scholarly journals Tracking the COVID-19 pandemic in Australia using genomics

2020 ◽  
Author(s):  
Torsten Seemann ◽  
Courtney Lane ◽  
Norelle Sherry ◽  
Sebastian Duchene ◽  
Anders Goncalves da Silva ◽  
...  
Keyword(s):  
Public Health ◽  
Genome Sequencing ◽  
Population Level ◽  
Genomic Diversity ◽  
Contact Tracing ◽  
Internal Quality ◽  
Reproductive Number ◽  
Healthcare Facilities ◽  
Travel Restrictions ◽  
Response Team

BACKGROUND: Whole-genome sequencing of pathogens can improve resolution of outbreak clusters and define possible transmission networks. We applied high-throughput genome sequencing of SARS-CoV-2 to 75% of cases in the State of Victoria (population 6.24 million) in Australia. METHODS: Cases of SARS-CoV-2 infection were detected through active case finding and contact tracing. A dedicated SARS-CoV-2 multidisciplinary genomic response team was formed to enable rapid integration of epidemiological and genomic data. Phylodynamic analysis was performed to assess the putative impact of social restrictions. RESULTS: Between 25 January and 14 April 2020, 1,333 COVID-19 cases were reported in Victoria, with a peak in late March. After applying internal quality control parameters, 903 samples were included in genomic analyses. Sequenced samples from Australia were representative of the global diversity of SARS-CoV-2, consistent with epidemiological findings of multiple importations and limited onward transmission. In total, 76 distinct genomic clusters were identified; these included large clusters associated with social venues, healthcare facilities and cruise ships. Sequencing of sequential samples from 98 patients revealed minimal intra-patient SARS-CoV-2 genomic diversity. Phylodynamic modelling indicated a significant reduction in the effective viral reproductive number (Re) from 1.63 to 0.48 after the implementation of travel restrictions and population-level physical distancing. CONCLUSIONS: Our data provide a comprehensive framework for the use of SARS-CoV-2 genomics in public health responses. The application of genomics to rapidly identify SARS-CoV-2 transmission chains will become critically important as social restrictions ease globally. Public health responses to emergent cases must be swift, highly focused and effective.

scholarly journals Genomic epidemiology reveals transmission patterns and dynamics of SARS-CoV-2 in Aotearoa New Zealand

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jemma L. Geoghegan ◽  
Xiaoyun Ren ◽  
Matthew Storey ◽  
James Hadfield ◽  
Lauren Jelley ◽  
...  
Keyword(s):  
Public Health ◽  
New Zealand ◽  
Health Interventions ◽  
Genomic Diversity ◽  
Reproductive Number ◽  
Genomic Epidemiology ◽  
Aotearoa New Zealand ◽  
Time Period ◽  
Essential Services ◽  
Health And Disease

AbstractNew Zealand, a geographically remote Pacific island with easily sealable borders, implemented a nationwide ‘lockdown’ of all non-essential services to curb the spread of COVID-19. Here, we generate 649 SARS-CoV-2 genome sequences from infected patients in New Zealand with samples collected during the ‘first wave’, representing 56% of all confirmed cases in this time period. Despite its remoteness, the viruses imported into New Zealand represented nearly all of the genomic diversity sequenced from the global virus population. These data helped to quantify the effectiveness of public health interventions. For example, the effective reproductive number, Re of New Zealand’s largest cluster decreased from 7 to 0.2 within the first week of lockdown. Similarly, only 19% of virus introductions into New Zealand resulted in ongoing transmission of more than one additional case. Overall, these results demonstrate the utility of genomic pathogen surveillance to inform public health and disease mitigation.

COVID-19 crisis risks deeper European rifts on privacy

2020 ◽  
Keyword(s):  
Public Health ◽  
Public Participation ◽  
Contact Tracing ◽  
Health Crisis ◽  
Content Type ◽  
Public Health Crisis ◽  
Travel Restrictions ◽  
Digital Strategy ◽  
Mass Surveillance ◽  
The Eu

Subject New privacy guidelines. Significance The EU wants contact tracing apps for tackling COVID-19 to be effective, secure and privacy-compliant. Its efforts have exposed how its existing rules on data are adapting (or not) to the extraordinary public health crisis. Impacts Fear of mass surveillance and data breaches will reduce public participation in tracer apps, casting doubts over their effectiveness. The EU’s digital strategy, notably in terms of reviewing the effectiveness of GDPR, may be rethought in response to the COVID-19 crisis. If tracer apps are not inter-operable across national borders, lifting intra-EU travel restrictions will become harder.

scholarly journals Temporal Contact Graph Reveals The Evolving Epidemic Situation of COVID-19

2021 ◽  
Author(s):  
Mincheng Wu ◽  
Chao Li ◽  
Zhangchong Shen ◽  
Shibo He ◽  
Lingling Tang ◽  
...  
Keyword(s):  
Participation Rate ◽  
Population Level ◽  
User Participation ◽  
Contact Tracing ◽  
Prevention Measures ◽  
Contact Graph ◽  
Individual Level ◽  
Related Data ◽  
Epidemic Size ◽  
Travel Restrictions

Abstract Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted from digital contact tracing for COVID-19 prevention and control. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location-related data contributed by 10,527,737 smartphone users in Wuhan, China. The temporal contact graph reveals five time-varying indicators can accurately capture actual contact trends at population level, demonstrating that travel restrictions (e.g., city lockdown) in Wuhan played an important role in containing COVID-19. We reveal a strong correlation between the contacts level and the epidemic size, and estimate several significant epidemiological parameters (e.g., serial interval). We also show that user participation rate exerts higher influence on situation evaluation than user upload rate does. At individual level, however, the temporal contact graph plays a limited role, since the behavior distinction between the infected and uninfected contacted individuals are not substantial. The revealed results can tell the effectiveness of digital contact tracing against COVID-19, providing guidelines for governments to implement interventions using information technology.

scholarly journals Multiplex SARS-CoV-2 Genotyping PCR for Population-Level Variant Screening and Epidemiologic Surveillance

2021 ◽  
Author(s):  
Hannah Wang ◽  
Jacob A. Miller ◽  
Michelle Verghese ◽  
Mamdouh Sibai ◽  
Daniel Solis ◽  
...  
Keyword(s):  
Public Health ◽  
Nucleic Acid ◽  
Whole Genome Sequencing ◽  
San Francisco ◽  
Genome Sequencing ◽  
High Throughput ◽  
Population Level ◽  
Nucleic Acid Amplification ◽  
Whole Genome ◽  
Epidemiologic Surveillance

ABSTRACTBackgroundEmergence of SARS-CoV-2 variants with concerning phenotypic mutations is of public health interest. Genomic surveillance is an important tool for pandemic response, but many laboratories do not have the resources to support population-level sequencing. We hypothesized that a spike genotyping nucleic acid amplification test (NAAT) could facilitate high-throughput variant surveillance.MethodsWe designed and analytically validated a one-step multiplex allele-specific reverse transcriptase polymerase chain reaction (RT-qPCR) to detect three non-synonymous spike protein mutations (L452R, E484K, N501Y). Assay specificity was validated with next-generation whole-genome sequencing. We then screened a large cohort of SARS-CoV-2 positive specimens from our San Francisco Bay Area population.ResultsBetween December 1, 2020 and March 1, 2021, we screened 4,049 unique infections by genotyping RT-qPCR, with an assay failure rate of 2.8%. We detected 1,567 L452R mutations (38.7%), 34 N501Y mutations (0.84%), 22 E484K mutations (0.54%), and 3 (0.07%) E484K+N501Y mutations. The assay had near-perfect (98-100%) concordance with whole-genome sequencing in a validation subset of 229 specimens, and detected B.1.1.7, B.1.351, B.1.427, B.1.429, B.1.526, and P.2 variants, among others. The assay revealed rapid emergence of L452R in our population, with a prevalence of 24.8% in December 2020 that increased to 62.5% in March 2021.ConclusionsWe developed and clinically implemented a genotyping RT-qPCR to conduct high-throughput SARS-CoV-2 variant screening. This approach can be adapted for emerging mutations and immediately implemented in laboratories already performing NAAT worldwide using existing equipment, personnel, and extracted nucleic acid.Summary / Key PointsEmergence of SARS-CoV-2 variants with concerning phenotypes is of public health interest. We developed a multiplex genotyping RT-qPCR to rapidly detect L452R, E484K, and N501Y with high sequencing concordance. This high-throughput alternative to resource-intensive sequencing enabled surveillance of L452R emergence.

scholarly journals COVID 19 and Nepal: Identification of Critical Public Health Measures

2020 ◽  
Vol 58 (225) ◽  
Author(s):  
Harish Chandra Neupane ◽  
Niki Shrestha ◽  
Shital Adhikari ◽  
Basanta Gauli
Keyword(s):  
Public Health ◽  
Social Life ◽  
Critical Mass ◽  
Rapid Response Team ◽  
Contact Tracing ◽  
Infection Prevention And Control ◽  
Response Team ◽  
National Public Health ◽  
Engagement Interventions ◽  
Critical Public Health

The COVID-19 pandemic is unfolding at an unprecedented pace. The unprecedented threat providesan opportunity to emerge with robust health systems. Nepal has implemented several containmentmeasures such as Rapid Response Team formulation; testing; isolation; quarantine; contact tracing;surveillance, establishment of COVID-19 Crisis Management Centre and designation of dedicatedhospitals to gear up for the pandemic. The national public health emergency managementmechanisms need further strengthening with the proactive engagement of relevant ministries; weneed a strong, real-time national surveillance system and capacity building of a critical mass of healthcare workers; there is a need to further assess infection prevention and control capacity; expandthe network of virus diagnostic laboratories in the private sector with adequate surge capacity;implement participatory community engagement interventions and plan for a phased lockdownexit strategy enabling sustainable suppression of transmission at low-level and enabling in resumingsome parts of economic and social life.

scholarly journals Intrinsic and realized generation intervals in infectious-disease transmission

2015 ◽  
Vol 282 (1821) ◽  
pp. 20152026 ◽  
Author(s):  
David Champredon ◽  
Jonathan Dushoff
Keyword(s):  
Public Health ◽  
Mathematical Models ◽  
Disease Transmission ◽  
Interval Data ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Infectious Disease Transmission ◽  
Generation Interval ◽  
Public Health Strategies ◽  
The Relationship

The generation interval is the interval between the time when an individual is infected by an infector and the time when this infector was infected. Its distribution underpins estimates of the reproductive number and hence informs public health strategies. Empirical generation-interval distributions are often derived from contact-tracing data. But linking observed generation intervals to the underlying generation interval required for modelling purposes is surprisingly not straightforward, and misspecifications can lead to incorrect estimates of the reproductive number, with the potential to misguide interventions to stop or slow an epidemic. Here, we clarify the theoretical framework for three conceptually different generation-interval distributions: the ‘intrinsic’ one typically used in mathematical models and the ‘forward’ and ‘backward’ ones typically observed from contact-tracing data, looking, respectively, forward or backward in time. We explain how the relationship between these distributions changes as an epidemic progresses and discuss how empirical generation-interval data can be used to correctly inform mathematical models.

The largest prison outbreak of TB in Western Europe investigated using whole-genome sequencing

2021 ◽  
Vol 25 (6) ◽  
pp. 491-497
Author(s):  
E. Roycroft ◽  
M. M. Fitzgibbon ◽  
D. M. Kelly ◽  
M. Scully ◽  
A. M. McLaughlin ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Western Europe ◽  
Education Programme ◽  
Multidrug Resistant ◽  
Case Finding ◽  
Contact Tracing ◽  
Whole Genome ◽  
Nucleotide Polymorphisms

BACKGROUND: In March 2011, the Department of Public Health East in Ireland were notified of two cases of TB in two prisoners sharing a cell. We define the resulting outbreak and highlight the role of public health and laboratory-based molecular epidemiology in mapping and control of a prison outbreak.METHODS: Cases were identified through clinical presentation, contact tracing, case-finding exercise or enhanced laboratory surveillance. Mycobacterium tuberculosis isolates were genotyped and underwent whole-genome sequencing (WGS).RESULTS: Of the 34 cases of TB linked to the outbreak, 27 were prisoners (79%), 4 prison officers (12%) and 3 community cases (9%). M. tuberculosis was isolated from 31 cases (culture positivity: 91%). A maximum of six single-nucleotide polymorphisms separated the isolates, with 22 being identical, suggestive of a highly infectious ‘super-spreader´ within the prison. Isolates belonged to the Beijing sub-lineage, and were susceptible to first-line anti-TB agents. A case-finding exercise incidentally detected a prisoner with multidrug-resistant TB. Of the 143 prison officers screened, 52% had latent TB infection. Litigation costs exceeded five million euros.CONCLUSION: This constitutes the largest prison outbreak of TB in Western Europe investigated using WGS. A robust prison entry TB screening and education programme is required to effect better TB control, and prevent future outbreaks and attendant litigation.

scholarly journals Estimating COVID Risk During a Period of Pandemic Decline

2021 ◽  
Vol 9 ◽  
Author(s):  
Timothy J. J. Inglis ◽  
Benjamin McFadden ◽  
Anthony Macali
Keyword(s):  
Public Health ◽  
Real Time ◽  
Health Resources ◽  
Risk Estimate ◽  
Contact Tracing ◽  
Business Continuity ◽  
Risk Monitoring ◽  
Open Source Data ◽  
Travel Restrictions ◽  
Community Transmission

Background: Many parts of the world that succeeded in suppressing epidemic coronavirus spread in 2020 have been caught out by recent changes in the transmission dynamics of SARS-CoV-2. Australia's early success in suppressing COVID-19 resulted in lengthy periods without community transmission. However, a slow vaccine rollout leaves this geographically isolated population vulnerable to leakage of new variants from quarantine, which requires internal travel restrictions, disruptive lockdowns, contact tracing and testing surges.Methods: To assist long term sustainment of limited public health resources, we sought a method of continuous, real-time COVID-19 risk monitoring that could be used to alert non-specialists to the level of epidemic risk on a sub-national scale. After an exploratory data assessment, we selected four COVID-19 metrics used by public health in their periodic threat assessments, applied a business continuity matrix and derived a numeric indicator; the COVID-19 Risk Estimate (CRE), to generate a daily spot CRE, a 3 day net rise and a seven day rolling average. We used open source data updated daily from all Australian states and territories to monitor the CRE for over a year.Results: Upper and lower CRE thresholds were established for the CRE seven day rolling average, corresponding to risk of sustained and potential outbreak propagation, respectively. These CRE thresholds were used in a real-time map of Australian COVID-19 risk estimate distribution by state and territory.Conclusions: The CRE toolkit we developed complements other COVID-19 risk management techniques and provides an early indication of emerging threats to business continuity.

scholarly journals Pandemic dynamics of COVID-19 using epidemic stage, instantaneous reproductive number and pathogen genome identity (GENI) score: modeling molecular epidemiology

2020 ◽  
Author(s):  
DJ Darwin R. Bandoy ◽  
Bart C. Weimer
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Transmission Dynamics ◽  
Reproductive Number ◽  
Evidence Based ◽  
Whole Genome ◽  
Genome Sequences ◽  
Genome Variation ◽  
Pathogen Genome

AbstractBackgroundGlobal spread of COVID-19 created an unprecedented infectious disease crisis that progressed to a pandemic with >180,000 cases in >100 countries. Reproductive number (R) is an outbreak metric estimating the transmission of a pathogen. Initial R values were published based on the early outbreak in China with limited number of cases with whole genome sequencing. Initial comparisons failed to show a direct relationship viral genomic diversity and epidemic severity was not established for SARS-Cov-2.MethodsEach country’s COVID-19 outbreak status was classified according to epicurve stage (index, takeoff, exponential, decline). Instantaneous R estimates (Wallinga and Teunis method) with a short and standard serial interval examined asymptomatic spread. Whole genome sequences were used to quantify the pathogen genome identity score that were used to estimate transmission time and epicurve stage. Transmission time was estimated based on evolutionary rate of 2 mutations/month.FindingsThe country-specific R revealed variable infection dynamics between and within outbreak stages. Outside China, R estimates revealed propagating epidemics poised to move into the takeoff and exponential stages. Population density and local temperatures had variable relationship to the outbreaks. GENI scores differentiated countries in index stage with cryptic transmission. Integration of incidence data with genome variation directly increases in cases with increased genome variation.InterpretationR was dynamic for each country and during the outbreak stage. Integrating the outbreak dynamic, dynamic R, and genome variation found a direct association between cases and genome variation. Synergistically, GENI provides an evidence-based transmission metric that can be determined by sequencing the virus from each case. We calculated an instantaneous country-specific R at different stages of outbreaks and formulated a novel metric for infection dynamics using viral genome sequences to capture gaps in untraceable transmission. Integrating epidemiology with genome sequencing allows evidence-based dynamic disease outbreak tracking with predictive evidence.FundingPhilippine California Advanced Research Institute (Quezon City, Philippines) and the Weimer laboratory.Research in contextReproductive number is (R) an epidemiological parameter that defines outbreak transmission dynamics. While early estimates of R exist for COVID-19, the sample size is relatively small (<2000 individuals) taken during the early stages of the disease in China. The outbreak is now a pandemic and a more comprehensive assessment is needed to guide public health efforts in making informed decisions to control regional outbreaks. Commonly, R is computed using a sliding window approach, hence assessment of impact of intervention is more difficult to estimate and often underestimates the dynamic nature of R as the outbreak progresses and expands to different regions of the world. Parallel to epidemiological metrics, pathogen whole genome sequencing is being used to infer transmission dynamics. Viral genome analysis requires expert knowledge in understanding viral genomics that can be integrated with the rapid responses needed for public health to advance outbreak mitigation. This study establishes integrative approaches of genome sequencing with established epidemiological outbreak metrics to provide an easily understandable estimate of transmission dynamics aimed at public health response using evidence-based estimates.Added value of this studyEstimates of R are dynamic within the progression of the epidemic curve. Using the framework defined in this study with dynamic estimates of R specific to each epicurve stage combined with whole genome sequencing led to creation of a novel metric called GENI (pathogen genome identity) that provides genomic evolution and variation in the context of the outbreak dynamics. The GENI scores were directly linked and proportional to outbreak changes when using disease incidence from epicurve stages (index, takeoff, exponential, and decline). By simulating short and standard (2 day and 7 day, respectively) serial intervals, we calculated instantaneous R followed by a global comparison that was associated with changes in GENI. This approach quantified R values that are impacted by public health intervention to change the outbreak trajectory and were linked to case incidence (i.e. exponential expansion or decelerating) by country. Integrating viral whole genome sequences to estimate GENI we were able to infer circulation time, local transmission, and index case introduction. Systematic integration of viral whole genome sequences with epidemiological parameters resulted in a simplified approach in assessing the status of outbreak that facilitates decisions using evidence from genomics and epidemiology in combination.Implications of all the available evidenceThis study created a framework of evidence-based intervention by integrating whole genome sequencing and epidemiology during the COVID-19 pandemic. Calculating instantaneous R at different stages of the epicurve for different countries provided an evidence-based assessment of control measures as well as the underlying genomic variation globally that changed the outbreak trajectory for all countries examined. Use of the GENI score translates sequencing data into a public health metric that can be directly integrated in epidemiology for outbreak intervention and global preparedness systems.

scholarly journals PEPR: Pipelines for evaluating prokaryotic references

2015 ◽  
Author(s):  
Nathan D. Olson ◽  
Justin M. Zook ◽  
Daniel V. Samarov ◽  
Scott A. Jackson ◽  
Marc L. Salit
Keyword(s):  
Public Health ◽  
Staphylococcus Aureus ◽  
Genome Sequencing ◽  
Genomic Diversity ◽  
Whole Genome ◽  
Clinical Testing ◽  
Sequencing Data ◽  
Bioinformatics Tool ◽  
Microbial Genomic ◽  
Application Specific

The rapid adoption of microbial whole genome sequencing in public health, clinical testing, and forensic laboratories requires the use of validated measurement processes. Reference materials that are well characterized, homogeneous, and stable can be used to evaluate measurement processes and help to establish confidence in the results. Given the variety of microbial genome sequencing applications and platforms, as well as the vast microbial genomic diversity, there is a need for application-specific genomic materials for method validation. We have developed a reproducible and transparent bioinformatics tool for characterizing prokaryotic genomic materials; ”PEPR”, Pipelines for Evaluating Prokaryotic References. We demonstrate the tool and its output using sequencing data while developing a Staphylococcus aureus candidate genomic reference material.

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