Identification of influenza urban transmission patterns by geographical, epidemiological and whole genome sequencing data: protocol for an observational study

Egli, Adrian; Saalfrank, Claudia; Goldman, Nina; Brunner, Myrta; Hollenstein, Yvonne; Vogel, Thomas J.; Augustin, Noemie; Wüthrich, Daniel; Seth-Smith, Helena M. B.; Roth, Elisa; Syedbasha, Mohammedyaseen; Mueller, Nicola Felix; Vogt, Dominik; Bauer, Jan; Amar-Sliwa, Nadezhda; Meinel, Dominik M.; Dubuis, Olivier; Naegele, Michael; Tschudin‐Sutter, Sarah; Buser, Andreas; Nickel, Christian H.; Zeller, Andreas; Ritz, Nicole; Battegay, Manuel; Stadler, Tanja; Schneider-Sliwa, Rita

doi:10.1136/bmjopen-2019-030913

Cited by 7 publications

(10 citation statements)

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“…We linked socioeconomic scores to each statistical block reflecting (i) the population density (inhabitants per hectare (ha)), (ii) the living space (per capita in m 2 ), and (iii) the net income (median in CHF). Each of these three key factors was translated to “socioeconomic points” ranging from one to five, which were added to generate a total socioeconomic score for each housing block: a score of three reflecting the lowest and a score of fifteen the highest possible socioeconomic value 20 ( Figure S2A-D ). The median socioeconomic scores of urban quarters ranged from three to ten.…”

Section: Resultsmentioning

confidence: 99%

“…During the 2016/2017 season, we screened patients presenting an influenza-like illness using an influenza-specific PCR. We included 663 influenza virus positive samples recruited from 12 different study sites across the city ( 32 ; Figure S7A ). The largest cohort within a single city, to the best of our knowledge.…”

Section: Resultsmentioning

confidence: 99%

“…The overall study design has been previously published 20 . Briefly, the study had retrospective and prospective parts.…”

Section: Methodsmentioning

confidence: 99%

“…Finally, we described the details of influenza transmission during the 2016/2017 season using whole genome sequencing of all collected influenza viruses, covering more than 650 isolates, combining the data, resulting in an unprecedented spatiotemporal resolution. The details on the study design for this project have previously been published 20 .…”

Section: Introductionmentioning

confidence: 99%

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High-resolution influenza mapping of a city reveals socioeconomic determinants of transmission within and between urban quarters

Egli

Goldman

Müller

et al. 2020

Preprint

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162/150) 39 40With two-thirds of the global population projected to be living in urban areas by 2050, 41 understanding the transmission patterns of viral pathogens within cities is crucial for effective 42 prevention strategies. Here, in unprecedented spatial resolution, we analysed the socioeconomic 43 determinants of influenza transmission in a European city. We combined geographical and 44 epidemiological data with whole genome sequencing of influenza viruses at the scale of urban 45 quarters and statistical blocks, the smallest geographic subdivisions within a city. We observed 46 annually re-occurring geographic clusters of influenza incidences, mainly associated with net Introduction: 54Transmission of influenza is influenced by extensive but poorly understood interactions between 55 various viral, host and environmental factors 1-3 . Influenza may serve as a model for pandemic 56 threats including the most recent COVID-19 pandemic. Whole viral genome sequencing has 57 enabled reconstruction of phylogenetic relatedness at high resolution. Using these approaches, 58the interactions and dynamics of influenza transmission events have been described across a 59 range of scales: globally 4-6 , across continents 1,7 , in university campuses 8 , or within households 9-60 12 . With two-thirds of the global population projected to be living in urban areas by 2050, 61 understanding the transmission patterns of influenza within cities is crucial for effective prevention 62 strategies and may help to prepare for pandemic threats. Previous work identified cities as 63 containing critical chains of transmission outside of peak climatic conditions (Dalziel, B. D. et al 64 Science 2019), but the resolution to look at these critical intra-city transmission chains in detail 65 has until now been lacking. Very few studies have explored transmission events and dynamics of 66 influenza viruses at the scale of a city 13-17 . Cities are heterogeneous with remarkably different 67 neighbourhoods based on the socioeconomic position of the individuals living there. 68Consequently, a high spatial resolution of the urban space and built environment is crucial to fully 69 understanding the impact of factors linked to health and disease 18,19 . 71In this study we combine epidemiologic, geographical and demographical factors at the 72 unprecedented resolution of urban quarters (i.e. neighbourhood/area) and statistical blocks (i.e. 73city block/street) levels, the smallest statistical enumeration areas within a city. Basel, 74Switzerland, serving as our model city, we explored the local patterns of influenza distribution and 75 transmission from 2013 to 2018. Basel has urban quarters that differ substantially in 76 socioeconomic indicators and housing structure. By using information at the level of statistical 77 blocks, we were able to construct a detailed picture of influenza transmission within the city. We 78 visualized kernel density estimates of influenza cases (reflecting the clustering of cases), a 79 fundamental data smoothing me...

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…The overall study design has been previously published 20 . Briefly, the study had retrospective and prospective parts.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

High-resolution influenza mapping of a city reveals socioeconomic determinants of transmission within and between urban quarters

Egli

Goldman

Müller

et al. 2020

Preprint

Self Cite

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“…Along with the R ef f , we co-estimated the sampling probability, that is the 263 probability of an infected individual being sampled. Since we followed the same 264 procedure for inclusion of patients throughout the epidemic season [15], we assumed 265 that this probability is constant throughout the influenza season. We estimated the 266 sampling probability to be between 3% and 5% (see figures 1d and 5).…”

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confidence: 99%

Characterising the epidemic spread of Influenza A/H3N2 within a city through phylogenetics

Müller

Wüthrich

Goldman

et al. 2020

Preprint

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Infecting large portions of the global population, seasonal influenza is a major burden on societies around the globe. While the global source sink dynamics of the different seasonal influenza viruses have been studied intensively, it's local spread remains less clear. In order to improve our understanding of how influenza is transmitted on a city scale, we collected an extremely densely sampled set of influenza sequences alongside patient metadata. To do so, we sequenced influenza viruses isolated from patients of two different hospitals, as well as private practitioners in Basel, Switzerland during the 2016/2017 influenza season. The genetic sequences reveal that repeated introductions into the city drove the influenza season. We then reconstruct how the effective reproduction number changed over the course of the season. We find trends in transmission dynamics correlated positively with trends in temperature, but not relative humidity nor school holidays. Alongside the genetic sequence data that allows us to see how individual cases are connected, we gathered patient information, such as the age or household status. Zooming into the local transmission outbreaks suggests that the April 26, 2020 1/23 Author summaryAs shown with the current SARS-CoV-2 pandemic, respiratory diseases can quickly spread around the globe. While it can be hugely important to understand how diseases spread around the globe, local spread is most often the main driver of novel infections of respiratory diseases such as SARS-CoV-2 or influenza. We here use genetic sequence data alongside patient information to better understand what the drives the local spread of influenza by looking at the 2016/2017 influenza season in Basel, Switzerland as an example. The genetic sequence data allows us to reconstruct the how the transmission dynamics changed over the course of the season, which we correlate to changes, but not humidity or school holidays. Additionally, the genetic sequence data allows us to see how individual cases are connected. Using patient information, such as age and household status our analyses suggest that the elderly mainly transmit within their own transmission network. Additionally, they suggest that school aged children, but not pre-school aged children are important drivers of the local spread of influenza. 12Phylogenetics allows us to see how individual cases are epidemiologically connected. 13 This is done by reconstructing the evolutionary relationship between temporally spaced 14 samples of genetic sequence data, isolated from different infected individuals. The 15 resulting phylogenetic tree displays how samples are related to each other, and branch 16 lengths in calendar time display the elapsed time. The phylogenetic tree can therefore 17 be interpreted as an approximation of the transmission chain of the sampled cases. Such 18 a view on part of the influenza transmission chain allows to further quantify the 19 epidemiological dynamics which gave rise to the observed phylogenetic tree using 20 phylodynamic methods [...

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Wastewater surveillance

Yadav

Chauhan

2023

Genomic Surveillance and Pandemic Preparedness

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Identification of influenza urban transmission patterns by geographical, epidemiological and whole genome sequencing data: protocol for an observational study

Cited by 7 publications

References 23 publications

High-resolution influenza mapping of a city reveals socioeconomic determinants of transmission within and between urban quarters

High-resolution influenza mapping of a city reveals socioeconomic determinants of transmission within and between urban quarters

Characterising the epidemic spread of Influenza A/H3N2 within a city through phylogenetics

Wastewater surveillance

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