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Euro Surveill ; 26(43)2021 10.
Article in English | MEDLINE | ID: covidwho-1547185


BackgroundIn the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.AimWe applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.MethodsWe investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.ResultsWe identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.ConclusionsEarly spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.

COVID-19 , Cross Infection , Cross Infection/epidemiology , Genome, Viral , Genomics , Germany/epidemiology , Hospitals , Humans , Phylogeny , SARS-CoV-2
Clin Infect Dis ; 73(9): e3055-e3065, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1501051


BACKGROUND: High infection rates among healthcare personnel in an uncontained pandemic can paralyze health systems due to staff shortages. Risk constellations and rates of seroconversion for healthcare workers (HCWs) during the first wave of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic are still largely unclear. METHODS: Healthcare personnel (n = 300) on different organizational units in the LMU Munich University Hospital were included and followed in this prospective longitudinal study from 24 March until 7 July 2020. Participants were monitored in intervals of 2 to 6 weeks using different antibody assays for serological testing and questionnaires to evaluate risk contacts. In a subgroup of infected participants, we obtained nasopharyngeal swabs to perform whole-genome sequencing for outbreak characterization. RESULTS: HCWs involved in patient care on dedicated coronavirus disease 2019 (COVID-19) wards or on regular non-COVID-19 wards showed a higher rate of SARS-CoV-2 seroconversion than staff in the emergency department and non-frontline personnel. The landscape of risk contacts in these units was dynamic, with a decrease in unprotected risk contacts in the emergency department and an increase on non-COVID-19 wards. Both intensity and number of risk contacts were associated with higher rates of seroconversion. On regular wards, staff infections tended to occur in clusters, while infections on COVID-19 wards were less frequent and apparently independent of each other. CONCLUSIONS: Risk of SARS-CoV-2 infection for frontline HCWs was increased during the first pandemic wave in southern Germany. Stringent measures for infection control are essential to protect all patient-facing staff during the ongoing pandemic.

COVID-19 , SARS-CoV-2 , Germany/epidemiology , Health Personnel , Hospitals, University , Humans , Longitudinal Studies , Pandemics , Prospective Studies
Gesundheitswesen ; 83(8-09): 581-592, 2021 Sep.
Article in German | MEDLINE | ID: covidwho-1397930


AIM: The aim of this review is to identify epidemiological studies on the risk of infection with SARS-CoV-2 during travel by train and bus and to critically evaluate them also with regard to extrapolating the findings to the German situation. METHODS: Systematic review based on searching two electronic databases (PubMed, Web of Science) according to the principle of Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) for epidemiological studies on SARS-CoV-2 or COVID-19 and travel by train or bus. RESULTS: Searches of the two electronic databases yielded 746 publications. Of these, 55 met the selection criteria and were included in the full-text search. Finally, 5 original publications were used to answer the question about SARS-CoV-2 infections related to long-distance travel by train and 4 related to bus travel. The studies were very heterogeneous and referred almost exclusively to long-distance travel in China. They consistently showed a risk of infection when infected persons travelled in the same train, car or bus without mouth-to-nose (MNB) coverage. The risk was not limited to those sitting in close proximity to an infected fellow traveler. Despite all the differences between travel by train and bus in China and Germany, there is no fundamental doubt that the reported results from China can also be extrapolated to Germany in qualitative terms. However, it must be taken into account that the results of the three key publications predominantly included the period before the lockdown in China without the strict use of MNB. Thus, the question remains whether the results would be similar under current conditions with MNB and more virulent viral mutations. No single study was found related to infection when using public transportation. CONCLUSIONS: There are several lines of evidence that travel by train is associated with a significantly lower risk of infection compared with the risk of infection in the home environment. Due to a lack of observational data, one will need to model the risk of infection for long-distance travel by bus and use of local public transport based on air exchange in the passenger compartment, travel duration, distance from other passengers, and ultimately passenger density.

COVID-19 , Communicable Disease Control , Epidemiologic Studies , Germany/epidemiology , Humans , SARS-CoV-2 , Travel