PT  - JOURNAL ARTICLE
AU  - Nguyen Thi Duy Nhat
AU  - Stacy Todd
AU  - Erwin de Bruin
AU  - Tran Thi Nhu Thao
AU  - Nguyen Ha Thao Vy
AU  - Tran Minh Quan
AU  - Dao Nguyen Vinh
AU  - Janko van Beek
AU  - Pham Hong Anh
AU  - Ha Minh Lam
AU  - Nguyen Thanh Hung
AU  - Nguyen Thi Le Thanh
AU  - Huynh Le Anh Huy
AU  - Vo Thi Hong Ha
AU  - Stephen Baker
AU  - Guy E Thwaites
AU  - Nguyen Thi Nam Lien
AU  - Tran Thi Kim Hong
AU  - Jeremy Farrar
AU  - Cameron P Simmons
AU  - Nguyen Van Vinh Chau
AU  - Marion Koopmans
AU  - Maciej F Boni
TI  - Structure of general-population antibody titer distributions to influenza A virus
AID  - 10.1101/090076
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 090076
4099  - http://biorxiv.org/content/early/2016/11/28/090076.short
4100  - http://biorxiv.org/content/early/2016/11/28/090076.full
AB  - Seroepidemiological studies aim to understand population-level exposure and immunity to infectious diseases. Results from serological assays are normally presented as binary outcomes describing the presence or absence of pathogen-specific antibody, despite the fact that many assays measure continuous quantities. A population’s natural distribution of antibody titers to an endemic infectious disease may in fact include information on multiple serological states – e.g. naiveté, recent infection, non-recent infection – depending on the disease in question and the acquisition and waning patterns of host immunity. In this study, we investigate a collection of 20,152 general-population serum samples from southern Vietnam collected between 2009 and 2013 from which we report antibody titers to the influenza virus HA1 protein using a continuous titer measurement from a protein microarray assay. We describe the distributions of antibody titers to subtypes 2009 H1N1 and H3N2. Using a model selection approach to fit mixture distributions, we show that 2009 H1N1 antibody titers fall into four titer subgroups and that H3N2 titers fall into three subgroups. For H1N1, our interpretation is that the two highest-titer subgroups correspond to recent infection and historical infection, which is consistent with 2009 pandemic attack rates. For H3N2, observations censored at the highest titer dilutions make similar interpretations difficult to validate.