Table 2 Statistical analyses to be completed by the endpoint

1.1 The number and the proportion of participants who report completing the HCV antibody testing in the intervention group

1.2 To assess whether the proportion of participants who report completing the HCV antibody testing in the intervention group is greater than that reported by the participants in the control group by a margin of 20%

Descriptive statistics:

Calculation of proportions with 95% CI of the difference in proportions will be evaluated by using the R function prop.test from the “stats” package, which relies on Wilson’s score method.

Test of proportions:

Two-sided test with a margin of 20%, implemented with the R function “stats::prop.test” with the following hypotheses: H₀: p_fo,I − p_fo,C ≤ 20%

H_A: p_fo,I − p_fo,C > 20%

where proportions are defined as p_x,y [x = investigated outcome (fo, pt, ref, trt), y = element of {intervention, control}]) comparing the proportion of individuals reporting HCV test results in the intervention versus control groups and between intervention groups.

The differences will be reported together with their confidence intervals and the p-value related to the statistical comparison mentioned above. The alpha level will be set at 0.025 (2 two-sided tests with an alpha level of 0.05, with the application of Bonferroni correction).

 2.1 Number and proportion of HCV antibody-positive individuals made aware of their status in the intervention versus the control group

Descriptive statistics:

Statistical testing comparing the numbers of individuals in the intervention versus control groups and between the intervention groups. For details, see the methodology described for endpoint 1.2.

 2.2 Number and proportion of HCV antibody-positive individuals who are referred for and complete HCV RNA confirmatory testing in the intervention versus control group

 2.3 Number and proportion of HCV RNA-positive individuals who begin treatment in the intervention versus the control group

 2.4 Analysis of survey responses using proportions and means

Descriptive statistics for survey responses (e.g. proportions, means), as appropriate for the type of response.

 2.5 Cost per test completed and cost per person diagnosed (serology, RNA) in the intervention versus control groups

Ingredients-based cost calculation approach.