Background: Since the introduction of HPV vaccines, several studies have been conducted in different countries to assess HPV knowledge and vaccine acceptance. The aim of this study was to perform a systematic literature review to summarize results and identify factors associated with HPV knowledge and vaccine acceptance in adolescents and their parents and to compile the measurement tools used in the published research studies performed in European countries where HPV is licensed. Methods: A systematic literature review was conducted for studies published between January 1st 2006 and December 31st 2017. Results: Seventy non-interventional studies performed in 16 European countries met the inclusion criteria. Thirty-eight of them reported data on HPV knowledge and 40 reported data on HPV vaccine acceptance. Further, 51.8% of adolescents (range 0% to 98.6%) and 64.4% of parents (range 1.7% to 99.3%) knew about HPV infection. Insufficient information and safety concerns were the main barriers to vaccination acceptance. Conclusion: HPV knowledge and vaccine acceptance are still modest and vary widely between studies across EU countries. Coordinated efforts should be made to provide the relevant population with information for informed decision-making about HPV vaccination.

NCT01900015.

We compare a rapid dilution method for the determination of antiviral susceptibility of herpes simplex virus (HSV) with the plaque reduction assay. A total of 84 HSV clinical isolates were studied by both methods to detect in-vitro resistance to acyclovir and foscarnet. The rapid method showed for the detection of HSV isolates resistant to acyclovir and foscarnet, a sensitivity of 96. 8% and 100% and specificity of 100% and 100%, respectively. This method provides an easy and accurate screening procedure for the susceptibility testing of HSV to antiviral agents.

Sentiment analysis is one of the hottest topics in the area of natural language. It has attracted a huge interest from both the scientific and industrial perspective. Identifying the sentiment expressed in a piece of textual information is a challenging task that several commercial tools have tried to address. In our aim of capturing the sentiment expressed in a set of tweets retrieved for a study about vaccines and diseases during the period 2015–2018, we found that some of the main commercial tools did not allow an accurate identification of the sentiment expressed in a tweet. For this reason, we aimed to create a meta-model which used the results of the commercial tools to improve the results of the tools individually. As part of this research, we had to deal with the problem of unbalanced data. This paper presents the main results in creating a metal-model from three commercial tools to the correct identification of sentiment in tweets by using different machine-learning techniques and methods and dealing with the unbalanced data problem.

This study analyzes the effect of highly active antiretroviral therapy (HAART) on visceral leishmaniasis in human immunodeficiency virus-infected individuals. We describe 66 episodes diagnosed in our hospital from 1994 through 2000 (35 episodes in patients who were not receiving HAART and 31 episodes in patients who were receiving HAART). Since HAART became available, the incidence of visceral leishmaniasis has significantly decreased and the number of first episodes has decreased, although the number of relapses is increasing.