Last updated:2022-02-10

Study design

Study design

Field experiment

  • Two sites (ravines) in Saint-Joseph municipality, southern Reunion Island

    • Langevin: control site

    • Payet: releases of sterile male mosquitoes (Ae. aegypti) coated with piriproxyfen, starting end of April 2021

    • Distance between Payet and Langevin site: 1,300 m

    • 12 CO2-baited BG traps, laying on the ground: 5 in Langevin, in Payet)

  • Results reported from 404 trapping sessions totaling 1,785 Ae. aegypti

  • Study period cut into 8 equal-length periods of 27.5 days (\(\simeq\) four weeks)

Number of trapping sessions by study period during a boosted SIT field experiment in La Reunion, Dec. 20 to July 21
Time periods (27.5 days) from 15 Dec. 20 to 21 Jul. 21
1 2 3 4 5 6 7 8
Langevin 20 20 20 20 15 10 20 17
Payet 31 28 28 28 21 42 27 28
<span style='font-size:11pt;font-weight:normal !important;'>Design (A), apparent density distribution (B) and seasonal pattern (C) of Ae. aegypti in a boosted-SIT field experiment in La Reunion, Dec. 20-July 21</span>

Design (A), apparent density distribution (B) and seasonal pattern (C) of Ae. aegypti in a boosted-SIT field experiment in La Reunion, Dec. 20-July 21

Shaping the data and building the model

Shaping the data and building the model

Goal, challenges and strategy

Goal

  • assess the effect of boosted SIT on the standardized apparent density (SAD) of an Ae. aegypti population

    • H0: constant SAD after starting boosted SIT

    • H1: decreasing trend in SAD, related to boosted SIT

Challenges

  • High variability in count data

  • two study sites (Payet and Langevin), with ecological differences

  • Boosted SIT only implemented in Payet, during a short time period (3 months)

  • Strong seasonal - as well as trap-to-trap, variations

Strategy

  • Choice of the outcome: apparent density of Ae. aegypti, standardized with respect to time period to eliminate other time trend than boosted SIT effect

  • Choice of a model to assess the boosted SIT effect, while providing useful information on spatial variation sources: we used a spatial (mixed-effect) Poisson model (Moraga 2019, chap. 6)

Shaping the data and building the model

Standardization of apparent density

Goal

  • Eliminate other time trend than boosted SIT effect, to get simpler models with meaningful parameters

Method

  • In each site \(s\) (Langevin or Payet), for each period \(i\) (1 to 8), the expected apparent density \(E_{s,i}\) was the average of trap-level apparent density

  • For each time period \(i\), \(E_{s,i}\) was divided by the expected density in Langevin \(E_{L,i}\) to get \(E_i\), the relative expected density. The average standardized apparent density (SAD) in Langevin, as well as in Payet before starting booster SIT (5th period), was a series of 1’s

  • Payet data included the boosted SIT effect for periods 6 to 8, which cases, we took as the density expectations in Payet, the expected density in Langevin, multiplied by the ratio of expected densities in Payet and Langevin when starting boosted SIT

<span style='font-size:11pt;font-weight:normal !important;'>Apparent density (A), and standardized apparent density (B) of _Ae. aegypti_ during a boosted-SIT field experiment in La Reunion, Dec. 20 - July 21</span>

Apparent density (A), and standardized apparent density (B) of Ae. aegypti during a boosted-SIT field experiment in La Reunion, Dec. 20 - July 21

Shaping the data and building the model

Spatio-temporal patterns

  • Between-trap differences, according to their location

  • Trap location did not change, and traps were close to each other: 58 m on average in Langevin (from 0 to 177 m), vs 92 m in Payet (0 to 177 m)

  • model should account for two sources of spatial variations

    • trap location (habitat suitability…)

    • trap proximity (flight range…)

  • To capture this correlation, site areas split into Voronoi polygons to compute neighborhood matrices used in the model