Introduction: “Vaccine hesitancy” is a concept frequently used in the discourse around vaccine acceptance. This study aims to contribute to the ongoing reflections on tools and indicators of vaccine hesitancy by providing results of a knowledge, attitudes and beliefs (KAB) survey conducted among parents.

Methods: Data were collected in 2014 through a computer-assisted telephone interview survey administered to a sample of parents of children aged between 2 months and 17 years of age.

Results: The majority of the 589 parents included in the analyses agreed on the importance of vaccination to protect their children’s health and to prevent the spread of diseases in the community. The majority of the parents (81%) reported that their child had received all doses of recommended vaccines and 40% of parents indicated having hesitated to have their child vaccinated. Fear of adverse events and low perceived vulnerability of the child or severity of the disease were the most frequent reasons mentioned by these vaccine-hesitant parents. In multivariate analyses, KAB items remaining significantly associated both with an incomplete vaccination status of the child and parents’ vaccine hesitancy were: not thinking that it is important to have the child vaccinated to prevent the spreading of diseases in the community; not trusting the received vaccination information and having felt pressure to have the child vaccinated.

Discussion: Further researches will be needed to better understand when, how and why these beliefs are formed in order to prevent the onset of vaccine hesitancy.

Introduction and Methods: Pertussis has recently re-emerged in the United States. Timely surveillance is vital to estimate the burden of this disease accurately and to guide public health response. However, the surveillance of pertussis is limited by delays in reporting, consolidation and dissemination of data to relevant stakeholders. We fit and assessed a real-time predictive Google model for pertussis in California using weekly incidence data from 2009-2014.

Results and Discussion: The linear model was moderately accurate (r = 0.88). Our findings cautiously offer a complementary, real-time signal to enhance pertussis surveillance in California and help to further define the limitations and potential of Google-based epidemic prediction in the rapidly evolving field of digital disease detection.

Introduction: The ability to predict the growth and decline of infectious disease incidence has advanced considerably in recent years. In particular, accurate forecasts of influenza epidemiology have been developed using a number of approaches.

Methods: Within our own group we produce weekly operational real-time forecasts of influenza at the municipal and state level in the U.S. These forecasts are generated using ensemble simulations depicting local influenza transmission dynamics, which have been optimized prior to forecast with observations of influenza incidence and data assimilation methods. The expected accuracy of a given forecast can be inferred in real-time through quantification of the agreement (e.g. the variance) among the ensemble of simulations.

Results: Here we show that forecast expected accuracy can be further discriminated with the additional consideration of the streak or persistence of the forecast—the number of consecutive weeks the forecast has converged to the same outcome.

Discussion: The findings indicate that the use of both the streak and ensemble agreement provides a more detailed and informative assessment of forecast expected accuracy.

Introduction: Further understanding of the genetic diversity and evolution of influenza A viruses circulating in swine (IAV-S) is important for the development of effective vaccines and our knowledge of pandemic threats. Until recently, very little was known of IAV-S diversity in Latin America, owing to a lack of surveillance.

Methods: To address this gap, we sequenced and conducted a phylogenetic analysis of 69 hemagglutinin (HA) sequences from IAV-S isolates collected in swine in Mexico and Chile during 2010-2014, including the H1N1, H1N2, and H3N2 subtypes.

Results: Our analysis identified multiple IAV-S lineages that appear to have been circulating undetected in swine for decades, including four novel IAV-S lineages of human seasonal virus origin that have not been previously identified in any swine populations globally. We also found evidence of repeated introductions of pandemic H1N1 viruses from humans into swine in Mexico and Chile since 2009, and incursions of H1 and H3 viruses from North American swine into Mexico.

Discussion: Overall, our findings indicate that at least 12 genetically distinct HA lineages circulate in Latin American swine herds, only two of which have been found in North American swine herds. Human-to-swine transmission, spatial migration via swine movements, and genomic reassortment are the key evolutionary mechanisms that generate this viral diversity. Additional antigenic characterization and whole-genome sequencing is greatly needed to understand the diversity and independent evolution of IAV-S in Latin America.