ABSTRACT
BackgroundTransmission chains within small urban areas (accommodating[~]30% of the European population) greatly contribute to case burden and economic impact during the ongoing COVID-19 pandemic, and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of SARS-CoV-2 transmission in a European urban area, Basel-City (Switzerland). Methodology. We combined detailed epidemiological, intra-city mobility, and socioeconomic data-sets with whole-genome-sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44% of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60% of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare-system burden (intensive-care-unit occupancy). Principal Findings. Transmissions were driven by socioeconomically weaker and highly mobile population groups with mostly cryptic transmissions, whereas amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90% transmission reduction, and 70-90% reduction of severe cases showed that prioritizing mobile, socioeconomically weaker populations for vaccination would effectively reduce case numbers. However, long-term intensive-care-unit occupation would also be effectively reduced if senior population groups were prioritized, provided there were no changes in testing and prevention strategies. Conclusions. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area. Author summaryWe examined SARS-CoV-2 transmission patterns within a European city (Basel, Switzerland) to infer drivers of the transmission during the first wave in spring 2020. The combination of diverse data (serological, genomic, transportation, socioeconomic) allowed us to combine phylogenetic analysis with mathematical modelling on related cases that were mapped to a residential address. As a result we could evaluate population groups driving SARS-CoV-2 transmission and quantify their effect on the transmission dynamics. We found traceable transmission chains in wealthier or more senior population groups and cryptic transmissions in the mobile, young or socioeconomic weaker population groups - these were identified as transmission drivers of the first wave. Based on this insight, we simulated vaccination scenarios for various vaccine efficacies to reflect different approaches undertaken to handle the epidemic. We conclude that vaccination of the mobile inherently younger population group would be most effective to handle following waves.
ABSTRACT
Introduction: SARS-CoV-2-detection is critical for clinical and epidemiological assessment of the ongoing CoVID-19 pandemic. Aim: To cross-validate manual and automated high-throughput (Roche-cobas6800-Target1/Target2) testing for SARS-CoV-2-RNA, to describe detection rates following lockdown and relaxation, and to evaluate SARS-CoV-2-loads in different specimens. Method: The validation cohort prospectively compared Basel-S-gene, Roche-E-gene, and Roche-cobas6800-Target1/Target2 in 1344 naso-oropharyngeal swabs (NOPS) taken in calendar week 13 using Basel-ORF8-gene-assay for confirmation. Follow-up-cohort-1 and -2 comprised 12363 and 10207 NOPS taken over 10 weeks until calendar week 24 and 34, respectively. SARS-CoV-2-loads were compared in follow-up NOPS, lower respiratory fluids, and plasma. Results: Concordant results were obtained in 1308 cases (97%) including 97 (9%) SARS-CoV-2-positives showing high quantitative correlations (Spearman r>0.95; p<0.001) for all assays. Discordant samples (N=36) had significantly lower SARS-CoV-2-loads (p<0.001). Following lockdown, weekly detection rates declined to <1% reducing single-test positive predictive values from 99.3% to 85.1%. Following relaxation, rates flared up to 4% with similarly high SARS-CoV-2-loads, but patients were significantly younger than during lockdown (34 vs 52 years, p<0.001). SARS-CoV-2-loads in follow-up NOPS declined by 3log10 copies/mL within 10 days post-diagnosis (p<0.001). SARS-CoV-2-loads in NOPS correlated weakly with those in time-matched lower respiratory fluids and plasma, but remained detectable in 14 and 7 cases of NOPS with undetectable SARS-CoV-2, respectively. Conclusion: Evaluated manual and automated assays are highly concordant and correlate quantitatively. Following successful lockdown, declining positive predictive values require dual-target-assays for clinical and epidemiologic assessment. Confirmatory and quantitative follow-up testing should be considered within <5 days, using lower respiratory fluids in symptomatic patients with SARS-CoV-2-negative NOPS.
ABSTRACT
BackgroundSARS-CoV-2 emerged in China in December 2019 as new cause of severe viral pneumonia (CoVID-19) reaching Europe by late January 2020. We validated the WHO-recommended assay and describe the epidemiology of SARS-CoV-2 and community-acquired respiratory viruses (CARVs). MethodsNaso-oropharyngeal swabs (NOPS) from 7663 individuals were prospectively tested by the Basel-S-gene and the WHO-based E-gene-assay (Roche) using Basel-N-gene-assay for confirmation. CARVs were tested in 2394 NOPS by multiplex-NAT, including 1816 together with SARS-CoV-2. ResultsBasel-S-gene and Roche-E-gene-assays were concordant in 7475 cases (97.5%) including 825 (11%) positive samples. In 188 (2.5%) discordant cases, SARS-CoV-2 loads were significantly lower than in concordant positive ones and confirmed in 105 NOPS. Adults were more likely to test positive for SARS-CoV-2, while children were more likely to test CARV-positive. CARV co-infections with SARS-CoV-2 occurred in 1.8%. SARS-CoV-2 replaced other CARVs within 3 weeks reaching 48% of all detected respiratory viruses followed by rhino/enterovirus (13%), influenzavirus (12%), coronavirus (9%), respiratory syncytial (6%) and metapneumovirus (6%). ConclusionsThe differential diagnosis for respiratory infections was broad during the early pandemic, affecting infection control and treatment decisions. We discuss the role of pre-existing immunity and competitive CARV replication for the epidemiology of SARS-CoV-2 infection among adults and children.
