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Table 1 Covariates included in constrained randomisation

From: The AWED trial (Applying Wolbachia to Eliminate Dengue) to assess the efficacy of Wolbachia-infected mosquito deployments to reduce dengue incidence in Yogyakarta, Indonesia: study protocol for a cluster randomised controlled trial

Category Covariate Rationale Balancing criterion
Potential confounders 1. Age: % of population < 15 yearsa Dengue risk is age dependent Each arm within ± 5% of overall population value
2. 3-year average dengue incidence ratea Historical dengue incidence may predict future risk Each arm within ± 5% of overall population value
3. Education: % completed high schoola Proxy for socioeconomic status that may predict dengue risk Each arm within ± 5% of overall population value
Potential sources of bias 4. Incidence of other febrile illnessf presenting to Puskesmas clinics in 2014–2015b Prevent chance association between other febrile illness and intervention Each arm within ± 5% of overall population value
Sample size 5. Number of clusters To maximise precision and power 12 clusters per study arm
  6. Cluster populationc To maximise precision and power Each arm 45–55% of total population
Logistics 7. Total cluster area (km2)d Releases to be done over approximately half the city Each arm 45–55% of total area
  8. Non-release area within cluster (km2)e To prevent an excess of non-residential areas falling in intervention arm Each arm 45–55% of total non-release area
  9. Four spatial strata To prevent a large contiguous intervention area Within each spatial stratum, three clusters per study arm
  1. Data sources: aYogyakarta and Bantul District Health Offices; bRecords from individual primary health clinics (Puskesmas); cStatistics Indonesia (BPS), 2015; dCalculated in ArcGIS; eCalculated in ArcGIS and Google Earth.
  2. fOther febrile illness extracted based on ICD10 codes R50 (Fever of other and unknown origin), R50.9 (Fever, unspecified), A75.9 (Typhus fever, unspecified), A49 (staphylococcal infection, unspecified site)