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Personal contacts drive COVID-19 infections. After being closed (23 March 2020) UK primary schools partially re-opened on 1 June 2020 with social distancing and new risk mitigation strategies. We conducted a structured expert elicitation of teachers to quantify primary school contact patterns and how contact rates changed upon re-opening with risk mitigation measures in place. These rates, with uncertainties, were determined using a performance-based algorithm. We report mean number of contacts per day for four cohorts within schools, with associated 90% confidence ranges. Prior to lockdown, younger children (Reception and Year 1) made 15 contacts per day [range 8.35] within school, older children (Year 6) 18 contacts [range 5.55], teaching staff 25 contacts [range 4.55] and non-classroom staff 11 contacts [range 2.27]. After re-opening, the mean number of contacts was reduced by 53% for young children, 62% for older children, 60% for classroom staff and 64% for other staff. Contacts between teaching and non-teaching staff reduced by 80%. The distributions of contacts per person are asymmetric with heavy tail reflecting a few individuals with high contact numbers. Questions on risk mitigation and supplementary structured interviews elucidated how new measures reduced daily contacts in-school and contribute to infection risk reduction.

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INTRODUCTION: Communication is an essential component of patient care, and although medical schools provide training on this topic, patients and physicians alike express the need to improve their communication skills. An international medical student collaboration explored whether complementary medicine (CM) has the ability to further enhance patient-doctor communication. METHODS: Twenty-two medical students, nine mentors and two public representatives from Israel and Germany participated in this 18-month international group project. The goal was to explore CM methods that could enrich doctor-patient communication in several aspects. The group eventually chose to focus on four CM modalities, which included Chinese medicine; Mind-Body medicine; Touch therapies; Mindfulness and Herbal medicine. One workshop took place in Haifa and two workshops in Berlin, with continued inter-group work in-between. The workshops included interactive group formats such as "World Café", self-experience sessions in CM, working in small groups and delivering presentations to the entire group. RESULTS: Besides benefitting from cultural exchange and networking, students learned various aspects of CM, with a particular focus on their relevance for enriching their communication skills. The main CM aspects that were highlighted included patient characterization in the context of Chinese medicine diagnosis, mindfulness, anamnesis regarding herbal use, and a physical exam based on concepts from touch therapies. Students summarized and condensed their observations into five educational modules, which are available online: http://www.b-zion.org.il/pages_e/6683.aspx. CONCLUSION: The cultural exchange and explorative process in this international medical student collaboration led to insights regarding the potential contribution of CM to patient-doctor communication. The outcomes of this international collaboration, specifically the educational modules it produced, should be further explored by medical schools, and assessed in clinical trials.

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In a pandemic setting, surveillance is essential to monitor the spread of the disease and assess its impact. Appropriate mitigation and healthcare preparedness strategies depend on fast and accurate epidemic surveillance data. During the 2009 influenza A(H1N1) pandemic, rapid improvements in influenza surveillance were made in Iceland. Here, we describe the improvements made in influenza surveillance during the pandemic , which could also be of great value in outbreaks caused by other pathogens. Following the raised level of pandemic influenza alert in April 2009, influenza surveillance was intensified. A comprehensive automatic surveillance system for influenza-like illness was developed, surveillance of influenza-related deaths was established and laboratory surveillance for influenza was strengthened. School absenteeism reports were also collected and compared with results from the automatic surveillance system. The first case of 2009 pandemic influenza A(H1N1) was diagnosed in Iceland in May 2009, but sustained community transmission was not confirmed until mid-August. The pandemic virus circulated during the summer and early autumn before an abrupt increase in the number of cases was observed in October. There were large outbreaks in elementary schools for children aged 6­15 years throughout the country that peaked in late October. School absenteeism reports from all elementary schools in Iceland gave a similar epidemiological curve as that from data from the healthcare system. Estimates of the proportion of the population infected with the pandemic virus ranged from 10% to 22%. This study shows how the sudden need for improved surveillance in the pandemic led to rapid improvements in data collection in Iceland. This reporting system will be improved upon and expanded to include other notifiable diseases, to ensure accurate and timely collection of epidemiological data.

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INTRODUCTION: Mathematical models allow us to extrapolate from current information about the state and progress of an outbreak, to predict the future and, most importantly, to quantify the uncertainty in these predictions. Here, we illustrate these principles in relation to the current H1N1 epidemic. SOURCES OF DATA: Many sources of data are used in mathematical modelling, with some forms of model requiring vastly more data than others. However, a good estimation of the number of cases is vitally important. AREAS OF AGREEMENT: Mathematical models, and the statistical tools that underpin them, are now a fundamental element in planning control and mitigation measures against any future epidemic of an infectious disease. Well-parameterized mathematical models allow us to test a variety of possible control strategies in computer simulations before applying them in reality. AREAS OF CONTROVERSY: The interaction between modellers and public-health practitioners and the level of detail needed for models to be of use. GROWING POINTS: The need for stronger statistical links between models and data. AREAS TIMELY FOR DEVELOPING RESEARCH: Greater appreciation by the medical community of the uses and limitations of models and a greater appreciation by modellers of the constraints on public-health resources.

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Using a novel interpretation of dynamic networks, we analyse the network of livestock movements in Great Britain in order to determine the risk of a large epidemic of foot-and-mouth disease (FMD). This network is exceptionally well characterized, as there are legal requirements that the date, source, destination and number of animals be recorded and held on central databases. We identify a percolation threshold in the structure of the livestock network, indicating that, while there is little possibility of a national epidemic of FMD in winter when the catastrophic 2001 epidemic began, there remains a risk in late summer or early autumn. These predictions are corroborated by a non-parametric simulation in which the movements of livestock in 2003 and 2004 are replayed as they occurred. Despite the risk, we show that the network displays small-world properties which can be exploited to target surveillance and control and drastically reduce this risk.

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We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

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Unilateral hydrocephalus due to foramen of Monro-obstruction was diagnosed in a newborn who presented with macrocephaly at birth. The mother had mumps in the second trimester of pregnancy and immunological studies indicated possible intrauterine infection of the baby with mumps virus. His condition deteriorated rapidly, and he developed myoclonic seizures. The possible relationship of intrauterine mumps infection to neonatal neurological complications is discussed.

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