scholarly journals Modeling University Reopening in Low Risk Countries During COVID-19

2021 ◽  
Author(s):  
Jing Yang (Sunny) Xi ◽  
Wai Kin (Victor) Chan
Keyword(s):  
High Risk ◽  
Virus Transmission ◽  
Low Risk ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Regular Screening ◽  
Nonpharmaceutical Interventions ◽  
Model Virus

ABSTRACTThe safety of students worldwide remains a key issue during COVID-19. The reopening of universities in high risk countries during Fall 2020 resulted in numerous outbreaks. While regular screening and testing on campus can prevent the transmission of SARS-CoV-2, they are extremely challenging to implement due to various reasons such as cost and logistics. However, for low risk countries, our study suggests that universities can fully reopen without testing, if students self-quarantine for 14 days on arrival and adopt proper nonpharmaceutical interventions (NPIs). We adopt agent-based simulation to model virus transmission on campus and test the effectiveness of several NPIs when school reopens. Assuming one initially infected student, results indicate that transmission between roommates causes the most infections with visitors, ground floors, and elevators, being the next main contributors. Limiting density and/or population are not impactful at flattening the curve. However, adopting masks, minimizing movement, and increasing the frequency of cleaning can effectively minimize infection and prevent outbreak, allowing for classes and activities to resume as normal.

scholarly journals SARS-CoV-2 Seroprevalence in Healthcare Workers in Germany: A Follow-Up Study

2021 ◽  
Vol 18 (9) ◽  
pp. 4540
Author(s):  
Johannes Korth ◽  
Benjamin Wilde ◽  
Sebastian Dolff ◽  
Jasmin Frisch ◽  
Michael Jahn ◽  
...  
Keyword(s):  
High Risk ◽  
Healthcare Workers ◽  
Risk Group ◽  
Close Contact ◽  
Virus Transmission ◽  
High Risk Group ◽  
Low Risk ◽  
University Hospital ◽  
Intermediate Risk ◽  
Igg Antibody

SARS-CoV-2 is a worldwide challenge for the medical sector. Healthcare workers (HCW) are a cohort vulnerable to SARS-CoV-2 infection due to frequent and close contact with COVID-19 patients. However, they are also well trained and equipped with protective gear. The SARS-CoV-2 IgG antibody status was assessed at three different time points in 450 HCW of the University Hospital Essen in Germany. HCW were stratified according to contact frequencies with COVID-19 patients in (I) a high-risk group with daily contacts with known COVID-19 patients (n = 338), (II) an intermediate-risk group with daily contacts with non-COVID-19 patients (n = 78), and (III) a low-risk group without patient contacts (n = 34). The overall seroprevalence increased from 2.2% in March–May to 4.0% in June–July to 5.1% in October–December. The SARS-CoV-2 IgG detection rate was not significantly different between the high-risk group (1.8%; 3.8%; 5.5%), the intermediate-risk group (5.1%; 6.3%; 6.1%), and the low-risk group (0%, 0%, 0%). The overall SARS-CoV-2 seroprevalence remained low in HCW in western Germany one year after the outbreak of COVID-19 in Germany, and hygiene standards seemed to be effective in preventing patient-to-staff virus transmission.

Hepatitis B virus transmission from a surgeon to patients during high-risk as well as low-risk procedures: unnoticed transmissions over a 4-year period

2000 ◽  
Vol 87 (7) ◽  
pp. 949-949
Author(s):  
I. J. B. Spijkerman ◽  
L. J. van Doorn ◽  
M. H. W. Janssen ◽  
C. J. Wijkmans ◽  
M. A. J. Bilkert-Mooiman ◽  
...  
Keyword(s):  
Hepatitis B Virus ◽  
High Risk ◽  
Hepatitis B ◽  
Virus Transmission ◽  
Low Risk ◽  
B Virus

scholarly journals The impact of vaccination to control COVID-19 burden in the United States: A simulation modeling approach

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254456
Author(s):  
Oguzhan Alagoz ◽  
Ajay K. Sethi ◽  
Brian W. Patterson ◽  
Matthew Churpek ◽  
Ghalib Alhanaee ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Simulation Modeling ◽  
Vaccine Coverage ◽  
The United States ◽  
Agent Based Simulation ◽  
Vaccination Programs ◽  
Agent Based ◽  
Nonpharmaceutical Interventions ◽  
The Impact

Introduction Vaccination programs aim to control the COVID-19 pandemic. However, the relative impacts of vaccine coverage, effectiveness, and capacity in the context of nonpharmaceutical interventions such as mask use and physical distancing on the spread of SARS-CoV-2 are unclear. Our objective was to examine the impact of vaccination on the control of SARS-CoV-2 using our previously developed agent-based simulation model. Methods We applied our agent-based model to replicate COVID-19-related events in 1) Dane County, Wisconsin; 2) Milwaukee metropolitan area, Wisconsin; 3) New York City (NYC). We evaluated the impact of vaccination considering the proportion of the population vaccinated, probability that a vaccinated individual gains immunity, vaccination capacity, and adherence to nonpharmaceutical interventions. We estimated the timing of pandemic control, defined as the date after which only a small number of new cases occur. Results The timing of pandemic control depends highly on vaccination coverage, effectiveness, and adherence to nonpharmaceutical interventions. In Dane County and Milwaukee, if 50% of the population is vaccinated with a daily vaccination capacity of 0.25% of the population, vaccine effectiveness of 90%, and the adherence to nonpharmaceutical interventions is 60%, controlled spread could be achieved by June 2021 versus October 2021 in Dane County and November 2021 in Milwaukee without vaccine. Discussion In controlling the spread of SARS-CoV-2, the impact of vaccination varies widely depending not only on effectiveness and coverage, but also concurrent adherence to nonpharmaceutical interventions.

Papillary Thyroid Carcinoma: How Radical Lymphadenectomy Should be Performed?

Swiss Surgery ◽  
2003 ◽  
Vol 9 (2) ◽  
pp. 63-68
Author(s):  
Schweizer ◽  
Seifert ◽  
Gemsenjäger
Keyword(s):  
High Risk ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Low Risk ◽  
Papillary Thyroid ◽  
Sentinel Nodes ◽  
Fand Sich ◽  
Radical Lymphadenectomy ◽  
N Status

Fragestellung: Die Bedeutung von Lymphknotenbefall bei papillärem Schilddrüsenkarzinom und die optimale Lymphknotenchirurgie werden kontrovers beurteilt. Methodik: Retrospektive Langzeitstudie eines Operateurs (n = 159), prospektive Dokumentation, Nachkontrolle 1-27 (x = 8) Jahre, Untersuchung mit Bezug auf Lymphknotenbefall. Resultate: Staging. Bei 42 Patienten wurde wegen makroskopischem Lymphknotenbefall (cN1) eine therapeutische Lymphadenektomie durchgeführt, mit pN1 Status bei 41 (98%) Patienten. Unter 117 Patienten ohne Anhalt für Lymphknotenbefall (cN0) fand sich okkulter Befall bei 5/29 (17%) Patienten mit elektiver (prophylaktischer) Lymphadenektomie, und bei 2/88 (2.3%) Patienten ohne Lymphadenektomie (metachroner Befall) (p < 0.005). Lymphknotenrezidive traten (1-5 Jahre nach kurativer Primärtherapie) bei 5/42 (12%) pN1 und bei 3/114 (2.6%) cN0, pN0 Tumoren auf (p = 0009). Das 20-Jahres-Überleben war bei TNM I + II (low risk) Patienten 100%, d.h. unabhängig vom N Status; pN1 vs. pN0, cN0 beeinflusste das Überleben ungünstig bei high risk (>= 45-jährige) Patienten (50% vs. 86%; p = 0.03). Diskussion: Der makroskopische intraoperative Lymphknotenbefund (cN) hat Bedeutung: - Befall ist meistens richtig positiv (pN1) und erfordert eine ausreichend radikale, d.h. systematische, kompartiment-orientierte Lymphadenektomie (Mikrodissektion) zur Verhütung von - kurablem oder gefährlichem - Rezidiv. - Okkulter Befall bei unauffälligen Lymphknoten führt selten zum klinischen Rezidiv und beeinflusst das Überleben nicht. Wir empfehlen eine weniger radikale (sampling), nur zentrale prophylaktische Lymphadenektomie, ohne Risiko von chirurgischer Morbidität. Ein empfindlicherer Nachweis von okkultem Befund (Immunhistochemie, Schnellschnitt von sampling Gewebe oder sentinel nodes) erscheint nicht rational. Bei pN0, cN0 Befund kommen Verzicht auf 131I Prophylaxe und eine weniger intensive Nachsorge in Frage.

Individuals at high risk for suicide are categorically distinct from those at low risk.

2017 ◽  
Vol 29 (4) ◽  
pp. 382-393 ◽  
Author(s):  
Tracy K. Witte ◽  
Jill M. Holm-Denoma ◽  
Kelly L. Zuromski ◽  
Jami M. Gauthier ◽  
John Ruscio
Keyword(s):  
High Risk ◽  
Low Risk
Sign in / Sign up

Export Citation Format

Share Document