Breaking the chain of transmission within a tertiary health service: An approach to contact tracing during the COVID-19 pandemic

Spatial spread of epidemic with Allee effect

The spatial spread of an epidemic is investigated in the case of a bistable dynamics, where the effective transmission rate depends on the fraction of infected and the state of no epidemic is linearly stable. The front propagation phenomenon is investigated both numerically and theoretically, by an analysis in a four-dimensional phase plane. A good agreement between numerical and theoretical results has been found both for the front profiles and for the speed of invasion. We discovered a novel phenomenon of front stoppage: In some regime of parameters, the front solution ceases to exist, and the propagating pulse of infection decays despite the initial outbreak.

Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China's Urban Communities

In the post-epidemic era, China's urban communities are at the forefront of implementing the whole chain of accurate epidemic prevention and control. However, the uncertainty of COVID-19, the loopholes in community management and people's overly optimistic judgment of the epidemic have led to the frequent rebound of the epidemic and serious consequences. Existing studies have not yet formed a panoramic framework of community anti-epidemic work under the concept of resilience. Therefore, this article first summarizes the current research progress of resilient communities from three perspectives, including ideas and perspectives, theories and frameworks and methods and means, and summarizes the gap of the current research. Then, an innovative idea on the epidemic resilience of urban communities in China is put forward: (1) the evolution mechanism of community anti-epidemic resilience is described through the change law of dynamic networks; (2) the anti-epidemic resilience of urban communities is evaluated or predicted through the measurement criteria; (3) a simulation platform based on Multi-Agent and dynamic Bayesian networks simulates the interactive relationship between "epidemic disturbance-cost constraint--epidemic resilience"; (4) the anti-epidemic strategies are output intelligently to provide community managers with decision-making opinions on community epidemic prevention and control.

Transmission dynamics of SARS-CoV-2 in a strictly-Orthodox Jewish community in the UK

Some social settings such as households and workplaces, have been identified as high risk for SARS-CoV-2 transmission. Identifying and quantifying the importance of these settings is critical for designing interventions. A tightly-knit religious community in the UK experienced a very large COVID-19 epidemic in 2020, reaching 64.3% seroprevalence within 10 months, and we surveyed this community both for serological status and individual-level attendance at particular settings. Using these data, and a network model of people and places represented as a stochastic graph rewriting system, we estimated the relative contribution of transmission in households, schools and religious institutions to the epidemic, and the relative risk of infection in each of these settings. All congregate settings were important for transmission, with some such as primary schools and places of worship having a higher share of transmission than others. We found that the model needed a higher general-community transmission rate for women (3.3-fold), and lower susceptibility to infection in children to recreate the observed serological data. The precise share of transmission in each place was related to assumptions about the internal structure of those places. Identification of key settings of transmission can allow public health interventions to be targeted at these locations.

Practical Strategies and Tools for Use by Occupational and Environmental Medicine Departments During COVID-19 Pandemic Surges

OBJECTIVES

Occupational and environmental medicine (OEM) departments in healthcare institutions can be quickly overwhelmed when COVID-19 infection rates rapidly and simultaneously increase in the workforce and the patients served. Our goal is to present a detailed toolkit of practical approaches for use by front-line OEM specialists to address workforce management tasks during pandemic surges.

METHODS

Specific focus is on tasks related to employee symptom triage, exposure risk assessment, workplace contact tracing, and work restrictions.

RESULTS

Tools include strategies used by customer call centers, two decision support algorithms (exposure due to cohabitation or non-cohabitation), a color-coded employee case tracking tool, a contact tracing protocol, and documentation templates that serve as memory aids for encounters.

CONCLUSIONS

These tools are created with commonly used software. Implementation is feasible in most front-line OEM settings, including those with limited resources.

Challenges and Ethical Issues Related to COVID-19 Contact Tracing Teams in Turkey

Objective

The purpose of this study was to determine and evaluate the challenges and ethical issues faced by COVID-19 filiation (contact tracing) teams and report the experiences of team members.

Methods

This is a descriptive study conducted to evaluate the performance of contact tracing field teams established by the Ministry of Health to identify, refer, and follow-up persons who tested positive for COVID-19 and their contacts. Reports were collected from various Turkish medical associations, the Turkish Ministry of Health, online news sources, and online interviews published between 11 March 2020 and 18 April 2021.

Results

A total of 32 reports published by the Turkish Ministry of Health, various medical associations in Turkey, and the Turkish Academy of Science, together with a number of online media reports on issues involving contact tracing teams, were reviewed. While the activities of the teams were overall found to be of benefit during the pandemic, numerous factors negatively impacting their success were identified. These factors included insufficient social support, wherein the fundamental bioethical values of solidarity, responsibility, respect, and trust were not adopted on a societal level, as well as issues involving the teams themselves, such as lack of time to properly conduct their work, inadequate communication skills and/or personal issues.

Conclusion

Studies conducted by the contact tracing teams were of vital importance in managing the pandemic. The teams were especially effective in reaching both educated and uneducated segments of the society, in diagnosing cases, and in informing the public regarding the pandemic. Evaluating the experiences of the contact tracing teams deployed in Turkey is of vital importance to ensure better preparation for any future pandemics.

Hospital-Based Contact Tracing of Patients With COVID-19 and Health Care Workers During the COVID-19 Pandemic in Eastern India: Cross-sectional Study

Background

The contact tracing and subsequent quarantining of health care workers (HCWs) are essential to minimizing the further transmission of SARS-CoV-2 infection and mitigating the shortage of HCWs during the COVID-19 pandemic situation.

Objective

This study aimed to assess the yield of contact tracing for COVID-19 cases and the risk stratification of HCWs who are exposed to these cases.

Methods

This was an analysis of routine data that were collected for the contact tracing of COVID-19 cases at the All India Institute of Medical Sciences, Bhubaneswar, in Odisha, India. Data from March 19 to August 31, 2020, were considered for this study. COVID-19 cases were admitted patients, outpatients, or HCWs in the hospital. HCWs who were exposed to COVID-19 cases were categorized, per the risk stratification guidelines, as high-risk contacts or low-risk contacts

Results

During contact tracing, 3411 HCWs were identified as those who were exposed to 360 COVID-19 cases. Of these 360 cases, 269 (74.7%) were either admitted patients or outpatients, and 91 (25.3%) were HCWs. After the risk stratification of the 3411 HCWs, 890 (26.1%) were categorized as high-risk contacts, and 2521 (73.9%) were categorized as low-risk contacts. The COVID-19 test positivity rates of high-risk contacts and low-risk contacts were 3.8% (34/890) and 1.9% (48/2521), respectively. The average number of high-risk contacts was significantly higher when the COVID-19 case was an admitted patient (number of contacts: mean 6.6) rather than when the COVID-19 case was an HCW (number of contacts: mean 4.0) or outpatient (number of contacts: mean 0.2; P=.009). Similarly, the average number of high-risk contacts was higher when the COVID-19 case was admitted in a non–COVID-19 area (number of contacts: mean 15.8) rather than when such cases were admitted in a COVID-19 area (number of contacts: mean 0.27; P<.001). There was a significant decline in the mean number of high-risk contacts over the study period (P=.003).

Conclusions

Contact tracing and risk stratification were effective and helped to reduce the number of HCWs requiring quarantine. There was also a decline in the number of high-risk contacts during the study period. This indicates the role of the implementation of hospital-based, COVID-19–related infection control strategies. The contact tracing and risk stratification approaches that were designed in this study can also be implemented in other health care settings.

Use of clinical data to augment healthcare worker contact tracing during the COVID-19 pandemic

OBJECTIVE

This work examined the secondary use of clinical data from the electronic health record (EHR) for screening our healthcare worker (HCW) population for potential exposures to patients with coronavirus disease 2019.

MATERIALS AND METHODS

We conducted a cross-sectional study at a free-standing, quaternary care pediatric hospital comparing first-degree, patient-HCW pairs identified by the hospital's COVID-19 contact tracing team (CTT) to those identified using EHR clinical event data (EHR Report). The primary outcome was the number of patient-HCW pairs detected by each process.

RESULTS

Among 233 patients with COVID-19, our EHR Report identified 4,116 patient-HCW pairs, including 2,365 (30.0%) of the 7,890 pairs detected by the CTT. The EHR Report also revealed 1,751 pairs not identified by the CTT. The highest number of patient-HCW pairs per patient was detected in the inpatient care venue. Nurses comprised the most frequently identified HCW role overall.

CONCLUSION

Automated methods to screen HCWs for potential exposure to patients with COVID-19 using clinical event data from the EHR are likely to improve epidemiologic surveillance by contact tracing programs and represent a viable and readily available strategy which should be considered by other institutions.