Dataset Information

The Relationship Between School Holidays and Transmission of Influenza in England and Wales.

ABSTRACT: School closure is often considered as an influenza control measure, but its effects on transmission are poorly understood. We used 2 approaches to estimate how school holidays affect the contact parameter (the per capita rate of contact sufficient for infection transmission) for influenza using primary care data from England and Wales (1967-2000). Firstly, we fitted an age-structured susceptible-infectious-recovered model to each year's data to estimate the proportional change in the contact parameter during school holidays as compared with termtime. Secondly, we calculated the percentage difference in the contact parameter between holidays and termtime from weekly values of the contact parameter, estimated directly from simple mass-action models. Estimates were combined using random-effects meta-analysis, where appropriate. From fitting to the data, the difference in the contact parameter among children aged 5-14 years during holidays as compared with termtime ranged from a 36% reduction to a 17% increase; estimates were too heterogeneous for meta-analysis. Based on the simple mass-action model, the contact parameter was 17% (95% confidence interval: 10, 25) lower during holidays than during termtime. Results were robust to the assumed proportions of infections that were reported and individuals who were susceptible when the influenza season started. We conclude that school closure may reduce transmission during influenza outbreaks.

SUBMITTER: Jackson C

PROVIDER: S-EPMC5860259 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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The Relationship Between School Holidays and Transmission of Influenza in England and Wales.

Jackson Charlotte C Vynnycky Emilia E Mangtani Punam P

American journal of epidemiology 20161015 9

School closure is often considered as an influenza control measure, but its effects on transmission are poorly understood. We used 2 approaches to estimate how school holidays affect the contact parameter (the per capita rate of contact sufficient for infection transmission) for influenza using primary care data from England and Wales (1967-2000). Firstly, we fitted an age-structured susceptible-infectious-recovered model to each year's data to estimate the proportional change in the contact par ...[more]

PMID: 27744384

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Project description:BACKGROUND:Recently, a small number of studies have suggested that gains in fitness and reductions in body fat achieved during the school term are reversed or stagnate during the holiday period. This may be associated with changed activity patterns. The aim of this study was to compare 24-h activity compositions between school and holiday periods in Australian children. METHODS:The participants in this study were 366 children (53% female, 13.4?±?2.3?years) who were a subgroup of the 2007 Australian National Children's Nutrition and Physical Activity Survey. Each child recalled use of time on at least one school day, one weekend day and one holiday using the Multimedia Activity Recall for Children and Adults. Composite "in-term" and "holiday" use-of-time profiles were generated by weighting school days by 5, and weekends by 2 where data were available. Difference between holiday and in-term time use was assessed using a compositional multivariate linear model for repeated measures. Subsequent models tested for interaction between time of measurement and socio-economic status or body mass index. RESULTS:Time use was significantly different between holidays and in-term days (F?=?103, p?<?0.0001). On holidays, children accumulated 140?min less School-related time, compensated by sleeping 40?min longer, 58?min more Screen Time, and 35?min more Domestic/Social time. Children spent 10?min less in vigorous physical activity, and although sitting time was 33?min/day less during holidays, estimated total daily energy expenditure (TDEE) was 5.4% lower. Differences between holiday and in-term activity compositions did not vary by parental education (F?=?1.2, p?=?0.25), postcode-level socio-economic status (F?=?0.9, p?=?0.56) or weight status (F?=?1.7, p =?0.07). CONCLUSIONS:In this subsample of a nationally representative survey of Australian children, holidays were characterised by longer sleep and higher TV and videogame time, lower vigorous activity and lower TDEE. Uncompensated by dietary adjustments, these differences would result in an accumulation of about 650?g of fat over a six-week holiday period. Holiday activity patterns may be a promising focus for obesity prevention efforts.

Project description:Many epidemic models approximate social contact behavior by assuming random mixing within mixing groups (e.g., homes, schools, and workplaces). The effect of more realistic social network structure on estimates of epidemic parameters is an open area of exploration. We develop a detailed statistical model to estimate the social contact network within a high school using friendship network data and a survey of contact behavior. Our contact network model includes classroom structure, longer durations of contacts to friends than non-friends and more frequent contacts with friends, based on reports in the contact survey. We performed simulation studies to explore which network structures are relevant to influenza transmission. These studies yield two key findings. First, we found that the friendship network structure important to the transmission process can be adequately represented by a dyad-independent exponential random graph model (ERGM). This means that individual-level sampled data is sufficient to characterize the entire friendship network. Second, we found that contact behavior was adequately represented by a static rather than dynamic contact network. We then compare a targeted antiviral prophylaxis intervention strategy and a grade closure intervention strategy under random mixing and network-based mixing. We find that random mixing overestimates the effect of targeted antiviral prophylaxis on the probability of an epidemic when the probability of transmission in 10 minutes of contact is less than 0.004 and underestimates it when this transmission probability is greater than 0.004. We found the same pattern for the final size of an epidemic, with a threshold transmission probability of 0.005. We also find random mixing overestimates the effect of a grade closure intervention on the probability of an epidemic and final size for all transmission probabilities. Our findings have implications for policy recommendations based on models assuming random mixing, and can inform further development of network-based models.

Project description:Very different influenza seasons have been observed from 2008/09-2011/12 in England and Wales, with the reported burden varying overall and by age group. The objective of this study was to estimate the impact of influenza on all-cause and cause-specific mortality during this period. Age-specific generalised linear regression models fitted with an identity link were developed, modelling weekly influenza activity through multiplying clinical influenza-like illness consultation rates with proportion of samples positive for influenza A or B. To adjust for confounding factors, a similar activity indicator was calculated for Respiratory Syncytial Virus. Extreme temperature and seasonal trend were controlled for. Following a severe influenza season in 2008/09 in 65+yr olds (estimated excess of 13,058 influenza A all-cause deaths), attributed all-cause mortality was not significant during the 2009 pandemic in this age group and comparatively low levels of influenza A mortality were seen in post-pandemic seasons. The age shift of the burden of seasonal influenza from the elderly to young adults during the pandemic continued into 2010/11; a comparatively larger impact was seen with the same circulating A(H1N1)pdm09 strain, with the burden of influenza A all-cause excess mortality in 15-64 yr olds the largest reported during 2008/09-2011/12 (436 deaths in 15-44 yr olds and 1,274 in 45-64 yr olds). On average, 76% of seasonal influenza A all-age attributable deaths had a cardiovascular or respiratory cause recorded (average of 5,849 influenza A deaths per season), with nearly a quarter reported for other causes (average of 1,770 influenza A deaths per season), highlighting the importance of all-cause as well as cause-specific estimates. No significant influenza B attributable mortality was detected by season, cause or age group. This analysis forms part of the preparatory work to establish a routine mortality monitoring system ahead of introduction of the UK universal childhood seasonal influenza vaccination programme in 2013/14.

Dataset Information

The Relationship Between School Holidays and Transmission of Influenza in England and Wales.

Publications

The Relationship Between School Holidays and Transmission of Influenza in England and Wales.

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