Reply to Satapathy et al.'s comment on "Dual cross-sectional and longitudinal perspective on the continuum of HIV care to disentangle natural epidemic evolution from real progress, Belgium 2014-2022"

Abstract

Reply to Satapathy et al.'s comment on "Dual cross-sectional and longitudinal perspective on the continuum of HIV care to disentangle natural epidemic evolution from real progress, Belgium 2014-2022" Dear Editor, We write in response to the letter by P. Satapathy et al. on our study "Dual cross-sectional and longitudinal perspective on the continuum of HIV care to disentangle natural epidemic evolution from real progress, Belgium 2014-2022" [1]. The following points were raised: (i) the use of 1-year cumulative incidence (CI) to describe diagnosis timing; (ii) the inclusion of cause-specific hazards or adjustment for the competing risk of loss to follow-up in our transition models; (iii) the validity of the discussed potential causes of the observed improvements; (iv) the generalisability of the findings to other countries. We appreciate the opportunity to clarify our findings and address the points raised. Firstly, we chose to present the results of the longitudinal continuum analyses through both cumulative incidence graphs (Fig. 3 in the article) and proportions reaching the endpoint after defined delays-specifically 1 year for diagnosis-the latter chosen for its clarity and ease of interpretation for readers. This approach effectively highlights the stark contrast between the diagnosis stage and subsequent transitions in care: while 31% were diagnosed within a year of HIV infection in 2020-22, for the next transitions in care high proportions of 81% of linkage to care, 91% of ART initiation, and 77% of viral suppression were reached within 3 months. This underscores that the diagnosis stage remains the slowest step in the continuum of care, making the disparity both visually and intuitively clear to readers. Median time to endpoints and IQR, as a supplementary descriptive indicator, are presented in Table 1. This alternative indicator yields the same conclusions as the published data and, similarly, highlights the sharp differences between the median time from infection to diagnosis, and the median times observed in the other transitions. Moreover, presenting the median time does not capture the tail end any better than the measures already reported in the article. In consequence, this supplementary analysis reaffirms that our indicator is reliable for informing testing policies.