, a cluster of cases of pneumonia of unknown etiology were reported linked to a market in Wuhan, China 1. The causative agent was identified as the species Severe acute respiratory syndrome-related coronavirus and was named SARS-CoV-2 (ref. 2). By 16 April the virus had spread to 185 different countries, infected over 2,000,000 people and resulted in over 130,000 deaths 3. In the Netherlands, the first case of SARS-CoV-2 was notified on 27 February. The outbreak started with several different introductory events from Italy, Austria, Germany and France followed by local amplification in, and later also outside, the south of the Netherlands. The combination of near to real-time whole-genome sequence analysis and epidemiology resulted in reliable assessments of the extent of SARS-CoV-2 transmission in the community, facilitating early decision-making to control local transmission of SARS-CoV-2 in the Netherlands. We demonstrate how these data were generated and analyzed, and how SARS-CoV-2 whole-genome sequencing, in combination with epidemiological data, was used to inform public health decision-making in the Netherlands. Whole-genome sequencing (WGS) is a powerful tool to understand the transmission dynamics of outbreaks and inform outbreak control decisions 4-7. Evidence of this was seen during the 2014-2016 West African Ebola outbreak when real-time WGS was used to help public health decision-making, a strategy dubbed 'precision public health pathogen genomics' 8,9. Immediate sharing and analysis of data during outbreaks is now recommended as an integral part of outbreak response 10-12. Feasibility of real-time WGS requires access to sequence platforms that provide reliable sequences, access to metadata for interpretation, and data analysis at high speed and low cost. Therefore, WGS for outbreak support is an active area of research. Nanopore sequencing has been employed in recent outbreaks of Usutu, Ebola, Zika and yellow fever virus owing to the ease of use and relatively low start-up cost 4-7. The robustness of this method has recently been validated using Usutu virus 13,14. In the Netherlands, the first COVID-19 case was confirmed on 27 February and WGS was performed in near to real-time using an amplicon-based sequencing approach. From 22 January, symptomatic travelers from countries where SARS-CoV-2 was known to circulate were routinely tested. The first case of SARS-CoV-2 infection in the Netherlands was identified on 27 February in a person with recent travel history to Italy and an additional case was identified one day later, also in a person with recent travel history to Italy. The genomes of these first two positive samples were generated and analyzed by 29 February. These two viruses clustered differently in the phylogenetic tree, confirming separate introductions (Fig. 1a). The advice to test hospitalized patients with serious respiratory infections was issued on 24 February and subsequent attempts to identify possible local transmission chains triggered testing for SARS-CoV-2 on a large scale in h...
SARS-CoV-2 is a novel coronavirus that has rapidly spread across the globe. In the Netherlands, the first case of SARS-CoV-2 has been notified on the 27 th of February. Here, we describe the first three weeks of the SARS-CoV-2 outbreak in the Netherlands, which started with several different introductory events from Italy, Austria, Germany and France followed by local amplification in, and later also, outside the South of the Netherlands. The timely generation of whole genome sequences combined with epidemiological investigations facilitated early decision making in an attempt to control local transmission of SARS-CoV-2 in the Netherlands.
Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in the Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in the Netherlands and Thailand.
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