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medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.10.26.20219642


Identifying linked cases of infection is a key part of the public health response to viral infectious disease. Viral genome sequence data is of great value in this task, but requires careful analysis, and may need to be complemented by additional types of data. The Covid-19 pandemic has highlighted the urgent need for analytical methods which bring together sources of data to inform epidemiological investigations. We here describe A2B-COVID, an approach for the rapid identification of linked cases of coronavirus infection. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and novel approaches to genome sequence data to assess whether or not cases of infection are consistent or inconsistent with linkage via transmission. We apply our method to analyse and compare data collected from two wards at Cambridge University Hospitals, showing qualitatively different patterns of linkage between cases on designated Covid-19 and non-Covid-19 wards. Our method is suitable for the rapid analysis of data from clinical or other potential outbreak settings.

28582 , 31543 , 59585
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.06.26.20139873


Background Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive artificial ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP). Objectives To study the incidence of VAP, as well as differences in secondary infections, and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients. Methods In this prospective observational study, we compared the incidence of VAP and secondary infections using a combination of a TaqMan multi-pathogen array and microbial culture. In addition, we determined the lung microbime composition using 16S RNA analyisis. The study involved eighteen COVID-19 and seven non-COVID-19 patients receiving invasive ventilation in three ICUs located in a single University teaching hospital between April 13th 2020 and May 7th 2020. Results We observed a higher percentage of confirmed VAP in COVID-19 patients. However, there was no statistical difference in the detected organisms or pulmonary microbiome when compared to non-COVID-19 patients. Conclusion COVID-19 makes people more susceptible to developing VAP, partly but not entirely due to the increased duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the array of secondary infections observed are similar to that seen in critically ill patients ventilated for other reasons.

11443 , 59585 , 37050 , 55222 , 52093