A Contact Tracing Prospective Cohort Retrieving Epidemiological Facts on SARS-CoV-2 Transmission Aspects: A Serological Analysis in an Iranian Community

Abstract Introduction Novel coronavirus spread seems mysterious enough for convincing us to double check the indices being used to predict its transmission. Serological analysis was applied for assessing some metric epidemiological aspects of the infection and its transmissibility among people who were in contact with SARA-CoV-2 patients. Methods In this contact tracing prospective cohort study, 453 contact cases of forty COVID 19 patients were followed for three months. SARS-CoV-2 patients were diagnosed by real time polymerase chain reaction testing of nasopharyngeal samples. The history of infectiousness was detected by serological testing of IgG and IgM. Trained expert team completed two questionnaires and blood samples were taken by experts in laboratory. Data were analyzed using SPSS (Ver.21) and R software. Some important epidemiological characteristics of the infection were calculated. Results Mean age of SARS-CoV-2 patients and contact cases were 53.0±18.2 and 30.8±19.3 years, respectively. Overall R0 of the infection was 2.56. Household and non-household secondary attack rates (SAR) were 20% (95%CI; 12.7 – 27.3) and 11.3% (95%CI; 6.1-16.5), respectively. Transmission probability in each contact was 0.0205 and the serial interval was 6.4±4.6 (95% CI; 5.2–7.6) days. SAR among contact cases who exposed asymptomatic primary cases (28%, 95%CI; 10-46%) was higher than that (13.8%, 95%CI;9.4-18.2) among contact cases exposing to symptomatic patients. Conclusions We concluded a herd immunity between 60 and 65% is needed in human communities. Findings demonstrated how much reduction in infection R0 is predicted based on both clinical and public health interventions.

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Recent SARS-CoV-2 seroconversion in a national, community-based prospective cohort of U.S. adults

10.1101/2021.02.12.21251659 ◽

2021 ◽

Author(s):

Denis Nash ◽

Madhura Rane ◽

Mindy Chang ◽

Sarah Gorrell Kulkarni ◽

Rebecca Zimba ◽

...

Keyword(s):

Public Health ◽

Risk Factors ◽

Cohort Study ◽

Prospective Cohort ◽

Ethnic Disparities ◽

Contact Tracing ◽

Community Based ◽

Cross Sectional ◽

National Community ◽

Epidemiologic Risk

SHORT ABSTRACTEpidemiologic risk factors for incident SARS-CoV-2 infection are best characterized via prospective cohort studies, complementing case-based surveillance and cross-sectional seroprevalence studies. In March 2020, we launched the CHASING COVID Cohort Study, a national, community-based prospective cohort study of 6,745 U.S. adults who underwent at-home specimen collection for repeat serologic testing for SARS-CoV-2 antibodies. We identify and quantify several policy-sensitive risk factors for recent SARS-CoV-2 seroconversion, highlight persistent racial/ethnic disparities in incidence, document continued elevated risk among essential workers, and call attention to major gaps in the coverage of public health interventions aimed at testing, isolation, and contact tracing. We conclude that modifiable risk factors and poor reach of public health strategies drive SARS-CoV-2 transmission and inequities across the U.S.

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Effectiveness of BNT162b2 mRNA COVID-19 vaccine against SARS-CoV-2 variant Beta (B.1.351) among persons identified through contact tracing in Israel: A prospective cohort study

EClinicalMedicine ◽

10.1016/j.eclinm.2021.101190 ◽

2021 ◽

Vol 42 ◽

pp. 101190

Author(s):

Shepherd R. Singer ◽

Frederick J. Angulo ◽

David L. Swerdlow ◽

John M. McLaughlin ◽

Itay Hazan ◽

...

Keyword(s):

Cohort Study ◽

Prospective Cohort Study ◽

Prospective Cohort ◽

Contact Tracing

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Piloting an integrated SARS-CoV-2 testing and data system for outbreak containment among college students: A prospective cohort study

PLoS ONE ◽

10.1371/journal.pone.0245765 ◽

2021 ◽

Vol 16 (1) ◽

pp. e0245765

Author(s):

Laura Packel ◽

Arthur Reingold ◽

Lauren Hunter ◽

Shelley Facente ◽

Yi Li ◽

...

Keyword(s):

Cohort Study ◽

Prospective Cohort Study ◽

Prospective Cohort ◽

Relevant Information ◽

Data System ◽

Contact Tracing ◽

Effective Control ◽

Easy Access ◽

Multiple Data ◽

To Come

Background Colleges and universities across the country are struggling to develop strategies for effective control of COVID-19 transmission as students return to campus. Methods and findings We conducted a prospective cohort study with students living on or near the UC Berkeley campus from June 1st through August 18th, 2020 with the goal of providing guidance for campus reopening in the safest possible manner. In this cohort, we piloted an alternative testing model to provide access to low-barrier, high-touch testing and augment student-driven testing with data-driven adaptive surveillance that targets higher-risk students and triggers testing notifications based on reported symptoms, exposures, or other relevant information. A total of 2,180 students enrolled in the study, 51% of them undergraduates. Overall, 6,247 PCR tests were administered to 2,178 students over the two-month period. Overall test positivity rate was 0.9%; 2.6% of students tested positive. Uptake and acceptability of regular symptom and exposure surveys was high; 98% of students completed at least one survey, and average completion rate was 67% (Median: 74%, IQR: 39%) for daily reporting of symptoms and 68% (Median: 75%, IQR: 40%) for weekly reporting of exposures. Of symptom-triggered tests, 5% were PCR-positive; of exposure-triggered tests, 10% were PCR-positive. The integrated study database augmented traditional contact tracing during an outbreak; 17 potentially exposed students were contacted the following day and sent testing notifications. At study end, 81% of students selected their desire “to contribute to UC Berkeley’s response to COVID-19” as a reason for their participation in the Safe Campus study. Conclusions Our results illustrate the synergy created by bringing together a student-friendly, harm reduction approach to COVID-19 testing with an integrated data system and analytics. We recommend the use of a confidential, consequence-free, incentive-based daily symptom and exposure reporting system, coupled with low-barrier, easy access, no stigma testing. Testing should be implemented alongside a system that integrates multiple data sources to effectively trigger testing notifications to those at higher risk of infection and encourages students to come in for low-barrier testing when needed.

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