Viral factors in influenza pandemic risk assessment
- Harvard TH Chan School of Public Health, United States
- Imperial College London, United Kingdom
- Massachusetts Institute of Technology, United States
- St Jude Children's Research Hospital, United States
- Centers for Disease Control and Prevention, United States
- University of Chicago, United States
- University of Virginia, United States
- University of California, Los Angeles, United States
- Agency for Science, Technology and Research, Singapore
- Ryerson University, Canada
- Fred Hutchinson Cancer Research Center, United States
- University of Wisconsin School of Veterinary Medicine, United States
- University of Georgia, United States
- Erasmus Medical Center, Netherlands
- MRC-University of Glasgow Centre For Virus Research, United Kingdom
- Institut de Recherche pour le Développement, France
- The University of Texas at Austin, United States
- University of Cambridge, United Kingdom
Abstract
The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.
Article and author information
Author details
James O Lloyd-Smith
Catherine AA Beauchemin
Funding
National Health and Medical Research Council (12/1/06/24/5793)
- Sebastian Maurer-Stroh
Wellcome (200861/Z/16/Z)
- Steven Riley
Medical Research Council (MR/J008761/1)
- Steven Riley
National Institute of General Medical Sciences (MIDAS U01 GM110721-01)
- Steven Riley
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VIDI grant 91715372)
- Sander Herfst
Agency for Science, Technology and Research (12/1/06/24/5793)
- Sebastian Maurer-Stroh
National Institute of Allergy and Infectious Diseases (Centers of Excellence for Influenza Research and Surveillance (Contract HHSN272201400006C))
- Charles J Russell
National Institutes of Health (R01 GM088344)
- Claus O Wilke
National Institutes of Health (R01 GM098304)
- Peter M Kasson
Royal Society (University Research Fellowship)
- Colin A Russell
Medical Research Council (G0801822)
- Pablo R Murcia
Wellcome (Project 093488/Z/10/Z)
- Steven Riley
Wellcome (200187/Z/15/Z)
- Steven Riley
National Institute of General Medical Sciences (MIDAS Center of Excellence Cooperative Agreement U54GM088558)
- Marc Lipsitch
Natural Sciences and Engineering Research Council of Canada (Discovery Grant (355837-2013))
- Catherine AA Beauchemin
Ministry of Research and Innovation (Early Researcher Award Award (ER13-09-040))
- Catherine AA Beauchemin
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
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Viral factors in influenza pandemic risk assessment
eLife 5:e18491.
https://doi.org/10.7554/eLife.18491
Further reading
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- Epidemiology and Global Health
- Microbiology and Infectious Disease
Background:
In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.
Methods:
We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).
Results:
275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.
Conclusions:
In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.
Funding:
This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).
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- Epidemiology and Global Health
Background:
The role of circulating metabolites on child development is understudied. We investigated associations between children’s serum metabolome and early childhood development (ECD).
Methods:
Untargeted metabolomics was performed on serum samples of 5004 children aged 6–59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children’s milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥1. The interaction between significant metabolites and the child’s age was tested.
Results:
Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child’s nutritional status, diet quality, and infant age. Cresol sulfate (β=–0.07; adjusted-p <0.001), hippuric acid (β=–0.06; adjusted-p <0.001), phenylacetylglutamine (β=–0.06; adjusted-p <0.001), and trimethylamine-N-oxide (β=–0.05; adjusted-p=0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged –1 SD: β=–0.05; pP=0.01;+1 SD: β=0.05; p=0.02) and methylhistidine (–1 SD: β = - 0.04; p=0.04;+1 SD: β=0.04; p=0.03).
Conclusions:
Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays.
Funding:
Supported by the Brazilian Ministry of Health and the Brazilian National Research Council.
