Accurately assessing the exposure of a population to a particular virus is difficult because the tools for doing so do not account for the fact that many viruses comprise multiple circulating strains, or the fact that people can be vaccinated or naturally immune, among other factors. Using influenza as a model, researchers have developed a new technique that overcomes many of these roadblocks, and they say the tool may be useful for better assessments of exposure to a variety of viruses, including the ones that cause COVID-19 and pneumonia.

«Without an accurate picture of a population’s exposure to a particular virus, we cannot effectively plan and implement public health interventions,» said Maciej Boni, associate professor of biology who led the study.

In their study, which appeared on Nov. 18 in the journal Nature Communications, the researchers specifically investigated the attack rate for human influenza A virus in a tropical setting, which comprises two subtypes — H3N2 and H1N1 — and multiple strains.

According to Boni, an attack rate is an estimate of how many people have been infected with a particular disease, regardless of whether they had symptoms or whether they were tested or not.

«Accurately estimating the attack rate of a virus sounds like something epidemiologists should be able to do quite easily,» he said, «but there are at least four major complications. First, you need to pre-plan collections of blood samples, otherwise there’s no way to get a snapshot of who in the population right now has antibodies and who doesn’t. Second, when testing for antibodies, you cannot always differentiate someone who was infected from someone who was vaccinated. Third, antibodies wane, so you may not be able to tell if someone was infected if their antibody levels are low now. Finally, many pathogens circulate as groups of strains or groups of variants, and there may be no laboratory assay to test for general exposure to any of these variants.»

The team, which included researchers from Vietnam and the Netherlands, created a new method that resolves many of these problems and presents accurate general-population, attack-rate estimates for influenza A virus. To conduct their study, the researchers used a dataset of 24,402 general-population serum — or blood plasma — samples collected in central and southern Vietnam between 2009 to 2015 and assayed the samples for antibodies to eleven different strains of human influenza A, including the 1918 pandemic ‘Spanish Flu’ strain and the 2009 ‘swine flu’ pandemic virus strain, which are within the H1N1 subtype. Next, they used this large set of antibody measurements to derive a ‘composite antibody measurement’ across both subtypes of influenza and across all the different strains.

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Materials provided by Penn State. Original written by Sara LaJeunesse. Note: Content may be edited for style and length.