To evaluate this new robustness of your design and you will possible inconsistencies into the study, i recalibrated the new design and you may determined the associated improvement in the latest incidence rate of syphilis, the fresh new installing parameters, additionally the god regarding match (sum of squared weighted residuals) (Dining table D inside the S1 Text).

Instead method to simply take the fresh new discrepancy regarding studies, i fitting a design provided that there is no difference between sign rate regarding syphilis certainly MSM

When assuming reported non-steady condomless anal intercourse (nsCAI) as the transmission risk instead of nsP, we estimated that MSM with nsCAI had 1 visit homepage.71 [IQR (1.65, 1.81)] times the incidence of MSM without nsCAI. However, the goodness of fit for this model was considerably worse than for the main model (378.8 vs. 148.3). Secondly, we assessed the impact of the assumption of different transmission rates of syphilis among MSM_wHD and MSM_w/oHD. In the main model we had to assume different transmission rates, because of an apparent discrepancy in the data: despite similar frequency of reported nsP among MSM_wHD and MSM_w/oHD, we observed much higher incidence of syphilis among MSM_wHD than MSM_w/oHD even when taking serosorting into account (Table B in S1 Text). To resolve this contradiction, in the main model, we assumed different transmission rates of syphilis (beta) in MSM_wHD and MSM_w/oHD in our model (Table A in S1 Text). In the absence of this assumption, the model was unable to reproduce the syphilis epidemic in Switzerland and led to either a large overestimation of syphilis incidence in MSM_w/oHD or a large underestimation in MSM_wHD (Fig N in S1 Text). _wHD and MSM_w/oHD but instead including a parameter to account for possible underreporting of syphilis cases to FOPH among MSM_w/oHD (Fig O in S1 Text). However, the goodness of fit for this model was worse than for the main model (sum of squared weighted residuals, 206.6 vs. 148.3) and required the assumption of an unrealistically high underreporting factor (40.8). _w/oHD. We fitted models assuming the proportion of MSM_w/oHD with nsP to be 25%, 50%, and 75% lower than the proportion of MSM_w/oHD with nsP estimated from data published in the Gaysurvey (Fig P in S1 Text). This corresponds to proportion of MSM_w/oHD with nsP in 2017 to be 0.54, 0.36, and 0.18 vs. 0.73, respectively. The estimated goodness of fit values for these models were slightly better than the goodness of fit for the main model (136.4, 124.4, and 123.6 vs. 148.3 respectively) suggesting that model is robust to the hypothesized overestimation.

Finally, we examined the feeling regarding a potential overestimation off sign exposure certainly one of MSM

Fourthly, we assessed the impact of the duration of syphilis infectiousness on the dependency between the screening frequency and the syphilis incidence. Instead of assuming zero infectiousness in the latent stage of syphilis (>3 months since infection), we varied the infectiousness of syphilis in the latent stage to be 1% and 10% of that in the primary and/or secondary stage of syphilis (? 3 months since infection) (Fig Q in S1 Text). The goodness of fit values for these models were worse than for the main model (154.3 and 397.6 vs 148.3 respectively). As depicted above in the counterfactual scenario, increase in the frequency of screening for syphilis among MSM_wHD with nsP led to reduced simulated syphilis incidence in 2017. Increased infectiousness during the latent stage led to a smaller estimated reduction in syphilis incidence in 2017 in the counterfactual scenarios (% and % vs. % by assuming the infectiousness in latent stage of syphilis to be 1% and 10% vs. 0% of that in primary and secondary stage of syphilis respectively) (Fig 5)