Contact Tracing: A Memory Task With Consequences for Public Health

Garry, Maryanne; Hope, Lorraine; Zajac, Rachel; Verrall, Ayesha; Robertson, Jamie

doi:10.1177/1745691620978205

Cited by 24 publications

(22 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Successful contact tracing is impacted by incomplete collection of information, specifically interviewees who provide imprecise information, omit critical interactions, or who are uncooperative. 35 The directional acyclic network graphs presented are consistent with transmission between individuals residing in multiple PCs in close proximity to each other. These tools could assist tracing investigations by focusing resources on the most likely locations where interactions between infected and uninfected persons occur.…”

Section: Discussionsupporting

confidence: 60%

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

Mucaki

Shirley

2021

F1000Res

View full text Add to dashboard Cite

Introduction: This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. Methods: COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area (FSA), and postal codes (PC) in municipal regions Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi*, Global Moran’s I spatial autocorrelation, and Local Moran’s I asymmetric clustering and outlier analyses. Case counts were also interpolated across geographic regions by Empirical Bayesian Kriging, which localizes high concentrations of COVID-19 positive tests, independent of FSA or PC boundaries. The Geostatistical Disease Epidemiology Toolbox, which is freely-available software, automates the identification of these regions and produces digital maps for public health professionals to assist in pandemic management of contact tracing and distribution of other resources. Results: This study provided indicators in real-time of likely, community-level disease transmission through innovative geospatial analyses of COVID-19 incidence data. Municipal and provincial results were validated by comparisons with known outbreaks at long-term care and other high density residences and on farms. PC-level analyses revealed hotspots at higher geospatial resolution than public reports of FSAs, and often sooner. Results of different tests and kriging were compared to determine consistency among hotspot assignments. Concurrent or consecutive hotspots in close proximity suggested potential community transmission of COVID-19 from cluster and outlier analysis of neighboring PCs and by kriging. Results were also stratified by population based-categories (sex, age, and presence/absence of comorbidities). Conclusions: Earlier recognition of hotspots could reduce public health burdens of COVID-19 and expedite contact tracing.

show abstract

Section: Discussionsupporting

confidence: 60%

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

Mucaki

Shirley

2021

F1000Res

View full text Add to dashboard Cite

show abstract

“…Contact tracing has been vital to identify potential sources of viral transmission from infected cases. Successful contact tracing is impacted by incomplete collection of information, specifically interviewees who provide imprecise information, omit critical interactions, or who are uncooperative 35 . The directional acyclic network graphs presented are consistent with transmission between individuals residing in multiple PCs in close proximity to each other.…”

Section: Discussionmentioning

confidence: 99%

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

Mucaki

Shirley

2021

Preprint

View full text Add to dashboard Cite

Introduction. This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario, Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. Methods. COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area [FSA], and postal codes [PC] in municipal regions covering Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi*, Global Moran's I spatial autocorrelation, and Local Moran's I asymmetric clustering and outlier analyses. Case counts were also interpolated across geographic regions by Empirical Bayesian Kriging, which localizes high concentrations of COVID-19 positive tests, independent of FSA or PC boundaries. The Geostatistical Disease Epidemiology Toolbox, which is freely-available software, automates the identification of these regions and produces digital maps for public health professionals to assist in pandemic management of contact tracing and distribution of other resources. Results/Discussion. This study provided indicators in real-time of likely, community-level disease transmission through innovative geospatial analyses of COVID-19 incidence data. Municipal and provincial results were validated by comparisons with known outbreaks at long-term care and other high density residences and on farms. PC-level analyses revealed hotspots at higher geospatial resolution than public reports of FSAs, and often sooner. Results of different tests and kriging were compared to determine consistency among hotspot assignments. Concurrent or consecutive hotspots in close proximity suggested potential community transmission of COVID-19 from cluster and outlier analysis of neighboring PCs and by kriging. Results were also stratified by population based-categories (sex, age, and presence/absence of comorbidities). Earlier recognition of hotspots could reduce public health burdens of COVID-19 and expedite contact tracing.

show abstract

“…The patients with a positive COVID-19 test who had no indication for hospitalization were released into the society and their contacts could not be traced. Studies have shown that among the few weapons for ghting COVID-19, contact tracing can be the most powerful case (33). Since the physicians and nurses used to practice according to protocols, in the absence of a speci c treatment protocol for COVID-19, they were subjected to moral injury because they did not exactly know, for instance, at what blood oxygen level the patient would require intubation.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Policy Responses to COVID-19: A Qualitative Study in Northern Iran

Farhadi

Salemi

Jahani

2021

Preprint

View full text Add to dashboard Cite

Background Preparation and financing of treatments, control of disease by limited resources, capacity building for the research and development related to the spread of disease, and measures to prevent and control the infection are known as the most important challenges encountered by the policy-makers involved in an epidemic outbreak. Therefore, the present study was conducted to analyze the policy responses of Babol University of Medical Sciences (BUMS) to Coronavirus (COVID-19). Methods For this purpose, a qualitative study was performed to investigate the policy responses of BUMS to COVID-19 in Babol (northern Iran) from the beginning of January to the end of March, 2021. The statistical population included the experts, pundits, policy-makers and planners involved in four areas of management, treatment, healthcare, and health donation. Data collection was done according to interviews and policy documents, and the obtained data were analyzed based on the Walt and Gilson’s policy triangle framework. Results Interviews and policy documents were determined after several stages of review according to the Walt and Gilson’s policy triangle framework, and the main themes were determined as: policy context, policy analysis, policy-making process, actors and stakeholders, and ways to deal with COVID-19 outbreak. Each theme was divided into 18 sub-themes. Finally, the related topics were extracted from the sub-themes. Conclusions Considering the large number of patients waiting for treatment, most of the decisions and policies were directed to their treatment, and the subject of prevention was at the second priority of policy making. Moreover, there was no practical program or policy for tracking the asymptomatic carriers in the community.

show abstract

Contact Tracing: A Memory Task With Consequences for Public Health

Cited by 24 publications

References 79 publications

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

Analysis of Policy Responses to COVID-19: A Qualitative Study in Northern Iran

Contact Info

Product

Resources

About