Unravelling the effect of New Year's Eve celebrations on SARS-CoV-2 transmission.

Public holidays have been associated with SARS-CoV-2 incidence surges, although a firm link remains to be established. This association is sometimes attributed to events where transmissions occur at a disproportionately high rate, known as superspreading events. Here, we describe a sudden surge in new cases with the Omicron BA.1 strain amongst higher education students in Belgium. Contact tracers classed most of these cases as likely or possibly infected on New Year's Eve, indicating a direct trigger by New Year celebrations. Using a combination of contact tracing and phylogenetic data, we show the limited role of superspreading events in this surge. Finally, the numerous simultaneous transmissions allowed a unique opportunity to determine the distribution of incubation periods of the Omicron strain. Overall, our results indicate that, even under social restrictions, a surge in transmissibility of SARS-CoV-2 can occur when holiday celebrations result in small social gatherings attended simultaneously and communitywide.

Individual level analysis of digital proximity tracing for COVID-19 in Belgium highlights major bottlenecks.

To complement labour-intensive conventional contact tracing, digital proximity tracing was implemented widely during the COVID-19 pandemic. However, the privacy-centred design of the dominant Google-Apple exposure notification framework has hindered assessment of its effectiveness. Between October 2021 and January 2022, we systematically collected app use and notification receipt data within a test and trace programme targeting around 50,000 university students in Leuven, Belgium. Due to low success rates in each studied step of the digital notification cascade, only 4.3% of exposed contacts (CI: 2.8-6.1%) received such notifications, resulting in 10 times more cases detected through conventional contact tracing. Moreover, the infection risk of digitally traced contacts (5.0%; CI: 3.0-7.7%) was lower than that of conventionally traced non-app users (9.8%; CI: 8.8-10.7%; p = 0.002). Contrary to common perception as near instantaneous, there was a 1.2-day delay (CI: 0.6-2.2) between case PCR result and digital contact notification. These results highlight major limitations of a digital proximity tracing system based on the dominant framework.

Indoor air surveillance and factors associated with respiratory pathogen detection in community settings in Belgium.

Currently, the real-life impact of indoor climate, human behaviour, ventilation and air filtration on respiratory pathogen detection and concentration are poorly understood. This hinders the interpretability of bioaerosol quantification in indoor air to surveil respiratory pathogens and transmission risk. We tested 341 indoor air samples from 21 community settings in Belgium for 29 respiratory pathogens using qPCR. On average, 3.9 pathogens were positive per sample and 85.3% of samples tested positive for at least one. Pathogen detection and concentration varied significantly by pathogen, month, and age group in generalised linear (mixed) models and generalised estimating equations. High CO2 and low natural ventilation were independent risk factors for detection. The odds ratio for detection was 1.09 (95% CI 1.03-1.15) per 100 parts per million (ppm) increase in CO2, and 0.88 (95% CI 0.80-0.97) per stepwise increase in natural ventilation (on a Likert scale). CO2 concentration and portable air filtration were independently associated with pathogen concentration. Each 100ppm increase in CO2 was associated with a qPCR Ct value decrease of 0.08 (95% CI -0.12 to -0.04), and portable air filtration with a 0.58 (95% CI 0.25-0.91) increase. The effects of occupancy, sampling duration, mask wearing, vocalisation, temperature, humidity and mechanical ventilation were not significant. Our results support the importance of ventilation and air filtration to reduce transmission.

Monitoring of SARS-CoV-2 concentration and circulation of variants of concern in wastewater of Leuven, Belgium.

Wastewater surveillance plays an important role in the management of the coronavirus disease 2019 (COVID-19) pandemic all over the world. Using different wastewater collection points in Leuven, we wanted to investigate the use of wastewater surveillance as an early warning system for an uprise of infections and as a tool to follow the circulation of specific variants of concern (VOCs) in particular geographic areas. Wastewater samples were collected from local neighborhood sewers and from a large regional wastewater treatment plant (WWTP) in the area of Leuven, Belgium. After virus concentration, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was quantified by real-time quantitative polymerase chain reaction (RT-qPCR) and normalized with the human fecal indicator pepper mild mottle virus (PMMoV). A combination of multiplex RT-qPCR assays was used to detect signature mutations of circulating VOCs. Fecal virus shedding of SARS-CoV-2 variants was measured in feces samples of hospitalized patients. In two residential sampling sites, a rise in wastewater SARS-CoV-2 concentration preceded peaks in positive cases. In the WWTP, viral load peaks were seen concomitant with the consecutive waves of positive cases caused by the original Wuhan SARS-CoV-2 strain and subsequent VOCs. During the Omicron BA.1 wave, the wastewater viral load increased to a lesser degree, even after normalization of SARS-CoV-2 concentration using PMMoV. This might be attributable to a lower level of fecal excretion of this variant. Circulation of SARS-CoV-2 VOCs Alpha, Delta, Omicron BA1/BA.2, and BA.4/BA.5 could be detected based on the presence of specific key mutations. The shift in variants was noticeable in the wastewater, with key mutations of two different variants being present simultaneously during the transition period. Wastewater-based surveillance is a sensitive tool to monitor SARS-CoV-2 circulation levels and VOCs in larger regions. In times of reduced test capacity, this can prove to be highly valuable. Differences in excretion levels of various SARS-CoV-2 variants should however be taken into account when using wastewater surveillance to monitor SARS-CoV-2 circulation levels in the population.

Risk factors for SARS-CoV-2 transmission in student residences: a case-ascertained study.

BACKGROUND: We aimed to investigate the overall secondary attack rates (SAR) of COVID-19 in student residences and to identify risk factors for higher transmission. METHODS: We retrospectively analysed the SAR in living units of student residences which were screened in Leuven (Belgium) following the detection of a COVID-19 case. Students were followed up in the framework of a routine testing and tracing follow-up system. We considered residence outbreaks followed up between October 30th 2020 and May 25th 2021. We used generalized estimating equations (GEE) to evaluate the impact of delay to follow-up, shared kitchen or sanitary facilities, the presence of a known external infection source and the recent occurrence of a social gathering. We used a generalized linear mixed model (GLMM) for validation. RESULTS: We included 165 student residences, representing 200 residence units (N screened residents = 2324). Secondary transmission occurred in 68 units which corresponded to 176 secondary cases. The overall observed SAR was 8.2%. In the GEE model, shared sanitary facilities (p = 0.04) and the recent occurrence of a social gathering (p = 0.003) were associated with a significant increase in SAR in a living unit, which was estimated at 3% (95%CI 1.5-5.2) in the absence of any risk factor and 13% (95%CI 11.4-15.8) in the presence of both. The GLMM confirmed these findings. CONCLUSIONS: Shared sanitary facilities and the occurrence of social gatherings increase the risk of COVID-19 transmission and should be considered when screening and implementing preventive measures.

Empirical evidence on the efficiency of backward contact tracing in COVID-19.

Standard contact tracing practice for COVID-19 is to identify persons exposed to an infected person during the contagious period, assumed to start two days before symptom onset or diagnosis. In the first large cohort study on backward contact tracing for COVID-19, we extended the contact tracing window by 5 days, aiming to identify the source of the infection and persons infected by the same source. The risk of infection amongst these additional contacts was similar to contacts exposed during the standard tracing window and significantly higher than symptomatic individuals in a control group, leading to 42% more cases identified as direct contacts of an index case. Compared to standard practice, backward traced contacts required fewer tests and shorter quarantine. However, they were identified later in their infectious cycle if infected. Our results support implementing backward contact tracing when rigorous suppression of viral transmission is warranted.