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A statistical calibration tool for methods used to sample outdoor-biting mosquitoes.

Halfan S Ngowo1,2, Alex J Limwagu3, Heather M Ferguson3,4

  • 1Department of Environmental Health & Ecological Sciences, Ifakara Health Institute, Ifakara, Tanzania. hngowo@ihi.or.tz.

Parasites & Vectors
|August 17, 2022
PubMed
Summary

Improved mosquito traps are needed for disease surveillance. This study developed a statistical framework and calibration tool to predict human-biting rates from exposure-free traps, aiding in assessing outdoor-biting risk.

Keywords:
Biting ratesCalibration toolDensity dependenceMosquitoesOutdoorSampling methods

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Area of Science:

  • Medical Entomology
  • Vector-borne Disease Surveillance
  • Statistical Modeling

Background:

  • Improved methods for sampling outdoor-biting mosquitoes are crucial for effective vector-borne disease surveillance.
  • Existing human landing catch (HLC) methods raise ethical and logistical concerns, necessitating alternative approaches.
  • A common framework for calibrating alternative sampling methods against HLC is required.

Purpose of the Study:

  • To develop and validate a statistical framework for predicting human-biting rates using exposure-free mosquito traps.
  • To create a calibration tool for estimating human exposure based on trap performance.
  • To evaluate the representativeness of different traps in assessing outdoor-biting risk.

Main Methods:

  • A year-long study in Tanzania compared six outdoor traps (SUN, BGS, MTR, MTRC, ITT-C, MMX) against human landing catch (HLC).
  • Generalized linear models within a Bayesian framework were used to analyze mosquito abundance data (Anopheles arabiensis, Anopheles funestus, Culex spp.).
  • Intra- and inter-specific density dependence were incorporated to assess trap associations with HLC.

Main Results:

  • Trap performance varied by mosquito taxa; no single trap was optimal for all species.
  • For An. arabiensis, Suna Trap (SUN) showed the strongest correlation with HLC (R²=19.4).
  • For An. funestus, BG Sentinel (BGS) correlated best with HLC (R²=53.4), while M-Trap (MTR) and M-Trap+CDC (MTRC) showed highest correlation for Culex spp. (R²=45.4 and R²=44.2, respectively).
  • Density dependence affected only BGS trap performance.
  • An interactive Shiny App calibration tool was developed.

Conclusions:

  • A calibration tool and statistical framework were successfully developed to assess outdoor-biting risk and estimate human exposure.
  • All tested traps underestimated HLC-derived exposures but their representativeness could be mathematically defined.
  • Emphasis is placed on consistent and representative sampling approaches over simply maximizing mosquito catch numbers.