Care for children with severe chronic skin diseases.

In this study, the care for children with a severe chronic skin disease in our national expert center of pediatric dermatology was evaluated. Patients and their parents were questioned by using existing questionnaires: 50 pediatric patients completed the modified "my positive health" questionnaire of Huber and 51 parents completed Pelentsov parental needs scale. Nineteen involved professionals answered a questionnaire with open boxes. Parents of children with a variety of chronic skin diseases and young adult patients were interviewed to find out what an optimal approach would look like according to them. Children with a severe chronic and/or congenital skin disorder score high on the "my positive health" questionnaire, indicating they are able to adapt and self-manage. Their highest median score was measured for the dimension "quality of life." Their parents expect improvement of "working with health care professionals," more specifically they want them to adopt a more holistic approach throughout the patient's life. Structured interviews showed they expect that a multidisciplinary team of care providers determine together with the patient and its family-in advance-which care is needed, at what time and by whom. The interviewed professionals indicated adoption of a holistic multidisciplinary approach as the single largest improvement to achieve better care.Conclusion: Although these children with a severe chronic and/or congenital skin disease were able to adapt and self-manage, they need a more personalized integrative multidisciplinary and systematic transmural approach covering all aspects of life during their lifetime. What is Known: • Severe skin disorders affect the child and its family in several ways. In our expert center, we try to optimize the care for these children through a multidisciplinary approach. What is New: • To our knowledge, no English publication describes the requirements for good care for pediatric patients with severe chronic skin disorders and how to optimize this care. We evaluated the health status of children with severe chronic skin disorders and the strengths and weaknesses of past and current care by questioning these children, their parents, adult patients, and involved professionals.

A consensus-based tool for ranking the risk of blood-transmissible infections.

BACKGROUND: Emerging infectious diseases (EIDs) pose a threat to blood transfusion safety. Despite a lack of evidence, safety interventions may be required. However, what should decision makers base their decisions on? A model was developed that allows valuing the perceived risk of an EID for blood safety as derived from a group of experts. The model requires estimates of four disease characteristics and the accuracy of these estimates. STUDY DESIGN AND METHODS: Sixteen selected experts ranked 24 hypothetical diseases, each comprising a quantitative estimate of four characteristics: transfusion transmissibility, proportion of asymptomatic infectious phase, prevalence of infection, and disease impact. Each of the characteristics was expressed at one of six predefined levels with varying ranges of uncertainty. The model was derived using probabilistic inversion and was applied to value the perceived risk of most currently known EIDs relevant to blood transfusion. RESULTS: The model demonstrated that transmissibility and prevalence are the most important risk drivers. However, disease impact and likelihood of transmission during the asymptomatic phase of infection are more important when the disease characteristics are unknown. In the ranking of currently known EIDs, diseases that have been identified previously as posing a serious risk to blood transfusion appear at the top of the list. CONCLUSION: With the current model, the perceived risk of EIDs for transfusion safety can be determined for both known and unknown diseases, even when little information is available. Extension of the expert base, further model development and validation, and continuous updating of the model are recommended.

Modelling the risk of transfusion transmission from travelling donors.

BACKGROUND: The EUFRAT (European Up-Front Risk Assessment Tool) was developed as an online risk assessment tool ( http://eufrattool.ecdc.europa.eu ) to help decision-makers assess the transmission risk of emerging infectious diseases (EID) through blood transfusion. The aim of this study is to extend the methodology developed in the EUFRAT project to quantify the transfusion transmission (TT) risk from travelling donors. METHODS: A generic model for estimating the TT risk from a group of travelling donors that visited an EID risk area was developed. In addition, the new model distinguishes projected future transmissions from those that have already occurred. As an illustration the model was applied to the outbreaks of chikungunya in Italy in 2007 and Q fever in the Netherlands in 2007-2009. RESULTS: Formulas for calculating the travelling donors' TT risk were derived. For the chikungunya outbreak in Italy an early intervention (at the end of week 7 after the start of the outbreak, so after only 19% of all cases) would have been required to prevent only 41% of all expected transmissions at that time. For Q fever, in which the transmission of chronic Q fever is considered, even at the end of the third annual outbreak's peak 47% of all (chronic) Q fever transmissions could still be prevented. CONCLUSIONS: The updated model allows estimation of the infection transmission risk from travelling donors. In combination with the distinction between past and future transmissions, these estimates provide valuable information to support decisions concerning communication with the public and/or the implementation of safety interventions.

Travel behavior and deferral of Dutch blood donors: consequences for donor availability.

BACKGROUND: Donors returning from areas with outbreaks of infectious diseases may donate infectious blood back home. Geographic donor deferral is an effective measure to ensure the blood safety, but donor deferral may pose a threat for the blood supply especially after holiday seasons. Insight into the travel behavior of blood donors is a first step to define appropriate deferral strategies. This study describes the travel behavior of Dutch donors, the actual deferral, and the consequences of deferral strategies on donor availability. STUDY DESIGN AND METHODS: A questionnaire designed to assess travel behavior (destination, frequency, and duration of travels) was sent to 2000 Dutch donors. The impact of travel deferral policies on donor availability was calculated, expressed as proportionate decrease in donor availability. The deferral policies considered were 1) deferral based on entire countries instead of affected regions where an infection is prevalent and 2) deferral after any travel outside Europe ("universal deferral"). RESULTS: Of the 1340 respondents, 790 (58.9%) donors traveled within Europe only, 61 (4.6%) outside Europe only, and 250 (18.7%) within and outside Europe. The deferral for entire countries and universal deferral would lead to 11.1 and 11.4% decrease in donor availability, respectively. CONCLUSION: Most Dutch donors traveled outside the Netherlands, while 23.2% traveled outside Europe. Universal deferral resulted in an additional decrease in donor availability of 0.3% compared with deferral for entire countries instead of affected regions where an infection is prevalent. Thus, the universal deferral could be considered as a simpler and safer measure.

Estimating the transfusion transmission risk of Q fever.

BACKGROUND: The Q fever outbreaks in the Netherlands in 2007 to 2009 initiated discussion on the necessity of measures to prevent transmission through blood products. Risk assessments help transfusion regulators decide when and where measures are required. This study assesses the transfusion transmission (TT) risk of Q fever using the European Up-Front Risk Assessment Tool (EUFRAT) model. STUDY DESIGN AND METHODS: We estimated the number of Q fever infections in recipients during the 2007 to 2009 outbreaks' peaks using selected notification data; estimates are calculated from the probability of a donor being infected. We compared this probability to the prevalence of infection estimated from an independent donation testing study and using the Biggerstaff model. We also quantified the risk reduction by implementing measures such as donation testing and donor deferral. RESULTS: At the peak of the 2007, 2008, and 2009 outbreaks, there were an estimated 0.21, 0.96, and 1.59 recipients infected with Q fever, respectively. Between June 1, 2009, and January 31, 2010, the probability of a donor being infected with Q fever in the high-incidence areas was estimated at 260 (95% confidence interval, 192-340) per 100,000 donors, consistent with results from the donation testing study. The EUFRAT estimates were also consistent with estimates from the Biggerstaff model. Scenario analyses showed that donation testing provided the largest risk reduction of various risk reduction strategies. CONCLUSION: The TT risk of Q fever during the 2007 to 2009 outbreaks was small, a result that is consistent with results of other studies. EUFRAT can be applied successfully to support decision making during outbreaks.

Modeling the transmission risk of emerging infectious diseases through blood transfusion.

BACKGROUND: A timely risk assessment is desired to guide decisions on preventive transfusion safety measures during emerging infectious disease (EID) outbreaks. The European Up-Front Risk Assessment Tool (EUFRAT) model was developed to provide quantitative transmission risk estimates of EIDs through blood transfusion. STUDY DESIGN AND METHODS: The generic model comprises five sequential steps to estimate the infection risks in the blood transfusion chain: 1) the prevalence of infection in the donor population, 2) the risk of obtaining infected donations, 3) infected components, 4) infected blood products, and 5) the risk of transmitting the infection to recipients. The model uses inputs from epidemiologic characteristics of an EID and transfusion practice. The model was applied to data from a recent chikungunya outbreak in Italy. RESULTS: Based on data from the outbreak peak, an estimated prevalence of 1.07 (95% confidence interval [CI], 0.38-2.03) per 100,000 donors would lead to 0.04 infected donations (95% CI, 0.01-0.10), 0.13 infected blood components, 0.13 infected end products, and 0.0001 severe infections in recipients. This estimated risk can be reduced by increasing the duration of quarantine of the donated blood and becomes zero after 7 or more days of quarantine. The model also estimated the probability of a donor returning from the outbreak area and subsequently donating infected blood in his home country to be 0.30 (95% CI, 0.01-0.65) per 100,000. CONCLUSION: The model can be used to quantify EID outbreak risks to blood transfusion recipients and the effect of targeted safety interventions and as such support public health decision-making.

The relationship between tuberculosis and influenza death during the influenza (H1N1) pandemic from 1918-19.

The epidemiological mechanisms behind the W-shaped age-specific influenza mortality during the Spanish influenza (H1N1) pandemic 1918-19 have yet to be fully clarified. The present study aimed to develop a formal hypothesis: tuberculosis (TB) was associated with the W-shaped influenza mortality from 1918-19. Three pieces of epidemiological information were assessed: (i) the epidemic records containing the age-specific numbers of cases and deaths of influenza from 1918-19, (ii) an outbreak record of influenza in a Swiss TB sanatorium during the pandemic, and (iii) the age-dependent TB mortality over time in the early 20th century. Analyzing the data (i), we found that the W-shaped pattern was not only seen in mortality but also in the age-specific case fatality ratio, suggesting the presence of underlying age-specific risk factor(s) of influenza death among young adults. From the data (ii), TB was shown to be associated with influenza death (P = 0.09), and there was no influenza death among non-TB controls. The data (iii) were analyzed by employing the age-period-cohort model, revealing harvesting effect in the period function of TB mortality shortly after the 1918-19 pandemic. These findings suggest that it is worthwhile to further explore the role of TB in characterizing the age-specific risk of influenza death.