Coronavirus disease (COVID-19)

Scarce European data in early 2021 suggested lower vaccine effectiveness (VE) against SARS-CoV-2 Omicron lineages than previous variants.

We aimed to estimate primary series (PS) and first booster VE against symptomatic BA.1/BA.2 infection and investigate potential biases.

This European test-negative multicentre study tested primary care patients with acute respiratory symptoms for SARS-CoV-2 in the BA.1/BA.2-dominant period. We estimated PS and booster VE among adults and adolescents (PS only) for all products combined and for Comirnaty alone, by time since vaccination, age and chronic condition. We investigated potential bias due to correlation between COVID-19 and influenza vaccination and explored effect modification and confounding by prior SARS-CoV-2 infection.

Among adults, PS VE was 37% (95% CI: 24–47%) overall and 60% (95% CI: 44–72%), 43% (95% CI: 26–55%) and 29% (95% CI: 13–43%) < 90, 90–179 and ≥ 180 days post vaccination, respectively. Booster VE was 42% (95% CI: 32–51%) overall and 56% (95% CI: 47–64%), 22% (95% CI: 2–38%) and 3% (95% CI: −78% to 48%), respectively. Primary series VE was similar among adolescents. Restricting analyses to Comirnaty had little impact. Vaccine effectiveness was higher among older adults. There was no signal of bias due to correlation between COVID-19 and influenza vaccination. Confounding by previous infection was low, but sample size precluded definite assessment of effect modification.

Primary series and booster VE against symptomatic infection with BA.1/BA.2 ranged from 37% to 42%, with similar waning post vaccination. Comprehensive data on previous SARS-CoV-2 infection would help disentangle vaccine- and infection-induced immunity.

Model projections of coronavirus disease 2019 (COVID-19) incidence help policymakers about decisions to implement or lift control measures. During the pandemic, policymakers in the Netherlands were informed on a weekly basis with short-term projections of COVID-19 intensive care unit (ICU) admissions.

We aimed at developing a model on ICU admissions and updating a procedure for informing policymakers.

The projections were produced using an age-structured transmission model. A consistent, incremental update procedure integrating all new surveillance and hospital data was conducted weekly. First, up-to-date estimates for most parameter values were obtained through re-analysis of all data sources. Then, estimates were made for changes in the age-specific contact rates in response to policy changes. Finally, a piecewise constant transmission rate was estimated by fitting the model to reported daily ICU admissions, with a changepoint analysis guided by Akaike's Information Criterion.

The model and update procedure allowed us to make weekly projections. Most 3-week prediction intervals were accurate in covering the later observed numbers of ICU admissions. When projections were too high in March and August 2020 or too low in November 2020, the estimated effectiveness of the policy changes was adequately adapted in the changepoint analysis based on the natural accumulation of incoming data.

The model incorporates basic epidemiological principles and most model parameters were estimated per data source. Therefore, it had potential to be adapted to a more complex epidemiological situation with the rise of new variants and the start of vaccination.

Wastewater surveillance has expanded globally as a means to monitor spread of infectious diseases. An inherent challenge is substantial noise and bias in wastewater data because of the sampling and quantification process, limiting the applicability of wastewater surveillance as a monitoring tool.

To present an analytical framework for capturing the growth trend of circulating infections from wastewater data and conducting scenario analyses to guide policy decisions.

We developed a mathematical model for translating the observed SARS-CoV-2 viral load in wastewater into effective reproduction numbers. We used an extended Kalman filter to infer underlying transmissions by smoothing out observational noise. We also illustrated the impact of different countermeasures such as expanded vaccinations and non-pharmaceutical interventions on the projected number of cases using three study areas in Japan during 2021–22 as an example.

Observed notified cases were matched with the range of cases estimated by our approach with wastewater data only, across different study areas and virus quantification methods, especially when the disease prevalence was high. Estimated reproduction numbers derived from wastewater data were consistent with notification-based reproduction numbers. Our projections showed that a 10–20% increase in vaccination coverage or a 10% reduction in contact rate may suffice to initiate a declining trend in study areas.

Our study demonstrates how wastewater data can be used to track reproduction numbers and perform scenario modelling to inform policy decisions. The proposed framework complements conventional clinical surveillance, especially when reliable and timely epidemiological data are not available.

The COVID-19 pandemic resulted in adaptation in infection control measures, increased patient transfer, high occupancy of intensive cares, downscaling of non-urgent medical procedures and decreased travelling.

To gain insight in the influence of these changes on antimicrobial resistance (AMR) prevalence in the Netherlands, a country with a low AMR prevalence, we estimated changes in demographics and prevalence of six highly resistant microorganisms (HRMO) in hospitalised patients in the Netherlands during COVID-19 waves (March–June 2020, October 2020–June 2021, October 2021–May 2022 and June–August 2022) and interwaves (July–September 2020 and July–September 2021) compared with pre-COVID-19 (March 2019–February 2020).

We investigated data on routine bacteriology cultures of hospitalised patients, obtained from 37 clinical microbiological laboratories participating in the national AMR surveillance. Demographic characteristics and HRMO prevalence were calculated as proportions and rates per 10,000 hospital admissions.

Although no significant persistent changes in HRMO prevalence were detected, some relevant non-significant patterns were recognised in intensive care units. Compared with pre-COVID-19 we found a tendency towards higher prevalence of meticillin-resistant Staphylococcus aureus during waves and lower prevalence of multidrug-resistant Pseudomonas aeruginosa during interwaves. Additionally, during the first three waves, we observed significantly higher proportions and rates of cultures with Enterococcus faecium (pooled 10% vs 6% and 240 vs 120 per 10,000 admissions) and coagulase-negative Staphylococci (pooled 21% vs 14% and 500 vs 252 per 10,000 admissions) compared with pre-COVID-19.

We observed no substantial changes in HRMO prevalence in hospitalised patients during the COVID-19 pandemic.

The I-MOVE-COVID-19 and VEBIS hospital networks have been measuring COVID-19 vaccine effectiveness (VE) in participating European countries since early 2021.

We aimed to measure VE against PCR-confirmed SARS-CoV-2 in patients ≥ 20 years hospitalised with severe acute respiratory infection (SARI) from December 2021 to July 2022 (Omicron-dominant period).

In both networks, 46 hospitals (13 countries) follow a similar test-negative case–control protocol. We defined complete primary series vaccination (PSV) and first booster dose vaccination as last dose of either vaccine received ≥ 14 days before symptom onset (stratifying first booster into received < 150 and ≥ 150 days after last PSV dose). We measured VE overall, by vaccine category/product, age group and time since first mRNA booster dose, adjusting by site as a fixed effect, and by swab date, age, sex, and presence/absence of at least one commonly collected chronic condition.

We included 2,779 cases and 2,362 controls. The VE of all vaccine products combined against hospitalisation for laboratory-confirmed SARS-CoV-2 was 43% (95% CI: 29–54) for complete PSV (with last dose received ≥ 150 days before onset), while it was 59% (95% CI: 51–66) after addition of one booster dose. The VE was 85% (95% CI: 78–89), 70% (95% CI: 61–77) and 36% (95% CI: 17–51) for those with onset 14–59 days, 60–119 days and 120–179 days after booster vaccination, respectively.

Our results suggest that, during the Omicron period, observed VE against SARI hospitalisation improved with first mRNA booster dose, particularly for those having symptom onset < 120 days after first booster dose.

The earliest recognised infections by the SARS-CoV-2 Omicron variant (Pango lineage B.1.1.529) in Belgium and Switzerland suggested a connection to an international water polo tournament, held 12–14 November 2021 in Brno, Czechia.

To study the arrival and subsequent spread of the Omicron variant in Belgium and Switzerland, and understand the overall importance of this international sporting event on the number of infections in the two countries.

We performed intensive forward and backward contact tracing in both countries, supplemented by phylogenetic investigations using virus sequences of the suspected infection chain archived in public databases.

Through contact tracing, we identified two and one infected athletes of the Belgian and Swiss water polo teams, respectively, and subsequently also three athletes from Germany. In Belgium and Switzerland, four and three secondary infections, and three and one confirmed tertiary infections were identified. Phylogenetic investigation demonstrated that this sporting event played a role as the source of infection, but without a direct link with infections from South Africa and not as a superspreading event; the virus was found to already be circulating at that time in the countries involved.

The SARS-CoV-2 Omicron variant started to circulate in Europe several weeks before its identification in South Africa on 24 November 2021. Accordingly, it can be assumed that travel restrictions are usually implemented too late to prevent the spread of newly detected SARS-CoV-2 variants to other regions. Phylogenetic analysis may modify the perception of an apparently clear result of intensive contact tracing.

Unprecedented non-pharmaceutical interventions to control the COVID-19 pandemic also had an effect on other infectious diseases.

We aimed to determine their impact on transmission and diagnosis of notifiable diseases other than COVID-19 in Bavaria, Germany, in 2020 and 2021.

We compared weekly cases of 15 notifiable infectious diseases recorded in Bavaria between 1 January 2016 and 31 December 2021 in time series analyses, median age and time-to-diagnosis using Wilcoxon rank sum test and hospitalisation rates using univariable logistic regression during three time periods: pre-pandemic (weeks 1 2016–9 2020), pandemic years 1 (weeks 10–52 2020) and 2 (2021).

Weekly case numbers decreased in pandemic year 1 for all diseases assessed except influenza, Lyme disease and tick-borne encephalitis; markedly for norovirus gastroenteritis (IRR = 0.15; 95% CI: 0.12–0.20) and pertussis (IRR = 0.22; 95% CI: 0.18–0.26). In pandemic year 2, influenza (IRR = 0.04; 95% CI: 0.02–0.09) and pertussis (IRR = 0.11; 95% CI: 0.09–0.14) decreased markedly, but also chickenpox, dengue fever, Haemophilus influenzae invasive infection, hepatitis C, legionellosis, noro- and rotavirus gastroenteritis and salmonellosis. For enterohaemorrhagic Escherichia coli infections, median age decreased in pandemic years 1 and 2 (4 years, interquartile range (IQR): 1–32 and 3 years, IQR: 1–18 vs 11 years, IQR: 2–42); hospitalisation proportions increased in pandemic year 1 (OR = 1.60; 95% CI: 1.08–2.34).

Reductions for various infectious diseases and changes in case characteristics in 2020 and 2021 indicate reduced transmission of notifiable diseases other than COVID-19 due to interventions and under-detection.