasis in Brazil. This study seeks to provide subsidies for the monitoring of the onchocerciasis transmission in the country. The study was carried out at the Homoxi and Thirei villages, located in the Yanomami Indigenous Land, in the state of Roraima. This area presents hyperendemicity, high blackflies densities, large population migrations and mining activities. The Homoxi and Thirei villages are assisted by the Brazilian Ministry of Health. To conduct the present study, the village leader, health leaders and the Brazilian Ethics Committee were consulted. Blackflies captures were carried out simultaneously at the Homoxi and Thirei, using systematized methods to allow for comparisons between the traditional Human Landing Catch (HLC) and HLC protected by the MosqTent®. The female blackflies were captured at two equidistant capture stations per locality, by two collectors per station, for five consecutive days. Individuals captured by interval/station/day were counted, identified and maintained at -20°C. The underlying probability distributions and the differences between the methods for the independent sample data were verified in a comparative statistical analysis between the use of the MosqTent® and the HLC. A total of 10,855 antropophilic blackflies were captured by both methodologies. A total of 7,367 (67.87%) blackflies belonging to seven species were captured by MosqTent® -Simulium incrustatum s.l (99.06%); S. guianense s.l (0.74%), S. oyapockense s.l (0.01%), S. exiguum (0.10%), S. metallicum (0.05%), S. ochraceum (0.03%) and S. minusculum s.l (0.01%). Moreover, 3,488 (32.14%) blackflies belonging to four species were captured by HLC-S. incrustatum s.l (98.33%); S. guianense s.l (1.38%), S. oyapockense s.l (0.26%) and S. metallicum (0.03%). The MosqTent® was more effective and efficient when compared to HLC. When comparing total blackflies captured/day, the MosqTent® was more efficient than HLC (p = 0.031) with a means of 799.4 blackflies/day versus 217.6 blackflies/day by HLC. The results demonstrated improved performance and high reliability of the MosqTent® compared to the traditional HLC method.

SUBMITTER: Nascimento-Carvalho ESD

PROVIDER: S-EPMC5519025 | biostudies-other | 2017

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Technological advances increase opportunities for novel wildlife survey methods. With increased detection methods, many organizations and agencies are creating habitat suitability models (HSMs) to identify critical habitats and prioritize conservation measures. However, multiple occurrence data types are used independently to create these HSMs with little understanding of how biases inherent to those data might impact HSM efficacy. We sought to understand how different data types can influence HSMs using three bat species (Lasiurus borealis, Lasiurus cinereus, and Perimyotis subflavus). We compared the overlap of models created from passive-only (acoustics), active-only (mist-netting and wind turbine mortalities), and combined occurrences to identify the effect of multiple data types and detection bias. For each species, the active-only models had the highest discriminatory ability to tell occurrence from background points and for two of the three species, active-only models preformed best at maximizing the discrimination between presence and absence values. By comparing the niche overlaps of HSMs between data types, we found a high amount of variation with no species having over 45% overlap between the models. Passive models showed more suitable habitat in agricultural lands, while active models showed higher suitability in forested land, reflecting sampling bias. Overall, our results emphasize the need to carefully consider the influences of detection and survey biases on modeling, especially when combining multiple data types or using single data types to inform management interventions. Biases from sampling, behavior at the time of detection, false positive rates, and species life history intertwine to create striking differences among models. The final model output should consider biases of each detection type, particularly when the goal is to inform management decisions, as one data type may support very different management strategies than another.

Dataset Information

A new methodology for sampling blackflies for the entomological surveillance of onchocerciasis in Brazil.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets