scholarly journals Epidemiological associations with genomic variation in SARS-CoV-2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ali Rahnavard ◽  
Tyson Dawson ◽  
Rebecca Clement ◽  
Nathaniel Stearrett ◽  
Marcos Pérez-Losada ◽  
...  
Keyword(s):  
Nonstructural Protein ◽  
Protein S ◽  
Disease Status ◽  
Genomic Variation ◽  
Disease Spread ◽  
Low Coherence ◽  
Health Measures ◽  
Host Sex ◽  
Analytical Approaches ◽  
High Coherence

AbstractSARS-CoV-2 (CoV) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. We divided the CoV genome into 29 constituent regions and applied novel analytical approaches to identify associations between CoV genomic features and epidemiological metadata. Our results show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation. S protein variation is correlated with nsp3, nsp6, and 3′-to-5′ exonuclease variation. Country of origin and time since the start of the pandemic were the most influential metadata associated with genomic variation, while host sex and age were the least influential. We define a novel statistic—coherence—and show its utility in identifying geographic regions (populations) with unusually high (many new variants) or low (isolated) viral phylogenetic diversity. Interestingly, at both global and regional scales, we identify geographic locations with high coherence neighboring regions of low coherence; this emphasizes the utility of this metric to inform public health measures for disease spread. Our results provide a direction to prioritize genes associated with outcome predictors (e.g., health, therapeutic, and vaccine outcomes) and to improve DNA tests for predicting disease status.

scholarly journals Epidemiological associations with genomic variation in SARS-CoV-2

2021 ◽  
Author(s):  
Ali Rahnavard ◽  
Rebecca Clement ◽  
Nathaniel Stearrett ◽  
Marcos Pérez-Losada ◽  
Keith A. Crandall ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Nonstructural Protein ◽  
Protein S ◽  
Disease Status ◽  
Virus Genome ◽  
Genomic Variation ◽  
Spike Protein ◽  
Genome Variation ◽  
Host Sex ◽  
Novel Coronavirus

Abstract The 2019 novel coronavirus (SARS-CoV-2) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. To diminish the short-term and long-term impacts of coronavirus (CoV), we investigated CoV differences at the nucleotide and protein level and CoV genomic variation associated with epidemiological variation and geography. We divided the CoV genome into 29 constituent regions for this analysis. Our results highlight the variation of CoV variants of lineage and show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation, which makes these two proteins potential targets for treatments. S protein variation is highly correlated with nsp3, nsp6, and 3'−to−5' exonuclease. Country of origin and time since the start of the pandemic were the most influential metadata in these differences. Host sex and age are the lowest in terms of explaining the virus genome variation. We quantified variation explained by regions of the CoV genome across different CoV viruses including, SARS-CoV-2, Middle East respiratory syndrome coronavirus (MERS-CoV), other severe acute respiratory syndrome coronavirus SARS-CoV (SARS-related), and bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses (Bat-SL-CoV). We found that Spike protein and nsp3 explain most of the variation among these viruses; they are also among the genomic regions with the highest number of sites under natural selection. Our results provide a direction to prioritize genes associated with outcome predictors, including health, therapeutic, and vaccine outcomes, and to inform improved DNA tests for predicting disease status.

scholarly journals Comparison of Schmallenberg virus sequences isolated from mammal host and arthropod vector

Virus Genes ◽  
2018 ◽  
Vol 54 (6) ◽  
pp. 792-803 ◽  
Author(s):  
Julia Kęsik-Maliszewska ◽  
Aleksandra Antos ◽  
Jerzy Rola ◽  
Magdalena Larska
Keyword(s):  
Molecular Diversity ◽  
Nonstructural Protein ◽  
Protein S ◽  
Sequence Variability ◽  
Biting Midges ◽  
Phylogenetic Relations ◽  
Acute Infections ◽  
Next Generation Sequencing Ngs ◽  
Mammal Host ◽  
Generation Sequencing

Abstract Schmallenberg virus (SBV) is the member of Peribunyaviridae family, which comprises pathogens of importance for human and veterinary medicine. The virus is transmitted only between animals and mainly by biting midges of the genus Culicoides. This study was performed in order to determine SBV genetic diversity and elucidate the host–vector adaptation. All three viral segments were analysed for sequence variability and phylogenetic relations. The Polish SBV strains obtained from acute infections of cattle, congenital cases in sheep, and from Culicoides midges were sequenced using Sanger and next-generation sequencing (NGS) methods. The obtained sequences were genetically similar (99.2–100% identity) to the first-detected strain BH80/11—4 from German cattle. The sampling year and origin of Polish sequences had no effect on molecular diversity of SBV. Considering all analysed Polish as well as European sequences, ovine-derived sequences were the most variable, while the midge ones were more conserved and encompassed unique substitutions located mainly in nonstructural protein S. SBV sequences isolated from Culicoides are the first submitted to GenBank and reported.

scholarly journals Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast Asia

2021 ◽  
Author(s):  
Wei Luo ◽  
Zhaoyin Liu ◽  
Yuxuan Zhou ◽  
Yumin Zhao ◽  
Yunyue Elita Li ◽  
...  
Keyword(s):  
Public Health ◽  
Southeast Asia ◽  
Spatiotemporal Analysis ◽  
Health Interventions ◽  
Disease Spread ◽  
Epidemic Dynamics ◽  
Health Measures ◽  
Global Pandemic ◽  
Public Health Strategies ◽  
Time Scan

The global pandemic of COVID-19 presented an unprecedented challenge to all countries in the world, among which Southeast Asia (SEA) countries managed to maintain and mitigate the first wave of COVID-19 in 2020. However, these countries were caught in the crisis after the Delta variant was introduced to SEA, though many countries had immediately implemented non-pharmaceutical intervention (NPI) measures along with vaccination in order to contain the disease spread. To investigate the potential linkages between epidemic dynamics and public health interventions, we adopted a prospective space-time scan method to conduct spatiotemporal analysis at the district level in the seven selected countries in SEA from June 2021 to October 2021. Results reveal the spatial and temporal propagation and progression of COVID-19 risks relative to public health measures implemented by different countries. Our research benefits continuous improvements of public health strategies in preventing and containing this pandemic.

scholarly journals The genomic variation landscape of globally-circulating clades of SARS-CoV-2 defines a genetic barcoding scheme

2020 ◽  
Author(s):  
Qingtian Guan ◽  
Mukhtar Sadykov ◽  
Raushan Nugmanova ◽  
Michael J. Carr ◽  
Stefan T. Arold ◽  
...  
Keyword(s):  
Viral Proteins ◽  
Genomic Variation ◽  
Genome Replication ◽  
High Quality ◽  
Dynamic Changes ◽  
Health Measures ◽  
Complete Genomes ◽  
Major Mutation ◽  
Genetic Barcoding ◽  
Over Time

ABSTRACTWe describe fifteen major mutation events from 2,058 high-quality SARS-CoV-2 genomes deposited up to March 31st, 2020. These events define five major clades (G, I, S, D and V) of globally-circulating viral populations, representing 85.7% of all sequenced cases, which we can identify using a 10 nucleotide genetic classifier or barcode. We applied this barcode to 4,000 additional genomes deposited between March 31st and April 15th and classified successfully 95.6% of the clades demonstrating the utility of this approach. An analysis of amino acid variation in SARS-CoV-2 ORFs provided evidence of substitution events in the viral proteins involved in both host-entry and genome replication. The systematic monitoring of dynamic changes in the SARS-CoV-2 genomes of circulating virus populations over time can guide therapeutic and prophylactic strategies to manage and contain the virus and, also, with available efficacious antivirals and vaccines, aid in the monitoring of circulating genetic diversity as we proceed towards elimination of the agent. The barcode will add the necessary genetic resolution to facilitate tracking and monitoring of infection clusters to distinguish imported and indigenous cases and thereby aid public health measures seeking to interrupt transmission chains without the requirement for real-time complete genomes sequencing.

scholarly journals A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China

10.2196/21685 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e21685
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  
Keyword(s):  
Public Health ◽  
Information And Communication Technologies ◽  
Ethical Issues ◽  
Rapid Development ◽  
Disease Outbreaks ◽  
Face Mask ◽  
Digital Data ◽  
Disease Spread ◽  
Health Measures ◽  
Digital Epidemiology

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

scholarly journals Investigating Disease Spread between Two Assessment Dates with Permutation Tests on a Lattice

2005 ◽  
Vol 95 (12) ◽  
pp. 1453-1461 ◽  
Author(s):  
Gaël Thébaud ◽  
Nathalie Peyrard ◽  
Sylvie Dallot ◽  
Agnès Calonnec ◽  
Gérard Labonne
Keyword(s):  
Binary Data ◽  
Prior Information ◽  
Mechanistic Model ◽  
Disease Status ◽  
Disease Spread ◽  
Spatial Structures ◽  
Monte Carlo Test ◽  
Point Patterns ◽  
Causes Of Disease ◽  
Insight Into

Mapping and analyzing the disease status of individual plants within a study area at successive dates can give insight into the processes involved in the spread of a disease. We propose a permutation method to analyze such spatiotemporal maps of binary data (healthy or diseased plants) in regularly spaced plantings. It requires little prior information on the causes of disease spread and handles missing plants and censored data. A Monte Carlo test is used to assess whether the location of newly diseased plants is independent of the location of previously diseased plants. The test takes account of the significant spatial structures at each date in order to separate nonrandomness caused by the structure at one date from nonrandomness caused by the dependence between newly diseased plants and previously diseased plants. If there is a nonrandom structure at both dates, independent patterns are simulated by randomly shifting the entire pattern observed at the second date. Otherwise, independent patterns are simulated by randomly reallocating the positions of one group of diseased plants. Simulated and observed patterns of disease are then compared through distance-based statistics. The performance of the method and its robustness are evaluated by its ability to accurately identify simulated independent and dependent bivariate point patterns. Additionally, two realworld spatiotemporal maps with contrasting disease progress illustrate how the tests can provide valuable clues about the processes of disease spread. This method can supplement biological investigations and be used as an exploratory step before developing a specific mechanistic model.

scholarly journals A modeling of a Diphtheria epidemic in the refugees camps

2017 ◽  
Author(s):  
María Torrea ◽  
José Luis Torrea ◽  
Daniel Ortega
Keyword(s):  
Public Health ◽  
Soviet Union ◽  
Vaccine Coverage ◽  
Disease Spread ◽  
Epidemic Outbreak ◽  
High Coverage ◽  
Infected People ◽  
Vaccination Rates ◽  
Health Measures ◽  
The Soviet Union

AbstractBackgroundDiphtheria has a big mortality rate. Vaccination practically eradicated it in industrialized countries. A decrease in vaccine coverage and public health deterioration cause a reemergence in the Soviet Union in 1990. These circumstances seem to be being reproduced in refugee camps with a potential risk of new outbreak.MethodsWe constructed a mathematical model that describes the evolution of the Soviet Union epidemic outbreak. We use it to evaluate how the epidemic would be modified by changing the rate of vaccination, and improving public health conditions.ResultsWe observe that a small decrease of 15% in vaccine coverage, translates an ascent of 47% in infected people. A coverage increase of 15% and 25% decreases a 44% and 66% respectively of infected people. Just improving health care measures a 5%, infected people decreases a 11.31%. Combining high coverage with public health measures produces a bigger reduction in the amount of infected people compare to amelioration of coverage rate or health measures alone.ConclusionsOur model estimates the evolution of a diphtheria epidemic outbreak. Small increases in vaccination rates and in public health measures can translate into large differences in the evolution of a possible epidemic. These estimates can be helpful in socioeconomic instability, to prevent and control a disease spread.

scholarly journals A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China (Preprint)

2020 ◽  
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  
Keyword(s):  
Public Health ◽  
Information And Communication Technologies ◽  
Ethical Issues ◽  
Rapid Development ◽  
Disease Outbreaks ◽  
Face Mask ◽  
Digital Data ◽  
Disease Spread ◽  
Health Measures ◽  
Digital Epidemiology

UNSTRUCTURED A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

scholarly journals Towards a quantitative model of epidemics during conflicts

2019 ◽  
Author(s):  
Soumya Banerjee
Keyword(s):  
Public Health ◽  
Disease Outbreaks ◽  
Integrated Approach ◽  
Quantitative Model ◽  
Disease Spread ◽  
Mathematical Framework ◽  
Health Measures ◽  
Conflict Zone ◽  
Socio Economic Development

Epidemics may both contribute to and arise as a result of conflict. The effects of conflict on infectious diseases are complex and there have been confounding observations of both increase and decrease in disease outbreaks during and after conflicts. However there is no unified mathematical model that explains all these counter-intuitive observations. There is an urgent need for a quantitative framework for modelling conflicts and epidemics. We introduce a set of mathematical models to understand the role of conflicts in epidemics. Our mathematical framework has the potential to explain the counterintuitive observations and the complex role of human conflicts in epidemics. Our work suggests that aid and peacekeeping organizations should take an integrated approach that combines public health measures, socio-economic development, and peacekeeping in the conflict zone. Our approach exemplifies the role of non-linear thinking in complex systems like human societies. We view our work as a step towards a quantitative model of disease spread in conflicts.

scholarly journals Temporal Patterns in the Evolutionary Genetic Distance of SARS-CoV-2 during the COVID-19 Pandemic

2022 ◽  
pp. 1-4
Author(s):  
Jingzhi Lou ◽  
Shi Zhao ◽  
Lirong Cao ◽  
Hong Zheng ◽  
Zigui Chen ◽  
...  
Keyword(s):  
Genetic Distance ◽  
Nonstructural Protein ◽  
Protein S ◽  
Genetic Distances ◽  
Spike Protein ◽  
Sequencing Data ◽  
Reading Frame ◽  
N Protein ◽  
Rdrp Region ◽  
Evolutionary Genetic

During coronavirus disease 2019 (COVID-19) pandemic, the genetic mutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred frequently. Some mutations in the spike protein are considered to promote transmissibility of the virus, while the mutation patterns in other proteins are less studied and may also be important in understanding the characteristics of SARS-CoV-2. We used the sequencing data of SARS-CoV-2 strains in California to investigate the time-varying patterns of the evolutionary genetic distance. The accumulative genetic distances were quantified across different time periods and in different viral proteins. The increasing trends of genetic distance were observed in spike protein (S protein), the RNA-dependent RNA polymerase (RdRp) region and nonstructural protein 3 (nsp3) of open reading frame 1 (ORF1), and nucleocapsid protein (N protein). The genetic distances in ORF3a, ORF8, and nsp2 of ORF1 started to diverge from their original variants after September 2020. By contrast, mutations in other proteins appeared transiently, and no evident increasing trend was observed in the genetic distance to the original variants. This study presents distinct patterns of the SARS-CoV-2 mutations across multiple proteins from the aspect of genetic distance. Future investigation shall be conducted to study the effects of accumulative mutations on epidemics characteristics.

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