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Table 5 Adjusted effects of mosquito-disseminated pyriproxyfen on Aedes egg-trap-derived endpoints: numerical results of the top-ranking (smallest-BIC) zero-inflated generalized linear mixed model

From: Measuring mosquito control: adult-mosquito catches vs egg-trap data as endpoints of a cluster-randomized controlled trial of mosquito-disseminated pyriproxyfen

Term

Estimate

SE

95% CI

Lower

Upper

Egg-count submodel

Fixed effects

Intercept (CC, BP)a

3.957

0.203

3.558

4.355

Intervention period (IP)

− 0.296

0.225

− 0.736

0.145

Intervention cluster (IC)

− 0.055

0.229

− 0.504

0.394

IP × IC

0.262

0.244

− 0.215

0.740

Temperatureb

0.695

0.113

0.473

0.917

Random effects SD

Dwelling ID

0.270

-

0.152

0.478

Month

0.244

-

0.115

0.519

Egg-trap negativity submodel

Fixed effects

Intercept (CC, BP)c

1.204

0.404

0.412

1.996

Intervention period (IP)

0.440

0.436

− 0.414

1.293

Intervention cluster (IC)

0.797

0.312

0.186

1.407

IP × IC

− 0.251

0.311

− 0.861

0.360

Temperatureb

− 1.255

0.200

− 1.646

− 0.863

Random effects SD

Dwelling ID

0.576

–

0.403

0.823

Month

0.593

–

0.384

0.916

  1. aThe intercept of the negative binomial (egg count) submodel estimates the (log-scale) expected mean number of Aedes eggs per egg-trap in CC, in the typical dwelling and at typical temperatures, during the BP; the other fixed-effect slope coefficients estimate changes in this expectation associated with period, cluster, intervention, and temperature effects; only this latter was clearly (sensu [55]) different from zero
  2. bSpecified as the (standardized) mean of minimum daily temperatures in the week before each sampling occasion (‘tmin_w’); the original variable had mean = 17.86 °C and SD = 2.89 °C. Given our focus on estimating adjusted intervention effects, we considered weather covariates as confounders; ‘tmin_w’ yielded better-performing models, as measured by BIC scores, than other measures of temperature and rainfall
  3. cThe intercept of the binomial (egg-trap negativity) submodel estimates the (logit-scale) expected proportion of negative egg-traps in the CC, in the typical dwelling and at typical temperatures, during the BP; the other fixed-effect slope coefficients estimate changes in this expectation associated with period, cluster, intervention, and temperature effects – with results suggesting higher baseline odds of egg-trap negativity in the CC and that warmer nights were independently associated with lower odds of egg-trap negativity
  4. Abbreviations: BIC, Bayesian information criterion; SE, standard error; 95% CI, 95% confidence interval (lower/upper limits); CC, control cluster; BP, baseline period; IP, intervention period; IC, intervention cluster; SD, standard deviation; ID, identity of each sampling dwelling