Knowledge and attitudes of parents and professionals to neonatal BCG vaccination in light of recent UK policy changes: A questionnaire study

<p>Abstract</p> <p>Background</p> <p>Universal BCG vaccination in the UK ended in 2005. The new vaccination policy instead offers a number of different forms of selective vaccination to newborns based on risk of acquiring TB. We set out to assess the attitudes and knowledge of both parents and professionals to the new policy for neonatal BCG vaccination.</p> <p>Methods</p> <p>A short questionnaire was designed, made up of demographic and attitude questions, as well as very basic knowledge questions. The researchers handed out the questionnaire to all parents and professionals in the antenatal and postnatal areas, as well as the paediatric and neonatal units during a 6-week period. The site was the Royal Oldham hospital, a district general hospital with 3250 deliveries per year and multi-ethnic in its population mix.</p> <p>Results</p> <p>A total of 253 completed questionnaires were collected. The ethnic origin of responders was 50.6% White British, 18.2% Bangladeshi, 8.7% Indian, 4% White/Asian, the remaining 18.5% of other origins. 71.5% of responders said they had heard of BCG vaccine. When asked if they knew the new policy for its use, 33.2% answered yes. 24.5% gave the most accurate response when asked who now receives BCG.</p> <p>Conclusion</p> <p>We have found that amongst parents and professionals alike there is a lack of knowledge of the new policy. This has lead to confusion and as knowledge amongst the professionals who identify neonates for vaccination is low, uptake may be sub-optimal. We suggest that units investigate the issue and ensure that the new policy is understood and implemented correctly.</p

Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods

Gibbons CL, Mangen M-JJ, Plaß D, et al. Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods. BMC Public Health. 2014;14(1): 147.Background: Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true' incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting. Methods: Within the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens. Results: MFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-,country-, age-, and sex-specific. Conclusions: When routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence