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3.
Open forum infectious diseases ; 8(Suppl 1):S101-S102, 2021.
Article in English | EuropePMC | ID: covidwho-1564540

ABSTRACT

Background In February 2019, California (CA) experienced its first C. auris outbreak in Orange County (OC). The CA Department of Public Health (CDPH) and OC with the Centers for Disease Control and Prevention (CDC), mounted a successful containment response;by November 2019, cases were limited to low-level spread in OC long-term acute care hospitals (LTACH). In May 2020, C. auris cases began to surge in OC, followed by extensive spread in six other southern CA local health jurisdictions (LHJ). CDPH with LHJ and CDC, initiated an aggressive, interjurisdictional containment response. Methods We carried out response and preventive point prevalence surveys (PPS), onsite infection prevention and control (IPC) assessments, and in-service trainings at outbreak and interconnected hospitals and skilled nursing facilities in six LHJ. Other regional activities included: epidemiologic investigation, contact and discharge tracking and screening;increasing laboratory testing capacity;screening patients admitted to and from LTACH;statewide healthcare facility (HCF) education and outreach;sending regional outbreak HCF lists to all HCF;and biweekly state-LHJ coordination calls. The Antibiotic Resistance (AR) Lab Network supported testing. Results From May 2020—May 2021, we conducted screening at 226 HCF, and identified 1192 cases at 93 HCF, mostly through screening (n=1109, 93%) and at LTACH (n=906, 76%);we identified 113 (10%) cases at ACH, including 35 (31%) in COVID-19-burdened units. Cases peaked in August 2020 (n=93) and February 2021 (n=191) and have since declined, with C. auris resurgence mirroring COVID-19 incidence. We conducted 98 onsite IPC assessments, and identified multiple, improper IPC practices which had been implemented in response to COVID-19, including double-gloving and -gowning, extended use of gowns and gloves outside patient rooms, and cohorting according to COVID-19 status only. Figure 1. C. auris and COVID-19 Cases in California through May 2021, and C. auris Cases by Local Health Jurisdiction (LHJ) May 2020–May 2021 Table 1. By Facility Type: Colonization Testing May 2020–May 2021, and Total Case Counts before and from May 2020 Table 2. COVID-19-related Infection Control Practices Affecting C. auris Spread, and Associated Public Health Recommendations Conclusion The C. auris resurgence in CA was likely a result of COVID-19-related practices and conditions. An aggressive, coordinated, interjurisdictional C. auris containment response, including proactive prevention activities at HCF interconnected with outbreak HCF, can help mitigate spread of C. auris and potentially other novel AR pathogens. Disclosures All Authors: No reported disclosures

4.
Open forum infectious diseases ; 8(Suppl 1):32-32, 2021.
Article in English | EuropePMC | ID: covidwho-1564210

ABSTRACT

Background OC is the 6th largest U.S. county with 70 NHs. Universal decolonization (chlorhexidine for routine bathing, and twice daily nasal iodophor Mon-Fri every other week) was adopted in 24 NHs prior to the COVID-19 pandemic, and 12 NHs (11 of those adopting decolonization) participated in a COVID prevention training program with a rolling launch from July-Sept 2020. We evaluated the impact of these initiatives on staff and resident COVID cases. Methods We conducted a quasi-experimental study of the impact of decolonization and COVID prevention training on staff and resident COVID cases during the CA winter surge (11/16/20-1/31/21), when compared to non-participating NHs. Decolonization NHs received weekly visits for encouraging adherence during the pandemic, and NHs in the COVID training program received 3 in-person training sessions for all work shifts plus weekly feedback about adherence to hand hygiene, masking, and breakroom safety using video monitoring. We calculated incident 1) staff COVID cases, 2) resident COVID cases, and 3) resident COVID deaths adjusting for NH average daily census. We assessed impact of initiatives on these outcomes using linear mixed effects models testing the interaction between any training participation and calendar date when clustering by NH. Because of the overlap of the two initiatives, we evaluated ‘any training’ vs ‘no training.’ Results 63 NHs had available data. 24 adopted universal decolonization, 12 received COVID training (11 of which participated in decolonization), and 38 were not enrolled in either. During the winter surge, the 63 NHs experienced 1867 staff COVID cases, 2186 resident COVID cases, and 251 resident deaths due to COVID, corresponding to 29.6, 34.7, and 4.0 events per NH, respectively. In NHs participating in either initiative, staff COVID cases were reduced by 31% (OR=0.69 (0.52, 0.92), P=0.01), resident COVID cases were reduced by 43% (OR=0.57 (0.39, 0.82), P=0.003), and resident deaths were reduced (non-significantly) by 26% (OR=0.74 (0.46, 1.21), P=0.23). The grey box represents the California COVID-19 winter surge (11/16/20-1/31/21). Incident and cumulative COVID-19 cases and deaths for each nursing home were divided by the nursing home’s average daily census and multiplied by 100, representing events per 100 beds, which were aggregated across groups. Conclusion NHs are vulnerable to COVID-19 outbreaks. A universal decolonization and COVID prevention training initiative in OC, CA significantly reduced staff and resident COVID cases in this high-risk care setting. Disclosures Gabrielle Gussin, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Raveena Singh, MA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Raheeb Saavedra, AS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Robert Pedroza, BS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Chase Berman, BS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)

5.
National Bureau of Economic Research Working Paper Series ; No. 27378, 2020.
Article in English | NBER | ID: grc-748582

ABSTRACT

Disease spread is in part a function of individual behavior. We examine the factors predicting individual behavior during the Covid-19 pandemic in the United States using novel data collected by Belot et al. (2020). Among other factors, we show that people with lower income, less flexible work arrangements (e.g., an inability to tele-work) and lack of outside space at home are less likely to engage in behaviors, such as social distancing, that limit the spread of disease. We also find evidence that region, gender and beliefs predict behavior. Broadly, our findings align with typical relationships between health and socio-economic status. Moreover, they suggest that the burden of measures designed to stem the pandemic are unevenly distributed across socio-demographic groups in ways that affect behavior and thus potentially the spread of illness. Policies that assume otherwise are unlikely to be effective or sustainable.

6.
Emerg Infect Dis ; 27(10): 2604-2618, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1486164

ABSTRACT

We conducted a detailed analysis of coronavirus disease in a large population center in southern California, USA (Orange County, population 3.2 million), to determine heterogeneity in risks for infection, test positivity, and death. We used a combination of datasets, including a population-representative seroprevalence survey, to assess the actual burden of disease and testing intensity, test positivity, and mortality. In the first month of the local epidemic (March 2020), case incidence clustered in high-income areas. This pattern quickly shifted, and cases next clustered in much higher rates in the north-central area of the county, which has a lower socioeconomic status. Beginning in April 2020, a concentration of reported cases, test positivity, testing intensity, and seropositivity in a north-central area persisted. At the individual level, several factors (e.g., age, race or ethnicity, and ZIP codes with low educational attainment) strongly affected risk for seropositivity and death.


Subject(s)
COVID-19 , Epidemics , California/epidemiology , Humans , SARS-CoV-2 , Seroepidemiologic Studies
7.
Sci Rep ; 11(1): 3081, 2021 02 04.
Article in English | MEDLINE | ID: covidwho-1387463

ABSTRACT

Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n = 2979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5-12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR] = 1.47, 95% CI 1.22-1.78) and household income < $50,000 (vs. > $100,000: PR = 1.42, 95% CI: 1.14 to 1.79). Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ~ 12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.


Subject(s)
Antibodies, Viral/analysis , COVID-19 , /statistics & numerical data , Adolescent , Adult , Bias , COVID-19/diagnosis , COVID-19/epidemiology , California/epidemiology , Female , Humans , Immunoglobulin G/analysis , Immunoglobulin M/analysis , Male , Middle Aged , Prevalence , Public Health Surveillance , Seroepidemiologic Studies , Young Adult
8.
Occup Environ Med ; 78(11): 789-792, 2021 11.
Article in English | MEDLINE | ID: covidwho-1373974

ABSTRACT

OBJECTIVES: We conducted serological SARS-CoV-2 antibody testing from October to November 2020 to estimate the SARS-CoV-2 seroprevalence among firefighters/paramedics in Orange County (OC), California. METHODS: OC firefighters employed at the time of the surveillance activity were invited to participate in a voluntary survey that collected demographic, occupational and previous COVID-19 testing data, and a SARS-CoV-2 immunoglobulin (Ig)G antibody blood test. We collected venous blood samples using mobile phlebotomy teams that travelled to individual fire stations, in coordination with an annual tuberculosis testing campaign for firefighters employed by OC Fire Authority (OCFA), and independently for firefighters employed by cities. We estimated seroprevalence and assessed several potential predictors of seropositivity. RESULTS: The seroprevalence was 5.3% among 923 OCFA personnel tested, with 92.2% participating. Among firefighters self-reporting a previous positive COVID-19 antibody or PCR test result, twenty-one (37%) did not have positive IgG tests in the current serosurvey. There were no statistically significant differences in demographic characteristics between cases and non-cases. Work city was a significant predictor of case status (p=0.015). Seroprevalence (4.8%) was similar when aggregated across seven city fire departments (42%-65% participation). In total, 1486°C fire personnel were tested. CONCLUSION: Using a strong serosurvey design and large firefighter cohort, we observed a SARS-CoV-2 IgG seroprevalence of 5.3%. The seroprevalence among OC firefighters in October 2020 was lower than the general county population estimated seroprevalence (11.5%) in August. The difference may be due in part to safety measures taken by OC fire departments at the start of the pandemic, as well as differences in antibody test methods and/or duration of antibody response.


Subject(s)
Antibodies, Viral/immunology , COVID-19/epidemiology , Firefighters/statistics & numerical data , SARS-CoV-2/immunology , Adult , COVID-19/immunology , California/epidemiology , Female , Humans , Immunoglobulin G/immunology , Male , Middle Aged , Occupational Exposure/statistics & numerical data , Seroepidemiologic Studies , Young Adult
9.
Open Forum Infect Dis ; 8(2): ofab015, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1091227

ABSTRACT

BACKGROUND: Understanding severe acute respiratory syndrome coronavirus 2 antibody prevalence in a spectrum of health care workers (HCWs) may provide benchmarks of susceptibility, help us understand risk stratification, and support enactment of better health policies and procedures. METHODS: Blood serum was sampled at enrollment and 8-week follow-up from HCWs (n = 3458) and from community first responders (n = 226) for immunoglobulin G (IgG) analyses. Demographics, job duties, location, and coronavirus disease 2019-related information were collected. RESULTS: The observed IgG antibody prevalence was 0.93% and 2.58% at enrollment (May/June) and 8-week follow-up (July/August), respectively, for HCWs, and 5.31% and 4.35% for first responders. For HCWs, significant differences (P < .05) between negative and positive at initial assessment were found for age, race, fever, and loss of smell, and at 8-week follow-up for age, race, and all symptoms. Antibody positivity persisted at least 8 weeks in all positive HCWs. CONCLUSIONS: We found considerably lower antibody prevalence among HCWs compared with other published studies. While rigorous safety process measures instituted in our workplace and heightened awareness at and outside of the workplace among our HCWs may have contributed to our findings, the significant discrepancy from our community prevalence warrants further studies on other contributing factors.

10.
J Popul Econ ; 34(2): 691-738, 2021.
Article in English | MEDLINE | ID: covidwho-1037410

ABSTRACT

Given the role of human behavior in the spread of disease, it is vital to understand what drives people to engage in or refrain from health-related behaviors during a pandemic. This paper examines factors associated with the adoption of self-protective health behaviors, such as social distancing and mask wearing, at the start of the Covid-19 pandemic in the USA. These behaviors not only reduce an individual's own risk of infection but also limit the spread of disease to others. Despite these dual benefits, universal adoption of these behaviors is not assured. We focus on the role of socioeconomic differences in explaining behavior, relying on data collected in April 2020 during the early stages of the Covid-19 pandemic. The data include information on income, gender and race along with unique variables relevant to the current pandemic, such as work arrangements and housing quality. We find that higher income is associated with larger changes in self-protective behaviors. These gradients are partially explained by the fact that people with less income are more likely to report circumstances that make adopting self-protective behaviors more difficult, such as an inability to tele-work. Both in the USA and elsewhere, policies that assume universal compliance with self-protective measures-or that otherwise do not account for socioeconomic differences in the costs of doing so-are unlikely to be effective or sustainable.

11.
PLoS One ; 15(11): e0240006, 2020.
Article in English | MEDLINE | ID: covidwho-922702

ABSTRACT

Serological surveys have been conducted to establish prevalence for COVID-19 antibodies in various cohorts and communities, reporting a wide range of outcomes. The prevalence of such antibodies among healthcare workers, presumed at higher risk for infection, has been increasingly investigated, more studies are needed to better understand the risks and infection transmission in different healthcare settings. The present study reports on initial sero-surveillance conducted on healthcare workers at a regional hospital system in Orange County, California, during May and June, 2020. Study subjects were recruited from the entire hospital employee workforce and the independent medical staff. Data were collected for job duties and locations, COVID-19 symptoms, a PCR test history, travel record since January 2020, and existence of household contacts with COVID-19. A blood sample was collected from each subject for serum analysis for IgG antibodies to SARS-CoV-2. Of 2,992 tested individuals, a total 2,924 with complete data were included in the analysis. Observed prevalence of 1.06% (31 antibody positive cases), adjusted prevalence of 1.13% for test sensitivity and specificity were identified. Significant group differences between positive vs. negative were observed for age (z = 2.65, p = .008), race (p = .037), presence of fever (p < .001), and loss of smell (p < .001), but not for occupations (p = .710). Possible explanation for this low prevalence includes a relatively low local geographic community prevalence (~4.4%) at the time of testing, the hospital's timely procurement of personal protective equipment, rigorous employee education, patient triage, and treatment protocol development and implementation. In addition, cross-reactive adaptive T cell mediated immunity, as recently described, may possibly play a greater role in healthcare workers than in the general population.


Subject(s)
Coronavirus Infections/epidemiology , Health Personnel/statistics & numerical data , Pneumonia, Viral/epidemiology , Adult , Antibodies, Viral/analysis , Betacoronavirus , COVID-19 , COVID-19 Testing , California/epidemiology , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Female , Humans , Male , Middle Aged , Pandemics , Prevalence , SARS-CoV-2 , Sensitivity and Specificity
12.
MMWR Morb Mortal Wkly Rep ; 69(33): 1139-1143, 2020 Aug 21.
Article in English | MEDLINE | ID: covidwho-724591

ABSTRACT

Preventing coronavirus disease 2019 (COVID-19) in correctional and detention facilities* can be challenging because of population-dense housing, varied access to hygiene facilities and supplies, and limited space for isolation and quarantine (1). Incarcerated and detained populations have a high prevalence of chronic diseases, increasing their risk for severe COVID-19-associated illness and making early detection critical (2,3). Correctional and detention facilities are not closed systems; SARS-CoV-2, the virus that causes COVID-19, can be transmitted to and from the surrounding community through staff member and visitor movements as well as entry, transfer, and release of incarcerated and detained persons (1). To better understand SARS-CoV-2 prevalence in these settings, CDC requested data from 15 jurisdictions describing results of mass testing events among incarcerated and detained persons and cases identified through earlier symptom-based testing. Six jurisdictions reported SARS-CoV-2 prevalence of 0%-86.8% (median = 29.3%) from mass testing events in 16 adult facilities. Before mass testing, 15 of the 16 facilities had identified at least one COVID-19 case among incarcerated or detained persons using symptom-based testing, and mass testing increased the total number of known cases from 642 to 8,239. Case surveillance from symptom-based testing has likely underestimated SARS-CoV-2 prevalence in correctional and detention facilities. Broad-based testing can provide a more accurate assessment of prevalence and generate data to help control transmission (4).


Subject(s)
Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/epidemiology , Disease Outbreaks/prevention & control , Mass Screening , Pneumonia, Viral/epidemiology , Prisons , COVID-19 , COVID-19 Testing , Coronavirus Infections/diagnosis , Coronavirus Infections/prevention & control , Housing/statistics & numerical data , Humans , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Prevalence , United States/epidemiology
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