Cascade of testing for chlamydia and gonorrhoea inclusive of an annual health check in an urban Aboriginal Community Controlled Health Service.

Background To gain an understanding of chlamydia (CT) and gonorrhoea (NG) testing conducted within an annual health check (AHC) and in standard clinical consultations for clients aged 15-29years attending an urban Aboriginal Community Controlled Health Service in the period 2016-2021. Methods De-identified electronic medical record data were extracted and analysed on CT and NG testing by sex, age, Indigenous status and the context of testing (conducted within an AHC or not). An access, testing, and diagnosis cascade for CT and NG, inclusive of an AHC, was constructed.

Chlamydia and gonorrhoea testing and positivity within an urban Aboriginal and Torres Strait Islander Community Controlled Health Service 2016-2021.

Background This study describes chlamydia and gonorrhoea testing, positivity, treatment, and retesting among individuals aged ≥15years attending an urban Aboriginal Community Controlled Health Service during the period 2016-2021. Method Utilising routinely collected clinical data from the ATLAS program (a national sentinel surveillance network), a retrospective time series analysis was performed. The study assessed testing rates, positivity, treatment efficacy, retesting and trends over time within an urban Aboriginal Community Controlled Health Service.

Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks.

In this paper, we present and compare four methods to enforce Dirichlet boundary conditions in Physics-Informed Neural Networks (PINNs) and Variational Physics-Informed Neural Networks (VPINNs). Such conditions are usually imposed by adding penalization terms in the loss function and properly choosing the corresponding scaling coefficients; however, in practice, this requires an expensive tuning phase. We show through several numerical tests that modifying the output of the neural network to exactly match the prescribed values leads to more efficient and accurate solvers.