Difference-in-differences analysis
malaria
REGRESSION, SECONDARY, MALARIA
For comparison, secondary difference-in-differences (DiD) analyses were performed comparing all follow-up survey timepoints with baseline for qPCR. Using SAS 9.4, the model used binomial logistic regression models that compared trends in malaria prevalence in the MDA + IRS arm to trends in malaria prevalence in the IRS arm, and adjusting for potential confounding variables, (age, ITN use, and gender). An interaction term between survey time and arm was used to estimate the DiD. Statistical significance threshold was set at 