Linking prediction models to government ordinances to support hospital operations during the COVID-19 pandemic

A simulation model for predicting hospital occupancy for Covid-19 using archetype analysis

COVID-19 pandemic has sent millions of people to hospitals worldwide, exhausting on many occasions the capacity of healthcare systems to provide care patients required to survive. Although several epidemiological research works have contributed a variety of models and approaches to anticipate the pandemic spread, very few have tried to translate the output of these models into hospital service requirements, particularly in terms of bed occupancy, a key question for hospital managers. This paper proposes a tool for predicting the current and future occupancy associated with COVID-19 patients of a hospital to help managers make informed decisions to maximize the availability of hospitalization and intensive care unit (ICU) beds and ensure adequate access to services for confirmed COVID-19 patients. The proposed tool uses a discrete event simulation approach that uses archetypes (i.e., empirical models of trajectories) extracted from empirical analysis of actual patient trajectories. Archetypes can be fitted to trajectories observed in different regions or to the particularities of current and forthcoming variants using a rather small amount of data. Numerical experiments on realistic instances demonstrate the accuracy of the tool's predictions and illustrate how it can support managers in their daily decisions concerning the system's capacity and ensure patients the access the resources they require.

Using simulation modelling and systems science to help contain COVID-19: A systematic review

This study systematically reviews applications of three simulation approaches, that is, system dynamics model (SDM), agent-based model (ABM) and discrete event simulation (DES), and their hybrids in COVID-19 research and identifies theoretical and application innovations in public health. Among the 372 eligible papers, 72 focused on COVID-19 transmission dynamics, 204 evaluated both pharmaceutical and non-pharmaceutical interventions, 29 focused on the prediction of the pandemic and 67 investigated the impacts of COVID-19. ABM was used in 275 papers, followed by 54 SDM papers, 32 DES papers and 11 hybrid model papers. Evaluation and design of intervention scenarios are the most widely addressed area accounting for 55% of the four main categories, that is, the transmission of COVID-19, prediction of the pandemic, evaluation and design of intervention scenarios and societal impact assessment. The complexities in impact evaluation and intervention design demand hybrid simulation models that can simultaneously capture micro and macro aspects of the socio-economic systems involved.

Effect of COVID-19 on the delivery of care for thoracic surgical patients

Objective

In this study we aimed to determine the effect of the COVID-19 pandemic on the delivery of care for thoracic surgical patients at an urban medical center.

Methods

A retrospective analysis of all thoracic surgical cases from May 1, 2019, to December 31, 2020, was conducted. Demographic characteristics, preoperative surgical indications, procedures, final pathologic diagnoses, and perioperative outcomes were recorded. A census of operative cases, relevant ancillary services, and outpatient thoracic clinics were obtained from our institutional database.

Results

Six hundred nineteen cases were included in this study (329 pre-COVID-19 and 290 COVID-19, representing an 11.8% reduction). There were no differences in type of thoracic procedures or perioperative outcomes among the 2 cohorts. Prolonged reduction of thoracic surgical cases (50% of baseline) during the first half of the COVID-19 period was followed by a resurgence of surgical volumes to 110% of baseline in the second half. A similar incidence of cases were performed for oncologic indications during the first half whereas more benign cases were performed in the second half, coinciding with the launch of our robotic foregut surgery program. After undergoing surgery during the pandemic, none of our patients reported COVID-19 symptoms within 14 days of discharge.

Conclusions

During the initial surge of COVID-19, while there was temporary closure of operative services, our health care system continued to provide safe care for thoracic surgery patients, particularly those with oncologic indications. Since phased reopening, we have experienced a rebound of surgical volume and case mix, ultimately mitigating the initial negative effect of the pandemic on delivery of thoracic surgical care.

Estimating COVID Risk During a Period of Pandemic Decline

Background: Many parts of the world that succeeded in suppressing epidemic coronavirus spread in 2020 have been caught out by recent changes in the transmission dynamics of SARS-CoV-2. Australia's early success in suppressing COVID-19 resulted in lengthy periods without community transmission. However, a slow vaccine rollout leaves this geographically isolated population vulnerable to leakage of new variants from quarantine, which requires internal travel restrictions, disruptive lockdowns, contact tracing and testing surges.

Methods: To assist long term sustainment of limited public health resources, we sought a method of continuous, real-time COVID-19 risk monitoring that could be used to alert non-specialists to the level of epidemic risk on a sub-national scale. After an exploratory data assessment, we selected four COVID-19 metrics used by public health in their periodic threat assessments, applied a business continuity matrix and derived a numeric indicator; the COVID-19 Risk Estimate (CRE), to generate a daily spot CRE, a 3 day net rise and a seven day rolling average. We used open source data updated daily from all Australian states and territories to monitor the CRE for over a year.

Results: Upper and lower CRE thresholds were established for the CRE seven day rolling average, corresponding to risk of sustained and potential outbreak propagation, respectively. These CRE thresholds were used in a real-time map of Australian COVID-19 risk estimate distribution by state and territory.

Conclusions: The CRE toolkit we developed complements other COVID-19 risk management techniques and provides an early indication of emerging threats to business continuity.