Genome informatics of influenza A: from data sharing to shared analytical capabilities

2010 ◽  
Vol 11 (1) ◽  
pp. 73-79 ◽  
Author(s):  
Daniel A. Janies ◽  
Igor O. Voronkin ◽  
Manirupa Das ◽  
Jori Hardman ◽  
Travis W. Treseder ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Data Sharing ◽  
Influenza A ◽  
Sequence Data ◽  
Emerging Infectious Diseases ◽  
Health Science ◽  
Wide Audience ◽  
Science And Policy ◽  
Animal Populations

AbstractEmerging infectious diseases are critical issues of public health and the economic and social stability of nations. As demonstrated by the international response to the severe acute respiratory syndrome (SARS) and influenza A, rapid genomic sequencing is a crucial tool to understand diseases that occur at the interface of human and animal populations. However, our ability to make sense of sequence data lags behind our ability to acquire the data. The potential of sequence data on pathogens is not fully realized until raw data are translated into public health intelligence. Sequencing technologies have become highly mechanized. If the political will for data sharing remains strong, the frontier for progress in emerging infectious diseases will be in analysis of sequence data and translation of results into better public health science and policy. For example, applying analytical tools such as Supramap (http://supramap.osu.edu) to genomic data for pathogens, public health scientists can track specific mutations in pathogens that confer the ability to infect humans or resist drugs. The results produced by the Supramap application are compelling visualizations of pathogen lineages and features mapped into geographic information systems that can be used to test hypotheses and to follow the spread of diseases across geography and hosts and communicate the results to a wide audience.

scholarly journals Ocular manifestations of emerging viral diseases

Eye ◽  
2021 ◽  
Author(s):  
Ashwin Venkatesh ◽  
Ravi Patel ◽  
Simran Goyal ◽  
Timothy Rajaratnam ◽  
Anant Sharma ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Influenza A ◽  
Emerging Infectious Diseases ◽  
Global Scale ◽  
Viral Diseases ◽  
Valley Fever ◽  
Ocular Manifestations ◽  
Influenza A H1n1 ◽  
Emerging Viral Diseases

AbstractEmerging infectious diseases (EIDs) are an increasing threat to public health on a global scale. In recent times, the most prominent outbreaks have constituted RNA viruses, spreading via droplets (COVID-19 and Influenza A H1N1), directly between humans (Ebola and Marburg), via arthropod vectors (Dengue, Zika, West Nile, Chikungunya, Crimean Congo) and zoonotically (Lassa fever, Nipah, Rift Valley fever, Hantaviruses). However, specific approved antiviral therapies and vaccine availability are scarce, and public health measures remain critical. Patients can present with a spectrum of ocular manifestations. Emerging infectious diseases should therefore be considered in the differential diagnosis of ocular inflammatory conditions in patients inhabiting or returning from endemic territories, and more general vigilance is advisable in the context of a global pandemic. Eye specialists are in a position to facilitate swift diagnosis, improve clinical outcomes, and contribute to wider public health efforts during outbreaks. This article reviews those emerging viral diseases associated with reports of ocular manifestations and summarizes details pertinent to practicing eye specialists.

scholarly journals Quantifying Pathogen Surveillance Using Temporal Genomic Data

mBio ◽  
2013 ◽  
Vol 4 (1) ◽  
Author(s):  
Joseph M. Chan ◽  
Raul Rabadan
Keyword(s):  
Public Health ◽  
Influenza A ◽  
Evolutionary Rate ◽  
Sequence Data ◽  
Quantitative Measure ◽  
Health Policies ◽  
West Nile ◽  
Public Health Policies ◽  
Sequence Collection ◽  
Animal Populations

ABSTRACTWith the advent of deep sequencing, genomic surveillance has become a popular method for detection of infectious disease, supplementing information gathered by classic clinical or serological techniques to identify host-determinant markers and trace the origin of transmission. However, two main factors complicate genomic surveillance. First, pathogens exhibiting high genetic diversity demand higher levels of scrutiny to obtain an accurate representation of the entire population. Second, current systems of detection are nonuniform, with significant gaps in certain geographic locations and animal reservoirs. Despite past unforeseen pandemics like the 2009 swine-origin H1N1 influenza virus, there is no standardized way of evaluating surveillance. A more complete surveillance system should capture a greater proportion of pathogen diversity. Here we present a novel quantitative method of assessing the completeness of genomic surveillance that incorporates the time of sequence collection, as well as the pathogen’s evolutionary rate. We propose theq2 coefficient, which measures the proportion of sequenced isolates whose closest neighbor in the past is within a genetic distance equivalent to 2 years of evolution, roughly the median time of changing strain selection for influenza A vaccines. Easily interpretable and significantly faster than other methods, theq2 coefficient requires no full phylogenetic characterization or use of arbitrary clade definitions. Application of theq2 coefficient to influenza A virus confirmed poor sampling of swine and avian populations and identified regions with deficient surveillance. We demonstrate that theq2 coefficient can not only be applied to other pathogens, including dengue and West Nile viruses, but also used to describe surveillance dynamics, particularly the effects of different public health policies.IMPORTANCESurveillance programs have become key assets in determining the emergence or prevalence of pathogens circulating in human and animal populations. Genomic surveillance, in particular, provides comprehensive information on the history of isolates and potential molecular markers for infectivity and pathogenicity. Current techniques for evaluating genomic surveillance are inaccurate, ignoring the pathogen’s evolutionary rate and biodiversity, as well as the timing of sequence collection. Using sequence data, we propose theq2 coefficient as a quantitative measure of surveillance completeness that combines elements of time and evolution without defining arbitrary criteria for clades or species. Through several case studies of influenza A, dengue, and West Nile viruses, we employed theq2 coefficient to identify sampling deficiencies in different host species and locations, as well as examine the effects of different public health policies through historical records of theq2 coefficient. These results can guide public health agencies to focus resource allocation and virus collection to bolster specific problems in surveillance.

scholarly journals Active surveillance of acute paediatric hospitalisations demonstrates the impact of vaccination programmes and informs vaccine policy in Canada and Australia

2020 ◽  
Vol 25 (25) ◽  
Author(s):  
Karina A Top ◽  
Kristine Macartney ◽  
Julie A Bettinger ◽  
Ben Tan ◽  
Christopher C Blyth ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Active Surveillance ◽  
Influenza A ◽  
Monitoring Program ◽  
Emerging Infectious Diseases ◽  
Emerging Infections ◽  
Public Health Response ◽  
Influenza A H1n1 ◽  
The Impact

Sentinel surveillance of acute hospitalisations in response to infectious disease emergencies such as the 2009 influenza A(H1N1)pdm09 pandemic is well described, but recognition of its potential to supplement routine public health surveillance and provide scalability for emergency responses has been limited. We summarise the achievements of two national paediatric hospital surveillance networks relevant to vaccine programmes and emerging infectious diseases in Canada (Canadian Immunization Monitoring Program Active; IMPACT from 1991) and Australia (Paediatric Active Enhanced Disease Surveillance; PAEDS from 2007) and discuss opportunities and challenges in applying their model to other contexts. Both networks were established to enhance capacity to measure vaccine preventable disease burden, vaccine programme impact, and safety, with their scope occasionally being increased with emerging infectious diseases’ surveillance. Their active surveillance has increased data accuracy and utility for syndromic conditions (e.g. encephalitis), pathogen-specific diseases (e.g. pertussis, rotavirus, influenza), and adverse events following immunisation (e.g. febrile seizure), enabled correlation of biological specimens with clinical context and supported responses to emerging infections (e.g. pandemic influenza, parechovirus, COVID-19). The demonstrated long-term value of continuous, rather than incident-related, operation of these networks in strengthening routine surveillance, bridging research gaps, and providing scalable public health response, supports their applicability to other countries.

Biosecurity and Public Health Ethics Issues Raised by Biological Threats

2019 ◽  
pp. 773-785
Author(s):  
Nicholas Evans ◽  
Thomas Inglesby
Keyword(s):  
Public Health ◽  
Resource Allocation ◽  
Infectious Diseases ◽  
Ethical Issues ◽  
Emerging Infectious Diseases ◽  
Biological Weapon ◽  
Ethical Values ◽  
Dual Use ◽  
Health Concerns ◽  
Trade Offs

This chapter introduces ethical issues that arise in the context of biosecurity: policies and actions intended to prevent the development or emergence, or mitigate the consequences, of serious biological threats. These threats could include deliberate biological weapon attacks (bioterrorism), pandemics, emerging infectious diseases, or major laboratory accidents. The basic values that underpin these public health concerns are first introduced. Ethical issues that arise before, during, and following a biosecurity crisis are then examined, including issues of resource allocation, dual-use research, and the possibility of quarantine. Their resolution requires trade-offs among different ethical values, including utility, fairness, and liberty.

Enhancing Student Learning on Emerging Infectious Diseases: An Ebola Exemplar

2018 ◽  
Vol 80 (7) ◽  
pp. 493-500
Author(s):  
Derek Dube ◽  
Tracie M. Addy ◽  
Maria R. Teixeira ◽  
Linda M. Iadarola
Keyword(s):  
Infectious Diseases ◽  
Undergraduate Students ◽  
Ebola Virus ◽  
Influenza Pandemic ◽  
Emerging Infectious Diseases ◽  
Health Science ◽  
Science Courses ◽  
Study Approach ◽  
Mode Of Instruction

Throughout global history, various infectious diseases have emerged as particularly relevant within an era. Some examples include the Bubonic plague of the fourteenth century, the Spanish Influenza pandemic of 1918, the HIV epidemic of the 1980s, and the Zika virus outbreak in 2015–16. These instances of emerging infectious disease represent ideal opportunities for timely, relevant instruction in natural and health science courses through case studies. Such instructional approaches can promote student engagement in the material and encourage application and higher-order thinking. We describe here how the case study approach was utilized to teach students about emerging infectious diseases using the 2014–16 Ebola virus outbreak as the subject of instruction. Results suggest that students completing the case study not only had positive perceptions of the mode of instruction, but also realized learning gains and misconception resolution. These outcomes support the efficacy of case pedagogy as a useful teaching tool in emerging infectious diseases, and augment the paucity of literature examining Ebola virus knowledge and misconceptions among undergraduate students within United States institutions.

scholarly journals Taiwan’s Successful COVID-19 Mitigation and Containment Strategy: Achieving Quasi Population Immunity

2020 ◽  
pp. 1-4 ◽  
Author(s):  
Li-Chien Chien ◽  
Christian K. Beÿ ◽  
Kristi L. Koenig
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Health Management ◽  
Mainland China ◽  
Emerging Infectious Diseases ◽  
Contact Tracing ◽  
Population Immunity ◽  
Containment Strategy ◽  
Local Transmission ◽  
Pharmaceutical Interventions

ABSTRACT The authors describe Taiwan’s successful strategy in achieving control of coronavirus disease (COVID-19) without economic shutdown, despite the prediction that millions of infections would be imported from travelers returning from Chinese New Year celebrations in Mainland China in early 2020. As of September 2, 2020, Taiwan reports 489 cases, 7 deaths, and no locally acquired COVID-19 cases for the last 135 days (greater than 4 months) in its population of over 23.8 million people. Taiwan created quasi population immunity through the application of established public health principles. These non-pharmaceutical interventions, including public masking and social distancing, coupled with early and aggressive identification, isolation, and contact tracing to inhibit local transmission, represent a model for optimal public health management of COVID-19 and future emerging infectious diseases.

scholarly journals When might Host Heterogeneity Drive the Evolution of Asymptomatic, Pandemic Coronaviruses?

2020 ◽  
Author(s):  
Kenichi W. Okamoto ◽  
Virakbott Ong ◽  
Robert G. Wallace ◽  
Rodrick Wallace ◽  
Luis Fernando Chaves
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Disease Control ◽  
Disease Surveillance ◽  
Fitness Landscape ◽  
Emerging Infectious Diseases ◽  
Disease Suppression ◽  
Contact Tracing ◽  
Pathogen Strains ◽  
Host Heterogeneity

For most emerging infectious diseases, including SARS-Coronavirus-2 (SARS-CoV-2), pharmaceutical intervensions such as drugs and vaccines are not available, and disease surveillance followed by isolating, contact-tracing and quarantining infectious individuals is critical for controlling outbreaks. These interventions often begin by identifying symptomatic individuals. However, by actively removing pathogen strains likely to be symptomatic, such interventions may inadvertently select for strains less likely to result in symptomatic infections. Additionally, the pathogen's fitness landscape is structured around a heterogeneous host pool. In particular, uneven surveillance efforts and distinct transmission risks across host classes can drastically alter selection pressures. Here we explore this interplay between evolution caused by disease control efforts, on the one hand, and host heterogeneity in the efficacy of public health interventions on the other, on the potential for a less symptomatic, but widespread, pathogen to evolve. We use an evolutionary epidemiology model parameterized for SARS-CoV-2, as the widespread potential for silent transmission by asymptomatic hosts has been hypothesized to account, in part, for its rapid global spread. We show that relying on symptoms-driven reporting for disease control ultimately shifts the pathogen's fitness landscape and can cause pandemics. We find such outcomes result when isolation and quarantine efforts are intense, but insufficient for suppression. We further show that when host removal depends on the prevalence of symptomatic infections, intense isolation efforts can select for the emergence and extensive spread of more asymptomatic strains. The severity of selection pressure on pathogens caused by these interventions likely lies somewhere between the extremes of no intervention and thoroughly successful eradication. Identifying the levels of public health responses that facilitate selection for asymptomatic pathogen strains is therefore critical for calibrating disease suppression and surveillance efforts and for sustainably managing emerging infectious diseases.

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