2021
DOI: 10.1101/2021.01.03.21249160
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Age-seroprevalence curves for the multi-strain structure of influenza A virus

Abstract: The relationship between age and seroprevalence provides the simplest and least expensive approach to computing the annual attack rate of an infectious disease. However, many pathogens circulate as multiple serologically distinct strains, with no single assay able to determine seropositivity or seronegativity to an entire clade or family of co-circulating pathogens. An approach is needed to describe population exposure to an antigenically variable group of pathogens without focusing on any particular strain or… Show more

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Cited by 4 publications
(8 citation statements)
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“…Second, we account for systematic shifts between datasets by developing a random forest algorithm using row-centered data (Methods), making our predictions far more robust. As a result, we inferred virus behavior between the Fonville and Vinh studies, even though they utilized different methods of HAI, had different dynamic ranges for their data, and used markedly different virus panels (Fonville et al, 2014;Vinh et al, 2021). After validating our predictions on available data, we expanded the Vinh panel to include 75 new viruses with 2•10 6 new measurements, increasing the original dataset by >10x.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Second, we account for systematic shifts between datasets by developing a random forest algorithm using row-centered data (Methods), making our predictions far more robust. As a result, we inferred virus behavior between the Fonville and Vinh studies, even though they utilized different methods of HAI, had different dynamic ranges for their data, and used markedly different virus panels (Fonville et al, 2014;Vinh et al, 2021). After validating our predictions on available data, we expanded the Vinh panel to include 75 new viruses with 2•10 6 new measurements, increasing the original dataset by >10x.…”
Section: Discussionmentioning
confidence: 99%
“…To test the limits of our approach, we used the Fonville datasets to predict values from a large-scale serological dataset by Vinh et al where only 6 influenza viruses were measured against 25,000 sera (Vinh et al, 2021). This exceptionally long-and-skinny matrix is challenging for several reasons.…”
Section: Breadth Of Matrix Completion: Predicting Values Based On a D...mentioning
confidence: 99%
“…Third, in large-scale serology studies where thousands of viruses/sera are assessed against a small number (~10) of sera/viruses (Harvey et al, 2016;Nguyen Vinh et al, 2021), the few sera/viruses chosen should be as functionally orthogonal to one another as possible to maximize the information gained. The ability to successfully matrix complete with only a fraction of measurements would suggest that the viruses are functionally similar, and a more diverse virus panel could be chosen.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, while earlier studies have performed matrix completion on the data within a given study (what we will call intra-table matrix completion, Figure 1A), the limits of intertable matrix completion are not clear (Figure 1B). It remains to be demonstrated to what extent partially overlapping studies from varying geographic regions and points in time can be integrated; whether different types of studies (e.g., infection versus vaccination, or using fluorescence versus hemagglutination inhibition (Fonville et al, 2014;Nguyen Vinh et al, 2021) can be combined; and whether studies across species (particularly human versus ferret in the case of influenza) can successfully inform each other in the context of matrix completion. Successful inference in these tasks could vastly increase the amount of data used to study viral evolution or develop vaccination strategies, and could be applied to improve ongoing experimental design.…”
Section: Introductionmentioning
confidence: 99%
“…Real-time estimation of seroprevalence or attack rate is challenging. A cross-sectional serological approach requires pre-planned periodic serum collections [13][14][15] and a high-throughput validated assay, but results will still be reported with a one month lag due to the delay from infection to IgG positivity in a serological assay. Estimates of attack rate using daily reported case numbers require us to be able to estimate (i) the number of unreported or untested symptomatic cases and (ii) the number of asymptomatic infections.…”
Section: Introductionmentioning
confidence: 99%