Concern about both safety and efficacy has made the use of whole-cell pertussis vaccines controversial. In some European countries, including Italy, the rate of vaccination against pertussis is low.

Nosocomial infections place a substantial burden on health care systems and represent one of the major issues in current public health, requiring notable efforts for its prevention. Understanding the dynamics of infection transmission in a hospital setting is essential for tailoring interventions and predicting the spread among individuals. Mathematical models need to be informed with accurate data on contacts among individuals. We used wearable active Radio-Frequency Identification Devices (RFID) to detect face-to-face contacts among individuals with a spatial resolution of about 1.5 meters, and a time resolution of 20 seconds. The study was conducted in a general pediatrics hospital ward, during a one-week period, and included 119 participants, with 51 health care workers, 37 patients, and 31 caregivers. Nearly 16,000 contacts were recorded during the study period, with a median of approximately 20 contacts per participants per day. Overall, 25% of the contacts involved a ward assistant, 23% a nurse, 22% a patient, 22% a caregiver, and 8% a physician. The majority of contacts were of brief duration, but long and frequent contacts especially between patients and caregivers were also found. In the setting under study, caregivers do not represent a significant potential for infection spread to a large number of individuals, as their interactions mainly involve the corresponding patient. Nurses would deserve priority in prevention strategies due to their central role in the potential propagation paths of infections. Our study shows the feasibility of accurate and reproducible measures of the pattern of contacts in a hospital setting. The obtained results are particularly useful for the study of the spread of respiratory infections, for monitoring critical patterns, and for setting up tailored prevention strategies. Proximity-sensing technology should be considered as a valuable tool for measuring such patterns and evaluating nosocomial prevention strategies in specific settings.

A resurgence of pertussis has been observed in Canada, the United States and Australia since the 1980s, but inconsistent data are currently available for Europe. The objective of this paper is to describe the epidemiology of pertussis in Western European countries to discuss future vaccination strategies. The European Community funded a network for the epidemiologic surveillance of measles and pertussis in 1998. Sixteen European countries provided national surveillance data for pertussis for the period 1998–2002 in a standard format. Data were pooled and analyzed to describe incidence rates by age group, seasonality, proportion of hospitalized patients and deaths among notified cases. Children younger than 1 year had the highest incidence during the entire period. Rates in the older than 14 years age group increased by 115% during the study period. Northern countries showed the highest incidence figures in all age groups. Among children younger than 1 year, 70% were admitted into hospital. Children younger than 6 months of age and those not vaccinated were most likely to be hospitalized. Thirty-two deaths were reported, 87% of which were in children younger than 6 months ofage. Pertussis is far from being controlled in Europe. Whereas the incidence in children younger than 1 year was high but remained stable, rates in adults doubled in 5 years.

Background: The integration of empirical data in computational frameworks designed to model the spread of infectious diseases poses a number of challenges that are becoming more pressing with the increasing availability of high-resolution information on human mobility and contacts. This deluge of data has the potential to revolutionize the computational efforts aimed at simulating scenarios, designing containment strategies, and evaluating outcomes. However, the integration of highly detailed data sources yields models that are less transparent and general in their applicability. Hence, given a specific disease model, it is crucial to assess which representations of the raw data work best to inform the model, striking a balance between simplicity and detail.Methods: We consider high-resolution data on the face-to-face interactions of individuals in a pediatric hospital ward, obtained by using wearable proximity sensors. We simulate the spread of a disease in this community by using an SEIR model on top of different mathematical representations of the empirical contact patterns. At the most detailed level, we take into account all contacts between individuals and their exact timing and order. Then, we build a hierarchy of coarse-grained representations of the contact patterns that preserve only partially the temporal and structural information available in the data. We compare the dynamics of the SEIR model across these representations.Results: We show that a contact matrix that only contains average contact durations between role classes fails to reproduce the size of the epidemic obtained using the high-resolution contact data and also fails to identify the most at-risk classes. We introduce a contact matrix of probability distributions that takes into account the heterogeneity of contact durations between (and within) classes of individuals, and we show that, in the case study presented, this representation yields a good approximation of the epidemic spreading properties obtained by using the high-resolution data.Conclusions: Our results mark a first step towards the definition of synopses of high-resolution dynamic contact networks, providing a compact representation of contact patterns that can correctly inform computational models designed to discover risk groups and evaluate containment policies. We show in a typical case of a structured population that this novel kind of representation can preserve in simulation quantitative features of the epidemics that are crucial for their study and management.

The mean annual incidence of hemolytic uremic syndrome in persons <15 years of age in Italy from 1988 to 2000 was 0.28 per 100,000 population. Laboratory investigations showed that Shiga toxin–producing Escherichia coli (STEC) infection occurred in 73.1% of patients. STEC O157 was the most common serotype, but a considerable number of cases were from infections by non-O157 STEC.