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. 2023 Oct 20;18(10):e0292346.
doi: 10.1371/journal.pone.0292346. eCollection 2023.

Key performance indicators of COVID-19 contact tracing in Belgium from September 2020 to December 2021

Cécile Kremer  1 , Lander Willem  2   3 , Jorden Boone  4 , Wouter Arrazola de Oñate  5   6 , Naïma Hammami  7 , Christel Faes  1 , Niel Hens  1   2
Affiliations

Key performance indicators of COVID-19 contact tracing in Belgium from September 2020 to December 2021

Cécile Kremer et al. PLoS One. .

Abstract

The goal of tracing, testing, and quarantining contacts of infected individuals is to contain the spread of infectious diseases, a strategy widely used during the COVID-19 pandemic. However, limited research exists on the effectiveness of contact tracing, especially with regard to key performance indicators (KPIs), such as the proportion of cases arising from previously identified contacts. In our study, we analyzed contact tracing data from Belgium collected between September 2020 and December 2021 to assess the impact of contact tracing on SARS-CoV-2 transmission and understand its characteristics. Among confirmed cases involved in contact tracing in the Flemish and Brussels-Capital regions, 19.1% were previously identified as close contacts and were aware of prior exposure. These cases, referred to as 'known' to contact tracing operators, reported on average fewer close contacts compared to newly identified individuals (0.80 versus 1.05), resulting in fewer secondary cases (0.23 versus 0.28). Additionally, we calculated the secondary attack rate, representing infections per contact, which was on average lower for the 'known' cases (0.22 versus 0.25) between December 2020 and August 2021. These findings indicate the effectiveness of contact tracing in Belgium in reducing SARS-CoV-2 transmission. Although we were unable to quantify the exact number of prevented cases, our findings emphasize the importance of contact tracing as a public health measure. In addition, contact tracing data provide indications of potential shifts in transmission patterns among different age groups associated with emerging variants of concern and increasing vaccination rates.

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Conflict of interest statement

Naima Hammami is an employee of the the Flemish Government’s Department of Care and Jorden Boone has been working as a consultant for this agency during the COVID-19 pandemic. Niel Hens declares that the Universities of Antwerp and Hasselt have received funding for advisory boards and research projects of MSD, GSK, JnJ, Pfizer outside the proposed work. Niel Hens has not received any personal remuneration related to this work. The other authors declare that they have no competing interests. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Evolution of key performance indicators.
Evolution in the (a) proportion of index cases that were previously identified as a risk contact, (b) average number of traced high-risk contacts (HRC) for ‘new’ and ‘known’ index cases, (c) average number of secondary cases for ‘new’ and ‘known’ index cases, and (d) secondary attack rate (SAR) among traced HRC of ‘new’ and ‘known’ index cases. Vertical bars represent the 95% confidence interval.
Fig 2
Fig 2. Delay distributions.
Delay distributions for the time between index symptom onset and test collection (black), between index symptom onset and test result (red), and between positive test index and the call from the tracing center (green).
Fig 3
Fig 3. Contact and transmission patterns.
Age-specific contact (left) and transmission (right) matrix for December 2020, April 2021 (i.e. Alpha VOC), July 2021 (i.e. Delta VOC), and December 2021 (i.e. Omicron VOC).
Fig 4
Fig 4. Serial interval.
Monthly moving average empirical serial interval (in days; 116,453 transmission pairs included; 15,190 transmission pairs with ‘known’ index and 101,263 with ‘new’ index included).
See this image and copyright information in PMC

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