Using serological measures to estimate influenza incidence in the presence of secular trends in exposure and immuno-modulation of antibody response.


Journal

Influenza and other respiratory viruses
ISSN: 1750-2659
Titre abrégé: Influenza Other Respir Viruses
Pays: England
ID NLM: 101304007

Informations de publication

Date de publication:
03 2021
Historique:
received: 08 06 2020
revised: 24 08 2020
accepted: 30 08 2020
pubmed: 28 10 2020
medline: 26 11 2021
entrez: 27 10 2020
Statut: ppublish

Résumé

Influenza infection is often measured by a fourfold antibody titer increase over an influenza season (ie seroconversion). However, this approach may fail when influenza seasons are less distinct as it does not account for transient effects from recent infections. Here, we present a method to determine seroconversion for non-paired sera, adjusting for changes in individuals' antibody titers to influenza due to the transient impact of recent exposures, varied sampling times, and laboratory processes. We applied our method using data for five H3N2 strains collected from 942 individuals, aged 2-90 years, during the first two study visits of the Fluscape cohort study (2009-2012) in Guangzhou, China. After adjustment, apparent seroconversion rates for non-circulating strains decreased while we observed a 20% increase in seroconversion rates to recently circulating strains. When examining seroconversion to the most recently circulating strain (A/Brisbane/20/2007) in our study, participants aged under 18, and over 64 had the highest seroconversion rates compared to other age groups. Our results highlight the need for improved methods when using antibody titers as an endpoint in settings where there is no clear influenza "off" season. Methods, like those presented here, that use titers from circulating and non-circulating strains may be key.

Sections du résumé

BACKGROUND
Influenza infection is often measured by a fourfold antibody titer increase over an influenza season (ie seroconversion). However, this approach may fail when influenza seasons are less distinct as it does not account for transient effects from recent infections. Here, we present a method to determine seroconversion for non-paired sera, adjusting for changes in individuals' antibody titers to influenza due to the transient impact of recent exposures, varied sampling times, and laboratory processes.
METHODS
We applied our method using data for five H3N2 strains collected from 942 individuals, aged 2-90 years, during the first two study visits of the Fluscape cohort study (2009-2012) in Guangzhou, China.
RESULTS
After adjustment, apparent seroconversion rates for non-circulating strains decreased while we observed a 20% increase in seroconversion rates to recently circulating strains. When examining seroconversion to the most recently circulating strain (A/Brisbane/20/2007) in our study, participants aged under 18, and over 64 had the highest seroconversion rates compared to other age groups.
CONCLUSIONS
Our results highlight the need for improved methods when using antibody titers as an endpoint in settings where there is no clear influenza "off" season. Methods, like those presented here, that use titers from circulating and non-circulating strains may be key.

Identifiants

pubmed: 33108707
doi: 10.1111/irv.12807
pmc: PMC7902255
doi:

Substances chimiques

Antibodies, Viral 0
Influenza Vaccines 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

235-244

Subventions

Organisme : FIC NIH HHS
ID : R01 TW008246
Pays : United States
Organisme : NIA NIH HHS
ID : R56 AG048075
Pays : United States
Organisme : Wellcome Trust
ID : 200861/Z/16/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/J008761/1
Pays : United Kingdom
Organisme : NIGMS NIH HHS
ID : U01 GM110721
Pays : United States
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom

Informations de copyright

© 2020 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.

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Auteurs

Talia M Quandelacy (TM)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Derek A T Cummings (DAT)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Department of Biology, University of Florida, Gainesville, FL, USA.

Chao Qiang Jiang (CQ)

Guangzhou No. 12 Hospital, Guangzhou, China.

Bingyi Yang (B)

Department of Biology, University of Florida, Gainesville, FL, USA.

Kin On Kwok (KO)

The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Stanley Ho Centre for Emerging Infectious Diseases, Hong Kong Special Administrative Region, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.

Byran Dai (B)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Ruiyin Shen (R)

Guangzhou No. 12 Hospital, Guangzhou, China.

Jonathan M Read (JM)

Center for Health Informatics Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UK.
Institute of Infection and Global Health, University of Liverpool, Liverpool, UK.

Huachen Zhu (H)

State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong, China.
Shantou University Medical College, Shantou, China.

Yi Guan (Y)

Shantou University Medical College, Shantou, China.
School of Public Health, Imperial College London, London, UK.

Steven Riley (S)

School of Public Health, Imperial College London, London, UK.

Justin Lessler (J)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

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