Correlation of National and Healthcare Workers COVID-19 Infection Data; Implications for Large-scale Viral Testing Programs

Time analysis of the course of an infectious disease epidemic is a critical way to understand the dynamics of pathogen transmission and the effect of population scale interventions. Computational methods have been applied to the progression of the COVID-19 outbreak in five different countries (Ireland, Germany, UK, South Korea and Iceland) using their reported daily infection data. A Gaussian convolution smoothing function constructed a continuous epidemic line profile that was segmented into longitudinal time series of mathematically fitted individual logistic curves. The time series of fitted curves allowed comparison of disease progression with differences in decreasing daily infection numbers following the epidemic peak being of specific interest. A positive relationship between rate of declining infections and countries with comprehensive COVID-19 testing regimes existed. In contrast, extended epidemic timeframes were recorded for those least prepared for large scale testing and contact tracing. As many countries continue to struggle to implement population wide testing it is prudent to explore additional measures that could be employed. Comparative analysis of healthcare worker (HCW) infection data from Ireland shows it closely related to that of the entire population with respect to trends of daily infection numbers and growth rates over a 57-day period. With 31.6% of all test-confirmed infections in healthcare workers (all employees of healthcare facilities), they represent a concentrated 3% subset of the national population which if exhaustively tested (regardless of symptom status) could provide valuable information on disease progression in the entire population (or set). Mathematically, national population and HCWs can be viewed as a set and subset with significant influences on each other, with solidarity between both an essential ingredient for ending this crisis.

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Correlation of national and healthcare workers COVID-19 infection data; implications for large-scale viral testing programs

PLoS ONE ◽

10.1371/journal.pone.0250699 ◽

2021 ◽

Vol 16 (4) ◽

pp. e0250699

Author(s):

Dan Wu ◽

Pól Mac Aonghusa ◽

Donal F. O’Shea

Keyword(s):

Time Series ◽

Disease Progression ◽

Healthcare Workers ◽

Large Scale ◽

Pathogen Transmission ◽

Entire Population ◽

Contact Tracing ◽

Smoothing Function ◽

Healthcare Facilities ◽

National Population

Time analysis of the course of an infectious disease epidemic is a critical way to understand the dynamics of pathogen transmission and the effect of population scale interventions. Computational methods have been applied to the progression of the COVID-19 outbreak in five different countries (Ireland, Germany, UK, South Korea and Iceland) using their reported daily infection data. A Gaussian convolution smoothing function constructed a continuous epidemic line profile that was segmented into longitudinal time series of mathematically fitted individual logistic curves. The time series of fitted curves allowed comparison of disease progression with differences in decreasing daily infection numbers following the epidemic peak being of specific interest. A positive relationship between the rate of declining infections and countries with comprehensive COVID-19 testing regimes existed. Insight into different rates of decline infection numbers following the wave peak was also possible which could be a useful tool to guide the reopening of societies. In contrast, extended epidemic timeframes were recorded for those least prepared for large-scale testing and contact tracing. As many countries continue to struggle to implement population wide testing it is prudent to explore additional measures that could be employed. Comparative analysis of healthcare worker (HCW) infection data from Ireland shows it closely related to that of the entire population with respect to trends of daily infection numbers and growth rates over a 57-day period. With 31.6% of all test-confirmed infections in healthcare workers (all employees of healthcare facilities), they represent a concentrated 3% subset of the national population which if exhaustively tested (regardless of symptom status) could provide valuable information on disease progression in the entire population (or set). Mathematically, national population and HCWs can be viewed as a set and subset with significant influences on each other, with solidarity between both an essential ingredient for ending this crisis.

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SIREN protocol: Impact of detectable anti-SARS-CoV-2 on the subsequent incidence of COVID-19 in 100,000 healthcare workers: do antibody positive healthcare workers have less reinfection than antibody negative healthcare workers?

10.1101/2020.12.15.20247981 ◽

2020 ◽

Author(s):

S. Wallace ◽

V. Hall ◽

A. Charlett ◽

P.D. Kirwan ◽

M.J. Cole ◽

...

Keyword(s):

Healthcare Workers ◽

Large Scale ◽

Antibody Test ◽

Study Entry ◽

Contact Tracing ◽

Staff Members ◽

Viral Culture ◽

The Uk ◽

Prospective Longitudinal ◽

The Impact

AbstractBackgroundThe overall risk of reinfection in individuals who have previously had COVID-19 is unknown. To determine if prior SARS-CoV-2 infection (as determined by at least one positive commercial antibody test performed in a laboratory) in healthcare workers confers future immunity to reinfection, we are undertaking a large-scale prospective longitudinal cohort study of healthcare staff across the United Kingdom.MethodsPopulation and Setting: staff members of healthcare organisations working in hospitals in the UKAt recruitment, participants will have their serum tested for anti-SARS-CoV-2 at baseline and using these results will be initially allocated to either antibody positive or antibody negative cohorts. Participants will undergo antibody and viral RNA testing at 1-4 weekly intervals throughout the study period, and based on these results may move between cohorts. Any results from testing undertaken for other reasons (e.g. symptoms, contact tracing etc.) or prior to study entry will also be included. Individuals will complete enrolment and fortnightly questionnaires on exposures and symptoms. Follow-up will be for at least 12 months from study entry.OutcomeThe primary outcome of interest is a reinfection with SARS -CoV-2 during the study period. Secondary outcomes will include incidence and prevalence (both RNA and antibody) of SARS-CoV-2, viral genomics, viral culture, symptom history and antibody/neutralising antibody titres.ConclusionThis large study will help us to understand the impact of the presence of antibodies on the risk of reinfection with SARS-CoV-2; the results will have substantial implications in terms of national and international policy, as well as for risk management of contacts of COVID-19 cases.Trial RegistrationIRAS ID 284460, HRA and Health and Care Research Wales approval granted 22 May 2020.

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SARS-Coronavirus-2 cases in healthcare workers may not regularly originate from patient care: lessons from a university hospital on the underestimated risk of healthcare worker to healthcare worker transmission

Antimicrobial Resistance and Infection Control ◽

10.1186/s13756-020-00848-w ◽

2020 ◽

Vol 9 (1) ◽

Author(s):

Sandra Schneider ◽

Brar Piening ◽

Pauline Assina Nouri-Pasovsky ◽

Anne Caroline Krüger ◽

Petra Gastmeier ◽

...

Keyword(s):

Healthcare Worker ◽

Healthcare Workers ◽

Critical Role ◽

Healthcare Setting ◽

University Hospital ◽

Contact Tracing ◽

Healthcare Facilities ◽

University Medicine ◽

Healthcare Associated ◽

Epidemiological Link

Abstract Background Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents an unprecedented healthcare challenge. Various SARS-CoV-2 outbreaks in healthcare facilities have been reported. Healthcare workers (HCWs) may play a critical role in the spread of the virus, particularly when asymptomatic. We examined four healthcare-associated outbreaks of SARS-CoV-2 infections that occurred at a university hospital in Berlin, Germany. We aimed to describe and analyze the spread of the virus in order to draw conclusions for effective containment of SARS-CoV-2 in healthcare facilities. Methods Healthcare-associated outbreaks of SARS-CoV-2 infections were defined as two or more laboratory confirmed infections with SARS-CoV-2 where an epidemiological link within the healthcare setting appeared likely. We focused our analysis on one of three sites of the Charité-University Medicine hospital within a 2 month period (March and April 2020). Results We observed four healthcare-associated outbreaks of SARS-CoV-2 infections, with a total of 24 infected persons (23 HCWs and one patient). The outbreaks were detected in the departments of nephrology and dialysis (n = 9), anesthesiology (n = 8), surgical pediatrics (n = 4), and neurology (n = 3). Each outbreak showed multiple unprotected contacts between infected HCWs. A combination of contact tracing, testing, physical distancing and mandatory continuous wearing of face masks by all HCWs was able to contain all four outbreaks. Conclusions HCW to HCW transmission represented the likely source of the four outbreaks. Ensuring proper physical distancing measures and wearing of protective equipment, also when interacting with colleagues, must be a key aspect of fighting COVID-19 in healthcare facilities.

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Quantification of healthcare workers’ exposure to cyclophosphamide, ifosfamide, methotrexate, and 5-fluorouracil by 24-h urine assay: A descriptive pilot study

Journal of Oncology Pharmacy Practice ◽

10.1177/1078155220907129 ◽

2020 ◽

Vol 26 (8) ◽

pp. 1864-1870

Author(s):

Marie Palamini ◽

Annick Dufour ◽

Roxane Therrien ◽

Jean-François Delisle ◽

Geneviève Mercier ◽

...

Keyword(s):

Pilot Study ◽

Healthcare Workers ◽

Large Scale ◽

Ultra Performance Liquid Chromatography ◽

Urine Samples ◽

Surveillance Program ◽

Healthcare Facilities ◽

Beta Alanine ◽

Liquid Chromatography Tandem Mass ◽

Hazardous Drugs

Purpose The objective of this pilot study was to determine the frequency of urination and the concentration of four hazardous drugs (cyclophosphamide, ifosfamide, methotrexate, and fluorouracil) in workers’ 24-h urine samples in relation to exposure to traces with hazardous drugs. Methods The study was conducted in three healthcare centers in the region of Montréal, Quebec, Canada. We recruited healthcare workers (nurses and pharmacy technicians) assigned to the hematology-oncology department. Each participant was asked to collect all urine voided during a 24-h period, to fill out an activity journal documenting tasks performed and to document the use of personal protective equipment. Samples were analyzed for cyclophosphamide, ifosfamide, methotrexate, and alpha-fluoro-beta-alanine (FBAL, the main urinary metabolite of 5-fluorouracil). Drugs were quantified by ultra-performance liquid chromatography-tandem mass spectrometry (positive electrospray MRM mode). Results Eighteen healthcare workers (10 nurses and 8 technicians) were recruited and provided consent to participate. Urine samples were obtained between 1 September and 30 September 2019. The number of urinations over the 24-h collection period ranged from 3 to 11 per participant. A total of 128 urine samples were analyzed for the 18 workers. All urine samples were negative for the four antineoplastics tested. Conclusion No traces of cyclophosphamide, ifosfamide, methotrexate, or FBAL were found in the 24-h urine samples of 18 healthcare workers practicing in three healthcare facilities in Quebec. Although it was feasible to collect 24-h urine samples in this research project, it appears unrealistic to do so recurrently as part of a large-scale surveillance program.

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COVID-19 Contact Tracing in a Pediatric Hospital: Maximizing Effectiveness Through Specialized Team and Automated Tools

Antimicrobial Stewardship & Healthcare Epidemiology ◽

10.1017/ash.2021.86 ◽

2021 ◽

Vol 1 (S1) ◽

pp. s46-s47

Author(s):

Lindsay Weir ◽

Jennifer Ormsby ◽

Carin Bennett-Rizzo ◽

Jonathan Bickel ◽

Colleen Dansereau ◽

...

Keyword(s):

Occupational Health ◽

Large Scale ◽

Infection Prevention ◽

Tracking System ◽

Contact Tracing ◽

Infectious Period ◽

Infection Prevention And Control ◽

Health Staff ◽

Healthcare Facilities ◽

Staff Meet

Background: In their interim infection prevention and control recommendations for the coronavirus disease 2019 (COVID-19) pandemic, the Centers for Disease Control and Prevention (CDC) recommend that healthcare facilities have a plan to identify, investigate, and trace potential COVID-19 exposures. In an academic hospital, the scale of such tracing is substantial, given that medically complex patients can have dozens of staff contacts across multiple locations during an encounter. Furthermore, the family-centered care model employed by pediatric institutions precludes visitor exclusion, further complicating tracing efforts. Despite this complexity, tracing accuracy and timeliness is of paramount importance for exposure management. To address these challenges, our institution developed a contact-tracing system that balanced expert participation with automated tracing tools. Methods: Our institution’s contact-tracing initiative includes positive patients, parents and/or visitors, and staff for the enterprise’s inpatient, procedural, and ambulatory locations at the main campus and 4 satellites. The team consists of 11 staff and is overseen by an infection preventionist. For positive patients and parents and/or visitors, potentially exposed staff are automatically identified via a report that extracts staff details for all encounters occurring during the patient’s infectious period. For positive staff, trained contact tracers call the staff member to determine whether mask and distancing practices could result in others meeting CDC exposure criteria. Any potentially exposed healthcare workers (HCWs) receive an e-mail that details exposure criteria and provides follow-up instructions. These HCWs are also entered into a secure, centralized tracking database that (1) allows infection prevention and occupational health staff to query and identify all epidemiologic links between traced patients, parents and/or visitors, and staff, and (2) initiates staff enrollment in a twice-daily symptom tracking system administered via REDCap. Potentially exposed patients and parents and/or visitors are contacted directly by a hospital representative. The contact tracing team, infection prevention staff, and occupational health staff meet daily to review positive staff cases in the last 24 hours. Results: To date, the team has traced ~1,300 patients, 15 parents and/or visitors, and 700 staff. Since the start of the pandemic, tracing and contact notification for all positive cases has been conducted within 24 hours. Through these proactive tracing efforts and other institutional infection prevention initiatives, the institution only experienced 1 staff cluster (N < 15) and <5 hospital-onset patient cases. Conclusions: Equipping a trained group of contact tracers with automated tracking tools can afford infection prevention and occupational health departments the ability to achieve and sustain timely and accurate contact tracing initiatives throughout a large-scale pandemic response.Funding: NoDisclosures: None

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Structured Manifold Broad Learning System: A Manifold Perspective for Large-Scale Chaotic Time Series Analysis and Prediction

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2018.2866149 ◽

2019 ◽

Vol 31 (9) ◽

pp. 1809-1821 ◽

Cited By ~ 16

Author(s):

Min Han ◽

Shoubo Feng ◽

C. L. Philip Chen ◽

Meiling Xu ◽

Tie Qiu

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Large Scale ◽

Chaotic Time Series ◽

Learning System ◽

Series Analysis ◽

System A ◽

Chaotic Time Series Analysis

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Can Copper Products and Surfaces Reduce the Spread of Infectious Microorganisms and Hospital-Acquired Infections?

Materials ◽

10.3390/ma14133444 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3444

Author(s):

Joji Abraham ◽

Kim Dowling ◽

Singarayer Florentine

Keyword(s):

Infection Control ◽

Hospital Admissions ◽

Copper Alloys ◽

Well Being ◽

Mortality Rates ◽

Pathogen Transmission ◽

Control Measures ◽

Traditional Use ◽

Healthcare Facilities ◽

Infection Control Measures

Pathogen transfer and infection in the built environment are globally significant events, leading to the spread of disease and an increase in subsequent morbidity and mortality rates. There are numerous strategies followed in healthcare facilities to minimize pathogen transfer, but complete infection control has not, as yet, been achieved. However, based on traditional use in many cultures, the introduction of copper products and surfaces to significantly and positively retard pathogen transmission invites further investigation. For example, many microbes are rendered unviable upon contact exposure to copper or copper alloys, either immediately or within a short time. In addition, many disease-causing bacteria such as E. coli O157:H7, hospital superbugs, and several viruses (including SARS-CoV-2) are also susceptible to exposure to copper surfaces. It is thus suggested that replacing common touch surfaces in healthcare facilities, food industries, and public places (including public transport) with copper or alloys of copper may substantially contribute to limiting transmission. Subsequent hospital admissions and mortality rates will consequently be lowered, with a concomitant saving of lives and considerable levels of resources. This consideration is very significant in times of the COVID-19 pandemic and the upcoming epidemics, as it is becoming clear that all forms of possible infection control measures should be practiced in order to protect community well-being and promote healthy outcomes.

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Tuberculosis contact investigation results among paediatric contacts in low-incidence settings in Finland

European Journal of Pediatrics ◽

10.1007/s00431-021-04000-7 ◽

2021 ◽

Author(s):

Antti Kontturi ◽

Satu Kekomäki ◽

Eeva Ruotsalainen ◽

Eeva Salo

Keyword(s):

Early Diagnosis ◽

Young Children ◽

Large Scale ◽

Index Case ◽

Contact Tracing ◽

Sputum Smear ◽

Endemic Country ◽

Household Contacts ◽

Contact Investigation ◽

Positive Index

AbstractTuberculosis (TB) risk is highest immediately after primary infection, and young children are vulnerable to rapid and severe TB disease. Contact tracing should identify infected children rapidly and simultaneously target resources effectively. We conducted a retrospective review of the paediatric TB contact tracing results in the Hospital District of Helsinki and Uusimaa from 2012 to 2016 and identified risk factors for TB disease or infection. Altogether, 121 index cases had 526 paediatric contacts of whom 34 were diagnosed with TB disease or infection. The maximum delay until first contact investigation visit among the household contacts under 5 years of age with either TB disease or infection was 7 days. The yield for TB disease or infection was 4.6% and 12.8% for household contacts, 0.5% and 0% for contacts exposed in a congregate setting and 1.4% and 5.0% for other contacts, respectively. Contacts born in a TB endemic country (aOR 3.07, 95% CI 1.10–8.57), with household exposure (aOR 2.96, 95% CI 1.33–6.58) or a sputum smear positive index case (aOR 3.96, 95% CI 1.20–13.03) were more likely to have TB disease or infection.Conclusions: Prompt TB investigations and early diagnosis can be achieved with a well-organised contact tracing structure. The risk for TB infection or disease was higher among contacts with household exposure, a sputum smear positive index case or born in a TB endemic country. Large-scale investigations among children exposed in congregate settings can result in a very low yield and should be cautiously targeted. What is Known:• Vulnerable young children are a high priority in contact tracing and should be evaluated as soon as possible after TB exposure What is New:• Prompt investigations for paediatric TB contacts and early diagnosis of infected children can be achieved with a well-organised contact tracing structure• Large-scale investigations among children exposed in congregate settings can result in a very low yield and should be cautiously targeted

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Subsidence Monitoring of Fill Area in Yan’an New District Based on Sentinel-1A Time Series Imagery

Remote Sensing ◽

10.3390/rs13153044 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3044

Author(s):

Mingjie Liao ◽

Rui Zhang ◽

Jichao Lv ◽

Bin Yu ◽

Jiatai Pang ◽

...

Keyword(s):

Time Series ◽

Large Scale ◽

Ground Deformation ◽

Dynamic Change ◽

Deformation Monitoring ◽

Chinese Loess Plateau ◽

Ground Subsidence ◽

Shanxi Province ◽

Environment Change ◽

Loess Area

In recent years, many cities in the Chinese loess plateau (especially in Shanxi province) have encountered ground subsidence problems due to the construction of underground projects and the exploitation of underground resources. With the completion of the world’s largest geotechnical project, called “mountain excavation and city construction,” in a collapsible loess area, the Yan’an city also appeared to have uneven ground subsidence. To obtain the spatial distribution characteristics and the time-series evolution trend of the subsidence, we selected Yan’an New District (YAND) as the specific study area and presented an improved time-series InSAR (TS-InSAR) method for experimental research. Based on 89 Sentinel-1A images collected between December 2017 to December 2020, we conducted comprehensive research and analysis on the spatial and temporal evolution of surface subsidence in YAND. The monitoring results showed that the YAND is relatively stable in general, with deformation rates mainly in the range of −10 to 10 mm/yr. However, three significant subsidence funnels existed in the fill area, with a maximum subsidence rate of 100 mm/yr. From 2017 to 2020, the subsidence funnels enlarged, and their subsidence rates accelerated. Further analysis proved that the main factors induced the severe ground subsidence in the study area, including the compressibility and collapsibility of loess, rapid urban construction, geological environment change, traffic circulation load, and dynamic change of groundwater. The experimental results indicated that the improved TS-InSAR method is adaptive to monitoring uneven subsidence of deep loess area. Moreover, related data and information would provide reference to the large-scale ground deformation monitoring and in similar loess areas.

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