Predicting consequences of COVID-19 control measure de-escalation on nosocomial transmission and mortality: a modelling study in a French rehabilitation hospital.

INTRODUCTION: Infection control measures are effective for nosocomial COVID-19 prevention but bear substantial health-economic costs, motivating their "de-escalation" in settings at low risk of SARS-CoV-2 transmission. Yet consequences of de-escalation are difficult to predict, particularly in light of novel variants and heterogeneous population immunity. AIM: To estimate how infection control measure de-escalation influences nosocomial COVID-19 risk. METHODS: An individual-based transmission model was used to simulate SARS-CoV-2 outbreaks and control measure de-escalation in a French long-term care hospital with multi-modal control measures in place (testing and isolation, universal masking, single-occupant rooms). Estimates of COVID-19 case fatality rates (CFRs) from reported outbreaks were used to quantify excess COVID-19 mortality due to de-escalation. RESULTS: In a population fully susceptible to infection, de-escalating both universal masking and single rooms resulted in hospital-wide outbreaks of 114 (95% CI: 103-125) excess infections, compared with five (three to seven) excess infections when de-escalating only universal masking or 15 (11-18) when de-escalating only single rooms. When de-escalating both measures and applying CFRs from the first wave of COVID-19, excess patient mortality ranged from 1.57 (1.41-1.71) to 9.66 (8.73-10.57) excess deaths/1000 patient-days. By contrast, when applying CFRs from subsequent pandemic waves and assuming susceptibility to infection among 40-60% of individuals, excess mortality ranged from 0 (0-0) to 0.92 (0.77-1.07) excess deaths/1000 patient-days. CONCLUSIONS: The de-escalation of bundled COVID-19 control measures may facilitate widespread nosocomial SARS-CoV-2 transmission. However, excess mortality is probably limited in populations at least moderately immune to infection and given CFRs resembling those estimated during the 'post-vaccine' era.

How have mathematical models contributed to understanding the transmission and control of SARS-CoV-2 in healthcare settings? A systematic search and review.

Since the onset of the COVID-19 pandemic, mathematical models have been widely used to inform public health recommendations regarding COVID-19 control in healthcare settings. The objective of this study was to systematically review SARS-CoV-2 transmission models in healthcare settings, and to summarize their contributions to understanding nosocomial COVID-19. A systematic search and review of published articles indexed in PubMed was carried out. Modelling studies describing dynamic inter-individual transmission of SARS-CoV-2 in healthcare settings, published by mid-February 2022 were included. Models have mostly focused on acute-care and long-term-care facilities in high-income countries. Models have quantified outbreak risk, showing great variation across settings and pandemic periods. Regarding surveillance, routine testing rather than symptom-based was highlighted as essential for COVID-19 prevention due to high rates of silent transmission. Surveillance impacts depended critically on testing frequency, diagnostic sensitivity, and turn-around time. Healthcare re-organization also proved to have large epidemiological impacts: beyond obvious benefits of isolating cases and limiting inter-individual contact, more complex strategies (staggered staff scheduling, immune-based cohorting) reduced infection risk. Finally, vaccination impact, while highly effective for limiting COVID-19 burden, varied substantially depending on assumed mechanistic impacts on infection acquisition, symptom onset and transmission. Modelling results form an extensive evidence base that may inform control strategies for future waves of SARS-CoV-2 and other viral respiratory pathogens. We propose new avenues for future models of healthcare-associated outbreaks, with the aim of enhancing their efficiency and contributions to decision-making.

Epidemiology and health-economic burden of urinary-catheter-associated infection in English NHS hospitals: a probabilistic modelling study.

BACKGROUND: Catheter-associated urinary tract infection (CAUTI) and bloodstream infection (CABSI) are leading causes of healthcare-associated infection in England's National Health Service (NHS), but health-economic evidence to inform investment in prevention is lacking. AIMS: To quantify the health-economic burden and value of prevention of urinary-catheter-associated infection among adult inpatients admitted to NHS trusts in 2016/17. METHODS: A decision-analytic model was developed to estimate the annual prevalence of CAUTI and CABSI, and their associated excess health burdens [quality-adjusted life-years (QALYs)] and economic costs (£ 2017). Patient-level datasets and literature were synthesized to estimate population structure, model parameters and associated uncertainty. Health and economic benefits of catheter prevention were estimated. Scenario and probabilistic sensitivity analyses were conducted. FINDINGS: The model estimated 52,085 [95% uncertainty interval (UI) 42,967-61,360] CAUTIs and 7529 (UI 6857-8622) CABSIs, of which 38,084 (UI 30,236-46,541) and 2524 (UI 2319-2956) were hospital-onset infections, respectively. Catheter-associated infections incurred 45,717 (UI 18,115-74,662) excess bed-days, 1467 (UI 1337-1707) deaths and 10,471 (UI 4783-13,499) lost QALYs. Total direct hospital costs were estimated at £54.4M (UI £37.3-77.8M), with an additional £209.4M (UI £95.7-270.0M) in economic value of QALYs lost assuming a willingness-to-pay threshold of £20,000/QALY. Respectively, CABSI accounted for 47% (UI 32-67%) and 97% (UI 93-98%) of direct costs and QALYs lost. Every catheter prevented could save £30 (UI £20-44) in direct hospital costs and £112 (UI £52-146) in QALY value. CONCLUSIONS: Hospital catheter prevention is poised to reap substantial health-economic gains, but community-oriented interventions are needed to target the large burden imposed by community-onset infection.

Sonogashira diversification of unprotected halotryptophans, halotryptophan containing tripeptides; and generation of a new to nature bromo-natural product and its diversification in water.

The blending together of synthetic chemistry with natural product biosynthesis represents a potentially powerful approach to synthesis; to enable this, further synthetic tools and methodologies are needed. To this end, we have explored the first Sonogashira cross-coupling to halotryptophans in water. Broad reaction scope is demonstrated and we have explored the limits of the scope of the reaction. We have demonstrated this methodology to work excellently in the modification of model tripeptides. Furthermore, through precursor directed biosynthesis, we have generated for the first time a new to nature brominated natural product bromo-cystargamide, and demonstrated the applicability of our reaction conditions to modify this novel metabolite.