News Release

Simulation study shows that pandemic swine flu had a minor impact in Finland

Peer-Reviewed Publication

PLOS

Researchers have used modeling to estimate the true impact of infectious diseases, such as swine flu, when underreporting can mean the surveillance from time of the pandemic can miss the vast majority of infections that occur in the population.

New research published in PLOS Computational Biology by Mikhail Shubin et al from the National Institute for Health and Welfare uses simulations to estimate the effect of the swine flu pandemic in Finland. This research offers a platform to assess the severity of flu seasons at various levels of the healthcare system, when previously the number of infected individuals has been uncertain.

The researchers built a low-scale simulation model of Finland that simulates the spread of influenza in the population. The model accounts for the transmission of influenza in the population, the impact of vaccination, outcomes of varying severity and imperfect detection of flu.

The study shows that the impact on Finland was minor, as less than 10% of the population was infected with swine flu during the first two seasons in 2009-2011, with the highest incidences of the disease initially occurring in younger people.

Shubin et al's research also measures the impact of the vaccination campaign in which approximately half of the Finnish population were vaccinated by February 2010. They show that vaccinations significantly reduced the transmissibility of the virus as the proportion of the population infected during the second season was only 3%. This research shows that the second season could have started earlier and caused a larger outbreak, leading to 4-8 times more infections overall.

The study emphasises that statistical modelling and simulation can be used to evaluate incomplete infectious disease surveillance data in emerging infections.

###

For further information please contact: Mikhail Shubin

In your coverage please use this URL to provide access to the freely available article in PLOS Computational Biology: http://dx.plos.org/10.1371/journal.pcbi.1004803

Press-only preview: https://www.plos.org/wp-content/uploads/2016/03/pcbi.1004803-PRESS-PREVIEW.pdf

Contact: Mikhail Shubin< Ph: 358445209938

Citation: Shubin M, Lebedev A, Lyytikäinen O, Auranen K (2016) Revealing the True Incidence of Pandemic A(H1N1)pdm09 Influenza in Finland during the First Two Seasons -- An Analysis Based on a Dynamic Transmission Model. PLoS Comput Biol 12 (3): e1004803. doi:10.1371/journal.pcbi.1004803

Funding: National Institute for Health and Welfare, Finland, funded the project and provided the dataset. MS was funded by FICS graduate school and Academy of Finland grant no. 251170. The funders had no role in study design, data analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

About PLOS Computational Biology

PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. For more information follow @PLOSCompBiol on Twitter or contact ploscompbiol@plos.org.

Media and Copyright Information

For information about PLOS Computational Biology relevant to journalists, bloggers and press officers, including details of our press release process and embargo policy, visit http://journals.plos.org/ploscompbiol/s/press-and-media .

PLOS Journals publish under a Creative Commons Attribution License, which permits free reuse of all materials published with the article, so long as the work is cited.

About the Public Library of Science

The Public Library of Science (PLOS) PLOS is a nonprofit publisher and advocacy organization founded to accelerate progress in science and medicine by leading a transformation in research communication. For more information, visit http://www.plos.org.

Disclaimer

This press release refers to upcoming articles in PLOS Computational Biology. The releases have been provided by the article authors and/or journal staff. Any opinions expressed in these are the personal views of the contributors, and do not necessarily represent the views or policies of PLOS. PLOS expressly disclaims any and all warranties and liability in connection with the information found in the release and article and your use of such information.


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.