scholarly journals A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

2021 ◽  
Author(s):  
Carmen Lía Murall ◽  
Eric Fournier ◽  
Jose Hector Galvez ◽  
Arnaud N’Guessan ◽  
Sarah J. Reiling ◽  
...  
Keyword(s):  
Epidemiological Data ◽  
Founder Effects ◽  
Canadian Province ◽  
Genomic Epidemiology ◽  
Spring Break ◽  
Health Measures ◽  
Travel Restrictions ◽  
Spatio Temporal ◽  
Pandemic Wave ◽  
Temporal Spread

AbstractUsing genomic epidemiology, we investigated the arrival of SARS-CoV-2 to Québec, the Canadian province most impacted by COVID-19, with >280,000 positive cases and >10,000 deaths in a population of 8.5 million as of March 1st, 2021. We report 2,921 high-quality SARS-CoV-2 genomes in the context of >12,000 publicly available genomes sampled globally over the first pandemic wave (up to June 1st, 2020). By combining phylogenetic and phylodynamic analyses with epidemiological data, we quantify the number of introduction events into Québec, identify their origins, and characterize the spatio-temporal spread of the virus. Conservatively, we estimated at least 500 independent introduction events, the majority of which happened from spring break until two weeks after the Canadian border closed for non-essential travel. Subsequent mass repatriations did not generate large transmission lineages (>50 cases), likely due to mandatory quarantine measures in place at the time. Consistent with common spring break and ‘snowbird’ destinations, most of the introductions were inferred to have originated from Europe via the Americas. Fewer than 100 viral introductions arrived during spring break, of which 5-10 led to the largest transmission lineages of the first wave (accounting for 36-58% of all sequenced infections). These successful viral transmission lineages dispersed widely across the province, consistent with founder effects and superspreading dynamics. Transmission lineage size was greatly reduced after March 11th, when a quarantine order for returning travelers was enacted. While this suggests the effectiveness of early public health measures, the biggest transmission lineages had already been ignited prior to this order. Combined, our results reinforce how, in the absence of tight travel restrictions or quarantine measures, fewer than 100 viral introductions in a week can ensure the establishment of extended transmission chains.

scholarly journals A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Carmen Lía Murall ◽  
Eric Fournier ◽  
Jose Hector Galvez ◽  
Arnaud N’Guessan ◽  
Sarah J. Reiling ◽  
...  
Keyword(s):  
Epidemiological Data ◽  
Founder Effects ◽  
Canadian Province ◽  
Genomic Epidemiology ◽  
Spring Break ◽  
Health Measures ◽  
Travel Restrictions ◽  
Returning Travellers ◽  
Viral Lineage ◽  
Pandemic Wave

Abstract Background Québec was the Canadian province most impacted by COVID-19, with 401,462 cases as of September 24th, 2021, and 11,347 deaths due mostly to a very severe first pandemic wave. In April 2020, we assembled the Coronavirus Sequencing in Québec (CoVSeQ) consortium to sequence SARS-CoV-2 genomes in Québec to track viral introduction events and transmission within the province. Methods Using genomic epidemiology, we investigated the arrival of SARS-CoV-2 to Québec. We report 2921 high-quality SARS-CoV-2 genomes in the context of > 12,000 publicly available genomes sampled globally over the first pandemic wave (up to June 1st, 2020). By combining phylogenetic and phylodynamic analyses with epidemiological data, we quantify the number of introduction events into Québec, identify their origins, and characterize the spatiotemporal spread of the virus. Results Conservatively, we estimated approximately 600 independent introduction events, the majority of which happened from spring break until 2 weeks after the Canadian border closed for non-essential travel. Subsequent mass repatriations did not generate large transmission lineages (> 50 sequenced cases), likely due to mandatory quarantine measures in place at the time. Consistent with common spring break and “snowbird” destinations, most of the introductions were inferred to have originated from Europe via the Americas. Once introduced into Québec, viral lineage sizes were overdispersed, with a few lineages giving rise to most infections. Consistent with founder effects, the earliest lineages to arrive tended to spread most successfully. Fewer than 100 viral introductions arrived during spring break, of which 7–12 led to the largest transmission lineages of the first wave (accounting for 52–75% of all sequenced infections). These successful transmission lineages dispersed widely across the province. Transmission lineage size was greatly reduced after March 11th, when a quarantine order for returning travellers was enacted. While this suggests the effectiveness of early public health measures, the biggest transmission lineages had already been ignited prior to this order. Conclusions Combined, our results reinforce how, in the absence of tight travel restrictions or quarantine measures, fewer than 100 viral introductions in a week can ensure the establishment of extended transmission chains.

scholarly journals Inference of Nipah virus Evolution, 1999-2015

2020 ◽  
Author(s):  
Shannon L M Whitmer ◽  
Michael K Lo ◽  
Hossain M S Sazzad ◽  
Sara Zufan ◽  
Emily S Gurley ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Nipah Virus ◽  
Whole Genome ◽  
Health Measures ◽  
Diffusion Analysis ◽  
History Of ◽  
Spatio Temporal ◽  
Viral Isolates ◽  
Targeted Enrichment ◽  
Temporal Spread

Abstract Despite near-annual human outbreaks of Nipah virus (NiV) disease in Bangladesh, typically due to individual spillover events from the local bat population, only 20 whole genome NiV sequences exist from humans and 10 from bats. NiV whole genome sequences (WGS) from annual outbreaks have been challenging to generate, primarily due to the low viral load in human throat swab and serum specimens. Here, we used targeted enrichment with custom NiV-specific probes and generated 35 additional unique full length genomic sequences directly from human specimens and viral isolates. We inferred the temporal and geographic evolutionary history of NiV in Bangladesh and expanded a tool to visualize NiV spatio-temporal spread from a Bayesian continuous diffusion analysis. We observed that strains from Bangladesh segregated into two distinct clades that have intermingled geographically in Bangladesh over time and space. As these clades expanded geographically and temporally, we did not observe evidence for significant branch and site-specific selection, except for a single site in the Henipavirus L polymerase. However, the Bangladesh 1 and 2 clades are differentiated by mutations initially occurring in the polymerase, with additional mutations accumulating in the N, G, F, P, and L genes on external branches. Modeling the historic geographical and temporal spread demonstrates that while widespread, NiV does not exhibit significant genetic variation in Bangladesh. Thus, future public health measures should address whether NiV within in the bat population also exhibits comparable genetic variation, if zoonotic transmission results in a genetic bottleneck and if surveillance techniques are detecting only a subset of NiV.

scholarly journals Assessing the Spatio-temporal Spread of COVID-19 via Compartmental Models with Diffusion in Italy, USA, and Brazil

2021 ◽  
Author(s):  
Malú Grave ◽  
Alex Viguerie ◽  
Gabriel F. Barros ◽  
Alessandro Reali ◽  
Alvaro L. G. A. Coutinho
Keyword(s):  
Differential Equation ◽  
Epidemiological Data ◽  
Compartmental Models ◽  
Modeling Framework ◽  
Differential Equation Models ◽  
The World ◽  
Spatio Temporal ◽  
Qualitative Characteristics ◽  
Good Agreement ◽  
Temporal Spread

AbstractThe outbreak of COVID-19 in 2020 has led to a surge in interest in the mathematical modeling of infectious diseases. Such models are usually defined as compartmental models, in which the population under study is divided into compartments based on qualitative characteristics, with different assumptions about the nature and rate of transfer across compartments. Though most commonly formulated as ordinary differential equation models, in which the compartments depend only on time, recent works have also focused on partial differential equation (PDE) models, incorporating the variation of an epidemic in space. Such research on PDE models within a Susceptible, Infected, Exposed, Recovered, and Deceased framework has led to promising results in reproducing COVID-19 contagion dynamics. In this paper, we assess the robustness of this modeling framework by considering different geometries over more extended periods than in other similar studies. We first validate our code by reproducing previously shown results for Lombardy, Italy. We then focus on the U.S. state of Georgia and on the Brazilian state of Rio de Janeiro, one of the most impacted areas in the world. Our results show good agreement with real-world epidemiological data in both time and space for all regions across major areas and across three different continents, suggesting that the modeling approach is both valid and robust.

Geographical spread of influenza incidence in Spain during the 2009 A(H1N1) pandemic wave and the two succeeding influenza seasons

2014 ◽  
Vol 142 (12) ◽  
pp. 2629-2641 ◽  
Author(s):  
D. GOMEZ-BARROSO ◽  
M. A. MARTINEZ-BENEITO ◽  
V. FLORES ◽  
R. AMORÓS ◽  
C. DELGADO ◽  
...  
Keyword(s):  
Influenza Surveillance ◽  
H1n1 Pandemic ◽  
Influenza Epidemic ◽  
North West ◽  
Mixed Regression ◽  
Influenza Activity ◽  
Spatio Temporal ◽  
Pandemic Wave ◽  
Epidemic Wave ◽  
Temporal Spread

SUMMARYThe aim of this study was to monitor the spatio-temporal spread of influenza incidence in Spain during the 2009 pandemic and the following two influenza seasons 2010–2011 and 2011–2012 using a Bayesian Poisson mixed regression model; and implement this model of geographical analysis in the Spanish Influenza Surveillance System to obtain maps of influenza incidence for every week. In the pandemic wave the maps showed influenza activity spreading from west to east. The 2010–2011 influenza epidemic wave plotted a north-west/south-east pattern of spread. During the 2011–2012 season the spread of influenza was geographically heterogeneous. The most important source of variability in the model is the temporal term. The model of spatio-temporal spread of influenza incidence is a supplementary tool of influenza surveillance in Spain.

scholarly journals A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread

2021 ◽  
Vol 18 (6) ◽  
pp. 7685-7710
Author(s):  
Yukun Tan ◽  
◽  
Durward Cator III ◽  
Martial Ndeffo-Mbah ◽  
Ulisses Braga-Neto ◽  
...  
Keyword(s):  
State Space ◽  
State Space Model ◽  
Synthetic Data ◽  
Public Health Intervention ◽  
Disease Outbreaks ◽  
Real Data ◽  
Epidemiological Data ◽  
Transmission Parameters ◽  
Intervention Measures ◽  
Spatio Temporal

<abstract><p>Mathematical models are widely recognized as an important tool for analyzing and understanding the dynamics of infectious disease outbreaks, predict their future trends, and evaluate public health intervention measures for disease control and elimination. We propose a novel stochastic metapopulation state-space model for COVID-19 transmission, which is based on a discrete-time spatio-temporal susceptible, exposed, infected, recovered, and deceased (SEIRD) model. The proposed framework allows the hidden SEIRD states and unknown transmission parameters to be estimated from noisy, incomplete time series of reported epidemiological data, by application of unscented Kalman filtering (UKF), maximum-likelihood adaptive filtering, and metaheuristic optimization. Experiments using both synthetic data and real data from the Fall 2020 COVID-19 wave in the state of Texas demonstrate the effectiveness of the proposed model.</p></abstract>

scholarly journals Genomic epidemiology reveals multiple introductions of SARS-CoV-2 followed by community and nosocomial spread, Germany, February to May 2020

2021 ◽  
Vol 26 (43) ◽  
Author(s):  
Maximilian Muenchhoff ◽  
Alexander Graf ◽  
Stefan Krebs ◽  
Caroline Quartucci ◽  
Sandra Hasmann ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Sequence Data ◽  
Phylogenetic Analyses ◽  
Local Level ◽  
University Hospital ◽  
Metropolitan Region ◽  
Viral Genomes ◽  
Genomic Epidemiology ◽  
Viral Spread ◽  
Spatio Temporal

Background In 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. Aim We 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. Methods We 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. Results We 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. Conclusions Early 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.

scholarly journals Temporal spread and evolution of SARS‐CoV‐2 in the second pandemic wave in Brazil

2021 ◽  
Author(s):  
Jonas Michel Wolf ◽  
Diéssy Kipper ◽  
Gabriela Ribeiro Borges ◽  
André Felipe Streck ◽  
Vagner Ricardo Lunge
Keyword(s):  
Pandemic Wave ◽  
Temporal Spread

scholarly journals State-wide Genomic Epidemiology Investigations of COVID-19 Infections in Healthcare Workers: Insights for Future Pandemic Preparedness

2021 ◽  
Author(s):  
Anne E Watt ◽  
Norelle L Sherry ◽  
Patiyan Andersson ◽  
Courtney R Lane ◽  
Sandra Johnson ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Genomic Analysis ◽  
Epidemiological Data ◽  
Pandemic Preparedness ◽  
Transmission Networks ◽  
Healthcare Facilities ◽  
Multiple Introductions ◽  
Genomic Epidemiology ◽  
Sequencing Coverage ◽  
Healthcare Settings

Background COVID-19 has resulted in many infections in healthcare workers (HCWs) globally. We performed state-wide SARS-CoV-2 genomic epidemiological investigations to identify HCW transmission dynamics and provide recommendations to optimise healthcare system preparedness for future outbreaks. Methods Genome sequencing was attempted on all COVID-19 cases in Victoria, Australia. We combined genomic and epidemiologic data to investigate the source of HCW infections across multiple healthcare facilities (HCFs) in the state. Phylogenetic analysis and fine-scale hierarchical clustering were performed for the entire Victorian dataset including community and healthcare cases. Facilities provided standardised epidemiological data and putative transmission links. Findings Between March and October 2020, approximately 1,240 HCW COVID-19 infection cases were identified; 765 are included here. Genomic sequencing was successful for 612 (80%) cases. Thirty-six investigations were undertaken across 12 HCFs. Genomic analysis revealed that multiple introductions of COVID-19 into facilities (31/36) were more common than single introductions (5/36). Major contributors to HCW acquisitions included mobility of staff and patients between wards and facilities, and characteristics and behaviours of individual patients including super-spreading events. Key limitations at the HCF level were identified. Interpretation Genomic epidemiological analyses enhanced understanding of HCW infections, revealing unsuspected clusters and transmission networks. Combined analysis of all HCWs and patients in a HCF should be conducted, supported by high rates of sequencing coverage for all cases in the population. Established systems for integrated genomic epidemiological investigations in healthcare settings will improve HCW safety in future pandemics.

SIMULATING THE SPATIO-TEMPORAL SPREAD OF COOLING FLUX IN CARDIAC TISSUE DUE TO CATHETERIZED CRYOABLATION

2010 ◽  
Author(s):  
Michael Seger ◽  
Gerald Fischer ◽  
Michael Handler ◽  
Florian Hintringer ◽  
Christian Baumgartner
Keyword(s):  
Cardiac Tissue ◽  
Spatio Temporal ◽  
Temporal Spread

scholarly journals Changing travel patterns in China during the early stages of the COVID-19 pandemic

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Hamish Gibbs ◽  
◽  
Yang Liu ◽  
Carl A. B. Pearson ◽  
Christopher I. Jarvis ◽  
...  
Keyword(s):  
Public Health ◽  
Human Mobility ◽  
Transportation Network ◽  
Mainland China ◽  
Disease Spread ◽  
Travel Patterns ◽  
Network Analyses ◽  
Early Stages ◽  
Travel Restrictions ◽  
Spatio Temporal

Abstract Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigate the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020, and discuss their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower healthcare capacity. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and did not lead to structural reorganisation of the transportation network during the study period.

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