The impact of delayed COVID-19 contact tracking on health outcomes
The impact of delayed COVID-19 contact tracking on health outcomes

The impact of delayed COVID-19 contact tracking on health outcomes

In a recent study posted to medRxiv* preprint server researchers evaluated the effect of a delay in tracking contacts with coronavirus disease 2019 (COVID-19) on health outcomes of transmissions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), hospitalizations and deaths in the UK.

Examination: Evaluation of the impact on health outcome of an incident that resulted in a delay in contact tracking of COVID-19 cases. Image credit: bob boz / Shutterstock

Contact detection has been crucial in assessing the general population’s health responses to SARS-CoV-2 and involves identifying contacts to SARS-CoV-2-positive individuals and advising on self-isolation to reduce SARS-CoV-2 transmission.

In September 2020, it failed to upload 15,861 COVID-19 cases of the second generation laboratory monitoring system (SGSS) to the CTAS (Contact Tracing Advisory Service) data tool and subsequently delayed the tracking of COVID-19 case contacts.

SGSS records contain demographic and diagnostic information from laboratory test reports for patients who tested positive for SARS-CoV-2, whereas CTAS records represent SARS-CoV-2 case episodes, including information on movements of cases during their infectious period, their contacts, and demographic and clinical characteristics.

About the study

In this observational study, researchers from the UK Health Security Agency, the University of Bristol and the University of Cambridge evaluated the effect of delay in contact tracking of COVID-19 cases on SARS-CoV-2 transmission and hospitalizations and deaths in the UK.

The UK Health Security Agency (UKHSA) provided the SGSS records, which were matched with the CTAS records to validate the cases affected by the event, and successive contacts and cases were identified. The study used CTAS data from SARS-CoV-2-positive individuals and their contacts for the analysis.

Matching was performed in multiple rounds based on combinations of identifiers such as the National Health Service (NHS) number. SGSS unique identifier, date of birth (DOB). first name, last name and postcode.

The CTAS dataset included the primary cases affected by the incident and these cases have been referred to as the ‘delay group’, whereas the primary cases belonging to the same time frame (between 30 September and 5 October 2020) were not affected by the incident included the ‘control group.

Graphs describing the time it takes to start and complete contact tracking of cases and contacts in the delay and control groups

Graphs describing the time it takes to start and complete contact tracking of cases and contacts in the delay and control groups

Secondary cases were described as the persons who reported contact with a primary case subject and persons who had contact with a primary case between day 2 and day 14 after the onset of symptoms or the test date among the secondary case subjects.

In addition, the contact datasets were linked to the UKHSA hospital debut COVID-19 dataset, which was extracted on 22 November 2021 and retrieves daily data from two national datasets, namely the Secondary Uses Services (SUS) dataset and the Emergency Care Data. Set (ECDS), which describes patient admissions and the use of emergency services, respectively.

The primary outcome measures included secondary rates of attack (SARs), hospitalizations, and deaths among primary contacts and secondary contacts compared with concomitant and unaffected cases.

Results

A total of 15,861 SGSS records were detected as affected by the incident, of which 98% (15,467) matched the CTAS records. Following data recovery, 96% (15,285) of primary cases affected by the delay were eligible for analysis. The control group included 43,742 simultaneous primary contact cases, including all CTAS records within the aforementioned time frame unaffected by the incident.

Initiation of contact tracking was delayed by three days in the primary contact cases among the delay group compared to controls, associated with the incomplete tracking of contacts of primary cases among the delay group individuals (80%) and controls (83%).

The delay increased viral transmission to non-household contacts. The SARs among non-household contacts were higher among the secondary contacts (7.9%) in the delay group compared to the controls (5.9%). Among secondary contacts, there were no statistically significant differences between the delay group individuals and controls with respect to hospitalization (crude odds ratio 1) and death (crude odds ratio 0.7).

Overall, the study results revealed that the delay in tracking contacts for the COVID-19 cases marginally affected their health.

*Important message

medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered essential, guide clinical practice / health-related behavior or be treated as established information.

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