Risk-based prediction for optimal timing of booster vaccination for COVID-19 to prevent severe disease (preprint)

While waning protection from vaccination and natural infection against SARS-CoV-2 infection is well-documented, recent analyses have also found waning of protection against severe COVID-19. This highlights a broader need to understand the optimal timing of COVID-19 booster vaccines specific to an individual to mitigate the risk of severe COVID-19, while accounting for waning of protection and differential risk by age group and immune status. Here we show that more frequent COVID-19 booster vaccination (every 6-12 months) in older age groups and the immunocompromised population would effectively mitigate the burden of severe COVID-19, while frequent boosters in the younger population may only provide modest benefit. Analyzing United States COVID-19 surveillance and seroprevalence data in a microsimulation model, we estimated that in persons 75+ years, annual and semiannual bivalent boosters would reduce annual absolute risk of severe COVID-19 by 311 (277-369) and 578 (494-671) cases, respectively, compared to a one-time bivalent booster dose. In contrast, for persons 18-49 years, the model estimated that annual and semiannual bivalent boosters would reduce annual absolute risk of severe COVID-19 by 20 (13-26) and 37 (24-50) cases per 100,000 persons, respectively, compared to a one-time bivalent booster dose. Persons with prior infection had a much lower benefit of more frequent boosting, while immunocompromised persons had larger benefit. This study underscores the benefit of customizing timing of COVID-19 booster vaccines based on individual risk.

An Overview of the Impact of the Covid-19 Pandemic on the Provision of Palliative Care.

The Sars-Cov-2 pandemic had an immeasurable impact on the provision of palliative care in Ireland, and continues to do so. Patients and families were affected by stringent infectious disease measures. Healthcare professionals were also impacted, with recent research demonstrating the psychological impact that the pandemic had on some of those working in palliative care during the pandemic. The services provided by palliative care services also shifted. Many patients opted to stay at home to receive end-of-life care or symptom management from their GP and community palliative homecare teams where possible. Palliative care services in the acute hospital setting were increasingly utilised to support teams to provide end-of-life care in a developing and challenging clinical environment. Communication technology was used to for multidisciplinary team meetings, to communicate with families and by community home care teams for some patient assessments. Our article outlines some of the major ways in which palliative care was impacted by the Sars-Cov-2 pandemic.

Is the Gap Closing? Comparison of Sociodemographic Disparities in COVID-19 Hospitalizations and Outcomes Between Two Temporal Waves of Admissions.

OBJECTIVE: The COVID-19 pandemic has disproportionately impacted minority communities, yet little data exists regarding whether disparities have improved at a health system level. This study examined whether sociodemographic disparities in hospitalization and clinical outcomes changed between two temporal waves of hospitalized COVID-19 patients. METHODS: This is a retrospective cohort study of primary care patients at Mass General Brigham (a large northeastern health system serving 1.27 million primary care patients) hospitalized in-system with COVID-19 between March 1, 2020, and March 1, 2021, categorized into two 6-month "wave" periods. We used chi-square tests to compare demographics between waves, and regression analysis to characterize the association of race/ethnicity and language with in-hospital severe outcomes (death, hospice discharge, intensive unit care need). RESULTS: Hispanic/Latino, Black, and non-English-speaking patients constituted 30.3%, 12.5%, and 29.7% of COVID-19 admissions in wave 1 (N = 5844) and 22.2%, 9.0%, and 22.7% in wave 2 (N = 4007), compared to 2019 general admission proportions of 8.8%, 6.3%, and 7.7%, respectively. Admissions from highly socially vulnerable census tracts decreased between waves. Non-English speakers had significantly higher odds of severe illness during wave 1 (OR 1.35; 95% CI: 1.10, 1.66) compared to English speakers; this association was non-significant during wave 2 (OR 1.01; 95% CI: 0.76, 1.36). CONCLUSIONS: Comparing two COVID-19 temporal waves, significant sociodemographic disparities in COVID-19 admissions improved between waves but continued to persist over a year, demonstrating the need for ongoing interventions to truly close equity gaps. Non-English-speaking language status independently predicted worse hospitalization outcomes in wave 1, underscoring the importance of targeted and effective in-hospital supports for non-English speakers.

Determining population-level allocation strategies for COVID-19 treatments in the United States using a quantitative framework, a case study using nirmatrelvir/ritonavir (preprint)

BackgroundNew COVID-19 medications force decision makers to weigh limited evidence of efficacy and cost in determining which patient populations to target for treatment. A case in point is nirmatrelvir/ritonavir, a drug that has been recommended for elderly, high-risk individuals, regardless of vaccination status, even though clinical trials have only evaluated it in unvaccinated patients. A simple optimization framework might inform a more reasoned approach to the tradeoffs implicit in the treatment allocation decision. MethodsWe used a mathematical model to analyze the cost-effectiveness of four nirmatrelvir/ritonavir allocation strategies, stratified by vaccination status and risk for severe disease. We considered treatment effectiveness at preventing hospitalization ranging from 21% to 89%. Sensitivity analyses were performed on major parameters of interest. A web-based tool was developed to permit decision-makers to tailor the analysis to their settings and priorities. ResultsProviding nirmatrelvir/ritonavir to unvaccinated patients at high-risk for severe disease was cost-saving when effectiveness against hospitalization exceeded 33% and cost-effective under all other data scenarios we considered. The cost-effectiveness of other allocation strategies, including those for vaccinated adults and those at lower-risk for severe disease, depended on willingness-to-pay thresholds, treatment cost and effectiveness, and the likelihood of severe disease. ConclusionsPriority for nirmatrelvir/ritonavir treatment should be given to unvaccinated persons at high-risk of severe disease from COVID-19. Further priority may be assigned by weighing treatment effectiveness, disease severity, drug cost, and willingness to pay for deaths averted.

Incidence of venous thrombotic events and events of special interest in a retrospective cohort of commercially insured US patients.

OBJECTIVE: To estimate the US incidence of thrombotic events and related rare diagnoses. DESIGN: Claims-based retrospective cohort study of incidence. SETTING: US commercial health insurance administrative claims database. PARTICIPANTS: Adults 25-64 years of age between 2015 and 2019 with a minimum of 12 consecutive thrombosis-free months of continuous enrolment beginning 2014 were selected. MAIN OUTCOMES: Age (10-year intervals) and sex stratum-specific incidence rates per 100 000 person-years were determined for venous thromboembolism (VTE), cerebral venous thrombosis (CVT) and other major venous thrombotic events, and events of special interest, including immune thrombocytopenic purpura (ITP), haemolytic-uremic syndrome (HUS) and heparin-induced thrombocytopenia (HIT). RESULTS: Of 13 249 229 enrollees (half female/male), incidence of venous thromboembolic events (deep vein thrombosis (DVT), pulmonary embolism (PE), CVT or other major venous thrombotic conditions) was 247.89 per 100 000 person-years (95% CI: 245.96 to 249.84). Incidence of VTE was 213.79 with ICD codes alone (95% CI: 211.99 to 215.59) and 129.34 (95% CI: 127.95 to 130.75) when also requiring a filled anticoagulation prescription or an inferior vena cava (IVC) filter. Incidence was 6.37 for CVT (95% CI: 6.07 to 6.69), 26.06 for ITP (95% CI: 25.44 to 26.78), 0.94 for HUS (95% CI: 0.82 to 1.06) and 4.82 for HIT (95% CI: 4.56 to 5.10). The co-occurrence of CVT with either ITP or HIT (diagnoses within 14 days of one another) was 0.090 (95% CI: 0.06 to 0.13). Incidence tended to increase with age and was higher for women under 55. Incidence for CVT, HUS and CVT with ITP or HIT was higher for women in all age groups. Incidence of PE and CVT increased significantly over the 5-year period, while DVT rates decreased. CONCLUSIONS: These results are the first US estimates for the incidence of thrombotic and rare events of interest in a large, commercially insured US population. Findings provide a critically important reference for determining excess morbidity associated with COVID-19 and more generally for vaccine pharmacovigilance.

Model-based estimates of deaths averted and cost per life saved by scaling-up mRNA COVID-19 vaccination in low and lower-middle income countries in the COVID-19 Omicron variant era (preprint)

Background: While almost 60% of the world has received at least one dose of COVID-19 vaccine, the global distribution of vaccination has not been equitable. Only 4% of the population of low-income countries has received a full primary vaccine series, compared to over 70% of the population of high-income nations. Methods: We used economic and epidemiologic models, parameterized with public data on global vaccination and COVID-19 deaths, to estimate the potential benefits of scaling up vaccination programs in low and lower-middle income countries (LIC/LMIC) in 2022 in the context of global spread of the Omicron variant of SARS-CoV2. Outcomes were expressed as number of avertable deaths through vaccination, costs of scale-up, and cost per death averted. We conducted sensitivity analyses over a wide range of parameter estimates to account for uncertainty around key inputs. Findings: Global scale up of vaccination to provide two doses of mRNA vaccine to everyone in LIC/LMIC would cost $35.5 billion and avert 1.3 million deaths from COVID-19, at a cost of $26,900 per death averted. Scaling up vaccination to provide three doses of mRNA vaccine to everyone in LIC/LMIC would cost $61.2 billion and avert 1.5 million deaths from COVID-19 at a cost of $40,800 per death averted. Lower estimated infection fatality ratios, higher cost-per-dose, and lower vaccine effectiveness or uptake lead to higher cost-per-death averted estimates in the analysis. Interpretation: Scaling up COVID-19 global vaccination would avert millions of COVID-19 deaths and represents a reasonable investment in the context of the value of a statistical life (VSL). Given the magnitude of expected mortality facing LIC/LMIC without vaccination, this effort should be an urgent priority.

Adventures in COVID-19 Policy Modeling: Education Edition.

PURPOSE OF REVIEW: To introduce readers to policy modeling, a multidisciplinary field of quantitative analysis, primarily used to help guide decision-making. This review focuses on the choices facing educational administrators, from K-12 to universities in the USA, as they confronted the COVID-19 pandemic. We survey three key model-based approaches to mitigation of SARS-CoV-2 spread in schools and on university campuses. RECENT FINDINGS: Frequent testing, coupled with strict attention to behavioral interventions to prevent further transmission can avoid large outbreaks on college campuses. K-12 administrators can greatly reduce the risks of severe outbreaks of COVID-19 in schools through various mitigation measures including classroom infection control, scheduling and cohorting strategies, staff and teacher vaccination, and asymptomatic screening. Safer re-opening of college and university campuses as well as in-person instruction for K-12 students is possible, under many though not all epidemic scenarios if rigorous disease control and screening programs are in place.

Maximizing the Efficiency of Active Case Finding for SARS-CoV-2 Using Bandit Algorithms.

Even as vaccination for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) expands in the United States, cases will linger among unvaccinated individuals for at least the next year, allowing the spread of the coronavirus to continue in communities across the country. Detecting these infections, particularly asymptomatic ones, is critical to stemming further transmission of the virus in the months ahead. This will require active surveillance efforts in which these undetected cases are proactively sought out rather than waiting for individuals to present to testing sites for diagnosis. However, finding these pockets of asymptomatic cases (i.e., hotspots) is akin to searching for needles in a haystack as choosing where and when to test within communities is hampered by a lack of epidemiological information to guide decision makers' allocation of these resources. Making sequential decisions with partial information is a classic problem in decision science, the explore v. exploit dilemma. Using methods-bandit algorithms-similar to those used to search for other kinds of lost or hidden objects, from downed aircraft or underground oil deposits, we can address the explore v. exploit tradeoff facing active surveillance efforts and optimize the deployment of mobile testing resources to maximize the yield of new SARS-CoV-2 diagnoses. These bandit algorithms can be implemented easily as a guide to active case finding for SARS-CoV-2. A simple Thompson sampling algorithm and an extension of it to integrate spatial correlation in the data are now embedded in a fully functional prototype of a web app to allow policymakers to use either of these algorithms to target SARS-CoV-2 testing. In this instance, potential testing locations were identified by using mobility data from UberMedia to target high-frequency venues in Columbus, Ohio, as part of a planned feasibility study of the algorithms in the field. However, it is easily adaptable to other jurisdictions, requiring only a set of candidate test locations with point-to-point distances between all locations, whether or not mobility data are integrated into decision making in choosing places to test.

Understanding the barriers to pooled SARS-CoV-2 testing in the United States (preprint)

Pooled testing for SARS-CoV-2 detection is instrumental for increasing test capacity while decreasing test cost, key factors for sustainable, long-term surveillance measures. While numerous pooled approaches have been described, uptake by labs has been limited. We surveyed 90 US labs to understand the barriers to implementing pooled testing.

Field Hospital Boston Hope: Defining Culture During Uncertainty.

As hospitals across the world realized their surge capacity would not be enough to care for patients with coronavirus disease-2019 (COVID-19) infection, an urgent need to open field hospitals prevailed. In this article the authors describe the implementation process of opening a Boston field hospital including the development of a culture unique to this crisis and the local community needs. Through first-person accounts, readers will learn (1) about Boston Hope, (2) how leaders managed and collaborated, (3) how the close proximity of the care environment impacted decision-making and management style, and (4) the characteristics of leaders under pressure as observed by the team.

The essential role of population health during and beyond COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has fundamentally changed how health care systems deliver services and revealed the tenuousness of care delivery based on face-to-face office visits and fee-for-service reimbursement models. Robust population health management, fostered by value-based contract participation, integrates analytics and agile clinical programs and is adaptable to optimize outcomes and reduce risk during population-level crises. In this article, we describe how mature population health programs in a learning health system have been rapidly leveraged to address the challenges of the pandemic. Population-level data and care management have facilitated identification of demographic-based disparities and community outreach. Telemedicine and integrated behavioral health have ensured critical primary care and specialty access, and mobile health and postacute interventions have shifted site of care and optimized hospital utilization. Beyond the pandemic, population health can lead as a cornerstone of a resilient health system, better prepared to improve public health and mitigate risk in a value-based paradigm.

Acute Arterial Thromboembolism in Patients with COVID-19 in the New York City Area.

BACKGROUND: Coronavirus disease 2019 (COVID-19) predisposes to arterial and venous thromboembolic complications. We describe the clinical presentation, management, and outcomes of acute arterial ischemia and concomitant infection at the epicenter of cases in the United States. METHODS: Patients with confirmed COVID-19 infection between March 1, 2020 and May 15, 2020 with an acute arterial thromboembolic event were reviewed. Data collected included demographics, anatomical location of the thromboembolism, treatments, and outcomes. RESULTS: Over the 11-week period, the Northwell Health System cared for 12,630 hospitalized patients with COVID-19. A total of 49 patients with arterial thromboembolism and confirmed COVID-19 were identified. The median age was 67 years (58-75) and 37 (76%) were men. The most common preexisting conditions were hypertension (53%) and diabetes (35%). The median D-dimer level was 2,673 ng/mL (723-7,139). The distribution of thromboembolic events included upper 7 (14%) and lower 35 (71%) extremity ischemia, bowel ischemia 2 (4%), and cerebral ischemia 5 (10%). Six patients (12%) had thrombus in multiple locations. Concomitant deep vein thrombosis was found in 8 patients (16%). Twenty-two (45%) patients presented with signs of acute arterial ischemia and were subsequently diagnosed with COVID-19. The remaining 27 (55%) developed ischemia during hospitalization. Revascularization was performed in 13 (27%) patients, primary amputation in 5 (10%), administration of systemic tissue- plasminogen activator in 3 (6%), and 28 (57%) were treated with systemic anticoagulation only. The rate of limb loss was 18%. Twenty-one patients (46%) died in the hospital. Twenty-five (51%) were successfully discharged, and 3 patients are still in the hospital. CONCLUSIONS: While the mechanism of thromboembolic events in patients with COVID-19 remains unclear, the occurrence of such complication is associated with acute arterial ischemia which results in a high limb loss and mortality.