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2.
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
3.
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
4.
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
5.
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
6.
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
7.
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
8.
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
9.
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
11.
J Am Geriatr Soc ; 69(10): 2745-2751, 2021 10.
Article in English | MEDLINE | ID: covidwho-1268122

ABSTRACT

BACKGROUND/OBJECTIVES: Transitional care management (TCM) visits delivered following hospitalization have been associated with reductions in mortality, readmissions, and total costs; however, uptake remains low. We sought to describe trends in TCM visit delivery during the COVID-19 pandemic. DESIGN: Cross-sectional study of ambulatory electronic health records from December 30, 2019 and January 3, 2021. SETTING: United States. PARTICIPANTS: Forty four thousand six hundred and eighty-one patients receiving transitional care management services. MEASUREMENTS: Weekly rates of in-person and telehealth TCM visits before COVID-19 was declared a national emergency (December 30, 2019 to March 15, 2020), during the initial pandemic period (March 16, 2020 to April 12, 2020) and later period (April 12, 2020 to January 3, 2021). Characteristics of patients receiving in-person and telehealth TCM visits were compared. RESULTS: A total of 44,681 TCM visits occurred during the study period with the majority of patients receiving TCM visits age 65 years and older (68.0%) and female (55.0%) Prior to the COVID-19 pandemic, nearly all TCM visits were conducted in-person. In the initial pandemic, there was an immediate decline in overall TCM visits and a rise in telehealth TCM visits, accounting for 15.4% of TCM visits during this period. In the later pandemic, the average weekly number of TCM visits was 841 and 14.0% were telehealth. During the initial and later pandemic periods, 73.3% and 33.6% of COVID-19-related TCM visits were conducted by telehealth, respectively. Across periods, patterns of telehealth use for TCM visits were similar for younger and older adults. CONCLUSION: The study findings highlight a novel and sustained shift to providing TCM services via telehealth during the COVID-19 pandemic, which may reduce barriers to accessing a high-value service for older adults during a vulnerable transition period. Further investigations comparing outcomes of in-person and telehealth TCM visits are needed to inform innovation in ambulatory post-discharge care.


Subject(s)
Aftercare , Ambulatory Care/statistics & numerical data , COVID-19 , Telemedicine , Transitional Care , Aftercare/methods , Aftercare/trends , Aged , COVID-19/mortality , COVID-19/prevention & control , COVID-19/therapy , Costs and Cost Analysis , Cross-Sectional Studies , Electronic Health Records/statistics & numerical data , Female , Humans , Male , Massachusetts/epidemiology , Mortality , Patient Discharge , Patient Readmission/statistics & numerical data , SARS-CoV-2 , Telemedicine/organization & administration , Telemedicine/statistics & numerical data , Telemedicine/trends , Transitional Care/organization & administration , Transitional Care/trends
13.
Environ Res ; 199: 111353, 2021 08.
Article in English | MEDLINE | ID: covidwho-1245946

ABSTRACT

Many environmental justice communities face elevated exposures to multiple stressors, given biases in urban and environmental policy and planning. This paper aims to evaluate sound level exposure in a densely populated environmental justice city in close proximity to major roadways, a nearby airport and high levels of industrial activity. In this study we collected various sound level metrics to evaluate the loudness and frequency composition of the acoustical environment in Chelsea, Massachusetts, USA. A total of 29 week-long sites were collected from October 2019 to June 2020, a time period that also included the influence of the COVID-19 pandemic, which drastically altered activity patterns and corresponding sound level exposures. We found that Chelsea is exposed to high levels of sound, both day and night (65 dB (A), and 80 dB and 90 dB for low frequency, and infrasound sound levels). A spectral analysis shows that 63 Hz was the dominant frequency. Distance to major roads and flight activity (both arrivals and departures) were most strongly correlated with all metrics, most notably with metrics describing contributing from lower frequencies. Overall, we found similar patterns during the COVID-19 pandemic but at levels up to 10 dB lower. Our results demonstrate the importance of noise exposure assessments in environmental justice communities and the importance of using additional metrics to describe communities inundated with significant air, road, and industrial sound levels. It also provides a snapshot of how much quieter communities can be with careful and intentional urban and environmental policy and planning.


Subject(s)
COVID-19 , Pandemics , Cities , Environmental Exposure , Humans , Massachusetts/epidemiology , SARS-CoV-2
14.
Health Aff (Millwood) ; 40(6): 886-895, 2021 06.
Article in English | MEDLINE | ID: covidwho-1243849

ABSTRACT

Delays in seeking emergency care stemming from patient reluctance may explain the rise in cases of out-of-hospital cardiac arrest and associated poor health outcomes during the COVID-19 pandemic. In this study we used emergency medical services (EMS) call data from the Boston, Massachusetts, area to describe the association between patients' reluctance to call EMS for cardiac-related care and both excess out-of-hospital cardiac arrest incidence and related outcomes during the pandemic. During the initial COVID-19 wave, cardiac-related EMS calls decreased (-27.2 percent), calls with hospital transportation refusal increased (+32.5 percent), and out-of-hospital cardiac arrest incidence increased (+35.5 percent) compared with historical baselines. After the initial wave, although cardiac-related calls remained lower (-17.2 percent), out-of-hospital cardiac arrest incidence remained elevated (+24.8 percent) despite fewer COVID-19 infections and relaxed public health advisories. Throughout Boston's fourteen neighborhoods, out-of-hospital cardiac arrest incidence was significantly associated with decreased cardiac-related calls, but not with COVID-19 infection rates. These findings suggest that patients were reluctant to obtain emergency care. Efforts are needed to ensure that patients seek timely care both during and after the pandemic to reduce potentially avoidable excess cardiovascular disease deaths.


Subject(s)
COVID-19 , Cardiopulmonary Resuscitation , Emergency Medical Services , Boston/epidemiology , Humans , Massachusetts/epidemiology , Pandemics , SARS-CoV-2
15.
Sci Rep ; 11(1): 10875, 2021 05 25.
Article in English | MEDLINE | ID: covidwho-1243310

ABSTRACT

The SARS-CoV-2 virus is responsible for the novel coronavirus disease 2019 (COVID-19), which has spread to populations throughout the continental United States. Most state and local governments have adopted some level of "social distancing" policy, but infections have continued to spread despite these efforts. Absent a vaccine, authorities have few other tools by which to mitigate further spread of the virus. This begs the question of how effective social policy really is at reducing new infections that, left alone, could potentially overwhelm the existing hospitalization capacity of many states. We developed a mathematical model that captures correlations between some state-level "social distancing" policies and infection kinetics for all U.S. states, and use it to illustrate the link between social policy decisions, disease dynamics, and an effective reproduction number that changes over time, for case studies of Massachusetts, New Jersey, and Washington states. In general, our findings indicate that the potential for second waves of infection, which result after reopening states without an increase to immunity, can be mitigated by a return of social distancing policies as soon as possible after the waves are detected.


Subject(s)
COVID-19/epidemiology , Health Policy , COVID-19/pathology , COVID-19/virology , Databases, Factual , Humans , Massachusetts/epidemiology , New Jersey/epidemiology , Physical Distancing , Public Policy , SARS-CoV-2/isolation & purification , Washington/epidemiology
16.
Am J Disaster Med ; 16(1): 13-24, 2021.
Article in English | MEDLINE | ID: covidwho-1218690

ABSTRACT

OBJECTIVE: The objective of this paper was to outline a novel model created for the management of the critical care surge due to coronavirus disease 2019 (COVID-19) in a Western Massachusetts hospital. SETTING: This model was created and implemented at a Western Massachusetts Level 1 Trauma and tertiary referral center. CONCLUSIONS: This article outlines a model devised by an interdisciplinary team for rapid expansion of critical care services by increasing allocated space, staffing, and supplies via modifications of existing systems of care to accommodate a predicted large critical care patient surge due to the COVID-19 pandemic. We predict that this model can be utilized and adapted for future critical care surges in times of similar pandemic situations.


Subject(s)
COVID-19 , Pandemics , Critical Care , Humans , Massachusetts/epidemiology , SARS-CoV-2
17.
Pediatrics ; 147(5)2021 05.
Article in English | MEDLINE | ID: covidwho-1207668

ABSTRACT

OBJECTIVES: To characterize the socioeconomic and racial and/or ethnic disparities impacting the diagnosis and outcomes of multisystem inflammatory syndrome in children (MIS-C). METHODS: This multicenter retrospective case-control study was conducted at 3 academic centers from January 1 to September 1, 2020. Children with MIS-C were compared with 5 control groups: children with coronavirus disease 2019, children evaluated for MIS-C who did not meet case patient criteria, children hospitalized with febrile illness, children with Kawasaki disease, and children in Massachusetts based on US census data. Neighborhood socioeconomic status (SES) and social vulnerability index (SVI) were measured via a census-based scoring system. Multivariable logistic regression was used to examine associations between SES, SVI, race and ethnicity, and MIS-C diagnosis and clinical severity as outcomes. RESULTS: Among 43 patients with MIS-C, 19 (44%) were Hispanic, 11 (26%) were Black, and 12 (28%) were white; 22 (51%) were in the lowest quartile SES, and 23 (53%) were in the highest quartile SVI. SES and SVI were similar between patients with MIS-C and coronavirus disease 2019. In multivariable analysis, lowest SES quartile (odds ratio 2.2 [95% confidence interval 1.1-4.4]), highest SVI quartile (odds ratio 2.8 [95% confidence interval 1.5-5.1]), and racial and/or ethnic minority background were associated with MIS-C diagnosis. Neither SES, SVI, race, nor ethnicity were associated with disease severity. CONCLUSIONS: Lower SES or higher SVI, Hispanic ethnicity, and Black race independently increased risk for MIS-C. Additional studies are required to target interventions to improve health equity for children.


Subject(s)
African Americans/statistics & numerical data , COVID-19/ethnology , European Continental Ancestry Group/statistics & numerical data , Hispanic Americans/statistics & numerical data , Socioeconomic Factors , Systemic Inflammatory Response Syndrome/ethnology , COVID-19/epidemiology , Case-Control Studies , Female , Humans , Male , Massachusetts/epidemiology , Retrospective Studies , Risk Factors , Social Determinants of Health , Systemic Inflammatory Response Syndrome/epidemiology
18.
JAMA Netw Open ; 4(4): e217523, 2021 04 01.
Article in English | MEDLINE | ID: covidwho-1198345

ABSTRACT

Importance: The incidence of mother-to-newborn SARS-CoV-2 transmission appears low and may be associated with biological and social factors. However, data are limited on the factors associated with neonatal clinical or viral testing outcomes. Objective: To ascertain the percentage of neonates who were born to mothers with positive SARS-CoV-2 test results during the birth hospitalization, the clinical and sociodemographic factors associated with neonatal test result positivity, and the clinical and virological outcomes for newborns during hospitalization and 30 days after discharge. Design, Setting, and Participants: This multicenter cohort study included 11 academic or community hospitals in Massachusetts and mother-neonate dyads whose delivery and discharge occurred between March 1, 2020, and July 31, 2020. Eligible dyads were identified at each participating hospital through local COVID-19 surveillance and infection control systems. Neonates were born to mothers with positive SARS-CoV-2 test results within 14 days before to 72 hours after delivery, and neonates were followed up for 30 days after birth hospital discharge. Exposures: Hypothesized maternal risk factors in neonatal test result positivity included maternal COVID-19 symptoms, vaginal delivery, rooming-in practice, Black race or Hispanic ethnicity, and zip code-derived social vulnerability index. Delivery indicated by worsening maternal COVID-19 symptoms was hypothesized to increase the risk of adverse neonatal health outcomes. Main Outcomes and Measures: Primary outcomes for neonates were (1) positive SARS-CoV-2 test results, (2) indicators of adverse health, and (3) clinical signs and viral testing. Test result positivity was defined as at least 1 positive result on a specimen obtained by nasopharyngeal swab using a polymerase chain reaction-based method. Clinical and testing data were obtained from electronic medical records of nonroutine health care visits within 30 days after hospital discharge. Results: The cohort included 255 neonates (mean [SD] gestational age at birth, 37.9 [2.6] weeks; 62 [24.3%] with low birth weight or preterm delivery) with 250 mothers (mean [SD] age, 30.4 [6.3] years; 121 [48.4%] were of Hispanic ethnicity). Of the 255 neonates who were born to mothers with SARS-CoV-2 infection, 225 (88.2%) were tested for SARS-CoV-2 and 5 (2.2%) had positive results during the birth hospitalization. High maternal social vulnerability was associated with higher likelihood of neonatal test result positivity (adjusted odds ratio, 4.95; 95% CI, 1.53-16.01; P = .008), adjusted for maternal COVID-19 symptoms, delivery mode, and rooming-in practice. Adverse outcomes during hospitalization were associated with preterm delivery indicated by worsening maternal COVID-19 symptoms. Of the 151 newborns with follow-up data, 28 had nonroutine clinical visits, 7 underwent SARS-CoV-2 testing, and 1 had a positive result. Conclusions and Relevance: The findings emphasize the importance of both biological and social factors in perinatal SARS-CoV-2 infection outcomes. Newborns exposed to SARS-CoV-2 were at risk for both direct and indirect adverse health outcomes, supporting efforts of ongoing surveillance of the virus and long-term follow-up.


Subject(s)
COVID-19 Testing , COVID-19 , Delivery, Obstetric , Infant, Newborn, Diseases , Infectious Disease Transmission, Vertical/statistics & numerical data , Pregnancy Complications, Infectious , Adult , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/transmission , COVID-19 Testing/methods , COVID-19 Testing/statistics & numerical data , Delivery, Obstetric/methods , Delivery, Obstetric/statistics & numerical data , Female , Gestational Age , Humans , Infant, Low Birth Weight , Infant, Newborn , Infant, Newborn, Diseases/diagnosis , Infant, Newborn, Diseases/epidemiology , Infant, Newborn, Diseases/virology , Male , Massachusetts/epidemiology , Pregnancy , Pregnancy Complications, Infectious/diagnosis , Pregnancy Complications, Infectious/epidemiology , Pregnancy Outcome/epidemiology , Premature Birth/epidemiology , Risk Factors , SARS-CoV-2/isolation & purification , Socioeconomic Factors
19.
Am J Med Qual ; 36(1): 5-16, 2021.
Article in English | MEDLINE | ID: covidwho-1149968

ABSTRACT

Routine outpatient epilepsy care has shifted from in-person to telemedicine visits in response to safety concerns posed by the coronavirus disease 2019 (COVID-19) pandemic. But whether telemedicine can support and maintain standardized documentation of high-quality epilepsy care remains unknown. In response, the authors conducted a quality improvement study at a level 4 epilepsy center between January 20, 2019, and May 31, 2020. Weekly average completion proportion of standardized documentation used by a team of neurologists for adult patients for the diagnosis of epilepsy, seizure classification, and frequency were analyzed. By December 15, 2019, a 94% average weekly completion proportion of standardized epilepsy care documentation was achieved that was maintained through May 31, 2020. Moreover, during the period of predominately telemedicine encounters in response to the pandemic, the completion proportion was 90%. This study indicates that high completion of standardized documentation of seizure-related information can be sustained during telemedicine appointments for routine outpatient epilepsy care at a level 4 epilepsy center.


Subject(s)
COVID-19/epidemiology , Epilepsy/therapy , Telemedicine , Adult , Female , Humans , Male , Massachusetts/epidemiology , Middle Aged , Quality of Health Care , Telemedicine/methods , Telemedicine/standards
20.
Public Health Rep ; 136(3): 368-374, 2021 05.
Article in English | MEDLINE | ID: covidwho-1138485

ABSTRACT

OBJECTIVE: Understanding the pattern of population risk for coronavirus disease 2019 (COVID-19) is critically important for health systems and policy makers. The objective of this study was to describe the association between neighborhood factors and number of COVID-19 cases. We hypothesized an association between disadvantaged neighborhoods and clusters of COVID-19 cases. METHODS: We analyzed data on patients presenting to a large health care system in Boston during February 5-May 4, 2020. We used a bivariate local join-count procedure to determine colocation between census tracts with high rates of neighborhood demographic characteristics (eg, Hispanic race/ethnicity) and measures of disadvantage (eg, health insurance status) and COVID-19 cases. We used negative binomial models to assess independent associations between neighborhood factors and the incidence of COVID-19. RESULTS: A total of 9898 COVID-19 patients were in the cohort. The overall crude incidence in the study area was 32 cases per 10 000 population, and the adjusted incidence per census tract ranged from 2 to 405 per 10 000 population. We found significant colocation of several neighborhood factors and the top quintile of cases: percentage of population that was Hispanic, non-Hispanic Black, without health insurance, receiving Supplemental Nutrition Assistance Program benefits, and living in poverty. Factors associated with increased incidence of COVID-19 included percentage of population that is Hispanic (incidence rate ratio [IRR] = 1.25; 95% CI, 1.23-1.28) and percentage of households living in poverty (IRR = 1.25; 95% CI, 1.19-1.32). CONCLUSIONS: We found a significant association between neighborhoods with high rates of disadvantage and COVID-19. Policy makers need to consider these health inequities when responding to the pandemic and planning for subsequent health needs.


Subject(s)
COVID-19/epidemiology , Ethnic Groups/statistics & numerical data , Medically Uninsured/statistics & numerical data , Poverty/statistics & numerical data , Residence Characteristics , Vulnerable Populations/statistics & numerical data , Adult , Aged , Female , Food Assistance/statistics & numerical data , Geographic Mapping , Humans , Incidence , Male , Massachusetts/epidemiology , Middle Aged , Socioeconomic Factors
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