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. 2017 Jan 3;16:4. doi: 10.1186/s12936-016-1652-4

Table 3.

Regression results showing percentage point change in total SPR adjusted for variations at district level

Timing in relation to IRS Percentage point change p value 95% confidence interval
Lower boundary Upper boundary
1 month after IRS −4.18 0.157 −9.98 1.63
2 month after IRS −6.48 0.037 −12.55 −0.41
3 month after IRS −7.11 0.038 −13.80 −0.41
4 month after IRS −0.39 0.912 −7.27 6.50
5 month after IRS −2.97 0.459 −10.87 4.93
6 month after IRS 8.37 0.510 −16.66 33.39

Two linear fixed effects regression models were regressed on the SPR as the outcome variable both at district and hospital level. The models are shown below

Hospital model SPR = β0 + β1 (time) + β2 (months past after spraying) + β3 (Hospital)

District model SPR = β0 + β1 (time) + β2 (months past after spraying) + β3 (District)

The regression results adjusted for variations at district level and the adjusted confidence intervals of the percentage changes in the SPR 6 months after IRS reveal the same results with a decrease in the SPR 1–3 months after IRS which wanes out in the fourth month following IRS. The same results are obtained when the SPR is analysed by age category as shown in Table 6. The SPR increases by the sixth month when compared to the spray month, the reference month = zero