Dataset Information

Longitudinal Surveillance for SARS-CoV-2 Among Staff in Six Colorado Long-Term Care Facilities: Epidemiologic, Virologic and Sequence Analysis.

ABSTRACT:

Background

SARS-CoV-2 emerged in 2019 and has become a major global pathogen. Its emergence is notable due to its impacts on individuals residing within long term care facilities (LTCFs) such as rehabilitation centers and nursing homes. LTCF residents tend to possess several risk factors for more severe SARS-CoV-2 outcomes, including advanced age and multiple comorbidities. Indeed, residents of LTCFs represent approximately 40% of SARS-CoV-2 deaths in the United States.

Methods

To assess the prevalence and incidence of SARS-CoV-2 among LTCF workers, determine the extent of asymptomatic SARS-CoV-2 infection, and provide information on the genomic epidemiology of the virus within these unique care settings, we collected nasopharyngeal swabs from workers for 8-11 weeks at six Colorado LTCFs, determined the presence and level of viral RNA and infectious virus within these samples, and sequenced 54 nearly complete genomes.

Findings

Our data reveal a strikingly high degree of asymptomatic/mildly symptomatic infection, a strong correlation between viral RNA and infectious virus, prolonged infections and persistent RNA in a subset of individuals, and declining incidence over time.

Interpretation

Our data suggest that asymptomatic SARS-CoV-2 infected individuals contribute to virus persistence and transmission within the workplace, due to high levels of virus. Genetic epidemiology revealed that SARS-CoV-2 likely spreads between staff within an LTCF.

Funding

Colorado State University Colleges of Health and Human Sciences, Veterinary Medicine and Biomedical Sciences, Natural Sciences, and Walter Scott, Jr. College of Engineering, the Columbine Health Systems Center for Healthy Aging, and the National Institute of Allergy and Infectious Diseases.

SUBMITTER: Gallichotte EN

PROVIDER: S-EPMC7302309 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 and has become a major global pathogen in an astonishingly short period of time. The emergence of SARS-CoV-2 has been notable due to its impacts on residents in long-term care facilities (LTCFs). LTCF residents tend to possess several risk factors for severe outcomes of SARS-CoV-2 infection, including advanced age and the presence of comorbidities. Indeed, residents of LTCFs represent approximately 40% of SARS-CoV-2 deaths in the United States. Few studies have focused on the prevalence and transmission dynamics of SARS-CoV-2 among LTCF staff during the early months of the pandemic, prior to mandated surveillance testing. To assess the prevalence and incidence of SARS-CoV-2 among LTCF staff, characterize the extent of asymptomatic infections, and investigate the genomic epidemiology of the virus within these settings, we sampled staff for 8 to 11 weeks at six LTCFs with nasopharyngeal swabs from March through June of 2020. We determined the presence and levels of viral RNA and infectious virus and sequenced 54 nearly complete genomes. Our data revealed that over 50% of infections were asymptomatic/mildly symptomatic and that there was a strongly significant relationship between viral RNA (vRNA) and infectious virus, prolonged infections, and persistent vRNA (4+ weeks) in a subset of individuals, and declining incidence over time. Our data suggest that asymptomatic SARS-CoV-2-infected LTCF staff contributed to virus persistence and transmission within the workplace during the early pandemic period. Genetic epidemiology data generated from samples collected during this period support that SARS-CoV-2 was commonly spread between staff within an LTCF and that multiple-introduction events were less common. IMPORTANCE Our work comprises unique data on the characteristics of SARS-CoV-2 dynamics among staff working at LTCFs in the early months of the SARS-CoV-2 pandemic prior to mandated staff surveillance testing. During this time period, LTCF residents were largely sheltering-in-place. Given that staff were able to leave and return daily and could therefore be a continued source of imported or exported infection, we performed weekly SARS-CoV-2 PCR on nasal swab samples collected from this population. There are limited data from the early months of the pandemic comprising longitudinal surveillance of staff at LTCFs. Our data reveal the surprisingly high level of asymptomatic/presymptomatic infections within this cohort during the early months of the pandemic and show genetic epidemiological analyses that add novel insights into both the origin and transmission of SARS-CoV-2 within LTCFs.

Project description:BackgroundLong-term care facilities (LTCFs) are vulnerable to outbreaks of coronavirus disease 2019 (COVID-19). Timely epidemiological surveillance is essential for outbreak response, but is complicated by a high proportion of silent (non-symptomatic) infections and limited testing resources.MethodsWe used a stochastic, individual-based model to simulate transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) along detailed inter-individual contact networks describing patient-staff interactions in a real LTCF setting. We simulated distribution of nasopharyngeal swabs and reverse transcriptase polymerase chain reaction (RT-PCR) tests using clinical and demographic indications and evaluated the efficacy and resource-efficiency of a range of surveillance strategies, including group testing (sample pooling) and testing cascades, which couple (i) testing for multiple indications (symptoms, admission) with (ii) random daily testing.ResultsIn the baseline scenario, randomly introducing a silent SARS-CoV-2 infection into a 170-bed LTCF led to large outbreaks, with a cumulative 86 (95% uncertainty interval 6-224) infections after 3 weeks of unmitigated transmission. Efficacy of symptom-based screening was limited by lags to symptom onset and silent asymptomatic and pre-symptomatic transmission. Across scenarios, testing upon admission detected just 34-66% of patients infected upon LTCF entry, and also missed potential introductions from staff. Random daily testing was more effective when targeting patients than staff, but was overall an inefficient use of limited resources. At high testing capacity (> 10 tests/100 beds/day), cascades were most effective, with a 19-36% probability of detecting outbreaks prior to any nosocomial transmission, and 26-46% prior to first onset of COVID-19 symptoms. Conversely, at low capacity (< 2 tests/100 beds/day), group testing strategies detected outbreaks earliest. Pooling randomly selected patients in a daily group test was most likely to detect outbreaks prior to first symptom onset (16-27%), while pooling patients and staff expressing any COVID-like symptoms was the most efficient means to improve surveillance given resource limitations, compared to the reference requiring only 6-9 additional tests and 11-28 additional swabs to detect outbreaks 1-6 days earlier, prior to an additional 11-22 infections.ConclusionsCOVID-19 surveillance is challenged by delayed or absent clinical symptoms and imperfect diagnostic sensitivity of standard RT-PCR tests. In our analysis, group testing was the most effective and efficient COVID-19 surveillance strategy for resource-limited LTCFs. Testing cascades were even more effective given ample testing resources. Increasing testing capacity and updating surveillance protocols accordingly could facilitate earlier detection of emerging outbreaks, informing a need for urgent intervention in settings with ongoing nosocomial transmission.

Project description:RationaleNontuberculous mycobacteria (NTM) are ubiquitous environmental microorganisms. Infection is thought to result primarily from exposure to soil and/or water sources. NTM disease prevalence varies greatly by geographic region, but the geospatial factors influencing this variation remain unclear.ObjectivesTo identify sociodemographic and environmental ecological risk factors associated with NTM infection and disease in Colorado.MethodsWe conducted an ecological study, combining data from patients with a diagnosis of NTM disease from National Jewish Health's electronic medical record database and ZIP code-level sociodemographic and environmental exposure data obtained from the U.S. Geological Survey, the U.S. Department of Agriculture, and the U.S. Census Bureau. We used spatial scan methods to identify high-risk clusters of NTM disease in Colorado. Ecological risk factors for disease were assessed using Bayesian generalized linear models assuming Poisson-distributed discrete responses (case counts by ZIP code) with the log link function.ResultsWe identified two statistically significant high-risk clusters of disease. The primary cluster included ZIP codes in urban regions of Denver and Aurora, as well as regions south of Denver, on the east side of the Continental Divide. The secondary cluster was located on the west side of the Continental Divide in rural and mountainous regions. After adjustment for sociodemographic, drive time, and soil variables, we identified three watershed areas with relative risks of 12.2, 4.6, and 4.2 for slowly growing NTM infections compared with the mean disease risk for all watersheds in Colorado. This study population carries with it inherent limitations that may introduce bias. The lack of complete capture of NTM cases in Colorado may be related to factors such as disease severity, education and income levels, and insurance status.ConclusionsOur findings provide evidence that water derived from particular watersheds may be an important source of NTM exposure in Colorado. The watershed with the greatest risk of NTM disease contains the Dillon Reservoir. This reservoir is also the main water supply for major cities located in the two watersheds with the second and third highest disease risk in the state, suggesting an important possible source of infection.