A cohort study of the effectiveness of insecticide-treated bed nets to prevent malaria in an area of moderate pyrethroid resistance, Malawi. Kim A Lindblade et al
https://malariajournal.biomedcentral.com/articles/10.1186/s12936-015-0554-1
In this study, clustering was at village, household (focus of study), and individual levels
Intervention: Insecticide-treated bed net use versus non-bed net use
Experimental units: Clusters of Households (907/2178 registered households)
Exposure measured at household level (Bed net use)
Outcome: Incident malaria among bed net users versus non-users, determined at the individual level (children) - 1199 children tested for malaria over a 12-months period and determined.
Hypothesized effects were a reduction in incident malaria among bed net users
The statistical model used to estimate the effect: Used Poisson regression with a generalized estimating equations approach (PROC GENMOD) to account for correlation from repeated measures on the same child using exchangeable correlation structure and households from the same village.
Exposure variable and covariates could be time varying.
Confounders included baseline parasitemia, exposure to malaria transmission, household altitude, socio-economic status, stunting/wasting/nutritional status, the number of sleeping rooms and density of bed nets used per household.
Log-transformed person-time was used as an offset and an exchangeable working correlation structure was specified. Any covariate with a p-value of >0.1 in univariate analysis was included in the multivariate model.
Rate ratios (RR) and 95% CI were calculated from model parameters and model-adjusted incidence rates for covariates presented.
Protective effectiveness (PE) was calculated as 100%*(1-R1/R0) where R1 is the rate among bed net users and R0 is the rate among non-bed net users.
The attributable rate difference was calculated as R1-R0 and interpreted as the number of malaria infections prevented by ITNs annually.
Alternative analytic method: Mixed effects model which can handle more than one level of clustering, able to conduct likelihood fits and more robust to potential bias due to missing data or drop-out.
Interaction terms: none mentioned/assessed. (Net use and socio-economic status
https://malariajournal.biomedcentral.com/articles/10.1186/s12936-015-0554-1