The influence of school holiday timing on epidemic impact.

The impact of reactive school closure on an epidemic is uncertain, since it is not clear how an unplanned closure will affect social mixing patterns. The effect of school holidays on social mixing patterns is better understood. Here, we use mathematical models to explore the influence of the timing of school holidays on the final size and peak incidence of an influenza-like epidemic. A well-timed holiday can reduce the impact of an epidemic, in particular substantially reducing an epidemic's peak. Final size and peak incidence cannot both be minimized: a later holiday is optimal for minimizing the final size, while an earlier holiday minimizes peak incidence. Using social mixing data from the UK, we estimated that, had the 2009 influenza epidemic not been interrupted by the school summer holidays, the final size would have been about 20% larger and the peak about 170% higher.

Rapid assessment of influenza vaccine effectiveness: analysis of an internet-based cohort.

The effectiveness of influenza vaccination programmes is seldom known during an epidemic. We developed an internet-based system to record influenza-like symptoms and response to infection in a participating cohort. Using self-reports of influenza-like symptoms and of influenza vaccine history and uptake, we estimated vaccine effectiveness (VE) without the need for individuals to seek healthcare. We found that vaccination with the 2010 seasonal influenza vaccine was significantly protective against influenza-like illness (ILI) during the 2010-2011 influenza season (VE 52%, 95% CI 27-68). VE for individuals who received both the 2010 seasonal and 2009 pandemic influenza vaccines was 59% (95% CI 27-77), slightly higher than VE for those vaccinated in 2010 alone (VE 46%, 95% CI 9-68). Vaccinated individuals with ILI reported taking less time off work than unvaccinated individuals with ILI (3.4 days vs. 5.3 days, P<0.001).

Measuring social networks in British primary schools through scientific engagement.

Primary schools constitute a key risk group for the transmission of infectious diseases, concentrating great numbers of immunologically naive individuals at high densities. Despite this, very little is known about the social patterns of mixing within a school, which are likely to contribute to disease transmission. In this study, we present a novel approach where scientific engagement was used as a tool to access school populations and measure social networks between young (4-11 years) children. By embedding our research project within enrichment activities to older secondary school (13-15) children, we could exploit the existing links between schools to achieve a high response rate for our study population (around 90% in most schools). Social contacts of primary school children were measured through self-reporting based on a questionnaire design, and analysed using the techniques of social network analysis. We find evidence of marked social structure and gender assortativity within and between classrooms in the same school. These patterns have been previously reported in smaller studies, but to our knowledge no study has attempted to exhaustively sample entire school populations. Our innovative approach facilitates access to a vitally important (but difficult to sample) epidemiological sub-group. It provides a model whereby scientific communication can be used to enhance, rather than merely complement, the outcomes of research.

The impact of illness and the impact of school closure on social contact patterns.

BACKGROUND: Mathematical models, based on data describing normal patterns of social mixing, are used to understand epidemics in order to predict patterns of disease spread and plan interventions and responses. However, individuals who are ill show behavioural changes that affect their social mixing patterns and predictive models should take into account these changes if they are to be effective. OBJECTIVES: To describe and quantify the changes in (1) social contact behaviour experienced by individuals when they are ill with pandemic H1N1 influenza (swine flu) and (2) mixing patterns of school children that take place as a result of swine flu-related school closures. METHODS: For the first part of the study, a self-completed questionnaire-based study was carried out in the autumn/winter of 2009-10. The study population was individuals who had been diagnosed with swine flu and who received a swine flu antiviral prescription from an antiviral distribution centre (ADC). It consisted of an initial survey to be filled in when participants were symptomatic with swine flu and a follow-up survey to be filled in when they had recovered. Each part of the questionnaire had two sections: patient details and a contact diary. The second part of the study was adapted to quantify the difference in mixing patterns of pupils between the school term and the half-term holiday as school closures did not occur during the study period. Eight schools participated and questionnaire packs were distributed to them, containing two surveys: one to be filled in during the school term and one during the spring half-term holiday. RESULTS: For the patient study, approximately 3800 surveys were distributed by 31 ADCs. Overall, 317 responses to the initial survey were received and 179 participants returned the follow-up survey. For all types of a contact, except contacts made at home, there were highly significant differences in contact behaviour (Wilcoxon signed-rank test, p < 0.001). Individuals made substantially fewer contacts when they were ill than when they were well. Analysis showed that returning to work was the most significant predictor of increased numbers of contacts. Also, the greater the change in the number of symptoms reported, the greater the change in the number of contacts. For the school study, approximately 1100 questionnaire packs were distributed and 134 responses were received, with 119 paired contact diaries. Pupils reported on average 18.51 contacts each day during term time and 9.24 during the half-term holiday - a reduction of over 50% and a highly significant change (Wilcoxon signed-rank test, p < 0.0001). CONCLUSIONS: The evidence from this study suggests that ill individuals make substantial changes to their social contact patterns. These changes are strongly linked to absence from work and the severity of the reported illness. Epidemiological modellers should therefore consider the implications of illness-related behavioural changes on model predictions. Future studies to measure the extent of behavioural change in a broader cross-section of infected cases could be valuable, along with more detailed studies of the social contact patterns of school children, focusing on differences between school terms and school holidays.

Modelling disease spread through random and regular contacts in clustered populations.

An epidemic spreading through a network of regular, repeated, contacts behaves differently from one that is spread by random interactions: regular contacts serve to reduce the speed and eventual size of an epidemic. This paper uses a mathematical model to explore the difference between regular and random contacts, considering particularly the effect of clustering within the contact network. In a clustered population random contacts have a much greater impact, allowing infection to reach parts of the network that would otherwise be inaccessible. When all contacts are regular, clustering greatly reduces the spread of infection; this effect is negated by a small number of random contacts.

Contact tracing strategies in heterogeneous populations.

Contact tracing is a well-established disease control measure that seeks to uncover cases by following chains of infection. This paper examines mathematical models of both single-step and iterative contact tracing schemes and analyses the ability of these procedures to trace core groups and the sensitivity of the intervention to the timescale of tracing. An iterative tracing process is shown to be particularly effective at uncovering high-risk individuals, and thus it provides a powerful public health tool. Further targeting of tracing effort is considered. When the population exhibits like-with-like (assortative) mixing the required effort for eradication can be significantly reduced by preferentially tracing the contacts of high-risk individuals; in populations where individuals have reliable information about their contacts, further gains in efficiency can be realized. Contact tracing is, therefore, potentially an even more potent tool than its present usage suggests.