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Table 2 A summary of common bias in larval control interventions and of ways for controlling these bias

From: Implementing a larviciding efficacy or effectiveness control intervention against malaria vectors: key parameters for success

No. Bias Corrective measures that could be applied
1 Random sequence generation (selection bias) A central randomization procedure could be applied for random larval spot check. About 30 habitats randomly generated using a computer assisted programme out of the total number of habitats can be selected at least once monthly for each cluster by the programme manager including habitat ID and coordinates. This information is sent to the field supervisor for habitat inspection. Inspections have to be undertaken 1 or 2 days after larviciding treatments according to the timetable of treatments. For larvicides having a longer residual effect, inspections has also to be undertaken at 6-7 days intervals.
2 Allocation of concealment (selection bias) Clusters have to be allocated as treated or untreated randomly. This random allocation can be done using a random table or a computer assisted programme.
3 Blinding of outcomes assessment (detection of bias) Data collectors and the personnel processing the sample in the laboratory can be blinded to the intervention status.
4 Performance bias Field applicators can be blinded for the sites choose for random larval spot check. Use automated methods for adult mosquito collection such as light traps. Use standardized measures for estimating larval densities.
5 Incomplete outcome data (attrition bias) The sample size can be increased by adding 1 or 2 additional clusters per treatment group. This bias if not important can also be solved during statistical analysis.
6 Selective reporting (reporting bias) All measured outcomes showing either a positive, non-significant or negative impact have to be reported as specified.
7 Baseline characteristics Baseline data including entomological, ecological data and human behavioural data for each site has to be recorded before the intervention. Adjustment for a set of covariates can be applied to control for chance variations and improve precision of the impact estimates.
8 Contamination due to mosquito spillover Consider a buffer zone of at least 1 km between treated and untreated clusters to minimise contamination due to mosquito spillover from untreated to treated zones. In addition, clusters have to be designed big enough so that the treatment is undertaken in the entire cluster but the evaluation is conducted only in the centre of the cluster (Fig. 1).
10 Incorrect data analysis Use appropriate statistical methods and take into consideration during data analysis the clustering effect, covariates and confounding factors effects.
11 Sampling bias Sampling has to be conducted in households selected randomly, use a large number of sites as possible for sampling, use automatic methods for sampling, carry mosquito collection during several days for each collection site to minimise bias due to rain or weather variations.