Fig 1.
Model comparison based on two goodness-of-fit measures and computation time, by village and level of covariate information.
The best-performing model is indicated with a star in each case. “Global only” means only covariates available from the coordinates are available, and “All” indicates all 28 covariates were used. “Z(s) removed” refers to the model outlined in Sec. 2.2 but with no spatial effects, “ε(s) removed” refers to the independent effects removed, and “Full model” refers to the full model. DIC and ML are defined in S1 Appendix.
Table 1.
Posterior of the effective range from the full-village analysis.
Each posterior is fit according to the model of Section 2.2, using two different sets of covariate information. The 95% highest posterior density interval (HPDI) is the smallest interval such that 95% of the posterior mass is contained within it.
Fig 2.
Fixed effect coefficients from fitting the model of Section 2.2 to all available data in each village.
Coefficients are on log odds scale. The blue point is the posterior mean, the bold orange line is the 50% HPDI, and the thin orange line is the 95% HPDI.
Fig 3.
Results from the simulation experiment for each village and predictor set.
The adaptive sampling procedure for varying α, along with random sampling, is performed for 50 initial sets of 10 houses. The x-axis is the percentage of houses in the final sampling design, and the y-axis is the true infestation rate remaining in the village. Diamonds show means, while cross-hairs show the 90% confidence intervals of the data corresponding to each axis. The red line indicates the 5% reduction target.
Table 2.
Performance of adaptive sampling in the simulation study, compared to random sampling.
Accuracy is the percentage of designs which met the control target, i.e. the out-of-sample infestation rate was below 5% (or 8%). Difference from random is the percentage of the village in the design, minus the corresponding percentage using random sampling, calculated for each initial design.