@article {Nhat090076, author = {Nguyen Thi Duy Nhat and Stacy Todd and Erwin de Bruin and Tran Thi Nhu Thao and Nguyen Ha Thao Vy and Tran Minh Quan and Dao Nguyen Vinh and Janko van Beek and Pham Hong Anh and Ha Minh Lam and Nguyen Thanh Hung and Nguyen Thi Le Thanh and Huynh Le Anh Huy and Vo Thi Hong Ha and Stephen Baker and Guy E Thwaites and Nguyen Thi Nam Lien and Tran Thi Kim Hong and Jeremy Farrar and Cameron P Simmons and Nguyen Van Vinh Chau and Marion Koopmans and Maciej F Boni}, title = {Structure of general-population antibody titer distributions to influenza A virus}, elocation-id = {090076}, year = {2016}, doi = {10.1101/090076}, publisher = {Cold Spring Harbor Laboratory}, abstract = {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{\textquoteright}s natural distribution of antibody titers to an endemic infectious disease may in fact include information on multiple serological states {\textendash} e.g. naivet{\'e}, recent infection, non-recent infection {\textendash} 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.}, URL = {https://www.biorxiv.org/content/early/2016/11/28/090076}, eprint = {https://www.biorxiv.org/content/early/2016/11/28/090076.full.pdf}, journal = {bioRxiv} }