Comparative assessment of viral dynamic models for SARS-CoV-2 for pharmacodynamic assessment in early treatment trials.

Pharmacometric analyses of time series viral load data may detect drug effects with greater power than approaches using single time points. Because SARS-CoV-2 viral load rapidly rises and then falls, viral dynamic models have been used. We compared different modelling approaches when analysing Phase II-type viral dynamic data. Using two SARS-CoV-2 datasets of viral load starting within 7 days of symptoms, we fitted the slope-intercept exponential decay (SI), reduced target cell limited (rTCL), target cell limited (TCL) and TCL with eclipse phase (TCLE) models using nlmixr. Model performance was assessed via Bayesian information criterion (BIC), visual predictive checks (VPCs), goodness-of-fit plots, and parameter precision. The most complex (TCLE) model had the highest BIC for both datasets. The estimated viral decline rate was similar for all models except the TCL model for dataset A with a higher rate (median [range] day-1 : dataset A; 0.63 [0.56-1.84]; dataset B: 0.81 [0.74-0.85]). Our findings suggest simple models should be considered during pharmacodynamic model development.

Reducing the risk of tuberculosis transmission for HCWs in high incidence settings.

Globally, tuberculosis (TB) is a leading cause of death from a single infectious agent. Healthcare workers (HCWs) are at increased risk of hospital-acquired TB infection due to persistent exposure to Mycobacterium tuberculosis (Mtb) in healthcare settings. The World Health Organization (WHO) has developed an international system of infection prevention and control (IPC) interventions to interrupt the cycle of nosocomial TB transmission. The guidelines on TB IPC have proposed a comprehensive hierarchy of three core practices, comprising: administrative controls, environmental controls, and personal respiratory protection. However, the implementation of most recommendations goes beyond minimal physical and organisational requirements and thus cannot be appropriately introduced in resource-constrained settings and areas of high TB incidence. In many low- and middle-income countries (LMICs) the lack of knowledge, expertise and practice on TB IPC is a major barrier to the implementation of essential interventions. HCWs often underestimate the risk of airborne Mtb dissemination during tidal breathing. The lack of required expertise and funding to design, install and maintain the environmental control systems can lead to inadequate dilution of infectious particles in the air, and in turn, increase the risk of TB dissemination. Insufficient supply of particulate respirators and lack of direction on the re-use of respiratory protection is associated with unsafe working practices and increased risk of TB transmission between patients and HCWs. Delayed diagnosis and initiation of treatment are commonly influenced by the effectiveness of healthcare systems to identify TB patients, and the availability of rapid molecular diagnostic tools. Failure to recognise resistance to first-line drugs contributes to the emergence of drug-resistant Mtb strains, including multidrug-resistant and extensively drug-resistant Mtb. Future guideline development must consider the social, economic, cultural and climatic conditions to ensure that recommended control measures can be implemented in not only high-income countries, but more importantly low-income, high TB burden settings. Urgent action and more ambitious investments are needed at both regional and national levels to get back on track to reach the global TB targets, especially in the context of the COVID-19 pandemic.

'Long-COVID': a cross-sectional study of persisting symptoms, biomarker and imaging abnormalities following hospitalisation for COVID-19.

Large numbers of people are being discharged from hospital following COVID-19 without assessment of recovery. In 384 patients (mean age 59.9 years; 62% male) followed a median 54 days post discharge, 53% reported persistent breathlessness, 34% cough and 69% fatigue. 14.6% had depression. In those discharged with elevated biomarkers, 30.1% and 9.5% had persistently elevated d-dimer and C reactive protein, respectively. 38% of chest radiographs remained abnormal with 9% deteriorating. Systematic follow-up after hospitalisation with COVID-19 identifies the trajectory of physical and psychological symptom burden, recovery of blood biomarkers and imaging which could be used to inform the need for rehabilitation and/or further investigation.