Salje, HenrikSrikiatkhachorn, Anon2022-08-232022-08-232016-02-152016-05-18J Infect Dis. 2016 Feb 15;213(4):604-10. doi: 10.1093/infdis/jiv470. Epub 2015 Sep 25. <a href="http://dx.doi.org/10.1093/infdis/jiv470">Link to article on publisher's site</a>0022-1899 (Linking)10.1093/infdis/jiv47026410592https://hdl.handle.net/20.500.14038/39942<p>Full author list omitted for brevity. For the full list of authors see article.</p>Proper understanding of the long-term epidemiology of chikungunya has been hampered by poor surveillance. Outbreak years are unpredictable and cases often misdiagnosed. Here we analyzed age-specific data from 2 serological studies (from 1973 and 2012) in Cebu, Philippines, to reconstruct both the annual probability of infection and population-level immunity over a 60-year period (1952-2012). We also explored whether seroconversions during 2012-2013 were spatially clustered. Our models identified 4 discrete outbreaks separated by an average delay of 17 years. On average, 23% (95% confidence interval [CI], 16%-37%) of the susceptible population was infected per outbreak, with > 50% of the entire population remaining susceptible at any point. Participants who seroconverted during 2012-2013 were clustered at distances of < 230 m, suggesting focal transmission. Large-scale outbreaks of chikungunya did not result in sustained multiyear transmission. Nevertheless, we estimate that > 350,000 infections were missed by surveillance systems. Serological studies could supplement surveillance to provide important insights on pathogen circulation.en-USCopyright © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, contact moc.puo@snoissimrep.slanruoj.http://creativecommons.org/licenses/by-nc-nd/4.0/Philippineschikungunyaepidemiologymodelingserological studyClinical EpidemiologyEpidemiologyImmunology of Infectious DiseaseInfectious DiseaseInternational Public HealthJournal Articlehttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=3756&amp;context=oapubs&amp;unstamped=1https://escholarship.umassmed.edu/oapubs/27518614703oapubs/2751