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Risk stratification as a tool to rationalize quarantine among health care workers exposed to COVID-19 cases – Evidence from a tertiary healthcare centre in India
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Abstract
Background
Quarantine of healthcare workers (HCWs) exposed to COVID -19 confirmed cases is a well-known strategy for limiting the transmission of infection. However, there is need of evidence-based guidelines for quarantine of HCWs in COVID -19.
Methods
We describe our experience of contact tracing and risk stratification of 3853 HCWs who were exposed to confirmed COVID-19 cases in a tertiary health care institution in India. We developed an algorithm, on the basis of risk stratification, to rationalize quarantine among HCWs. Risk stratification was based on the duration of exposure, distance from the patient, and appropriateness of personal protection equipment (PPE) usage. Only high-risk contacts were quarantined for 14 days. They underwent testing for COVID-19 after five days of exposure, while low-risk contacts continued their work with adherence to physical distancing, hand hygiene, and appropriate use of PPE. The low-risk contacts were encouraged to monitor for symptoms and report for COVID-19 screening if fever, cough, or shortness of breath occurred. We followed up all contacts for 14 days from the last exposure and observed for symptoms of COVID-19 and test positivity.
Results and interpretation
Out of total 3853 contacts, 560 (14.5%) were categorized as high-risk contacts, and 40 of them were detected positive for COVID-19, with a test positivity rate of 7.1% (95% CI = 5.2 – 9.6). Overall, 118 (3.1%) of all contacts tested positive. Our strategy prevented 3215 HCWs from being quarantined and saved 45,010 person-days of health workforce until June 8, 2020, in the institution.
We conclude that exposure-based risk stratification and quarantine of HCWs is a viable strategy to prevent unnecessary quarantine, in a healthcare institution.
Summary
What is already known about this subject?
Quarantine of HCWs is a well-known strategy for community and HCWs to prevent the transmission of COVID-19.
Though success stories of prompt contact tracing and quarantine to control COVID-19 are available from countries like South Korea, Singapore, and Hong Kong, there is a scarcity of evidence that could guide targeted quarantine of HCWs exposed to COVID -19 in India.
What does this study add?
Only 14.5% HCWs exposed to COVID-19 cases were stratified “high risk” contacts, and the most common reason for high-risk contacts was non-formal workplace interactions such as having meals together.
The overall test positivity rate among the high-risk contacts was 7.1%, while it was higher in symptomatic high-risk contacts as compared to those who were asymptomatic (10.2% vs. 6.3%).
How might this impact on clinical practice?
Contact tracing and risk stratification can be used to minimize unnecessary quarantine of COVID-19 exposed health care workers and prevent the depletion of healthcare workers amidst the pandemic to continue the healthcare services optimally.
Title: Risk stratification as a tool to rationalize quarantine among health care workers exposed to COVID-19 cases – Evidence from a tertiary healthcare centre in India
Description:
Abstract
Background
Quarantine of healthcare workers (HCWs) exposed to COVID -19 confirmed cases is a well-known strategy for limiting the transmission of infection.
However, there is need of evidence-based guidelines for quarantine of HCWs in COVID -19.
Methods
We describe our experience of contact tracing and risk stratification of 3853 HCWs who were exposed to confirmed COVID-19 cases in a tertiary health care institution in India.
We developed an algorithm, on the basis of risk stratification, to rationalize quarantine among HCWs.
Risk stratification was based on the duration of exposure, distance from the patient, and appropriateness of personal protection equipment (PPE) usage.
Only high-risk contacts were quarantined for 14 days.
They underwent testing for COVID-19 after five days of exposure, while low-risk contacts continued their work with adherence to physical distancing, hand hygiene, and appropriate use of PPE.
The low-risk contacts were encouraged to monitor for symptoms and report for COVID-19 screening if fever, cough, or shortness of breath occurred.
We followed up all contacts for 14 days from the last exposure and observed for symptoms of COVID-19 and test positivity.
Results and interpretation
Out of total 3853 contacts, 560 (14.
5%) were categorized as high-risk contacts, and 40 of them were detected positive for COVID-19, with a test positivity rate of 7.
1% (95% CI = 5.
2 – 9.
6).
Overall, 118 (3.
1%) of all contacts tested positive.
Our strategy prevented 3215 HCWs from being quarantined and saved 45,010 person-days of health workforce until June 8, 2020, in the institution.
We conclude that exposure-based risk stratification and quarantine of HCWs is a viable strategy to prevent unnecessary quarantine, in a healthcare institution.
Summary
What is already known about this subject?
Quarantine of HCWs is a well-known strategy for community and HCWs to prevent the transmission of COVID-19.
Though success stories of prompt contact tracing and quarantine to control COVID-19 are available from countries like South Korea, Singapore, and Hong Kong, there is a scarcity of evidence that could guide targeted quarantine of HCWs exposed to COVID -19 in India.
What does this study add?
Only 14.
5% HCWs exposed to COVID-19 cases were stratified “high risk” contacts, and the most common reason for high-risk contacts was non-formal workplace interactions such as having meals together.
The overall test positivity rate among the high-risk contacts was 7.
1%, while it was higher in symptomatic high-risk contacts as compared to those who were asymptomatic (10.
2% vs.
6.
3%).
How might this impact on clinical practice?
Contact tracing and risk stratification can be used to minimize unnecessary quarantine of COVID-19 exposed health care workers and prevent the depletion of healthcare workers amidst the pandemic to continue the healthcare services optimally.
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