Modelling the recovery of elective waiting lists following COVID-19: scenario projections for England

Background: A significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England's National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7m by August 2021. Aims: The objective of this study was to estimate the trajectory of future waiting list size and waiting times to December 2025. Methods: A scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0, 25, 50 and 75%) of the estimated 7.1 million referrals 'missed' during the pandemic. Future capacity assumed 90, 100 and 110% of that provided in the 12 months immediately before the pandemic. Results: As a worst case, the waiting list would reach 13.6m (95% CI: 12.4m to 15.6m) by Autumn 2022, if 75% of missed referrals returned and only 90% of pre pandemic capacity could be achieved. Under this scenario, the proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4% to 46.2%) with the number waiting over 52 weeks reaching 1.6m (0.8m to 3.1m) by Summer 2023. At this time, 29.0% (21.3% to 36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60% (against the 92% constitutional target). Conclusions: This study reveals the long-term challenge for the NHS in recovering elective waiting lists as well as potential implications for patient outcomes and experience.

Applying projections of gross regional product to determine the possible extent of economic damage under various case scenarios of the coronavirus epidemic impact on the region's economy

Subject. This article explores the issues related to the system of indicators of forecasting of gross regional product and their relationship. Objectives. The article aims to obtain projections of the extent of economic damage of the coronavirus epidemic impact on the region's economy in various case scenarios, based on scenario projections of gross regional product. Methods. For the study, I used the techniques of mathematical modeling in economics. Results. The article presents forecast estimates of the gross regional product of the Republic of Sakha (Yakutia) for 2018–2020 by an inertial scenario and the coronavirus epidemic impact on the region's economy in various case scenarios for 2020, as well as the extent of possible economic damage. Conclusions. The methodological approach developed helps provide adequate projections of possible economic damage of the coronavirus epidemic impact on the region's economy in various case scenarios.

Generalized logistic growth modeling of the COVID-19 outbreak: comparing the dynamics in the 29 provinces in China and in the rest of the world

Started in Wuhan, China, the COVID-19 has been spreading all over the world. We calibrate the logistic growth model, the generalized logistic growth model, the generalized Richards model and the generalized growth model to the reported number of infected cases for the whole of China, 29 provinces in China, and 33 countries and regions that have been or are undergoing major outbreaks. We dissect the development of the epidemics in China and the impact of the drastic control measures both at the aggregate level and within each province. We quantitatively document four phases of the outbreak in China with a detailed analysis on the heterogeneous situations across provinces. The extreme containment measures implemented by China were very effective with some instructive variations across provinces. Borrowing from the experience of China, we made scenario projections on the development of the outbreak in other countries. We identified that outbreaks in 14 countries (mostly in western Europe) have ended, while resurgences of cases have been identified in several among them. The modeling results clearly show longer after-peak trajectories in western countries, in contrast to most provinces in China where the after-peak trajectory is characterized by a much faster decay. We identified three groups of countries in different level of outbreak progress, and provide informative implications for the current global pandemic.