Evidence map›Paper›PMID 42009019›Full record

Observational studyThe Lancet. Infectious diseases2026

Measuring population immunity against influenza using individual antibody titres: a multicountry, retrospective observational study.

Weijia Xiong, Xiaotong Huang, Tran Thi Nhu Thao, Nguyen Thi Le Thanh, Liping Peng, Ranawaka A P M Perera, Vicky J Fang, Bingyi Yang, Sook-San Wong, Nancy H L Leung and 7 more

Abstract readObservational StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in The Lancet. Infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Weijia XiongWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Xiaotong HuangWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Tran Thi Nhu ThaoOxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Viet Nam.
Nguyen Thi Le ThanhOxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Viet Nam.
Liping PengWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Ranawaka A P M PereraWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Vicky J FangWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Bingyi YangWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Sook-San WongHKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China; Centre for Immunology and Infection, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
Nancy H L LeungWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Sheena G SullivanSchool of Clinical Sciences, Monash University, Melbourne, VIC, Australia.
Dennis K M IpWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Malik PeirisWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Centre for Immunology and Infection, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
Ted M RossCenter for Vaccines and Immunology, Athens, GA, USA; Department of Infectious Diseases, University of Georgia, Athens, GA, USA; Florida Research and Innovation Center, Cleveland Clinic, Port Saint Lucie, FL, USA; Department of Infection Biology, Lehner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
Maciej F BoniOxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Viet Nam; Department of Biology, Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
Benjamin J CowlingWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Tim K TsangWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China. Electronic address: timtsang@connect.hku.hk.

Funding

COVID Supplement - COMPONENT A OF THE COLLABORATIVE INFLUENZA VACCINE INNOVATION CENTERS (CIVICS) PROGRAM TO DESIGN AND EVALUATE INNOVATIVE INFLUENZA VACCINE APPROACHES,75N93019C00052 · NIAID · UNIVERSITY OF GEORGIA · PI ROSS, TED · 2019 to 2025
$74.6M
NIAID NIH HHS 75N93019C00052
6 · The paper itself

Abstract

backgroundMeasuring population immunity is crucial for epidemic preparedness, but methods to translate individual immunity into population-level immunity metrics remain underdeveloped. We aimed to develop and evaluate population immunity estimators using influenza as a model pathogen.

methodsIn this multicountry, retrospective observational study, we analysed 41 835 serum samples from six studies in China, Hong Kong, Viet Nam, and the USA across 27 influenza epidemics in 2009-24. We constructed four population-immunity estimators from individual antibody titres: geometric mean titre, proportion of non-naive individuals, proportion of population immune, and relative reduction in reproductive number calculated using a next-generation matrix framework. We evaluated the ability of these estimators to predict which subtype (H1N1 vs H3N2) would dominate, to predict whether epidemics would be larger or smaller than the previous season, and to correlate with subsequent cumulative incidence in a longitudinal Hong Kong cohort spanning eight influenza seasons with within-epidemic serum collection.

findingsSubtype-specific relative changes in these estimators from previous seasons correctly predicted 57-86% of H1N1-dominant seasons and 100% of H3N2-dominant seasons, with an area under the receiver operating characteristic curve (AUROC) of 79-93%. The estimators correctly predicted larger epidemics in 67-83% of cases and smaller epidemics in 90-100% of cases, with an AUROC of 83-92%. Performance varied by estimator and influenza subtype, with wide uncertainty intervals for some estimates indicating modest precision. In the longitudinal Hong Kong cohort, all four estimators negatively correlated with subsequent 30-day cumulative incidence for H1N1 (Pearson correlations -0·23 to -0·46), whereas H3N2 correlations were mostly non-significant.

interpretationWe developed and validated four complementary population immunity estimators derived from individual antibody titres that showed predictive utility for influenza subtype dominance and epidemic size direction across diverse settings. These estimators could inform seasonal influenza preparedness, surveillance prioritisation, and health-care resource planning.

fundingHong Kong Health Bureau and Research Grants Council.

Indexed as

Antibodies, ViralInfluenza A Virus, H1N1 SubtypeInfluenza, HumanChinaEpidemicsHong KongHumansInfluenza A Virus, H3N2 SubtypeRetrospective StudiesSeasonsUnited StatesVietnamAntibodies, Viral

Identifiers

PMID42009019
PMCPMC13277641

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.