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2.
AJR Am J Roentgenol ; 217(5): 1093-1102, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1484970

ABSTRACT

BACKGROUND. Previous studies compared CT findings of COVID-19 pneumonia with those of other infections; however, to our knowledge, no studies to date have included noninfectious organizing pneumonia (OP) for comparison. OBJECTIVE. The objectives of this study were to compare chest CT features of COVID-19, influenza, and OP using a multireader design and to assess the performance of radiologists in distinguishing between these conditions. METHODS. This retrospective study included 150 chest CT examinations in 150 patients (mean [± SD] age, 58 ± 16 years) with a diagnosis of COVID-19, influenza, or non-infectious OP (50 randomly selected abnormal CT examinations per diagnosis). Six thoracic radiologists independently assessed CT examinations for 14 individual CT findings and for Radiological Society of North America (RSNA) COVID-19 category and recorded a favored diagnosis. The CT characteristics of the three diagnoses were compared using random-effects models; the diagnostic performance of the readers was assessed. RESULTS. COVID-19 pneumonia was significantly different (p < .05) from influenza pneumonia for seven of 14 chest CT findings, although it was different (p < .05) from OP for four of 14 findings (central or diffuse distribution was seen in 10% and 7% of COVID-19 cases, respectively, vs 20% and 21% of OP cases, respectively; unilateral distribution was seen in 1% of COVID-19 cases vs 7% of OP cases; non-tree-in-bud nodules was seen in 32% of COVID-19 cases vs 53% of OP cases; tree-in-bud nodules were seen in 6% of COVID-19 cases vs 14% of OP cases). A total of 70% of cases of COVID-19, 33% of influenza cases, and 47% of OP cases had typical findings according to RSNA COVID-19 category assessment (p < .001). The mean percentage of correct favored diagnoses compared with actual diagnoses was 44% for COVID-19, 29% for influenza, and 39% for OP. The mean diagnostic accuracy of favored diagnoses was 70% for COVID-19 pneumonia and 68% for both influenza and OP. CONCLUSION. CT findings of COVID-19 substantially overlap with those of influenza and, to a greater extent, those of OP. The diagnostic accuracy of the radiologists was low in a study sample that contained equal proportions of these three types of pneumonia. CLINICAL IMPACT. Recognized challenges in diagnosing COVID-19 by CT are furthered by the strong overlap observed between the appearances of COVID-19 and OP on CT. This challenge may be particularly evident in clinical settings in which there are substantial proportions of patients with potential causes of OP such as ongoing cancer therapy or autoimmune conditions.


Subject(s)
COVID-19/diagnostic imaging , Cryptogenic Organizing Pneumonia/diagnostic imaging , Influenza, Human/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Tomography, X-Ray Computed , Diagnosis, Differential , Female , Humans , Influenza, Human/virology , Male , Massachusetts , Middle Aged , Observer Variation , Pneumonia, Viral/virology , Radiography, Thoracic , Retrospective Studies , SARS-CoV-2
4.
Crit Care Med ; 49(10): 1739-1748, 2021 10 01.
Article in English | MEDLINE | ID: covidwho-1475872

ABSTRACT

OBJECTIVES: The coronavirus disease 2019 pandemic has overwhelmed healthcare resources even in wealthy nations, necessitating rationing of limited resources without previously established crisis standards of care protocols. In Massachusetts, triage guidelines were designed based on acute illness and chronic life-limiting conditions. In this study, we sought to retrospectively validate this protocol to cohorts of critically ill patients from our hospital. DESIGN: We applied our hospital-adopted guidelines, which defined severe and major chronic conditions as those associated with a greater than 50% likelihood of 1- and 5-year mortality, respectively, to a critically ill patient population. We investigated mortality for the same intervals. SETTING: An urban safety-net hospital ICU. PATIENTS: All adults hospitalized during April of 2015 and April 2019 identified through a clinical database search. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 365 admitted patients, 15.89% had one or more defined chronic life-limiting conditions. These patients had higher 1-year (46.55% vs 13.68%; p < 0.01) and 5-year (50.00% vs 17.22%; p < 0.01) mortality rates than those without underlying conditions. Irrespective of classification of disease severity, patients with metastatic cancer, congestive heart failure, end-stage renal disease, and neurodegenerative disease had greater than 50% 1-year mortality, whereas patients with chronic lung disease and cirrhosis had less than 50% 1-year mortality. Observed 1- and 5-year mortality for cirrhosis, heart failure, and metastatic cancer were more variable when subdivided into severe and major categories. CONCLUSIONS: Patients with major and severe chronic medical conditions overall had 46.55% and 50.00% mortality at 1 and 5 years, respectively. However, mortality varied between conditions. Our findings appear to support a crisis standards protocol which focuses on acute illness severity and only considers underlying conditions carrying a greater than 50% predicted likelihood of 1-year mortality. Modifications to the chronic lung disease, congestive heart failure, and cirrhosis criteria should be refined if they are to be included in future models.


Subject(s)
COVID-19/therapy , Crisis Intervention/standards , Resource Allocation/methods , Academic Medical Centers/organization & administration , Academic Medical Centers/statistics & numerical data , Adult , COVID-19/epidemiology , Crisis Intervention/methods , Crisis Intervention/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Male , Massachusetts , Middle Aged , Resource Allocation/statistics & numerical data , Retrospective Studies , Safety-net Providers/organization & administration , Safety-net Providers/statistics & numerical data , Standard of Care/standards , Standard of Care/statistics & numerical data , Urban Population/statistics & numerical data
10.
PLoS One ; 16(9): e0252794, 2021.
Article in English | MEDLINE | ID: covidwho-1381276

ABSTRACT

While there has been much speculation on how the pandemic has affected work location patterns and home location choices, there is sparse evidence regarding the impacts that COVID-19 has had on amenity visits in American cities, which typically constitute over half of all urban trips. Using aggregate app-based GPS positioning data from smartphone users, this study traces the changes in amenity visits in Somerville, MA from January 2019 to December 2020, describing how visits to particular types of amenities have changed as a result of business closures during the public health emergency. Has the pandemic fundamentally shifted amenity-oriented travel behavior or is consumer behavior returning to pre-pandemic trends? To address this question, we calibrate discrete choice models that are suited to Census block-group level analysis for each of the 24 months in a two-year period, and use them to analyze how visitors' behavioral responses to various attributes of amenity clusters have shifted during different phases of the pandemic. Our findings suggest that in the first few months of the pandemic, amenity-visiting preferences significantly diverged from expected patterns. Even though overall trip volumes remained far below normal levels throughout the remainder of the year, preferences towards specific cluster attributes mostly returned to expected levels by September 2020. We also construct two scenarios to explore the implications of another shutdown and a full reopening, based on November 2020 consumer behavior. While government restrictions have played an important role in reducing visits to amenity clusters, our results imply that cautionary consumer behavior has played an important role as well, suggesting a likely long and slow path to economic recovery. By drawing on mobile phone location data and behavioral modeling, this paper offers timely insights to help decision-makers understand how this unprecedented health emergency is affecting amenity-related trips and where the greatest needs for intervention and support may exist.


Subject(s)
COVID-19 , Consumer Behavior/economics , Pandemics/economics , SARS-CoV-2 , Smartphone , Travel/economics , COVID-19/economics , COVID-19/epidemiology , Cities , Humans , Massachusetts/epidemiology , United States
11.
Public Health Rep ; 136(6): 765-773, 2021.
Article in English | MEDLINE | ID: covidwho-1354647

ABSTRACT

OBJECTIVES: Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2. METHODS: We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran's I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts. RESULTS: Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%. CONCLUSION: Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Vulnerable Populations/statistics & numerical data , Age Factors , COVID-19 Testing , Housing , Humans , Language , Massachusetts/epidemiology , Pandemics , Public Health , SARS-CoV-2 , Socioeconomic Factors , Spatial Analysis
12.
JAMA Intern Med ; 181(10): 1315-1321, 2021 10 01.
Article in English | MEDLINE | ID: covidwho-1347379

ABSTRACT

Importance: COVID-19 incidence and mortality are higher among incarcerated persons than in the general US population, but the extent to which prison crowding contributes to their COVID-19 risk is unknown. Objective: To estimate the associations between prison crowding, community COVID-19 transmission, and prison incidence rates of COVID-19. Design, Setting, and Participants: This was a longitudinal ecological study among all incarcerated persons in 14 Massachusetts state prisons between April 21, 2020, and January 11, 2021. Exposures: The primary exposure of interest was prison crowding, measured by (1) the size of the incarcerated population as a percentage of the prison's design capacity and (2) the percentage of incarcerated persons housed in single-cell units. The analysis included the weekly COVID-19 incidence in the county where each prison is located as a covariate. Main Outcomes and Measures: The primary outcome was the weekly COVID-19 incidence rate as determined by positive SARS-CoV-2 tests among incarcerated persons at each prison over discrete 1-week increments. Results: There was on average 6876 people incarcerated in 14 prisons during the study period. The median level of crowding during the observation period ranged from 25% to 155% of design capacity. COVID-19 incidence was significantly higher in prisons where the incarcerated population was a larger percentage of the prison's design capacity (incidence rate ratio [IRR] per 10-percentage-point difference, 1.14; 95% CI, 1.03-1.27). COVID-19 incidence was lower in prisons where a higher proportion of incarcerated people were housed in single-cell units (IRR for each 10-percentage-point increase in single-cell units, 0.82; 95% CI, 0.73-0.93). COVID-19 transmission in the surrounding county was consistently associated with COVID-19 incidence in prisons (IRR [for each increase of 10 cases per 100 000 person-weeks in the community], 1.06; 95% CI, 1.05-1.08). Conclusions and Relevance: This longitudinal ecological study found that within 14 Massachusetts state prisons, increased crowding was associated with increased incidence rates of COVID-19. Researchers and policy makers should explore strategies that reduce prison crowding, such as decarceration, as potential ways to mitigate COVID-19 morbidity and mortality among incarcerated persons.


Subject(s)
COVID-19/epidemiology , Crowding , Prisons/statistics & numerical data , Adult , COVID-19/diagnosis , Female , Humans , Incidence , Longitudinal Studies , Male , Massachusetts , Retrospective Studies
13.
Cancer Med ; 10(18): 6327-6335, 2021 09.
Article in English | MEDLINE | ID: covidwho-1344970

ABSTRACT

BACKGROUND: We aimed to investigate the effects of COVID-19 on computed tomography (CT) imaging of cancer. METHODS: Cancer-related CTs performed at one academic hospital and three affiliated community hospitals in Massachusetts were retrospectively analyzed. Three periods of 2020 were considered as follows: pre-COVID-19 (1/5/20-3/14/20), COVID-19 peak (3/15/20-5/2/20), and post-COVID-19 peak (5/3/20-11/14/20). 15 March 2020 was the day a state of emergency was declared in MA; 3 May 2020 was the day our hospitals resumed to non-urgent imaging. The volumes were assessed by (1) Imaging indication: cancer screening, initial workup, active cancer, and surveillance; (2) Care setting: outpatient and inpatient, ED; (3) Hospital type: quaternary academic center (QAC), university-affiliated community hospital (UACH), and sole community hospitals (SCHs). RESULTS: During the COVID-19 peak, a significant drop in CT volumes was observed (-42.2%, p < 0.0001), with cancer screening, initial workup, active cancer, and cancer surveillance declining by 81.7%, 54.8%, 30.7%, and 44.7%, respectively (p < 0.0001). In the post-COVID-19 peak period, cancer screening and initial workup CTs did not recover (-11.7%, p = 0.037; -20.0%, p = 0.031), especially in the outpatient setting. CT volumes for active cancer recovered, but inconsistently across hospital types: the QAC experienced a 9.4% decline (p = 0.022) and the UACH a 41.5% increase (p < 0.001). Outpatient CTs recovered after the COVID-19 peak, but with a shift in utilization away from the QAC (-8.7%, p = 0.020) toward the UACH (+13.3%, p = 0.013). Inpatient and ED-based oncologic CTs increased post-peak (+20.0%, p = 0.004 and +33.2%, p = 0.009, respectively). CONCLUSIONS: Cancer imaging was severely impacted during the COVID-19 pandemic. CTs for cancer screening and initial workup did not recover to pre-COVID-19 levels well into 2020, a finding that suggests more patients with advanced cancers may present in the future. A redistribution of imaging utilization away from the QAC and outpatient settings, toward the community hospitals and inpatient setting/ED was observed.


Subject(s)
COVID-19/epidemiology , Neoplasms/diagnostic imaging , Pandemics/statistics & numerical data , Emergency Service, Hospital/statistics & numerical data , Hospitals , Humans , Inpatients/statistics & numerical data , Massachusetts/epidemiology , Outpatients/statistics & numerical data , Retrospective Studies , SARS-CoV-2/pathogenicity , Tomography, X-Ray Computed/methods
14.
MMWR Morb Mortal Wkly Rep ; 70(31): 1059-1062, 2021 Aug 06.
Article in English | MEDLINE | ID: covidwho-1344580

ABSTRACT

During July 2021, 469 cases of COVID-19 associated with multiple summer events and large public gatherings in a town in Barnstable County, Massachusetts, were identified among Massachusetts residents; vaccination coverage among eligible Massachusetts residents was 69%. Approximately three quarters (346; 74%) of cases occurred in fully vaccinated persons (those who had completed a 2-dose course of mRNA vaccine [Pfizer-BioNTech or Moderna] or had received a single dose of Janssen [Johnson & Johnson] vaccine ≥14 days before exposure). Genomic sequencing of specimens from 133 patients identified the B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, in 119 (89%) and the Delta AY.3 sublineage in one (1%). Overall, 274 (79%) vaccinated patients with breakthrough infection were symptomatic. Among five COVID-19 patients who were hospitalized, four were fully vaccinated; no deaths were reported. Real-time reverse transcription-polymerase chain reaction (RT-PCR) cycle threshold (Ct) values in specimens from 127 vaccinated persons with breakthrough cases were similar to those from 84 persons who were unvaccinated, not fully vaccinated, or whose vaccination status was unknown (median = 22.77 and 21.54, respectively). The Delta variant of SARS-CoV-2 is highly transmissible (1); vaccination is the most important strategy to prevent severe illness and death. On July 27, CDC recommended that all persons, including those who are fully vaccinated, should wear masks in indoor public settings in areas where COVID-19 transmission is high or substantial.* Findings from this investigation suggest that even jurisdictions without substantial or high COVID-19 transmission might consider expanding prevention strategies, including masking in indoor public settings regardless of vaccination status, given the potential risk of infection during attendance at large public gatherings that include travelers from many areas with differing levels of transmission.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Crowding , Disease Outbreaks , Adolescent , Adult , Aged , COVID-19 Vaccines/administration & dosage , Child , Child, Preschool , Female , Humans , Infant , Male , Massachusetts/epidemiology , Middle Aged , Young Adult
15.
J Am Geriatr Soc ; 69(10): 2716-2721, 2021 10.
Article in English | MEDLINE | ID: covidwho-1325028

ABSTRACT

During the COVID-19 pandemic, frontline nursing home staff faced extraordinary stressors including high infection and mortality rates and ever-changing and sometimes conflicting federal and state regulations. To support nursing homes in evidence-based infection control practices, the Massachusetts Senior Care Association and Hebrew SeniorLife partnered with the Agency for Healthcare Research and Quality AHRQ ECHO National Nursing Home COVID-19 Action Network (the network). This educational program provided 16 weeks of free weekly virtual sessions to 295 eligible nursing homes, grouped into nine cohorts of 30-33 nursing homes. Eighty-three percent of eligible nursing homes in Massachusetts participated in the Network, and Hebrew SeniorLife's Training Center served the vast majority. Each cohort was led by geriatrics clinicians and nursing home leaders, and coaches trained in quality improvement. The interactive sessions provided timely updates on COVID-19 infection control best practices to improve care and also created a peer-to-peer learning community to share ongoing challenges and potential solutions. The weekly Network meetings were a source of connection, emotional support, and validation and may be a valuable mechanism to support resilience and well-being for nursing home staff.


Subject(s)
COVID-19 , Health Personnel , Nursing Homes , Online Social Networking , Resilience, Psychological , Skilled Nursing Facilities , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/psychology , Education, Distance/methods , Evidence-Based Practice/education , Health Personnel/education , Health Personnel/psychology , Humans , Infection Control/methods , Massachusetts/epidemiology , Nursing Homes/standards , Nursing Homes/trends , Quality Improvement/organization & administration , SARS-CoV-2 , Skilled Nursing Facilities/standards , Skilled Nursing Facilities/trends , Social Support
16.
BMC Health Serv Res ; 21(1): 719, 2021 Jul 21.
Article in English | MEDLINE | ID: covidwho-1320532

ABSTRACT

BACKGROUND: Studies on the impact of the novel SARS-CoV-2 virus (COVID) for healthcare workers (HCWs) rarely include the full spectrum of hospital workers, including less visible patient support roles. In the early days of the pandemic, COVID testing was preferentially available to HCWs. The objective of this study was to understand how individual experiences for all HCWs during the pandemic were associated with perceptions of access to, and receipt of COVID testing . METHODS: All hospital employees (n = 6736) in a single academic medical center in Boston, Massachusetts were invited to participate in a cross-sectional survey regarding perceived access to, and receipt of COVID testing during the first wave of the pandemic (March - August 2020). Responses were linked to human resources data. Log binomial univariate and multivariable models were used to estimate associations between individual and employment variables and COVID testing. RESULTS: A total of 2543 employees responded to the survey (38 %). The mean age was 40 years (± 14). Respondents were female (76 %), white (55 %), worked as nurses (27 %), administrators (22 %) and patient support roles (22 %); 56 % of respondents wanted COVID testing. Age (RR 0.91, CI 0.88-0.93), full time status (RR 0.85, CI 0.79-0.92), employment tenure (RR 0.96, CI 0.94-0.98), changes in quality of life (RR 0.94, CI 0.91-0.96), changes in job duties (RR 1.19, CI 1.03-1.37), and worry about enough paid sick leave (RR 1.21, CI 1.12-1.30) were associated with interest in testing. Administrators (RR 0.64, CI 0.58-0.72) and patient support staff (RR 0.85, CI 0.78-0.92) were less likely than nurses to want testing. Age (RR 1.04, CI 1.01-1.07), material hardships (RR 0.87, CI 0.79-0.96), and employer sponsored insurance (RR 1.10, CI 1.00-1.22) were associated with receiving a COVID test. Among all employees, only administrative/facilities staff were less likely to receive COVID testing (RR 0.69, CI 0.59-0.79). CONCLUSIONS: This study adds to our understanding of how hospital employees view availability of COVID testing. Hazard pay or other supports for hospital workers may increase COVID testing rates. These findings may be applicable to perceived barriers towards vaccination receipt.


Subject(s)
COVID-19 Testing , COVID-19 , Adult , Boston , Cross-Sectional Studies , Female , Health Personnel , Humans , Massachusetts , Quality of Life , SARS-CoV-2
18.
Front Public Health ; 9: 695442, 2021.
Article in English | MEDLINE | ID: covidwho-1317258

ABSTRACT

The COVID-19 pandemic caused more than 30 million infections in the United States between March 2020 and April 2021. In response to systemic disparities in SARS-CoV2 testing and COVID-19 infections, health systems, city leaders and community stakeholders in Worcester, Massachusetts created a citywide Equity Task Force with a specific goal of making low-barrier testing available to individuals throughout our community. Within months, the state of Massachusetts announced the Stop the Spread campaign, a state-funded testing venture. With this funding, and through our community-based approach, our team tested more than 48,363 individuals between August 3, 2020 and February 28, 2021. Through multiple PDSA (Plan-Do-Study-Act) cycles, we optimized our process to test close to 300 individuals per hour. Our positivity rate ranged from 1.5% with our initial testing events to a high of 13.4% on January 6, 2021. During the challenges of providing traditional inpatient and ambulatory care during the pandemic, our health system, city leadership, and community advocacy groups united to broaden the scope of care to include widespread, population-based SARS-CoV2 testing. We anticipate that the lessons learned in conducting this testing campaign can be applied to further surges of SARS-CoV2, international environments, and future respiratory disease pandemics.


Subject(s)
COVID-19 , RNA, Viral , Humans , Massachusetts/epidemiology , Pandemics/prevention & control , SARS-CoV-2 , United States/epidemiology
19.
BMC Infect Dis ; 21(1): 686, 2021 Jul 16.
Article in English | MEDLINE | ID: covidwho-1314255

ABSTRACT

BACKGROUND: Associations between community-level risk factors and COVID-19 incidence have been used to identify vulnerable subpopulations and target interventions, but the variability of these associations over time remains largely unknown. We evaluated variability in the associations between community-level predictors and COVID-19 case incidence in 351 cities and towns in Massachusetts from March to October 2020. METHODS: Using publicly available sociodemographic, occupational, environmental, and mobility datasets, we developed mixed-effect, adjusted Poisson regression models to depict associations between these variables and town-level COVID-19 case incidence data across five distinct time periods from March to October 2020. We examined town-level demographic variables, including population proportions by race, ethnicity, and age, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM2.5), and institutional facilities. We calculated incidence rate ratios (IRR) associated with these predictors and compared these values across the multiple time periods to assess variability in the observed associations over time. RESULTS: Associations between key predictor variables and town-level incidence varied across the five time periods. We observed reductions over time in the association with percentage of Black residents (IRR = 1.12 [95%CI: 1.12-1.13]) in early spring, IRR = 1.01 [95%CI: 1.00-1.01] in early fall) and COVID-19 incidence. The association with number of long-term care facility beds per capita also decreased over time (IRR = 1.28 [95%CI: 1.26-1.31] in spring, IRR = 1.07 [95%CI: 1.05-1.09] in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidences of COVID-19 throughout the pandemic (e.g., IRR = 1.30 [95%CI: 1.27-1.33] in spring, IRR = 1.20 [95%CI: 1.17-1.22] in fall). Towns with higher proportions of Latinx residents also had sustained elevated incidence over time (IRR = 1.19 [95%CI: 1.18-1.21] in spring, IRR = 1.14 [95%CI: 1.13-1.15] in fall). CONCLUSIONS: Town-level COVID-19 risk factors varied with time in this study. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence may have decreased across the first 8 months of the pandemic, perhaps indicating greater success in risk mitigation in selected communities. Our approach can be used to evaluate effectiveness of public health interventions and target specific mitigation efforts on the community level.


Subject(s)
COVID-19/epidemiology , Occupations/statistics & numerical data , Social Environment , Transportation/statistics & numerical data , Adult , Aged , Aged, 80 and over , COVID-19/ethnology , Ethnic Groups/statistics & numerical data , Female , Health Status Disparities , Humans , Incidence , Income/statistics & numerical data , Male , Massachusetts/epidemiology , Middle Aged , Movement/physiology , Pandemics , Residence Characteristics/statistics & numerical data , Risk Factors , SARS-CoV-2/physiology , Socioeconomic Factors , Time Factors , Vulnerable Populations/ethnology , Vulnerable Populations/statistics & numerical data , Young Adult
20.
BMC Med ; 19(1): 162, 2021 07 13.
Article in English | MEDLINE | ID: covidwho-1308097

ABSTRACT

BACKGROUND: When three SARS-CoV-2 vaccines came to market in Europe and North America in the winter of 2020-2021, distribution networks were in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation was critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs likely require that distribution is prioritized to the elderly, health care workers, teachers, essential workers, and individuals with comorbidities putting them at risk of severe clinical progression. METHODS: We evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not have been included in the first round of vaccination. And, we account for age-specific immune patterns in both states at the time of the start of the vaccination program. Our analysis assumes that health systems during winter 2020-2021 had equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. RESULTS: We find that allocating a substantial proportion (>75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. This result is robust to different profiles of waning vaccine efficacy and several different assumptions on age mixing during and after lockdown periods. As we do not explicitly model other high-mortality groups, our results on vaccine allocation apply to all groups at high risk of mortality if infected. A median of 327 to 340 deaths can be avoided in Rhode Island (3444 to 3647 in Massachusetts) by optimizing vaccine allocation and vaccinating the elderly first. The vaccination campaigns are expected to save a median of 639 to 664 lives in Rhode Island and 6278 to 6618 lives in Massachusetts in the first half of 2021 when compared to a scenario with no vaccine. A policy of vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and would result in 0.5% to 1% reductions in cumulative hospitalizations and deaths by mid-2021. CONCLUSIONS: Assuming high vaccination coverage (>28%) and no major changes in distancing, masking, gathering size, hygiene guidelines, and virus transmissibility between 1 January 2021 and 1 July 2021 a combination of vaccination and population immunity may lead to low or near-zero transmission levels by the second quarter of 2021.


Subject(s)
COVID-19 Vaccines/supply & distribution , COVID-19 , Communicable Disease Control/organization & administration , Health Care Rationing/organization & administration , Resource Allocation/organization & administration , Vaccination Coverage , Vaccination , Age Factors , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Incidence , Massachusetts/epidemiology , Models, Theoretical , Public Health/methods , Public Health/standards , Rhode Island/epidemiology , SARS-CoV-2 , Vaccination/methods , Vaccination/statistics & numerical data , Vaccination Coverage/statistics & numerical data , Vaccination Coverage/supply & distribution
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