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Ex-vivo lung perfusion (EVLP) has improved organ utilization for lung transplantation, but it is not yet known whether the benefits of this technology offset its additional costs. We compared the institutional costs of lung transplantation before vs after EVLP was available to identify predictors of costs and determine the health-economic impact of EVLP.We performed a retrospective, before-after, propensity-score weighted cohort study of patients wait-listed for lung transplant at University Health Network (UHN) in Ontario, Canada, between January 2005 and December 2019 using institutional administrative data. We compared costs, in 2019 Canadian Dollars ($), between patients referred for transplant before EVLP was available (Pre-EVLP) to after (Modern EVLP). Cumulative costs were estimated using a novel application of multistate survival models. Predictors of costs were identified using weighted log-gamma generalized linear regression.A total of 1,199 patients met inclusion criteria (352 Pre-EVLP; 847 Modern EVLP). Mean total costs for the transplant hospitalization were $111,878 ($94,123-$130,767) in the Pre-EVLP era and $110,969 ($87,714-$136,000) in the Modern EVLP era. Cumulative five-year costs since referral were $278,777 ($82,575-$298,135) in the Pre-EVLP era and $293,680 ($252,832-$317,599) in the Modern EVLP era. We observed faster progression to transplantation when EVLP was available. EVLP availability was not a predictor of waitlist (cost ratio [CR] 1.04 [0.81-1.37]; p = 0.354) or transplant costs (CR 1.02 [0.80-1.29]; p = 0.425) but was associated with lower costs during posttransplant years 12 (CR 0.75 [0.58-1.06]; p = 0.05) and posttransplant years 3+ (CR 0.43 [0.26-0.74]; p = 0.001).At our center, EVLP availability was associated with faster progression to transplantation at no significant marginal cost.

There is wide variation in mortality among patients hospitalized with COVID-19. Whether this is related to patient or hospital factors is unknown.To compare the risk of mortality for patients hospitalized with COVID-19 and to determine whether the majority of that variation was explained by differences in patient characteristics across sites.An international multicenter cohort study of hospitalized adults with laboratory-confirmed COVID-19 enrolled from 10 hospitals in Ontario, Canada and 8 hospitals in Copenhagen, Denmark between January 1, 2020 and November 11, 2020.Inpatient mortality. We used a multivariable multilevel regression model to compare the in-hospital mortality risk across hospitals and quantify the variation attributable to patient-level factors.There were 1364 adults hospitalized with COVID-19 in Ontario (n = 1149) and in Denmark (n = 215). In Ontario, the absolute risk of in-hospital mortality ranged from 12.0% to 39.8% across hospitals. Ninety-eight percent of the variation in mortality in Ontario was explained by differences in the characteristics of the patients. In Denmark, the absolute risk of inpatients ranged from 13.8% to 20.6%. One hundred percent of the variation in mortality in Denmark was explained by differences in the characteristics of the inpatients.There was wide variation in inpatient COVID-19 mortality across hospitals, which was largely explained by patient-level factors, such as age and severity of presenting illness. However, hospital-level factors that could have affected care, including resource availability and capacity, were not taken into account. These findings highlight potential limitations in comparing crude mortality rates across hospitals for the purposes of reporting on the quality of care.

ObjectiveTo estimate costs, quality-adjusted life-years, and the value of undertaking a future randomized controlled trial for different oxygenation thresholds used to initiate invasive ventilation in hypoxemic respiratory failure.DesignModel-based cost-utility estimation with individual-level simulation and value-of-information analysis.SettingCritical care units.ParticipantsAdults admitted to critical care receiving non-invasive oxygen.InterventionsWe compared four strategies: initiation of invasive ventilation at thresholds of saturation-to-inspired oxygen fraction ratio (SF) < 110, < 98, or < 88, and usual care.Main resultsAn invasive ventilation initiation threshold of SF < 110, compared to usual care, resulted in more predicted invasive ventilation (62% vs 31%), hospital survival (78.4% vs 75.5%), quality-adjusted life years (QALYs) (8.48 vs 8.34), and lifetime costs (86,700 Canadian dollars (CAD) vs 75,600 CAD). Among the four strategies, threshold SF < 110 had the highest expected net monetary benefit (761,000 CAD), but there was significant uncertainty, because all four strategies had similar probability (range: 23.5% to 27.5%) of having the best net monetary benefit. The expected value to society over the next 10 years of a 400-person randomized trial of oxygenation thresholds was 4.27 billion CAD, and remained high (2.64 billion CAD) in a scenario analysis considering a hypothetical threshold that resulted in less invasive ventilation and similar survival compared to usual care.ConclusionThe preferred threshold to initiate invasive ventilation in hypoxemic respiratory failure is uncertain. It would be highly valuable to society to identify thresholds that, in comparison to usual care, either improve survival or reduce invasive ventilation without reducing survival.Key pointsQuestionWhat are the costs and quality-adjusted life-years associated with different oxygenation thresholds for initiating invasive ventilation, and what is the expected value to society of a randomized controlled trial?FindingsIn this health economic evaluation comparing usual care to three different thresholds for initiating invasive ventilation in hypoxemic respiratory failure based on the saturation-to-inspired oxygen fraction ratio (SF), we found that threshold SF < 110 had the highest expected quality-adjusted life-years and net monetary benefit, despite increased predicted invasive ventilation use. However, there was significant residual uncertainty, and the expected value to society of a 400-person randomized trial to compare thresholds for initiating invasive ventilation was greater than 2.5 billion Canadian dollars.MeaningThe preferred threshold to initiate invasive ventilation in hypoxemic respiratory failure is uncertain and further study would be valuable to society.Social media summaryWhen should we intubate and start invasive ventilation for people with hypoxemic respiratory failure? Our health economic evaluation shows that the preferred threshold is uncertain, but that a clinical trial to determine such a threshold would be immensely valuable to patients and society

BACKGROUND: Understanding resource use for coronavirus disease 2019 (COVID-19) is critical. We conducted a descriptive analysis using public health data to describe age- and sex-specific acute care use, length of stay (LOS) and mortality associated with COVID-19. METHODS: We conducted a descriptive analysis using Ontario's Case and Contact Management Plus database of individuals who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Ontario from Mar. 1 to Sept. 30, 2020, to determine age- and sex-specific hospital admissions, intensive care unit (ICU) admissions, use of invasive mechanical ventilation, LOS and mortality. We stratified analyses by month of infection to study temporal trends and conducted subgroup analyses by long-term care residency. RESULTS: During the observation period, 56 476 individuals testing positive for SARS-CoV-2 were reported; 41 049 (72.7%) of these were younger than 60 years, and 29 196 (51.7%) were female. Proportion of cases shifted from older populations (> 60 yr) to younger populations (10-39 yr) over time. Overall, 5383 (9.5%) of individuals were admitted to hospital; of these, 1183 (22.0%) were admitted to the ICU, and 712 (60.2%) of these received invasive mechanical ventilation. Mean LOS for individuals in the ward, ICU without invasive mechanical ventilation and ICU with invasive mechanical ventilation was 12.8 (standard deviation [SD] 15.4), 8.5 (SD 7.8) and 20.5 (SD 18.1) days, respectively. Among patients receiving care in the ward, ICU without invasive mechanical ventilation and ICU with invasive mechanical ventilation, 911/3834 (23.8%), 124/418 (29.7%) and 287/635 (45.2%) died, respectively. All outcomes varied by age and decreased over time, overall and within age groups. INTERPRETATION: This descriptive study shows use of acute care and mortality varying by age and decreasing between March and September 2020 in Ontario. Improvements in clinical practice and changing risk distributions among those infected may contribute to fewer severe outcomes.

RESUME CONTEXTE: La propagation a l’echelle planetaire de la maladie a coronavirus 2019 (COVID-2019) se poursuit dans plusieurs pays, mettant a rude epreuve les systemes de sante. Cette etude avait pour but de predire les repercussions de la pandemie sur les issues des patients et l’utilisation des ressources hospitalieres en Ontario (Canada). METHODES: Nous avons concu un modele de simulation axe sur les personnes illustrant le flux de patients atteints de la COVID-19 dans les hopitaux ontariens. Nous avons simule diverses combinaisons de trajectoires epidemiques et de capacites de soins hospitaliers. Les parametres a l’etude etaient le nombre de patients devant etre admis au service d’hospitalisation ou a l’unite des soins intensifs (USI) —avec ou sans respirateur mecanique —, le nombre de jours jusqu’a l’epuisement des ressources, le nombre de patients en attente de ressources et le nombre de deces. RESULTATS: Nous avons constate que la mise en place rapide de mesures de sante publique efficaces eviterait l’epuisement des ressources hospitalieres. Les simulations dans lesquelles les mesures d’eloignement sanitaire etaient inefficaces ou adoptees tardivement ont montre que l’epuisement des ressources prendrait de 14 a 26 jours et qu’il y aurait, dans le pire des cas, 13 321 deces de personnes en attente de ressources. Cet epuisement pourrait etre evite ou retarde par la mise en place de mesures rigoureuses visant a ameliorer la capacite des hopitaux en matiere de soins intensifs, de respirateurs mecaniques et de soins hospitaliers. INTERPRETATION: Sans l’adoption de mesures d’eloignement sanitaire rigoureuses, le systeme de sante ontarien n’aurait pas eu les ressources necessaires pour prendre en charge le nombre attendu de patients atteints de la COVID-19, meme en cas d’augmentation rapide de sa capacite hospitaliere. Les penuries auraient fait augmenter le taux de mortalite. En ralentissant la transmission de la maladie par la mise en place de mesures de sante publique et l’augmentation de la capacite des hopitaux, l’Ontario a probablement evite que ces derniers subissent une pression catastrophique.

Unstructured Abstract (250 words) In Ontario, on March 16th, 2020, a directive was issued to all acute care hospitals to halt non-essential procedures in anticipation for a potential surge in COVID-19 patients. This included scheduled outpatient cardiac surgical and interventional procedures that required the use of intensive care units, ventilators, and skilled critical care personnel, given that these procedures would draw from the same pool of resources required for critically ill COVID-19 patients. We adapted the COVID-19 Resource Estimator (CORE) decision analytic model by adding a cardiac component to determine the impact of various policy decisions on the incremental waitlist growth and estimated waitlist mortality for three key groups of cardiovascular disease patients; coronary artery disease, valvular heart disease, and arrhythmias. We provided predictions based on COVID-19 epidemiology available in real-time, in 3 phases. First, in the initial crisis phase, in a worst case scenario, we showed that the potential number of waitlist related cardiac deaths would be orders of magnitude less than those who would die of COVID-19 if critical cardiac care resources were diverted to the care of COVID-19 patients. Second, with better local epidemiology data, we predicted that across five regions of Ontario, there may be insufficient resources to resume all elective outpatient cardiac procedures. Finally in the recovery phase, we showed that the estimated incremental growth in waitlist for all cardiac procedures is likely substantial. These outputs informed timely, data-driven decisions during the COVID-19 pandemic regarding the provision of cardiovascular care., In Ontario, on March 16th, 2020, a directive was issued to all acute care hospitals to halt non-essential procedures in anticipation for a potential COVID-19 patient surge. This manuscript provides examples of how decision analytic models have helped informed policy decisions and to assess the impact of these policies on incremental waitlist activity for cardiac procedures during the COVID-19 pandemic.

BACKGROUND: The global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing substantial strain to health care systems. The purpose of our study was to predict the effect of the COVID-19 pandemic on patient outcomes and use of hospital resources in Ontario, Canada. METHODS: We developed an individual-level simulation to model the flow of patients with COVID-19 through the hospital system in Ontario. We simulated different combined scenarios of epidemic trajectory and hospital health care capacity. Our outcomes included the number of patients who needed admission to the ward or to the intensive care unit (ICU) with or without the need for mechanical ventilation, number of days to resource depletion, number of patients awaiting resources and number of deaths. RESULTS: We found that with effective early public health measures, hospital system resources would not be depleted. For scenarios with late or ineffective implementation of physical distancing, hospital resources would be depleted within 14–26 days, and in the worst case scenario, 13 321 patients would die while waiting for needed resources. Resource depletion would be avoided or delayed with aggressive measures to increase ICU, ventilator and acute care hospital capacities. INTERPRETATION: We found that without aggressive physical distancing measures, the Ontario hospital system would have been inadequately equipped to manage the expected number of patients with COVID-19 despite a rapid increase in capacity. This lack of hospital resources would have led to an increase in mortality. By slowing the spread of the disease using public health measures and by increasing hospital capacity, Ontario may have avoided catastrophic stresses to its hospitals.

BackgroundAs the transmission of SARS-CoV-2 variants intensifies globally, the burden of COVID-19 on the already strained health systems is becoming increasingly concerning. While there is growing literature on the effects of various variants-of-concern (VOC) on increased transmission, the extent to which VOCs may lead to more severe disease remains debated.MethodsIn the current analysis, we use a population-based propensity-score matched cohort study of all incident laboratory-confirmed COVID-19 cases with VOC testing in Ontario, Canada to estimate healthcare resource use and health outcomes attributable to VOCs introduced to Ontario between January 1 and April 9, 2021, relative to the previously circulating wild-type strain.ResultsWe find that VOCs are associated with a higher odds of hospitalisation (odds ratio [OR], 2.25; 95% confidence interval [CI], 2.10-2.40) and ICU admission (OR, 3.31; 95%CI, 2.84-3.86); as well as with a higher odds of mortality for both the general COVID-19 population (OR 1.75; 1.47-2.09) and hospitalised cases (OR, 1.62; 95%CI, 1.23-2.15).ConclusionTaken together, these findings suggest that health systems may face increased demand for healthcare resources as VOCs predominate worldwide in view of low global vaccination coverage.

Based on Ontario cremation data, there has been a 12.8% increase in the number of deaths during the COVID-19 pandemic, compared to the expected numbers of deaths informed by previous years’ cremation data. The causes of these excess deaths include infection with SARS-CoV-2, as well as causes likely related to the pandemic but not due to COVID-19 itself.

Remdesivir, a direct-acting antiviral agent, may reduce mortality and progression to mechanical ventilation in moderately ill patients hospitalized with COVID-19 on supplemental low-flow oxygen. The benefits of remdesivir for critically ill patients requiring supplemental oxygen via high-flow nasal cannula or mask, or non-invasive mechanical ventilation, is uncertain. Remdesivir does not benefit and may harm critically ill patients already receiving mechanical ventilation or requiring extra-corporeal membrane oxygenation (ECMO), and it does not provide substantial benefit for hospitalized patients who do not require supplemental oxygen. Remdesivir appears to have comparable effects when used for 5 days or 10 days, and does not appear to be associated with significant adverse effects. Remdesivir is recommended in moderately ill hospitalized patients with COVID-19 requiring supplemental oxygen (Figure 1). Remdesivir may be considered for patients requiring oxygen supplementation via high-flow nasal cannula or mask, or non-invasive mechanical ventilation. It should not be used in critically ill patients on mechanical ventilation or those receiving ECMO. Remdesivir should not be used in patients who do not require supplemental oxygen.

Highlights • This commentary discusses the different types of models that can be used for pandemic planning in response to coronavirus disease 2019 (COVID-19). This article reviews different types of transmission models for infectious diseases and health-system models based on decision-analysis principles. • We include steps to guide conceptualization of a health-system model with a transmission component to aid decision makers and support public health policy using our COVID-19 Resource Estimator model, which was developed to estimate hospital resources in Ontario, Canada. • This article will be of most interest to health care decision makers, methodologists, health service researchers, and specialists in knowledge translation as well as infectious diseases. While the pandemic has been controlled in some parts of the world, many experts suggest an inevitable second wave. This article will be timely to equip quantitative researchers and decision makers with a guide to understand how modeling and early collaboration can be useful in predicting future consequences of this pandemic and impacts of potential interventions.

Key Points Question What is the association of school reopening or closure with incident and cumulative COVID-19 case numbers compared with other community-based nonpharmaceutical interventions? Findings In this decision analytical modelling study of a synthetic population of 1 000 000 individuals in Ontario, Canada, compared with community-based nonpharmaceutical interventions, school closure was associated with a small change in estimated COVID-19 incidence trajectories and cumulative case counts. Meaning These findings suggest that community-based interventions to reduce COVID-19 case counts should take precedence over school closure., This decision analytical modelling study uses a simulated population of people in Ontario, Canada, to estimate COVID-19 case counts associated with school closures and reopenings vs community-based nonpharmaceutical interventions., Importance Resurgent COVID-19 cases have resulted in the reinstitution of nonpharmaceutical interventions, including school closures, which can have adverse effects on families. Understanding the associations of school closures with the number of incident and cumulative COVID-19 cases is critical for decision-making. Objective To estimate the association of schools being open or closed with the number of COVID-19 cases compared with community-based nonpharmaceutical interventions. Design, Setting, and Participants This decision analytical modelling study developed an agent-based transmission model using a synthetic population of 1 000 000 individuals based on the characteristics of the population of Ontario, Canada. Members of the synthetic population were clustered into households, neighborhoods, or rural districts, cities or rural regions, day care facilities, classrooms (ie, primary, elementary, or high school), colleges or universities, and workplaces. Data were analyzed between May 5, 2020, and October 20, 2020. Exposures School reopening on September 15, 2020, vs schools remaining closed under different scenarios for nonpharmaceutical interventions. Main Outcomes and Measures Incident and cumulative COVID-19 cases between September 1, 2020, and October 31, 2020. Results Among 1 000 000 simulated individuals, the percentage of infections among students and teachers acquired within schools was less than 5% across modeled scenarios. Incident COVID-19 case numbers on October 31, 2020, were 4414 (95% credible interval [CrI], 3491-5382) cases in the scenario with schools remaining closed and 4740 (95% CrI, 3863-5691) cases in the scenario for schools reopening, with no other community-based nonpharmaceutical intervention. In scenarios with community-based nonpharmaceutical interventions implemented, the incident case numbers on October 31 were 714 (95% CrI, 568-908) cases for schools remaining closed and 780 (95% CrI, 580-993) cases for schools reopening. When scenarios applied the case numbers observed in early October in Ontario, the cumulative case numbers were 777 (95% CrI, 621-993) cases for schools remaining closed and 803 (95% CrI, 617-990) cases for schools reopening. In scenarios with implementation of community-based interventions vs no community-based interventions, there was a mean difference of 39 355 cumulative COVID-19 cases by October 31, 2020, while keeping schools closed vs reopening them yielded a mean difference of 2040 cases. Conclusions and Relevance This decision analytical modeling study of a synthetic population of individuals in Ontario, Canada, found that most COVID-19 cases in schools were due to acquisition in the community rather than transmission within schools and that the changes in COVID-19 case numbers associated with school reopenings were relatively small compared with the changes associated with community-based nonpharmaceutical interventions.

As the COVID-19 pandemic has progressed, more local data has become available, enabling a more granular modeling approach. In March 2020, we developed a COVID-19 Resource Estimator (CORE) model to estimate the acute care resource use in Ontario, Canada. In this paper, we describe the evolution of CORE2.0 to incorporate age, sex, and time-dependent acute care resource use, length of stay, and mortality to simulate hospital occupancy. Demographics (e.g., age and sex) of infected cases are informed by 4-month averages between March-June, and July-October using 10-year age groups. The probability of hospitalization, ICU admission, and requiring mechanical ventilation are all age and sex-dependent. LOS for each acute care level ranges from 5.7 to 16.15 days in the ward, 6.5 to 10.7 days in the ICU without ventilation, and 14.8 to 21.6 days on the ventilator, depending on month of infection. We calibrated some LOS components to reported ward and ICU occupancy between June 15 and October 31, 2020. Furthermore, we demonstrate the use of CORE2.0 for a regional analysis of Region of Waterloo, Ontario, Canada to simulate the ward bed, ICU bed, and ventilator occupancies for 30 days starting December 2020 for three case trajectory scenarios. Moving forward, this model has become highly flexible and customizable to data updates, and can better inform acute care planning and public measures as the pandemic progresses.

ImportanceResurgent COVID-19 cases have resulted in the re-institution of nonpharmaceutical interventions, including school closure, which can have adverse effects on families. Understanding the impact of schools on the number of incident and cumulative COVID-19 cases is critical for decision-making.ObjectiveTo determine the quantitative effect of schools being open or closed relative to community-based nonpharmaceutical interventions on the number of COVID-19 cases.DesignAn agent-based transmission model.SettingA synthetic population of one million individuals based on the characteristics of the population of Ontario, Canada.ParticipantsMembers of the synthetic population clustered into households, neighborhoods or rural districts, cities or a rural region, day care facilities, classrooms – primary, elementary or high school, colleges or universities and workplaces.ExposureSchool reopening on September 15, 2020, versus schools remaining closed under different scenarios for nonpharmaceutical interventions.Main Outcome and MeasuresIncident and cumulative COVID-19 cases between September 1, 2020 and October 31, 2020.ResultsThe percentage of infections among students and teachers acquired within schools was less than 5% across modelled scenarios. Incident case numbers on October 31, 2020, were 4,414 (95% credible interval, CrI: 3,491, 5,382) and 4,740 (95% CrI 3,863, 5,691), for schools remaining closed versus reopening, respectively, with no other community-based nonpharmaceutical intervention; 714 (95%, CrI: 568, 908) and 780 (95% CrI 580, 993) for schools remaining closed versus reopening, respectively, with community-based nonpharmaceutical interventions implemented; 777 (95% credible CrI: 621, 993) and 803 (95% CrI 617, 990) for schools remaining closed versus reopening, respectively, applied to the observed case numbers in Ontario in early October 2020. Contrasting the scenarios with implementation of community-based interventions versus not doing so yielded a mean difference of 39,355 cumulative COVID-19 cases by October 31, 2020, while keeping schools closed versus reopening them yielded a mean difference of 2,040 cases.Conclusions and relevanceOur simulations suggest that the majority of COVID-19 infections in schools were due to acquisition in the community rather than transmission within schools and that the effect of school reopening on COVID-19 case numbers is relatively small compared to the effects of community-based nonpharmaceutical interventions.KEY POINTSQuestionWith resurgence of COVID-19, reinstitution of school closure remains a possibility. Given the harm that closures can cause to children and families, the expected quantitative effect of school reopening or closure on incident and cumulative COVID-19 case numbers is an important consideration.FindingRelative to community-based nonpharmaceutical interventions, school closure resulted in a small change in COVID-19 incidence trajectories and cumulative case counts.MeaningCommunity-based interventions should take precedence over school closure.

BackgroundUnderstanding resource use for COVID-19 is critical. We conducted a population-based cohort study using public health data to describe COVID-19 associated age- and sex-specific acute care use, length of stay (LOS), and mortality.MethodsWe used Ontario’s Case and Contact Management (CCM) Plus database of individuals who tested positive for COVID-19 in Ontario from March 1 to September 30, 2020 to determine age- and sex-specific hospitalizations, intensive care unit (ICU) admissions, invasive mechanical ventilation (IMV) use, LOS, and mortality. We stratified analyses by month of infection to study temporal trends and conducted subgroup analyses by long-term care residency.ResultsDuring the observation period, 56,476 COVID-19 cases were reported (72% < 60 years, 52% female). The proportion of cases shifted from older populations (> 60 years) to younger populations (10-39 years) over time. Overall, 10% of individuals were hospitalized, of those 22% were admitted to ICU, and 60% of those used IMV. Mean LOS for individuals in the ward, ICU without IMV, and ICU with IMV was 12.8, 8.5, 20.5 days, respectively. Mortality for individuals receiving care in the ward, ICU without IMV, and ICU with IMV was 24%, 30%, and 45%, respectively. All outcomes varied by age and decreased over time, overall and within age groups.InterpretationThis descriptive study shows acute care use and mortality varying by age, and decreasing between March and September in Ontario. Improvements in clinical practice and changing risk distributions among those infected may contribute to fewer severe outcomes among those infected with COVID-19.

BackgroundPredicting potential healthcare resource use under different scenarios will help to prepare the healthcare system for a surge in COVID-19 patients. In this study, we aim to predict the effect of COVID-19 on hospital resources in Nigeria.MethodWe adopted a previously published discrete-time, individual-level, health-state transition model of symptomatic COVID-19 patients to the Nigerian healthcare system and COVID-19 epidemiology. We simulated different combined scenarios of epidemic trajectories and acute care capacity. Primary outcomes included expected cumulative number of cases, days until depletion resources, and number of deaths associated with resource constraints. Outcomes were predicted over a 60-day time horizon.ResultsIn our best-case epidemic trajectory, which implies successful implementation of public health measures to control COVID-19 spread, the current number of ventilator resources in Nigeria (conservative resources scenario), were expended within five days, and 901 patients may die while waiting for hospital resources in conservative resource scenario. In our expanded resource scenarios, ventilated ICU beds were depleted in all three epidemic trajectories within 60 days. Acute care resources were only sufficient in the best-case and intermediate epidemic scenarios, combined with a substantial increase in healthcare resources.ConclusionCurrent hospital resources are inadequate to manage the COVID-19 pandemic in Nigeria. Given Nigeria’s limited resources, it is imperative to increase healthcare resources and maintain aggressive public health measures to reduce COVID-19 transmission.KEY QUESTIONSWhat is already known on this subject?While western countries seem to be recovering from the COVID-19 pandemic, there is an increasing community spread of the virus in many African countries.The limited healthcare resources available in the region may not be sufficient to cope with increasing numbers of COVID-19 cases.What this study adds?Using the COVID-19 Resource Estimator (CORE) model, we demonstrate that implementing and maintaining aggressive public health measures to keep the epidemic growth at a low rate, while simultaneously substantially increasing healthcare resources is critical to minimize the impact of COVID-19 on morbidity and mortality.The impact of COVID-19 in low resource settings will likely overwhelm health system capacity if aggressive public health measures are not implemented. To mitigate the impact of COVID-19 in these settings, it is essential to develop strategies to substantially increase health system capacities, including hospital resources, personal protective equipment and trained healthcare personnel and to implement and maintain aggressive public health measures.

In addition to instituting public health measures for COVID-19, managing healthcare resources is important for outcomes. The experiences in Italy and New York have shown that personal protective equipment (PPE) shortages can cause increased morbidity and mortality. We demonstrate a method to predict PPE demand across a health care system.

BackgroundThe global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing significant strain to healthcare systems. The purpose of our study is to predict the impact of the COVID-19 pandemic on patient outcomes and the healthcare system in Ontario, Canada.MethodsWe developed an individual-level simulation to model the flow of COVID-19 patients through the Ontario healthcare system. We simulated different combined scenarios of epidemic trajectory and healthcare capacity. Outcomes include numbers of patients needing admission to the ward, Intensive Care Unit (ICU), and requiring ventilation; days to resource depletion; and numbers of patients awaiting resources and deaths associated with limited access to resources.FindingsWe demonstrate that with effective early public health measures system resources need not be depleted. For scenarios considering late or ineffective implementation of physical distancing, health system resources would be depleted within 14-26 days. Resource depletion was also avoided or delayed with aggressive measures to rapidly increase ICU, ventilator, and acute care hospital capacity.InterpretationWe found that without aggressive physical distancing measures the Ontario healthcare system would have been inadequately equipped to manage the expected number of patients with COVID-19, despite the rapid capacity increase. This overall lack of resources would have led to an increase in mortality. By slowing the spread of the disease via ongoing public health measures and having increased healthcare capacity, Ontario may have avoided catastrophic stresses to its health care system.

Objectives Venovenous extracorporeal membrane oxygenation is increasingly being used to support patients with severe acute respiratory distress syndrome, but its cost-effectiveness is unknown. We assessed the cost-utility of venovenous extracorporeal membrane oxygenation for severe acute respiratory distress syndrome in adults compared with standard lung protective ventilation from the perspective of the healthcare system. Design We conducted a cost-utility analysis with a cohort state transition decision model using a lifetime time horizon, 1.5% discount rate, and outcomes reported as cost per quality-adjusted life year. Literature reviews were conducted to inform the model variables. Deterministic and probabilistic sensitivity analyses were conducted to assess uncertainty in the model. Setting Canadian publicly funded healthcare system. Patients Hypothetical cohort of adults with severe acute respiratory distress syndrome. Interventions Venovenous extracorporeal membrane oxygenation or standard lung protective ventilation. Measurements and main results In our model, the use of venovenous extracorporeal membrane oxygenation compared with lung protective ventilation resulted in a gain of 5.2 life years and 4.05 quality-adjusted life years, at an additional lifetime cost of $145,697 Canadian dollars. The incremental cost-effectiveness ratio was $36,001/quality-adjusted life year. Sensitivity analyses show that the incremental cost-effectiveness ratio is sensitive to the efficacy of extracorporeal membrane oxygenation therapy and costs. Conclusions Based on current data, venovenous extracorporeal membrane oxygenation is cost-effective for patients with severe acute respiratory distress syndrome. Additional evidence on the efficacy of venovenous extracorporeal membrane oxygenation for acute respiratory distress syndrome and in different subgroups of patients will allow for greater certainty in its cost-effectiveness.

To examine the attitudes and preferences of surrogate decision makers (SDMs) regarding their involvement in the consent to research process for ICU patients.We presented 136 SDMs of critically ill patients in five ICUs with four hypothetical research scenarios: baseline interventional study of a placebo controlled RCT; study with higher risk of treatment complication; study comparing two accepted treatments; study with shorter enrolment window. For each we asked SDMs if they would want to be involved in the consent to research decision, and to rate the acceptability of their comfort with, and their sense of burden with their involvement. Participants were screened for symptoms of anxiety and depression using the Hospital Anxiety and Depression Scale.For the baseline scenario, most SDMs wished to be involved in research decision making (90 %; 95 % CI 84-95 %); responses varied little across study permutations. The majority considered their involvement to be acceptable (85 %; 95 % CI 77-90 %), whereas, a small minority rated it as being unacceptable (2 %; 95 % CI 1-6 %). Many were comfortable with being involved (50 %; 95 % CI 41-59 %), but the number decreased when risk of harm was higher (34 %; 95 % CI 26-43 %) or enrolment window was shorter (41 %; 95 % CI 33-50 %). A majority (62 %) reported symptoms of anxiety and many (38 %) had symptoms of depression.Most of the interviewed SDMs wished to be involved in research decision making for critically ill and incapable loved ones. Variability existed, however, in their desire to be involved when decisions were time-sensitive or perceived risk was greater.