RESUMEN
This study investigated how factors and barriers to flu vaccination among college students has changed over the past 16 years. Data were collected from 440 students using a survey and compared to previous data from the same university. Respondents were also asked about their experiences with Covid-19 and its effect on their intent to vaccinate. We found that vaccination rates had increased from 12.4 to 30.5%. Among the unvaccinated, expense, fear of getting influenza from vaccination, fear of side effects, and lack of information have decreased by 28%, 20%, 17%, and 15% respectively. Time, convenience, and perceived risk are still significant barriers to vaccination. Students are getting more encouragement to vaccinate from their health care providers and parents, but it is becoming less effective. The Covid-19 pandemic has changed vaccine attitudes and vaccine fatigue has been a large contributor. Additionally, political affiliation has become a predictor of flu vaccine uptake with conservatives being less likely to vaccinate. There has also been a shift in motivation from concern for personal safety to concern for public safety.
Asunto(s)
Vacunas contra la Influenza , Gripe Humana , Humanos , Gripe Humana/prevención & control , Estaciones del Año , Pandemias/prevención & control , Conocimientos, Actitudes y Práctica en Salud , Vacunas contra la Influenza/uso terapéutico , VacunaciónRESUMEN
Much of today's molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner's ability to correctly map sequences. In most cases, for research into chromatin structure and nucleosome positioning, ATAC-seq, ChIP-seq, and MNase-seq experiments use short read lengths. How well aligners manage these reads is critical. Most aligner programs will output mapped reads and unmapped reads. However, from a biological point of view, reads will fall into one of three categories: correctly mapped, incorrectly mapped, and unmapped. While increased sequencing depth can often compensate for unmapped reads, incorrectly and correctly mapped reads appear algorithmically identical but can produce biologically significant alterations in the results. For this reason, we are benchmarking various alignment programs to determine their propensity to incorrectly map short reads. As short-read alignment is an important step in ATAC-seq, ChIP-seq, and MNase-seq experiments, caution should be taken in mapping reads to ensure that the most accurate conclusions can be made from the data generated. Our analysis is intended to help investigators new to the field pick the alignment program best suited for their experimental conditions. In general, the aligners we tested performed well. BWA, Bowtie2, and Chromap were all exceptionally accurate, and we recommend using them. Furthermore, we show that longer read lengths do in fact lead to more accurate mappings.