Hospital bed capacity and usage across secondary healthcare providers in England during the first wave of the COVID-19 pandemic: a descriptive analysis

Relationship between sociodemographic, clinical, and laboratory characteristics and severity of COVID-19 in pediatric patients

COVID-19 affects children less seriously than adults; however, severe cases and deaths are documented. This study objective is to determine socio-demographic, clinical and laboratory indicators associated with severe pediatric COVID-19 and mortality at hospital entrance. A multicenter, retrospective, cross-sectional study was performed in 13 tertiary hospitals in Bolivia. Clinical records were collected retrospectively from patients less than 18 years of age and positive for SARS-CoV-2 infection. All variables were measured at hospital entrance; outcomes of interest were ICU admission and death. A score for disease severity was developed using a logistic regression model. 209 patients were included in the analysis. By the end of the study, 43 (20.6%) of children were admitted to the Intensive care unit (ICU), and 17 (8.1%) died. Five indicators were independently predictive of COVID-19 severity: age below 10 years OR: 3.3 (CI95%: 1.1-10.4), days with symptoms to medical care OR: 2.8 (CI95%: 1.2-6.5), breathing difficulty OR: 3.4 (CI95%: 1.4-8.2), vomiting OR: 3.3 (CI95%: 1.4-7.4), cutaneous lesions OR: 5.6 (CI95%: 1.9-16.6). Presence of three or more of these risk factors at hospital entrance predicted severe disease in COVID-19 positive children. Age, presence of underlying illness, male sex, breathing difficulty, and dehydration were predictive of death in COVID-19 children. Our study identifies several predictors of severe pediatric COVID-19 and death. Incorporating these predictors, we developed a tool that clinicians can use to identify children at high risk of severe COVID-19 in limited-resource settings.

Surge Capacity of Taipei's Regional Emergency Medical System during COVID-19: A System Dynamics Approach

Background

The community transmission of COVID-19 has caused the breakdown of the regional emergency medical system (REMS), impacting the rights and care of regional patients with acute and severe conditions. This study proposes a model for the surge capacity of REMS to plan for readiness and preparedness during challenging events that overload capacity.

Methods

The surge capacity of REMS during the COVID-19 pandemic was studied. The data collection included 26 hospitals that received the data. To simulate the dynamics of Taipei's REMS surge capacity, we observed its ability to treat COVID-19 patients with moderate to severe acute respiratory distress syndrome (ARDS). This will involve monitoring the stock of ventilators, physicians, and nurses within the subsystem loops.

Results

Healthcare managers and administrators can use the overload model and hypothetical scenarios to develop new scenarios with different demands on surge capacity. The REMS system capacity model can be used as an aid to guide planning and cross-checking for address Prepare to plan.

Conclusions

We combined data regarding the availability of ventilators, physicians, nurses, specialized beds, and general acute care beds in our simulations. Thus, our simulations, with support from a well-established regional command and management structure, could help REMS achieve the optimal surge capacity.

Post-hospital recovery trajectories of family members of critically ill COVID-19 survivors: an international qualitative investigation

PURPOSE

The immediate impact of coronavirus disease 2019 (COVID-19) visiting restrictions for family members has been well-documented. However, the longer-term trajectory, including mechanisms for support, is less well-known. To address this knowledge gap, we aimed to explore the post-hospital recovery trajectory of family members of patients hospitalised with a critical care COVID-19 admission. We also sought to understand any differences across international contexts.

METHODS

We undertook semi-structured interviews with family members of patients who had survived a COVID-19 critical care admission. Family members were recruited from Spain and the United Kingdom (UK) and telephone interviews were undertaken. Interviews were analysed using a thematic content analysis.

RESULTS

Across the international sites, 19 family members were interviewed. Four themes were identified: changing relationships and carer burden; family health and trauma; social support and networks and differences in lived experience. We found differences in the social support and networks theme across international contexts, with Spanish participants more frequently discussing religion as a form of support.

CONCLUSIONS

This international qualitative investigation has demonstrated the challenges which family members of patients hospitalised with a critical care COVID-19 admission experience following hospital discharge. Specific support mechanisms which could include peer support networks, should be implemented for family members to ensure ongoing needs are met.

Relationship between intensive care surge capacity and hospital factors: an extensive experience

As a prolonged surge scenario, the COVID-19 pandemic has offered an unparalleled opportunity to improve hospital surge capacity (SC) understanding and the ability to manage it. In this study, the authors report the experience of a large hospital network and evaluate potential relationships between Intensive Care Units SC (ICU-SC) and some hospital-related variables: bed occupancy, emergency department admissions, ward admission from ED, and elective surgery procedures. Pearson's partial correlation coefficient (r) has been used to define the relationship between SC and the daily values of the above variables, collected through a dedicated digital platform that also ensured a regular quality check of the data. The observation has concerned several levels of analysis, namely two different types of SC calculation (SC base-SCb and SC actual-SCa), hospital category level and multi-hospital level, and two consecutive pandemic waves. Among the 16 hospitals observed, the correlation was shown to be moderate-positive with non-ICU bed occupancy (r/ = 0.62, r/ = 0.54), strong/moderate with ICU bed occupancy (r/ = 0.72, r/ = 0.54), and moderate with ward admissions from ED (r/ = 0.50, r/ = 0.51) On the contrary, the correlation proved to be moderate-negative with ED admissions (r/ =  - 0.69, r/ =  - 0.62) and low with the number of elective surgery procedures (r/ =  - 0.10, r/ =  - 0.16). This study identified a positive correlation between SC and three variables monitored: ICU bed occupancy, non-ICU bed occupancy, and ward admissions from ED. On the contrary, the correlation was negative for ED admission and the number of elective surgery procedures. The results have been confirmed across all levels of analysis adopted.

Can I go home now? The safety and efficacy of a new UK paediatric febrile neutropenia protocol for risk-stratified early discharge on oral antibiotics

OBJECTIVE

To evaluate a new protocol of risk stratification and early discharge for children with febrile neutropenia (FN).

DESIGN

Prospective service evaluation from 17 April 2020 to 16 April 2021.

SETTING

13 specialist centres in the UK.

PATIENTS

405 children presenting with FN.

INTERVENTION

All children received intravenous antibiotics at presentation. Risk stratification was determined using the Australian-UK-Swiss (AUS) rule and eligibility for homecare assessed using criteria including disease, chemotherapy, presenting features and social factors. Those eligible for homecare could be discharged on oral antibiotics after a period of observation proportional to their risk group.

MAIN OUTCOME MEASURES

Median duration of admission and of intravenous antibiotics, and percentage of patients with positive blood cultures, significant infection, readmission within 7 days of initial presentation, intensive care unit (ICU) admission, death from infection and death from other causes.

RESULTS

13 centres contributed 729 initial presentations of 405 patients. AUS rule scores were positively correlated with positive blood cultures, significant infection, ICU admission and death. 20% of children were eligible for homecare with oral antibiotics, of which 55% were low risk (AUS 0-1). 46% low-risk homecare eligible patients were discharged by 24 hours vs 2% homecare ineligible. Homecare readmission rates were 14% overall and 16% for low-risk cases (similar to a meta-analysis of previous studies). No child eligible for homecare was admitted to ICU or died.

CONCLUSIONS

Use of the AUS rule and homecare criteria allow for safe early outpatient management of children with FN.

Response of UK community hospitals to the COVID-19 pandemic: an appreciative inquiry

INTRODUCTION

The 500 community hospitals in the UK provide a range of services to their communities. The response of these small, mainly rural, hospitals to the COVID-19 pandemic has not yet been examined and so this study sought to address this gap.

METHOD

Appreciative inquiry was used to understand staff perspectives of how community hospitals responded to the COVID-19 (SARS-CoV-2) pandemic. A total of 20 organisations participated, representing 168 (34%) community hospitals in the UK. Qualitative interviews were conducted, with a total of 85 staff members, using an online video platform. 30 case studies were developed from these interviews.

RESULTS

Staff described positive changes that were made in the context of the fear and uncertainty experienced in the pandemic. Quality improvements were reported in a wide range of services and models of care such as the use of the inpatient beds, and the access and management of urgent care services. Rapid changes were made in the way that services were managed, such as communications and leadership. Programmes of accelerated training were offered for existing and redeployed staff. Attention to staff health and well-being was a feature and there were a variety of innovations designed to support patients and their families. The impact of the changes was viewed as strengthening of integrated working between staff and sectors, the ability to rapidly innovate and improve quality, and the scope to use local decision-making to make changes.

CONCLUSION

Staff of community hospitals described innovative and rapid quality improvements in their community hospitals in response to the pandemic. The case studies illustrated the features of community hospitals, showing that they can be resilient, flexible, responsive, creative, compassionate and integrated. The case studies of quality improvements are being used to encourage sharing and learning across community hospitals and beyond.

Emergency contracting and the delivery of elective care services across the English National Health Service and independent sector during COVID-19: a descriptive analysis

BACKGROUND

Following a virtual standstill in the delivery of elective procedures in England, a national block contract between the NHS and the independent sector aimed to help restart surgical care. This study aims to describe subsequent changes in trends in elective care service delivery following implementation of the initial iteration of this contract.

METHODS

Population-based retrospective cohort study, assessing the delivery of all publicly funded and privately funded elective care delivered in England between 1 April 2020 and 31 July 2020 compared with the same period in 2019. Discharge data from the Hospital Episode Statistics and private healthcare data from the Private Health Information Network was stratified by specialty, procedure, length of stay and patient complexity in terms of age and Charlson Comorbidity Index.

RESULTS

COVID-19 significantly reduced publicly funded elective care activity, though changes were more pronounced in the independent sector (-65.1%) compared with the NHS (-52.7%), whereas reductions in privately funded elective care activity were similar in both independent sector hospitals (-74.2%) and NHS hospitals (-72.9%). Patient complexity increased in the independent sector compared with the previous year, with mixed findings in NHS hospitals. Most specialties, irrespective of sector or funding mechanisms, experienced a reduction in hospital admissions. However, some specialities, including medical oncology, clinical oncology, clinical haematology and cardiology, experienced an increase in publicly-funded elective care activity in the independent sector.

CONCLUSION

Elective care delivered by the independent sector remained significantly below historic levels, although this overlooks significant variation between regions and specialities. There may be opportunities to learn from regions which achieved more significant increases in publicly funded elective care in independent sector providers as a strategy to address the growing backlog of elective care.

Factors associated with, and variations in, COVID-19 hospital death rates in England's first two waves: observational study

OBJECTIVES

To assess patient-level and hospital-level predictors of death and variation in death rates following admission for COVID-19 in England's first two waves after accounting for random variation. To quantify the correlation between hospitals' first and second wave death rates.

DESIGN

Observational study using administrative data.

SETTING

Acute non-specialist hospitals in England.

PARTICIPANTS

All patients admitted with a primary diagnosis of COVID-19.

PRIMARY AND SECONDARY OUTCOMES

In-hospital death.

RESULTS

Hospital Episode Statistics (HES) data were extracted for all acute hospitals in England for COVID-19 admissions from March 2020 to March 2021. In wave 1 (March to July 2020), there were 74 484 admissions and 21 883 deaths (crude rate 29.4%); in wave 2 (August 2020 to March 2021), there were 165 642 admissions and 36 040 deaths (21.8%). Wave 2 patients were younger, with more hypertension and obesity but lower rates of other comorbidities. Mortality improved for all ages; in wave 2, it peaked in December 2020 at 24.2% (lower than wave 1's peak) but halved by March 2021. In multiple multilevel modelling combining HES with hospital-level data from Situational Reports, wave 2 and wave 1 variables significantly associated with death were mostly the same. The median odds ratio for wave 1 was just 1.05 and for wave 2 was 1.07. At 99.8% control limits, 3% of hospitals were high and 7% were low funnel plot outliers in wave 1; these figures were 9% and 12% for wave 2. Four hospitals were (low) outliers in both waves. The correlation between hospitals' adjusted mortality rates between waves was 0.45 (p<0.0001). Length of stay was similar in each wave.

CONCLUSIONS

England's first two COVID-19 waves were similar regarding predictors and moderate interhospital variation. Despite the challenges, variation in death rates and length of stay between hospitals was modest and might be accounted for by unobserved patient factors.

A country-level analysis comparing hospital capacity and utilisation during the first COVID-19 wave across Europe

BACKGROUND

The exponential increase in SARS-CoV-2 infections during the first wave of the pandemic created an extraordinary overload and demand on hospitals, especially intensive care units (ICUs), across Europe. European countries have implemented different measures to address the surge ICU capacity, but little is known about the extent. The aim of this paper is to compare the rates of hospitalised COVID-19 patients in acute and ICU care and the levels of national surge capacity for intensive care beds across 16 European countries and Lombardy region during the first wave of the pandemic (28 February to 31 July).

METHODS

For this country level analysis, we used data on SARS-CoV-2 cases, current and/or cumulative hospitalised COVID-19 patients and current and/or cumulative COVID-19 patients in ICU care. To analyse whether capacities were exceeded, we also retrieved information on the numbers of hospital beds, and on (surge) capacity of ICU beds during the first wave of the COVID-19 pandemic from the COVID-19 Health System Response Monitor (HSRM). Treatment days and mean length of hospital stay were calculated to assess hospital utilisation.

RESULTS

Hospital and ICU capacity varied widely across countries. Our results show that utilisation of acute care bed capacity by patients with COVID-19 did not exceed 38.3% in any studied country. However, the Netherlands, Sweden, and Lombardy would not have been able to treat all patients with COVID-19 requiring intensive care during the first wave without an ICU surge capacity. Indicators of hospital utilisation were not consistently related to the number of SARS-CoV-2 infections. The mean number of hospital days associated with one SARS-CoV-2 case ranged from 1.3 (Norway) to 11.8 (France).

CONCLUSION

In many countries, the increase in ICU capacity was important to accommodate the high demand for intensive care during the first COVID-19 wave.

Ethnic, clinical, and pharmacological predictors of high social dependence in COVID-19 patients admitted to post-acute care

The COVID-19 epidemic affected both acute hospitals and post-acute care, which experienced various degrees of overcrowding. We evaluated all the patients admitted to a post-acute care facility during the second wave of the epidemic to detect features possibly associated with social frailty. We analyzed the socio-demographic characteristics and comorbidities of the patients and the pattern of their previous hospitalization as available in their discharge letter. In addition, we evaluated their clinical features and tests on admission to post-acute care. We found that COVID-19 patients without social problems had distinctive features. Those with a higher need for specific pharmacological treatments during their stay in an acute hospital were less likely to be admitted to post-acute care for concomitant social problems ( p < 0.05 for all types of medication). They were also more likely to be native (p = 0.02), obese (p = 0.009), and with hypertension (p = 0.03). Patients with social problems usually stayed longer and were less frequently discharged home with a negative swab (p = 0.0009). In COVID-19 patients, recognition of distinctive features predicting that their need for a longer hospital stay is due to social problems can lead to more appropriate discharge and to more appropriate use of post-acute care.

Experiences and concerns of health workers throughout the first year of the COVID-19 pandemic in the UK: A longitudinal qualitative interview study

OBJECTIVE

To identify the experiences and concerns of health workers (HWs), and how they changed, throughout the first year of the COVID-19 pandemic in the UK.

METHODS

Longitudinal, qualitative study with HWs involved in patient management or delivery of care related to COVID-19 in general practice, emergency departments and hospitals. Participants were identified through snowballing. Semi-structured telephone or video interviews were conducted between February 2020 and February 2021, audio-recorded, summarised, and transcribed. Data were analysed longitudinally using framework and thematic analysis.

RESULTS

We conducted 105 interviews with 14 participants and identified three phases corresponding with shifts in HWs' experiences and concerns. (1) Emergency and mobilisation phase (late winter-spring 2020), with significant rapid shifts in responsibilities, required skills, and training, and challenges in patient care. (2) Consolidation and preparation phase (summer-autumn 2020), involving gradual return to usual care and responsibilities, sense of professional development and improvement in care, and focus on learning and preparing for future. (3) Exhaustion and survival phase (autumn 2020-winter 2021), entailing return of changes in responsibilities, focus on balancing COVID-19 and non-COVID care (until becoming overwhelmed with COVID-19 cases), and concerns about longer-term impacts of unceasing pressure on health services. Participants' perceptions of COVID-19 risk and patient/public attitudes changed throughout the year, and tiredness and weariness turned into exhaustion.

CONCLUSIONS

Results showed a long-term impact of the COVID-19 pandemic on UK HWs' experiences and concerns related to changes in their roles, provision of care, and personal wellbeing. Despite mobilisation in the emergency phase, and trying to learn from this, HWs' experiences seemed to be similar or worse in the second wave partly due to many COVID-19 cases. The findings highlight the importance of supporting HWs and strengthening system-level resilience (e.g., with resources, processes) to enable them to respond to current and future demands and emergencies.

Specific nutritional and metabolic characteristics of COVID‐19 persistent critically ill patients

Background

Little is known about metabolic and nutrition characteristics of patients with coronavirus disease 2019 (COVID‐19) and persistent critical illness. We aimed to compare those characteristics in patients with PCI and COVID‐19 and patients without COVID‐19 infection (non‐CO)—primarily, their energy balance.

Methods

This is a prospective observational study including two consecutive cohorts, defined as needing intubation for >10 days. We collected demographic data, severity scores, nutrition variables, length of stay, and mortality.

Results

Altogether, 104 patients (52 per group) were included (59 ± 14 years old [mean ± SD], 75% men) between July 2019 and May 2020. SAPSII, Nutrition Risk Screening (NRS) score, proportion of obese patients, duration of intubation (18.2 ± 11.7 days), and mortality rates were similar. Patients with COVID‐19 (vs non‐CO) had lower SOFA scores (P = 0.013) and more frequently needed prone position (P < 0.0001) and neuromuscular blockade (P < 0.0001): lengths of ICU (P = 0.03) and hospital stays were shorter (P < 0.0001). Prescribed energy targets were below those of the ICU protocol. The energy balance of patients with COVID‐19 was significantly more negative after day 10. Enteral nutrition (EN) started earlier (P < 0.0001). During the first 10 days, COVID‐19 patients received more lipid (propofol sedation) and less protein. Higher admission C‐reactive protein (P = 0.002) decreased faster (P < 0.001). Whereas intestinal function was characterized by constipation in both groups during the first 10 days, diarrhea was less common in patients with COVID‐19 thereafter.

Conclusion

Compared with non‐CO patients, COVID‐19 patients were not more obese, had lower SOFA scores, and were fed more rapidly with EN, because of a more normal gastrointestinal function possibly due to fewer non–respiratory organ failures: their energy balances were more negative after the first 10 days. Propofol sedation reduced protein delivery.

Lived experiences of healthcare workers on the front line during the COVID-19 pandemic: a qualitative interview study

OBJECTIVES

This study aimed to investigate the presence of perceived stressors, psychological safety and teamwork in healthcare professionals. As the timeframe for this study spanned the first wave of the COVID-19 pandemic, data were captured demonstrating the impact of the pandemic on these factors.

DESIGN

Qualitative interview study.

SETTING

All staff working within the emergency and critical care departments of one National Health Service Trust in London, UK.

PARTICIPANTS

Forty-nine participants were recruited using a purposive sampling technique and interviewed when the first wave of the COVID-19 pandemic had subsided.

MAIN OUTCOME MEASURES

Evaluation of changes in perceived stressors, psychological safety and teamwork in individuals working during the COVID-19 pandemic.

RESULTS

The thematic analysis relating to a participant's lived experiences while working during COVID-19 led to the construction of five key themes, including 'psychological effects' and 'changes in team dynamics'. Several psychological effects were described, including the presence of psychological distress and insights into the aetiology of moral injury. There was marked heterogeneity in participants' response to COVID-19, particularly with respect to changes in team dynamics and the perception of a psychologically safe environment. Descriptions of improved team cohesiveness and camaraderie contrasted with stories of new barriers, notably due to the high workload and the impact of personal protective equipment. Building on these themes, a map of key changes arising due to the pandemic was developed, highlighting potential opportunities to provide targeted support.

CONCLUSIONS

Working on the front line of a pandemic can have significant implications for healthcare workers, putting them at risk of psychological distress and moral injury, as well as affecting team dynamics. There is striking heterogeneity in the manifestation of these challenges. Team leaders can use the themes and qualitative data from this study to help identify areas for management focus and individual and team support.

Trends in 28-Day Mortality of Critical Care Patients With Coronavirus Disease 2019 in the United Kingdom: A National Cohort Study, March 2020 to January 2021

OBJECTIVES

To determine whether the previously described trend of improving mortality in people with coronavirus disease 2019 in critical care during the first wave was maintained, plateaued, or reversed during the second wave in United Kingdom, when B117 became the dominant strain.

DESIGN

National retrospective cohort study.

SETTING

All English hospital trusts (i.e., groups of hospitals functioning as single operational units), reporting critical care admissions (high dependency unit and ICU) to the Coronavirus Disease 2019 Hospitalization in England Surveillance System.

PATIENTS

A total of 49,862 (34,336 high dependency unit and 15,526 ICU) patients admitted between March 1, 2020, and January 31, 2021 (inclusive).

INTERVENTIONS

Not applicable.

MEASUREMENTS AND MAIN RESULTS

The primary outcome was inhospital 28-day mortality by calendar month of admission, from March 2020 to January 2021. Unadjusted mortality was estimated, and Cox proportional hazard models were used to estimate adjusted mortality, controlling for age, sex, ethnicity, major comorbidities, social deprivation, geographic location, and operational strain (using bed occupancy as a proxy). Mortality fell to trough levels in June 2020 (ICU: 22.5% [95% CI, 18.2-27.4], high dependency unit: 8.0% [95% CI, 6.4-9.6]) but then subsequently increased up to January 2021: (ICU: 30.6% [95% CI, 29.0-32.2] and high dependency unit, 16.2% [95% CI, 15.3-17.1]). Comparing patients admitted during June-September 2020 with those admitted during December 2020-January 2021, the adjusted mortality was 59% (CI range, 39-82) higher in high dependency unit and 88% (CI range, 62-118) higher in ICU for the later period. This increased mortality was seen in all subgroups including those under 65.

CONCLUSIONS

There was a marked deterioration in outcomes for patients admitted to critical care at the peak of the second wave of coronavirus disease 2019 in United Kingdom (December 2020-January 2021), compared with the post-first-wave period (June 2020-September 2020). The deterioration was independent of recorded patient characteristics and occupancy levels. Further research is required to determine to what extent this deterioration reflects the impact of the B117 variant of concern.

Machine Learning-Based Prediction of COVID-19 Mortality With Limited Attributes to Expedite Patient Prognosis and Triage: Retrospective Observational Study

Background

The onset and development of the COVID-19 pandemic have placed pressure on hospital resources and staff worldwide. The integration of more streamlined predictive modeling in prognosis and triage–related decision-making can partly ease this pressure.

Objective

The objective of this study is to assess the performance impact of dimensionality reduction on COVID-19 mortality prediction models, demonstrating the high impact of a limited number of features to limit the need for complex variable gathering before reaching meaningful risk labelling in clinical settings.

Methods

Standard machine learning classifiers were employed to predict an outcome of either death or recovery using 25 patient-level variables, spanning symptoms, comorbidities, and demographic information, from a geographically diverse sample representing 17 countries. The effects of feature reduction on the data were tested by running classifiers on a high-quality data set of 212 patients with populated entries for all 25 available features. The full data set was compared to two reduced variations with 7 features and 1 feature, respectively, extracted using univariate mutual information and chi-square testing. Classifier performance on each data set was then assessed on the basis of accuracy, sensitivity, specificity, and received operating characteristic–derived area under the curve metrics to quantify benefit or loss from reduction.

Results

The performance of the classifiers on the 212-patient sample resulted in strong mortality detection, with the highest performing model achieving specificity of 90.7% (95% CI 89.1%-92.3%) and sensitivity of 92.0% (95% CI 91.0%-92.9%). Dimensionality reduction provided strong benefits for performance. The baseline accuracy of a random forest classifier increased from 89.2% (95% CI 88.0%-90.4%) to 92.5% (95% CI 91.9%-93.0%) when training on 7 chi-square–extracted features and to 90.8% (95% CI 89.8%-91.7%) when training on 7 mutual information–extracted features. Reduction impact on a separate logistic classifier was mixed; however, when present, losses were marginal compared to the extent of feature reduction, altogether showing that reduction either improves performance or can reduce the variable-sourcing burden at hospital admission with little performance loss. Extreme feature reduction to a single most salient feature, often age, demonstrated large standalone explanatory power, with the best-performing model achieving an accuracy of 81.6% (95% CI 81.1%-82.1%); this demonstrates the relatively marginal improvement that additional variables bring to the tested models.

Conclusions

Predictive statistical models have promising performance in early prediction of death among patients with COVID-19. Strong dimensionality reduction was shown to further improve baseline performance on selected classifiers and only marginally reduce it in others, highlighting the importance of feature reduction in future model construction and the feasibility of deprioritizing large, hard-to-source, and nonessential feature sets in real world settings.

Disability-Adjusted Life Years for the COVID-19 Pandemic in the Mexican Population

Mexico is one of the countries most affected by the COVID-19 disease. Although there is vast information on the disease, there still are unknown data on the societal and economic cost of the pandemic. To estimate this impact, the disability-adjusted life years (DALYs) can be a useful tool. Objective: To assess the DALYs due to COVID-19 in Mexico. Methods: We used the data released by the Mexican Ministry of Health to estimate the DALYs by the sum of the years of life lived with disability (YLDs) and the years of life lost (YLLs). Results: A total of 1,152,885 confirmed cases and 324,570 suspected cases of COVID-19 have been registered. Half of the cases were men, with a median age of 43.4 ± 16.9 years. About 8.3% died. A total of 39,202 YLDs were attributable to COVID-19. The total YLLs caused by COVID-19 were 2,126,222. A total of 2,165,424.5 DALYs for COVID-19 were estimated. The total DALYs were the highest in people between 50 and 59 years. The DALYs for each COVID-19 case were the highest in individuals between 60 and 79 years. Conclusion: The DALYs generated by the COVID-19 represent a more significant disease burden than that reported for other causes, such as the 2009 H1N1 influenza pandemic. Although it impacts all age groups in terms of disability, the most affected group are people over 50 years of age, whose risk of death is higher.

The association between mechanical ventilator compatible bed occupancy and mortality risk in intensive care patients with COVID-19: a national retrospective cohort study

BACKGROUND

The literature paints a complex picture of the association between mortality risk and ICU strain. In this study, we sought to determine if there is an association between mortality risk in intensive care units (ICU) and occupancy of beds compatible with mechanical ventilation, as a proxy for strain.

METHODS

A national retrospective observational cohort study of 89 English hospital trusts (i.e. groups of hospitals functioning as single operational units). Seven thousand one hundred thirty-three adults admitted to an ICU in England between 2 April and 1 December, 2020 (inclusive), with presumed or confirmed COVID-19, for whom data was submitted to the national surveillance programme and met study inclusion criteria. A Bayesian hierarchical approach was used to model the association between hospital trust level (mechanical ventilation compatible), bed occupancy, and in-hospital all-cause mortality. Results were adjusted for unit characteristics (pre-pandemic size), individual patient-level demographic characteristics (age, sex, ethnicity, deprivation index, time-to-ICU admission), and recorded chronic comorbidities (obesity, diabetes, respiratory disease, liver disease, heart disease, hypertension, immunosuppression, neurological disease, renal disease).

RESULTS

One hundred thirty-five thousand six hundred patient days were observed, with a mortality rate of 19.4 per 1000 patient days. Adjusting for patient-level factors, mortality was higher for admissions during periods of high occupancy (> 85% occupancy versus the baseline of 45 to 85%) [OR 1.23 (95% posterior credible interval (PCI): 1.08 to 1.39)]. In contrast, mortality was decreased for admissions during periods of low occupancy (< 45% relative to the baseline) [OR 0.83 (95% PCI 0.75 to 0.94)].

CONCLUSION

Increasing occupancy of beds compatible with mechanical ventilation, a proxy for operational strain, is associated with a higher mortality risk for individuals admitted to ICU. Further research is required to establish if this is a causal relationship or whether it reflects strain on other operational factors such as staff. If causal, the result highlights the importance of strategies to keep ICU occupancy low to mitigate the impact of this type of resource saturation.

A national retrospective study of the association between serious operational problems and COVID-19 specific intensive care mortality risk

OBJECTIVES

To describe the relationship between reported serious operational problems (SOPs), and mortality for patients with COVID-19 admitted to intensive care units (ICUs).

DESIGN

English national retrospective cohort study.

SETTING

89 English hospital trusts (i.e. small groups of hospitals functioning as single operational units).

PATIENTS

All adults with COVID-19 admitted to ICU between 2nd April and 1st December, 2020 (n = 6,737).

INTERVENTIONS

N/A.

MAIN OUTCOMES AND MEASURES

Hospital trusts routinely submit declarations of whether they have experienced 'serious operational problems' in the last 24 hours (e.g. due to staffing issues, adverse weather conditions, etc.). Bayesian hierarchical models were used to estimate the association between in-hospital mortality (binary outcome) and: 1) an indicator for whether a SOP occurred on the date of a patient's admission, and; 2) the proportion of the days in a patient's stay that had a SOP occur within their trust. These models were adjusted for individual demographic characteristics (age, sex, ethnicity), and recorded comorbidities.

RESULTS

Serious operational problems (SOPs) were common; reported in 47 trusts (52.8%) and were present for 2,701 (of 21,716; 12.4%) trust days. Overall mortality was 37.7% (2,539 deaths). Admission during a period of SOPs was associated with a substantially increased mortality; adjusted odds ratio (OR) 1.34 (95% posterior credible interval (PCI): 1.07 to 1.68). Mortality was also associated with the proportion of a patient's admission duration that had concurrent SOPs; OR 1.47 (95% PCI: 1.10 to 1.96) for mortality where SOPs were present for 100% compared to 0% of the stay.

CONCLUSION AND RELEVANCE

Serious operational problems at the trust-level are associated with a significant increase in mortality in patients with COVID-19 admitted to critical care. The link isn't necessarily causal, but this observation justifies further research to determine if a binary indicator might be a valid prognostic marker for deteriorating quality of care.

COVID-19 Vaccine Priority Strategy Using a Heterogenous Transmission Model Based on Maximum Likelihood Estimation in the Republic of Korea

(1) Background: The vaccine supply is likely to be limited in 2021 due to constraints in manufacturing. To maximize the benefit from the rollout phase, an optimal strategy of vaccine allocation is necessary based on each country's epidemic status. (2) Methods: We first developed a heterogeneous population model considering the transmission matrix using maximum likelihood estimation based on the epidemiological records of individual COVID-19 cases in the Republic of Korea. Using this model, the vaccine priorities for minimizing mortality or incidence were investigated. (3) Results: The simulation results showed that the optimal vaccine allocation strategy to minimize the mortality (or incidence) was to prioritize elderly and healthcare workers (or adults) as long as the reproductive number was below 1.2 (or over 0.9). (4) Conclusion: Our simulation results support the current Korean government vaccination priority strategy, which prioritizes healthcare workers and senior groups to minimize mortality, under the condition that the reproductive number remains below 1.2. This study revealed that, in order to maintain the current vaccine priority policy, it is important to ensure that the reproductive number does not exceed the threshold by concurrently implementing nonpharmaceutical interventions.