| Literature DB >> 36201428 |
Kirsten E Wiens1, Barbara Jauregui2, Benjamin F Arnold3,4, Kathryn Banke5, Djibril Wade6, Kyla Hayford7, Adriana Costero-Saint Denis8, Robert H Hall8, Henrik Salje9, Isabel Rodriguez-Barraquer10,11, Andrew S Azman1,12,13, Guy Vernet2,14, Daniel T Leung15,16.
Abstract
The use of biomarkers to measure immune responses in serum is crucial for understanding population-level exposure and susceptibility to human pathogens. Advances in sample collection, multiplex testing, and computational modeling are transforming serosurveillance into a powerful tool for public health program design and response to infectious threats. In July 2018, 70 scientists from 16 countries met to perform a landscape analysis of approaches that support an integrated serosurveillance platform, including the consideration of issues for successful implementation. Here, we summarize the group's insights and proposed roadmap for implementation, including objectives, technical requirements, ethical issues, logistical considerations, and monitoring and evaluation.Entities:
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Year: 2022 PMID: 36201428 PMCID: PMC9536637 DOI: 10.1371/journal.pntd.0010657
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Published studies for different use-cases of sero-epidemiology by pathogen and source of infection.
Pathogens that could be considered for an integrated platform are listed and grouped by primary source of infections. Ways in which sero-epidemiology has previously been used in surveillance of each pathogen are indicated and accompanied by published examples, including both reviews and primary research articles. The numbers in the table indicate references and the gaps illustrate research or surveillance use-cases where serology has not been applied.
| Primary source of infection | Pathogen for consideration in an integrated platform | Incidence rate estimates from cross-sectional data | Cumulative infection rate estimates (lasting/saturating Abs) | Vaccine vs. natural infection potentially discernible | Cross-sectional correlates of protection | Used for confirming elimination | Multi-pathogen surveillance via multiplex bead assays |
|---|---|---|---|---|---|---|---|
| Blood and/or other bodily fluids |
| [ | [ | [ | |||
| Ebola virus | [ | ||||||
| Hepatitis B virus | [ | [ | |||||
| Hepatitis C virus | |||||||
| HIV | [ | [ | |||||
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| Food, water, and/or soil |
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| Enterotoxigenic | [ | [ | |||||
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| [ | [ | |||||
| Hepatitis A virus | [ | [ | |||||
| Hepatitis E virus | [ | [ | |||||
| Lassa virus | [ | ||||||
| Norovirus | [ | [ | |||||
| Poliovirus | [ | ||||||
| [ | [ | [ | |||||
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| Respiratory droplets and/or aerosols |
| [ | [ | [ | |||
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| Measles | [ | [ | [ | ||||
| Mumps | [ | [ | [ | ||||
| Respiratory syncytial virus | |||||||
| Rhinoviruses | |||||||
| Rubella | [ | [ | [ | ||||
| SARS-CoV-2 | [ | [ | |||||
| Arthropod vectors | Chikungunya virus | [ | [ | [ | [ | ||
| Crimean-Congo hemorrhagic fever virus | [ | ||||||
| Dengue virus | [ | [ | [ | ||||
| Mayaro virus | [ | [ | [ | ||||
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| Vector saliva antigens | |||||||
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| Yellow fever virus | |||||||
| Zika virus | [ |