Surgical challenges and research priorities in the era of the COVID-19 pandemic: EAES membership survey.

BACKGROUND: Healthcare systems and general surgeons are being challenged by the current pandemic. The European Association for Endoscopic Surgery (EAES) aimed to evaluate surgeons' experiences and perspectives, to identify gaps in knowledge, to record shortcomings in resources and to register research priorities. METHODS: An ad hoc web-based survey of EAES members and affiliates was developed by the EAES Research Committee. The questionnaire consisted of 69 items divided into the following sections: (Ι) demographics, (II) institutional burdens and management strategies, and (III) analysis of resource, knowledge, and evidence gaps. Descriptive statistics were summarized as frequencies, medians, ranges,, and interquartile ranges, as appropriate. RESULTS: The survey took place between March 25th and April 16th with a total of 550 surgeons from 79 countries. Eighty-one percent had to postpone elective cases or suspend their practice and 35% assumed roles not related to their primary expertise. One-fourth of respondents reported having encountered abdominal pathologies in COVID-19-positive patients, most frequently acute appendicitis (47% of respondents). The effect of protective measures in surgical or endoscopic procedures on infected patients, the effect of endoscopic surgery on infected patients, and the infectivity of positive patients undergoing laparoscopic surgery were prioritized as knowledge gaps and research priorities. CONCLUSIONS: Perspectives and priorities of EAES members in the era of the pandemic are hereto summarized. Research evidence is urgently needed to effectively respond to challenges arisen from the pandemic.

Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization.

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

Determinants of access to the SARS-CoV-2 vaccine: a preliminary approach.

BACKGROUND: The determinants of access to immunizers are still poorly understood, leading to questions about which criteria were considered in this distribution. Given the above, the present study aimed to analyze the determinants of access to the SARS-CoV-2 vaccine by different countries. METHODS: The study covered 189 countries using data from different public databases, and collected until February 19, 2021. We used eight explanatory variables: gross domestic product (GDP), extreme poverty, human development index (HDI), life expectancy, median age, coronavirus disease 2019 (COVID-19) cases, COVID-19 tests, and COVID-19 deaths. The endogenous variables were total vaccine doses, vaccine doses per thousand, and days of vaccination. The structural equation modeling (SEM) technique was applied to establish the causal relationship between the country's COVID-19 impact, socioeconomic variables, and vaccine access. To support SEM, we used confirmatory factor analysis, t-test, and Pearson's correlation. RESULTS: We collected the sample on February 19, and to date, 80 countries (42.1%) had already received a batch of immunizers against COVID-19. The countries with first access to the vaccine (e.g., number of days elapsed since they took the first dose) were the United Kingdom (68), China (68), Russia (66), and Israel (62). The countries receiving the highest doses were the United States, China, India, and Israel. The countries with extreme poverty had lower access to vaccines and the richer countries gained priority access. Countries most affected by COVID (deaths and cases) also received immunizers earlier and in greater volumes. Unfortunately, similar to other vaccines, indicators, such as income, poverty, and human development, influence vaccines' access. Thus affecting the population of vulnerable and less protected countries. Therefore, global initiatives for the equitable distribution of COVID need to be discussed and encouraged. CONCLUSIONS: Determinants of vaccine distribution consider the impact of the disease in the country and are also affected by favorable socioeconomic indicators. The COVID-19 vaccines need to be accessible to all affected countries, regardless of their social hands.

Time-varying optimization of COVID-19 vaccine prioritization in the context of limited vaccination capacity.

Dynamically adapting the allocation of COVID-19 vaccines to the evolving epidemiological situation could be key to reduce COVID-19 burden. Here we developed a data-driven mechanistic model of SARS-CoV-2 transmission to explore optimal vaccine prioritization strategies in China. We found that a time-varying vaccination program (i.e., allocating vaccines to different target groups as the epidemic evolves) can be highly beneficial as it is capable of simultaneously achieving different objectives (e.g., minimizing the number of deaths and of infections). Our findings suggest that boosting the vaccination capacity up to 2.5 million first doses per day (0.17% rollout speed) or higher could greatly reduce COVID-19 burden, should a new wave start to unfold in China with reproduction number ≤1.5. The highest priority categories are consistent under a broad range of assumptions. Finally, a high vaccination capacity in the early phase of the vaccination campaign is key to achieve large gains of strategic prioritizations.

Allocation of scarce resources in a pandemic: rapid systematic review update of strategies for policymakers.

OBJECTIVE: In pandemics like COVID-19, the need for medical resources quickly outpaces available supply. policymakers need strategies to inform decisions about allocating scarce resources. STUDY DESIGN AND SETTING: We updated a systematic review on evidence-based approaches and searched databases through May 2020 for evaluation of strategies for policymakers. RESULTS: The 201 identified studies evaluated reducing demand for healthcare, optimizing existing resources, augmenting resources, and adopting crisis standards of care. Most research exists to reduce demand (n = 149); 39 higher quality studies reported benefits of contact tracing, school closures, travel restrictions, and mass vaccination. Of 28 strategies to augment resources, 6 higher quality studies reported effectiveness of establishing temporary facilities, use of volunteers, and decision support software. Of 23 strategies to optimize existing resources, 12 higher quality studies reported successful scope of work expansions and building on existing interagency agreements. Of 15 COVID-19 studies, 5 higher quality studies reported on combinations of policies and benefits of community-wide mask policies. CONCLUSION: Despite the volume, the evidence base is limited; few strategies were empirically tested in robust study designs. The review provides a comprehensive overview of the effects of strategies to allocate resources and provides critical appraisal to identify the best available evidence.

COVID-19 Vaccine Administration, by Race and Ethnicity - North Carolina, December 14, 2020-April 6, 2021.

COVID-19 has disproportionately affected non-Hispanic Black or African American (Black) and Hispanic persons in the United States (1,2). In North Carolina during January-September 2020, deaths from COVID-19 were 1.6 times higher among Black persons than among non-Hispanic White persons (3), and the rate of COVID-19 cases among Hispanic persons was 2.3 times higher than that among non-Hispanic persons (4). During December 14, 2020-April 6, 2021, the North Carolina Department of Health and Human Services (NCDHHS) monitored the proportion of Black and Hispanic persons* aged ≥16 years who received COVID-19 vaccinations, relative to the population proportions of these groups. On January 14, 2021, NCDHHS implemented a multipronged strategy to prioritize COVID-19 vaccinations among Black and Hispanic persons. This included mapping communities with larger population proportions of persons aged ≥65 years among these groups, increasing vaccine allocations to providers serving these communities, setting expectations that the share of vaccines administered to Black and Hispanic persons matched or exceeded population proportions, and facilitating community partnerships. From December 14, 2020-January 3, 2021 to March 29-April 6, 2021, the proportion of vaccines administered to Black persons increased from 9.2% to 18.7%, and the proportion administered to Hispanic persons increased from 3.9% to 9.9%, approaching the population proportion aged ≥16 years of these groups (22.3% and 8.0%, respectively). Vaccinating communities most affected by COVID-19 is a national priority (5). Public health officials could use U.S. Census tract-level mapping to guide vaccine allocation, promote shared accountability for equitable distribution of COVID-19 vaccines with vaccine providers through data sharing, and facilitate community partnerships to support vaccine access and promote equity in vaccine uptake.

[Consensus of the Genetics Branch of the Chilean Society of Pediatrics on the prioritization of people with Down syndrome and rare diseases for vaccination against SARS-CoV-2]. / Consenso de la Rama de Genética de la Sociedad Chilena de Pediatría sobre priorización de personas con Síndrome de Down y otras condiciones poco frecuentes en la Campaña de Vacunación COVID-19.

In the framework of the vaccination campaign against the SARS-CoV-2 virus, the Chilean Ministry of Health requested advice from the Genetics Branch of the Chilean Society of Pediatrics, to define the level of prioritization for people with Down Syndrome . A panel of geneticists worked on the development of this consensus, in which not only patients with Down syndrome were included, but the search was extended to patients with other types of disabilities, in both pediatric and adult ages in or der to contribute to the development of public health measures against the COVID-19 pandemic. The consensus concludes that, given the prevalence of comorbidities associated with Down syndrome, the higher incidence of cases with severe COVID-19 in this population group and a higher mortality, individuals with trisomy 21 should be considered as a high-risk population, and therefore, vaccina tion against SARS-CoV-2 should have a high priority for all people with Down syndrome regardless of their age (except for the age limit established by the clinical trials of each vaccine), and should be preceded only by the groups of health personnel and adults aged > 60-65 years. Likewise, this group of experts urges health authorities to include people with intellectual disabilities and related conditions as a priority population (other chromosomal abnormalities other than Down syndrome, intellectual disability, congenital anomalies and conditions that cause disability with microcephaly), as well as the caregivers of people with this type of conditions. Vaccination in children with this type of disorders should be considered as part of the first priority group, once safe vaccines against SARS-CoV-2 are available for use in children and adolescents.

Equitable allocation of COVID-19 vaccines in the United States.

Many vaccine rationing guidelines urge planners to recognize, and ideally reduce, inequities. In the United States, allocation frameworks are determined by each of the Centers for Disease Control and Prevention's 64 jurisdictions (50 states, the District of Columbia, five cities and eight territories). In this study, we analyzed vaccine allocation plans published by 8 November 2020, tracking updates through to 30 March 2021. We evaluated whether jurisdictions adopted proposals to reduce inequity using disadvantage indices and related place-based measures. By 30 March 2021, 14 jurisdictions had prioritized specific zip codes in combination with metrics such as COVID-19 incidence, and 37 jurisdictions (including 34 states) had adopted disadvantage indices, compared to 19 jurisdictions in November 2020. Uptake of indices doubled from 7 to 14 among the jurisdictions with the largest shares of disadvantaged communities. Five applications were distinguished: (1) prioritizing disadvantaged groups through increased shares of vaccines or vaccination appointments; (2) defining priority groups or areas; (3) tailoring outreach and communication; (4) planning the location of dispensing sites; and (5) monitoring receipt. To ensure that equity features centrally in allocation plans, policymakers at the federal, state and local levels should universalize the uptake of disadvantage indices and related place-based measures.

Coronavirus Vaccine Distribution: Moving to a Race Conscious Approach for a Racially Disparate Problem.

Strikingly ignoring the critical impact of systemic racism in vulnerabilities to the deadly coronavirus, phase one of the vaccine rollout is not reaching the Black population that has suffered the most from COVID. An urgent need exists for a race-conscious approach that ensures equitable opportunities to both access and receive the vaccines.

Examining hospital staff members' preferences for allocating a ventilator to a COVID-19 patient with and without Alzheimer's disease.

The COVID 19 pandemic has led to an increase in the number of patients in need of ventilation. Limitations in the number of respirators may cause an ethical problem for the medical and nursing staff in deciding who should be connected to the available respirators.  We conducted a cross-sectional survey among a convenience sample of 278 healthcare professionals at one medical center. They were asked to rank their preference in respirator allocation to three COVID-19 patients, one 80 years old with no cognitive illness, one 50 years old with Alzheimer's disease (AD), and one 80 years old with AD. Most respondents (75%) chose the 80-year-old AD patient as last preference, but were evenly divided on how to rank the other two patients. Medical staff have difficulty deciding whether age or cognitive status should be the deciding factor ventilator allocation. Determination of a set policy would help professionals with these decisions.

Developing the COVID-19 intensive care medical equipment distribution platform: outcomes and lessons learned.

During the first wave of the coronavirus pandemic, the UK government took the decision to centralise the procurement, allocation and distribution of mission-critical intensive care unit (ICU) medical equipment. Establishing new supply chains in the context of global shortages presented significant challenges. This report describes the development of an innovative platform developed rapidly and voluntarily by clinical engineers, to mobilise the UK's shared medical equipment inventory, in order to match ICU capacity to dynamically evolving clinical demand. The 'Coronavirus ICU Medical Equipment Distribution' platform was developed to optimise ICU equipment allocation, distribution, collection, redeployment and traceability across the National Health Service. Although feedback on the platform has largely been very positive, the platform was built for a scenario that did not fully materialise in the UK and this affected the implementation approach. As such, it was not used to its full potential. Nonetheless, the platform and the insights derived and disseminated in its development have been extremely valuable. It provides a prototype for not only optimising system capacity in future pandemic scenarios but also a means for maximally exploiting the large amount of new equipment in the UK health system, as a result of the coronavirus pandemic. This early stage innovation has demonstrated that a system-wide pooled information resource can benefit the operations of individual organisations. It has also generated numerous lessons to be borne in mind in innovation projects.

Assessment of a Risk-Based Approach for Triaging Mammography Examinations During Periods of Reduced Capacity.

Importance: Breast cancer screening, surveillance, and diagnostic imaging services were profoundly limited during the initial phase of the coronavirus disease 2019 (COVID-19) pandemic. Objective: To develop a risk-based strategy for triaging mammograms during periods of decreased capacity. Design, Setting, and Participants: This population-based cohort study used data collected prospectively from mammography examinations performed in 2014 to 2019 at 92 radiology facilities in the Breast Cancer Surveillance Consortium. Participants included individuals undergoing mammography. Data were analyzed from August 10 to November 3, 2020. Exposures: Clinical indication for screening, breast symptoms, personal history of breast cancer, age, time since last mammogram/screening interval, family history of breast cancer, breast density, and history of high-risk breast lesion. Main Outcomes and Measures: Combinations of clinical indication, clinical history, and breast cancer risk factors that subdivided mammograms into risk groups according to their cancer detection rate were identified using classification and regression trees. Results: The cohort included 898 415 individuals contributing 1 878 924 mammograms (mean [SD] age at mammogram, 58.6 [11.2] years) interpreted by 448 radiologists, with 1 722 820 mammograms in individuals without a personal history of breast cancer and 156 104 mammograms in individuals with a history of breast cancer. Most individuals were aged 50 to 69 years at imaging (1 113 174 mammograms [59.2%]), and 204 305 (11.2%) were Black, 206 087 (11.3%) were Asian or Pacific Islander, 126 677 (7.0%) were Hispanic or Latina, and 40 021 (2.2%) were another race/ethnicity or mixed race/ethnicity. Cancer detection rates varied widely based on clinical indication, breast symptoms, personal history of breast cancer, and age. The 12% of mammograms with very high (89.6 [95% CI, 82.3-97.5] to 122.3 [95% CI, 108.1-138.0] cancers detected per 1000 mammograms) or high (36.1 [95% CI, 33.1-39.3] to 47.5 [95% CI, 42.4-53.3] cancers detected per 1000 mammograms) cancer detection rates accounted for 55% of all detected cancers and included mammograms to evaluate an abnormal mammogram or breast lump in individuals of all ages regardless of breast cancer history, to evaluate breast symptoms other than lump in individuals with a breast cancer history or without a history but aged 60 years or older, and for short-interval follow-up in individuals aged 60 years or older without a breast cancer history. The 44.2% of mammograms with very low cancer detection rates accounted for 13.1% of detected cancers and included annual screening mammograms in individuals aged 50 to 69 years (3.8 [95% CI, 3.5-4.1] cancers detected per 1000 mammograms) and all screening mammograms in individuals younger than 50 years regardless of screening interval (2.8 [95% CI, 2.6-3.1] cancers detected per 1000 mammograms). Conclusions and Relevance: In this population-based cohort study, clinical indication and individual risk factors were associated with cancer detection and may be useful for prioritizing mammography in times and settings of decreased capacity.