The success of Australia’s ‘No Jab,No Pay’ policy at a local level; retrospective clinical audit of a single medical practice assessing incidence of catch-up vaccinations

Vaccination is a vital health care initiative to prevent individual and population infection. To increase vaccination rates the federal government implemented the ‘No Jab, No Pay’ policy, where eligibility for several government benefits required children to be fully vaccinated by removing ‘conscientious objections’ and expanding the age range of children whose families receive benefits. This study assesses the impact of this policy at a local area within a single medical practice community in NSW, Australia. A retrospective clinical audit was performed between 2012 and 2017 on a single general practice's vaccination records for children ≤19 years. Catch-up vaccinations were assessed based on age at vaccination. Incidence of catch-up vaccinations was assessed for each of four years before and two years after the implementation of the ‘No Jab, No Pay’ policy in January 2016, along with the age of children and vaccination(s) given. Catch-up vaccinations were assessed temporally either side of implementation of ‘No Jab, No Pay’. Comparing the average annual vaccination catch-up incidence rate of 6.2% pre-implementation (2012–2015), there was an increase to 9.2% in 2016 (p < .001) and 7.8% in 2017 (p = .027). Secondary outcome measurement of catch-up vaccination incidence rates before (2012–2015) and after (2016–2017) ‘No Jab, No Pay’ implementation showed statistically significant increases for children aged 8–11 years (3.2%–5.6%, p = .038), 12–15 years (7.5%–14.7%, p < .001) and 16–19 years (3.3%–10.2%, p < .001) along with a statistically significant reduction in children aged 1–3 years (11.4%–6.2%, p = .015). Also, catch-up rates for DTPa significantly increased after program implementation. This study demonstrates that the Australian federal government vaccination policy ‘No Jab, No Pay’ was coincident with an increase in catch-up vaccinations within a rural NSW community served by one medical practice, especially for older children.     

Influences of simulated gastrointestinal environment on physicochemical properties of gold nanoparticles and their implications on intestinal epithelial permeability

Gold nanoparticles (Au NPs) hold great promise in food, industrial and biomedical applications due to their unique physicochemical properties. However, influences of the gastrointestinal tract (GIT), a likely route for Au NPs administration, on the physicochemical properties of Au NPs has been rarely evaluated. Here, we investigated the influence of GIT fluids on the physicochemical properties of Au NPs (5, 50, and 100?nm) and their implications on intestinal epithelial permeability in vitro. Au NPs aggregated in fasted gastric fluids and generated hydroxyl radicals in the presence of H₂O₂. Cell studies showed that GIT fluids incubation of Au NPs affected the cellular uptake of Au NPs but did not induce cytotoxicity or disturb the intestinal epithelial permeability.     

Neuroendocrine,epigenetic, and intergenerational effects of general anesthetics

The progress of modern medicine would be impossible without the use of general anesthetics (GAs). Despite advancements in refining anesthesia approaches, the effects of GAs are not fully reversible upon GA withdrawal. Neurocognitive deficiencies attributed to GA exposure may persist in neonates or endure for weeks to years in the elderly. Human studies on the mechanisms of the long-term adverse effects of GAs are needed to improve the safety of general anesthesia but they are hampered not only by ethical limitations specific to human research, but also by a lack of specific biological markers that can be used in human studies to safely and objectively study such effects. The latter can primarily be attributed to an insufficient understanding of the full range of the biological effects induced by GAs and the molecular mechanisms mediating such effects even in rodents, which are far more extensively studied than any other species. Our most recent experimental findings in rodents suggest that GAs may adversely affect many more people than is currently anticipated. Specifically, we have shown that anesthesia with the commonly used GA sevoflurane induces in exposed animals not only neuroendocrine abnormalities (somatic effects), but also epigenetic reprogramming of germ cells (germ cell effects). The latter may pass the neurobehavioral effects of parental sevoflurane exposure to the offspring, who may be affected even at levels of anesthesia that are not harmful to the exposed parents. The large number of patients who require general anesthesia, the even larger number of their future unexposed offspring whose health may be affected, and a growing number of neurodevelopmental disorders of unknown etiology underscore the translational importance of investigating the intergenerational effects of GAs. In this mini review, we discuss emerging experimental findings on neuroendocrine, epigenetic, and intergenerational effects of GAs.     

Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.