Term

Estimate

SE

95% CI


Lower

Upper


Aedes aegypti

Fixed effects

Intercept (CC, BP)^{a}

− 0.618

0.354

− 1.312

0.077

Intervention period (IP)^{b}

− 0.535

0.367

− 1.253

0.184

Intervention cluster (IC)

0.508

0.319

− 0.118

1.134

IP × IC^{c}

− 0.916

0.295

− 1.493

− 0.338

Rainfall^{d}

0.829

0.146

0.543

1.116

Random effects SD

Dwelling ID

0.766

–

0.585

1.001

Month

0.455

–

0.275

0.755

Culex quinquefasciatus

Fixed effects

Intercept (CC, BP)^{a}

0.430

0.396

− 0.346

1.205

Intervention period (IP)^{b}

0.080

0.382

− 0.669

0.828

Intervention cluster (IC)

− 1.172

0.380

− 1.917

− 0.427

IP × IC^{c}

− 0.807

0.291

− 1.378

− 0.237

Temperature^{d}

0.707

0.156

0.400

1.012

Random effects SD

Dwelling ID

1.091

–

0.868

1.370

Month

0.502

–

0.328

0.767

 ^{a}The intercept estimates the (logscale) expected mean number of mosquitoes caught per 10 minutes aspiration in the CC, in the typical dwelling and at typical temperatures, during the BP; the other fixedeffect slope coefficients estimate changes in this expectation associated with period, cluster, intervention, and rainfall or temperature effects
 ^{b}Note that both models estimate nonsignificant changes in (log) mean mosquitocatch as the CC entered the IP (but received no intervention), with the 95% confidence intervals including zero
 ^{c}The ‘IP × IC’ interaction coefficients estimate the (log) change in expected mean mosquitocatch that can be attributed to the intervention (deployment of 150 pyriproxyfen dissemination stations over 13 months (the IP) in the IC). The Aedes model estimates an e^{− 0.916} = 0.400 incidence rate ratio, indicating that the intervention resulted in a 100 − 40.0 = 60.0% reduction (95% CI: 28.7–77.5%) of the expected mean Aedescatch; the Culex model estimates an e^{− 0.807} = 0.446 incidence rate ratio, or a 55.4% reduction (95% CI: 21.1–74.8%) of the expected mean Culex catch
 ^{d}Specified as the (standardized) total rainfall in the month before sampling (‘rain_m’) for the Aedes model and as the mean of minimum daily temperatures in the month before sampling (‘tmin_m’) for the Culex model; the original variables had the following means (SDs): ‘rain_m’, 131.6 mm (111.3); ‘tmin_m’, 17.39°C (1.73). Given our focus on estimating adjusted intervention effects, we considered weather covariates as confounders; those in the table yielded betterperforming models, as measured by BIC scores, than other measures of temperature and rainfall
 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