scholarly journals Know Thine Enemy: Viral Genome Sequencing in Outbreaks

2020 ◽  
pp. 34-37
Author(s):  
Katherine Colvin
Keyword(s):  
Public Health ◽  
Vaccine Development ◽  
Treatment Options ◽  
Epidemiologic Study ◽  
Latency Period ◽  
Contact Tracing ◽  
Genomic Sequencing ◽  
Remote Communities ◽  
Public Health Response ◽  
Health Measures

CONTAINING a viral outbreak with public health measures firstly requires identification of the causative virus, followed by more detailed understanding of viral features. Genomic sequencing provides exhaustive insight into viral features that may help predict outbreak behaviours, assist in diagnosis and tracking, and shape treatment and vaccination strategies. When coupled with epidemiologic study of outbreak data, viral genomic sequencing can be used to direct public health measures and increase the speed of understanding compared to epidemiology alone. Community spread of cases can be used to guide mathematic models and contact tracing of viral outbreaks for public health response. However, epidemiologic data alone better suits responses to low-prevalence and less-widespread outbreaks. Where pathogens have a longer latency period or spread affects rural and remote communities, features of the virus itself must be considered in determining the response. Genotypic and phenotypic characteristics, identified using molecular biology tools, can clarify the type and strain of a virus responsible for an outbreak, and inform and improve case diagnosis, treatment options, and vaccine development, as well as improve tracing accuracy.1

scholarly journals Ethics of instantaneous contact tracing using mobile phone apps in the control of the COVID-19 pandemic

2020 ◽  
Vol 46 (7) ◽  
pp. 427-431 ◽  
Author(s):  
Michael J Parker ◽  
Christophe Fraser ◽  
Lucie Abeler-Dörner ◽  
David Bonsall
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Mobile Phone ◽  
Public Health Practice ◽  
Disease Outbreaks ◽  
Contact Tracing ◽  
Mobile Phone Data ◽  
Public Health Response ◽  
Infectious Disease Outbreaks ◽  
Ethical Implications

In this paper we discuss ethical implications of the use of mobile phone apps in the control of the COVID-19 pandemic. Contact tracing is a well-established feature of public health practice during infectious disease outbreaks and epidemics. However, the high proportion of pre-symptomatic transmission in COVID-19 means that standard contact tracing methods are too slow to stop the progression of infection through the population. To address this problem, many countries around the world have deployed or are developing mobile phone apps capable of supporting instantaneous contact tracing. Informed by the on-going mapping of ‘proximity events’ these apps are intended both to inform public health policy and to provide alerts to individuals who have been in contact with a person with the infection. The proposed use of mobile phone data for ‘intelligent physical distancing’ in such contexts raises a number of important ethical questions. In our paper, we outline some ethical considerations that need to be addressed in any deployment of this kind of approach as part of a multidimensional public health response. We also, briefly, explore the implications for its use in future infectious disease outbreaks.

scholarly journals A Second-Order Disaster? Digital Technologies During the COVID-19 Pandemic

2020 ◽  
Vol 6 (3) ◽  
pp. 205630512094816
Author(s):  
Mirca Madianou
Keyword(s):  
Public Health ◽  
Social Inequalities ◽  
Digital Technologies ◽  
Second Order ◽  
Contact Tracing ◽  
Remote Work ◽  
Public Health Response ◽  
Marginalized Communities ◽  
Health Response ◽  
The One

One of the most striking features of the COVID-19 pandemic in the United Kingdom has been the disproportionate way in which it has affected Black, Asian, ethnic minority, and working class people. In this article, I argue that digital technologies and data practices in the response to COVID-19 amplify social inequalities, which are already accentuated by the pandemic, thus leading to a “second-order disaster”—a human-made disaster which further traps disadvantaged people into precarity. Inequalities are reproduced both in the everyday uses of technology for distance learning and remote work as well as in the public health response. Applications such as contact tracing apps raise concerns about “function creep”—the reuse of data for different purposes than the one for which they were originally collected—while they normalize surveillance which has been traditionally used on marginalized communities. The outsourcing of the digital public health response consolidates the arrival of the privatized digital welfare state, which increases risks of potential discrimination.

Situating ‘careful surveillance’

2021 ◽  
pp. 136787792199745
Author(s):  
Mark Andrejevic ◽  
Hugh Davies ◽  
Ruth DeSouza ◽  
Larissa Hjorth ◽  
Ingrid Richardson
Keyword(s):  
Public Health ◽  
Public Space ◽  
Social Care ◽  
Cultural Practices ◽  
Contact Tracing ◽  
Social Distancing ◽  
Health Measures ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship

In this article we explore preliminary findings from the study COVIDSafe and Beyond: Perceptions and Practices conducted in Australia in 2020. The study involved a survey followed by interviews, and aimed to capture the dynamic ways in which members of the Australian public perceive the impact of Covid practices – especially public health measures like the introduction of physical and social distancing, compulsory mask wearing, and contact tracing. In the rescripting of public space, different notions of formal and informal surveillance, along with different textures of mediated and social care, appeared. In this article, we explore perceptions around divergent forms of surveillance across social, technological, governmental modes, and the relationship of surveillance to care in our media and cultural practices. What does it mean to care for self and others during a pandemic? How does care get enacted in, and through, media interfaces and public interaction?

scholarly journals MicrobeTrace: Retooling Molecular Epidemiology for Rapid Public Health Response

2020 ◽  
Author(s):  
Ellsworth M. Campbell ◽  
Anthony Boyles ◽  
Anupama Shankar ◽  
Jay Kim ◽  
Sergey Knyazev ◽  
...  
Keyword(s):  
Public Health ◽  
Molecular Epidemiology ◽  
Spanning Trees ◽  
Healthcare Providers ◽  
Contact Tracing ◽  
Surveillance Systems ◽  
Multiple Sources ◽  
Public Health Response ◽  
Link Type ◽  
Novel Approach

AbstractMotivationOutbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions.ResultsWe developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. Using publicly available HIV sequences and other data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020.Availability and ImplementationMicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully-operational without an internet connection. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. The source code is available at https://github.com/cdcgov/[email protected]

scholarly journals Lessons Learned From COVID-19 Contact Tracing During a Public Health Emergency: A Prospective Implementation Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Tyler Shelby ◽  
Christopher Schenck ◽  
Brian Weeks ◽  
Justin Goodwin ◽  
Rachel Hennein ◽  
...  
Keyword(s):  
Public Health ◽  
Incomplete Information ◽  
Median Time ◽  
Intraclass Correlation ◽  
Contact Tracing ◽  
Successful Implementation ◽  
Adjusted Relative Risk ◽  
Implementation Study ◽  
Public Health Response ◽  
Implementation Framework

Background: Contact tracing is a core element of the public health response to emerging infectious diseases including COVID-19. Better understanding the implementation context of contact tracing for pandemics, including individual- and systems-level predictors of success, is critical to preparing for future epidemics.Methods: We carried out a prospective implementation study of an emergency volunteer contact tracing program established in New Haven, Connecticut between April 4 and May 19, 2020. We assessed the yield and timeliness of case and contact outreach in reference to CDC benchmarks, and identified individual and programmatic predictors of successful implementation using multivariable regression models. We synthesized our findings using the RE-AIM implementation framework.Results: Case investigators interviewed only 826 (48%) of 1,705 cases and were unable to reach 545 (32%) because of incomplete information and 334 (20%) who missed or declined repeated outreach calls. Contact notifiers reached just 687 (28%) of 2,437 reported contacts, and were unable to reach 1,597 (66%) with incomplete information and 153 (6%) who missed or declined repeated outreach calls. The median time-to-case-interview was 5 days and time-to-contact-notification 8 days. However, among notified contacts with complete time data, 457 (71%) were reached within 6 days of exposure. The least likely groups to be interviewed were elderly (adjusted relative risk, aRR 0.74, 95% CI 0.61–0.89, p = 0.012, vs. young adult) and Black/African-American cases (aRR 0.88, 95% CI 0.80–0.97, pairwise p = 0.01, vs. Hispanic/Latinx). However, ties between cases and their contacts strongly influenced contact notification success (Intraclass Correlation Coefficient (ICC) 0.60). Surging caseloads and high volunteer turnover (case investigator n = 144, median time from sign-up to retirement from program was 4 weeks) required the program to supplement the volunteer workforce with paid public health nurses.Conclusions: An emergency volunteer-run contact tracing program fell short of CDC benchmarks for time and yield, largely due to difficulty collecting the information required for outreach to cases and contacts. To improve uptake, contact tracing programs must professionalize the workforce; better integrate testing and tracing services; capitalize on positive social influences between cases and contacts; and address racial and age-related disparities through enhanced community engagement.

scholarly journals MicrobeTrace: Retooling molecular epidemiology for rapid public health response

2021 ◽  
Vol 17 (9) ◽  
pp. e1009300 ◽  
Author(s):  
Ellsworth M. Campbell ◽  
Anthony Boyles ◽  
Anupama Shankar ◽  
Jay Kim ◽  
Sergey Knyazev ◽  
...  
Keyword(s):  
Public Health ◽  
Molecular Epidemiology ◽  
Spanning Trees ◽  
Healthcare Providers ◽  
Contact Tracing ◽  
Surveillance Systems ◽  
Multiple Sources ◽  
Public Health Response ◽  
Link Type ◽  
Novel Approach

Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email [email protected] for support. The source code is available at https://github.com/cdcgov/microbetrace.

scholarly journals Investigating the first wave of the COVID-19 pandemic in Ukraine using epidemiological and genomic sequencing data

2021 ◽  
Author(s):  
Yuriy Gankin ◽  
Vladimir Koniukhovskii ◽  
Alina Nemira ◽  
Gerardo Chowell ◽  
Thomas A. Weppelmann ◽  
...  
Keyword(s):  
Public Health ◽  
Genomic Data ◽  
World Health ◽  
Viral Population ◽  
Genomic Sequencing ◽  
Sequencing Data ◽  
Population Number ◽  
The Public ◽  
Health Measures ◽  
The Impact

AbstractThe novel coronavirus SARS-CoV-2 emerged in China in December 2019 and has rapidly spread around the globe. The World Health Organization declared COVID-19 a pandemic in March 2020 just three months after the introduction of the virus. Individual nations have implemented and enforced with varying degrees of success a variety of social distancing interventions to slow the virus spread. Investigating the role of non-pharmaceutical interventions on COVID-19 transmission in different settings is an important research. While most transmission modeling studies have focused on the dynamics in China, neighboring Asian counties, Western Europe, and North America, there is a scarcity of studies for Eastern Europe. This study starts to fill this gap by analyzing the characteristics of the first epidemic wave in Ukraine using mathematical and statistical models together with epidemiological and genomic sequencing data. Using an agent-based model, the trajectory of the first wave in terms of cases and deaths and explore the impact of quarantine strategies via simulation studies have been characterized. The implemented stochastic model for epidemic counts suggests, that even a small delay of weeks could have increased the number of cases by up to 50%, with the potential to overwhelm hospital systems. The genomic data analysis suggests that there have been multiple introductions of SARS-CoV-2 into Ukraine during the early stages of the epidemic with eight distinct transmission clusters identified. The basic reproduction number for the epidemic has been estimated independently both from case counts data and from genomic data. The findings support the hypothesis that, the public health measures did not have a decreasing effect on the existing viral population number at the time of implementation, since strains were detected after the quarantine date. However, the public health measures did help to prevent the appearance of new (and potentially more virulent) SARS-CoV-2 variants in Ukraine.

scholarly journals Genomic Epidemiology of the Los Angeles COVID-19 Outbreak

2021 ◽  
Author(s):  
Longhua Guo​ ◽  
James Boocock​ ◽  
Evann E. Hilt​ ◽  
Sukantha Chandrasekaran​ ◽  
Yi Zhang​ ◽  
...  
Keyword(s):  
Public Health ◽  
Los Angeles ◽  
Severe Acute Respiratory Syndrome ◽  
Genome Sequencing ◽  
Transmission Rate ◽  
Washington State ◽  
Public Health Response ◽  
Viral Genomes ◽  
The Public ◽  
Health Measures

Abstract Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global disruption to human health and activity. Being able to trace the early outbreak of SARS-CoV-2 within a locality will inform public health measures and provide insights to contain or prevent the viral transmission to save lives. Investigation of the transmission history requires efficient sequencing methods and analytic strategy, which can be generally useful in the study of viral outbreaks. Methods Los Angeles (LA) County has sustained a large outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To learn about the transmission history, we carried out surveillance viral genome sequencing to determine 142 viral genomes from unique patients seeking care at UCLA Health System. 86 of these genomes are from samples collected before April 19, 2020. Results We found that the early outbreak in LA, as in other international air travel hubs, was seeded by multiple introductions of strains from Asia and Europe. We identified a US-specific strain, B.1.43, which has been found predominantly in California and Washington State. While samples from LA County carry the ancestral B.1.43 genome, viral genomes from neighboring counties in California and from counties in Washington State carry additional mutations, suggesting a potential origin of B.1.43 in Southern California. We quantified the transmission rate of SARS-CoV-2 over time, and found evidence that the public health measures put in place in LA County to control the virus were effective at preventing transmission, but may have been undermined by the many introductions of SARS-CoV-2 into the region. Conclusion Our work demonstrates that genome sequencing can be a powerful tool for investigating outbreaks and informing the public health response. Our results reinforce the critical need for the U.S. to have coordinated inter-state responses to the pandemic.

scholarly journals Prevalence of asymptomatic COVID-19 infection using a seroepidemiological survey

2020 ◽  
Vol 148 ◽  
Author(s):  
M. Shakiba ◽  
M. Nazemipour ◽  
A. Heidarzadeh ◽  
M. A. Mansournia
Keyword(s):  
Public Health ◽  
Rapid Test ◽  
Asymptomatic Infection ◽  
Mitigation Strategy ◽  
Contact Tracing ◽  
Cross Sectional ◽  
Health Measures ◽  
Critical Measure ◽  
History Of ◽  
Guilan Province

Abstract The prevalence of asymptomatic infection by coronavirus disease 2019 (COVID-19) as a critical measure for effectiveness of mitigation strategy has been reported to be widely varied. In this study, we aimed to determine the prevalence of asymptomatic infection using serosurvey on general population. In a cross-sectional seroprevalence survey in Guilan province, Iran, the specific antibody against COVID-19 in a representative sample was detected using rapid test kits. Among 117 seropositive subjects, prevalence of asymptomatic infection was determined based on the history of symptoms during the preceding 3 months. The design-adjusted prevalence of asymptomatic infection was 57.2% (95% confidence interval (CI) 44–69). The prevalence was significantly lower in subjects with previous contacts to COVID-19 patients (12%, 95% CI 2–49) than others without (69%, 95% CI, 46–86). The lowest prevalence was for painful body symptom (74.4%). This study revealed that more than half of the infected COVID-19 patients had no symptoms. The implications of our findings include the importance of adopting public health measures such as social distancing and inefficiency of contact tracing to interrupt epidemic transmission.

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