Cross-reactive antibody responses to the 2009 A/H1N1v influenza virus in the Italian population in the pre-pandemic period

Sensitivity and Specificity of Serologic Assays for Detection of Human Infection with 2009 Pandemic H1N1 Virus in U.S. Populations

“…Since the majority (86%) of our rRT-PCR-confirmed cases were Ͻ30 years of age, it was not possible to stratify the sensitivity results by age or to estimate sensitivity in adults Ն60 years of age. Because prepandemic cross-reactive antibody to the 2009 H1N1 virus has been demonstrated particularly in older adults (13,16,17,20,22), we compared the specificities for detection of 2009 H1N1 virus antibody in different age groups. For individuals Ͻ60 years of age, the MN titer cutoff that gave optimal sensitivity (Ն40) was only 83% specific, whereas the comparable HI titer cutoff (Ն20) gave 91% specificity.…”

“…The 2009 H1N1 virus is antigenically and genetically distinct from seasonal H1N1 viruses that have circulated in the last 60 years (11). Nevertheless, studies in Europe and the United States demonstrated that, prior to the 2009 pandemic, approximately 20 to 30% of adults 60 to 65 years old and older possessed serum antibody cross-reactive with 2009 H1N1 virus (13,20,22).…”

Pandemic Influenza H1N1

“…To calculate estimates of the reproduction number, we required both baseline (preoutbreak) and postoutbreak serosurvey data by age. Studies that reported only prepandemic data [53][54][55][56][57][58][59][60] or that did not provide a representative prepandemic baseline 61-65 were excluded. Of the remaining 11 studies, 66 -76 3 74 -76 did not report sufficient age-specific data for the full age-adjusted analysis; therefore, we calculated only unadjusted estimates of the reproduction number for these studies.…”

The role of different social contexts in shaping influenza transmission during the 2009 pandemic

“…household, schools, workplaces, and the general community) and indirectly estimating the transmission rate given an adequate contact. To do this Bayesian statistical techniques are employed here to analyze serological data collected before and after the 2009 H1N1 influenza pandemic in Italy3031. This analysis allows us to parametrize the model and to estimate the fractions of infections generated in different social settings.…”