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We aimed to demonstrate the role of real-time, on-site, whole-genome sequencing (WGS) of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in the management of hospital outbreaks of coronavirus disease 2019 (COVID-19).
This retrospective study was undertaken at our institutions in Sydney, New South Wales, Australia, between July 2021 and April 2022. We included SARS-CoV-2 outbreaks due to SARS-CoV-2 δ (delta) and ο (omicron) variants. All unexpected SARS-CoV-2–positive cases identified within the hospital were managed by the infection control team. An outbreak was defined as 2 or more cases acquired on a single ward. We included only outbreaks with 2 or more suspected transmission events in which WGS was utilized to assist with outbreak assessment and management.
We studied 8 outbreaks involving 266 patients and 486 staff, of whom 73 (27.4%) and 39 (8.0%), respectively, tested positive for SARS-CoV-2 during the outbreak management. WGS was used to evaluate the source of the outbreak, to establish transmission chains, to highlight deficiencies in infection control practices, and to delineate between community and healthcare acquired infection.
Real-time, on-site WGS combined with epidemiologic assessment is a useful tool to guide management of hospital SARS-CoV-2 outbreaks. WGS allowed us (1) to establish likely transmission events due to personal protective equipment (PPE) breaches; (2) to detect inadequacies in infection control infrastructure including ventilation; and (3) to confirm multiple viral introductions during periods of high community SARS-CoV-2 transmission. Insights gained from WGS-guides outbreak management directly influenced policy including modifying PPE requirements, instituting routine inpatient SARS-CoV-2 surveillance, and confirmatory SARS-CoV-2 testing prior to placing patients in a cohort setting.
The Institute is a world leader in macroeconomic modelling and forecasting. It has produced quarterly economic forecasts for around sixty years, supported by macroeconomic models. The aim of the original builders of macroeconomic models was to transform understanding of how economies worked and use that knowledge to improve economic policy. In the early years, when computers were rare, macroeconomic modelling was a new frontier and Institute economists were among the first to produce a working model of the UK economy. It is remarkable how quickly models were being used to produce forecasts, assess policy and influence the international macroeconomic research agenda. The models built at the Institute were mainstream in the sense that they followed the contents of standard macroeconomic textbooks, developed with the subject, and fitted the facts as they were known at the time. There were continual improvements in understanding as the subject developed in response to new ideas and developments in the global economy. This article celebrates the development of macroeconomic modelling at the Institute and the contribution it has made to public life.
Argentina, the second largest country in South America is a federation of 23 provinces and its capital, the autonomous city of Buenos Aires. Its population is a little over 40 million, 50% of whom reside in its five largest metropolitan areas. The rural areas are extensively under-populated. The city of Buenos Aires and its suburb contain 15.5 million inhabitants, making it one of the largest urban areas in the world.
This article demonstrates how the use of balanced data can affect a forecasting exercise. The forecast published by the National Institute in November 1989 is revised with the constant and current price residual errors in the National Accounts being assigned to component parts in a manner consistent with the overall pattern of imbalances within the accounts at the time. One of the main results is that preliminary estimates for some components of the accounts, available at the time of the forecast, may also need to be adjusted. This is required to ensure that the forecast is consistent with both balanced data over the future and the structure of the model itself.
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