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Infectious intestinal disease (IID) is common, and children are more likely than adults both to have IID and to transmit infection onto others. Before the introduction of the vaccine, rotavirus was the leading cause of severe childhood diarrhea, with norovirus and
The aim of this study is to explore the role and utility of school attendance registers in the detection and surveillance of IID in children. The secondary aims are to estimate the burden of IID on school absenteeism and to assess the impact of the rotavirus vaccine on illness absence among school-aged children.
This study is a retrospective analysis of school attendance registers to investigate whether school absences due to illness can be used to capture seasonal trends and outbreaks of infectious intestinal disease among school-aged children. School absences in Merseyside, United Kingdom will be compared and combined with routine health surveillance data from primary care, laboratories, and telehealth services. These data will be used to model spatial and temporal variations in the incidence of IID and to apportion likely causes to changes in school absenteeism trends. This will be used to assess the potential utility of school attendance data in the surveillance of IID and to estimate the burden of IID absenteeism in schools. It will also inform an analysis of the impact of the rotavirus vaccine on disease within this age group.
This study has received ethical approval from the University of Liverpool Research Ethics Committee (reference number 1819). Use of general practice data has been approved for the evaluation of rotavirus vaccination in Merseyside by NHS Research Ethics Committee, South Central-Berkshire REC Reference 14/SC/1140.
This study is unique in considering whether school attendance registers could be used to enhance the surveillance of IID. Such data have multiple potential applications and could improve the identification of outbreaks within schools, allowing early intervention to reduce transmission both within and outside of school settings. These data have the potential to act as an early warning system, identifying infections circulating within the community before they enter health care settings. School attendance data could also inform the evaluation of vaccination programs, such as rotavirus and, in time, norovirus.
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Infectious intestinal diseases (IIDs) are common in both high- and low-income countries, causing an estimated 2 billion cases globally each year [
Children are disproportionately affected by IID, with those younger than 5 years accounting for 38% of foodborne cases globally [
Public health surveillance of IID is primarily based on health care data such as laboratory reports, statutory notifications, hospital admissions, primary care consultations, and calls to remote telehealth services [
School attendance registers offer a novel data set that could be used to identify community cases of IID that might not otherwise be detected. School absenteeism data have shown potential in the surveillance of both seasonal and pandemic influenza [
This study aims to explore the role and utility of school attendance registers in the detection and surveillance of IID in children. The secondary aims are to estimate the burden of IID on school absenteeism and to assess the impact of the rotavirus vaccine on illness absence among school-aged children.
This study will take place in local government areas within Merseyside in the North West of England. Merseyside is a predominately urban, metropolitan county with a population of 1.38 million, over 240,000 of whom are school-aged children [
The study will be a retrospective analysis of school absenteeism data to investigate whether school attendance registers can be used to capture seasonal trends and outbreaks of IID among school-aged children. Although these data are routinely collected by local government for school attendance management [
School absenteeism data is available at the individual school level. Attendance data for schools providing primary (4-11 years of age) and secondary (11-16 years of age) education, regardless of type of school, will be sought from the local government in Merseyside, with data broken down by school and year group. Total absences and absences due to illness will be requested. Details of the number of children in each school and year group will also be obtained to allow corresponding rates to be calculated.
Laboratory data reported to Public Health England (PHE) North West will be used to obtain organism-specific rates of IID within the different geographical areas. These data are routinely collected and reported to PHE from diagnostic and reference laboratories [
Primary care consultations for diarrhea or vomiting will be used as another measure of probable cases of IID. These data have recently been collected from clinical commissioning groups and general practices across Merseyside to inform an evaluation of the rotavirus vaccine [
To facilitate the spatiotemporal modeling, numbers from each data set will be aggregated to weekly rates to enable a common timescale. The spatial measurement will depend upon the data source; for school absenteeism data, the postcode of the school will be used alongside the catchment area (where appropriate). Primary care consultation data has been mapped to lower super output areas (LSOAs), which represents a geographical area with between 1000 and 3000 residents [
To allow the analysis to be conducted at the year-group level, the surveillance data will include details of the patient’s age (year of birth) and their sex. All other personally identifiable information will be removed from the data before it is transferred to the research team. The outcomes of the analysis will be based on aggregated data.
Data will be examined retrospectively from July 2007 to June 2016, capturing 9 IID seasons. Each season is considered to start in calendar week 27 and end in calendar week 26 of the following year.
This study will focus on three of the five local government areas within Merseyside to reflect the coverage of primary care data collected to inform an evaluation of the rotavirus vaccine [
The total number of schools across the three local government areas is 372, consisting of 299 primary schools and 103 secondary schools. Of these schools, 30 deliver both primary and secondary education. The total pupil population across all included schools is 140,164. Assuming that each year one in four pupils are affected by IID [
The case definitions used within each data set are outlined in
Absence with registration code “I” (illness, not medical or dental appointments)
Calls for vomiting
Calls for diarrhea
Diarrhea and vomiting (19G)
Diarrhea symptom not otherwise specified (19F6)
Viral gastroenteritis (A07y0)
Diarrhea (19F2)
Gastroenteritis—presumed infectious origin (A0812)
Diarrhea of presumed infectious origin (A083)
Infantile viral gastroenteritis (A07y1)
Infectious gastroenteritis (A0803)
Enteritis due to rotavirus (A0762)
Infectious diarrhea (A082)
Detection of bacterial, viral, or protozoal infectious intestinal disease organisms in a fecal specimen
Recruitment will be conducted at a local government level. Local government will be approached via their public health departments and invited to participate in this study. Consent for use of aggregated school attendance data will be sought from the local government, who carry the legal responsibility for the data and its use. As the data are aggregated and anonymized, consent will not be sought from individual schools or parents.
A descriptive analysis will be undertaken of each data set to examine and describe the temporal trends and seasonality of illness absenteeism rates and of confirmed and probable cases of IID. The analysis will be stratified by age to capture varying rates of disease in different year groups. Rotavirus-specific incidence data will be obtained from laboratory reports. The mathematical and statistical analysis will include an organism-specific dynamic transmission model and a mixed effect regression analysis to apportion cause to the variations in absenteeism and to estimate organism-specific incidence rates. The complexity of dynamical models will be decided during the project based on the outputs of the descriptive analysis. Rotavirus modeling will include an interrupted time series analysis to explore changes in school absenteeism rates pre- and postintroduction of the vaccine. This will support an assessment of the impact of vaccination on disease transmission in the community. Other organisms that commonly cause IID in children will also be included in the analysis (eg, norovirus and
This study received ethical approval from the University of Liverpool Research Ethics Committee (reference number 1819). Use of general practice data has been approved for the evaluation of rotavirus vaccination in Merseyside by the NHS Research Ethics Committee, South Central-Berkshire REC Reference 14/SC/1140. Study findings will be submitted to open access peer-reviewed journals and presented at scientific conferences and meetings, including meetings with stakeholders.
Current surveillance of IID is predominantly based on health care data, and therefore, illness that is managed within the community will often go undetected. This study is unique in considering whether school absenteeism data could be used to enhance the surveillance of IID. The findings could have several important applications. These data could support the improved identification of outbreaks in schools, allowing early intervention to reduce transmission both within and outside of the school setting. As children may be the first affected by seasonal illness, these data have the potential to act as an early warning system, identifying infections circulating within the community before they enter health care settings. Absenteeism data could also be used to inform the evaluation of vaccination programs, such as rotavirus and potentially, in time, norovirus. Similarly, these data could be used to monitor the impact of health improvement programs such as handwashing interventions.
However, there are some limitations that should be considered. The most pertinent is the low specificity of the case definition for illness absenteeism. As a single code is used for all causes of illness absenteeism, these data cannot distinguish between absences caused by IID and absences from other illnesses such as respiratory tract infections. Therefore, the burden of IID on absenteeism cannot be directly measured, and modeling of routine surveillance data is required to apportion likely cause to changes in absenteeism rates. A further consideration in this study is the spatial measure available within each data set; the NHS 111 telehealth service does not collect information below the level of postcode district and hence the statistical modeling, when including this data set, will be restricted to this geographical level. This limits the ability of this analysis to test whether school absenteeism data can detect localized outbreaks of IID within communities. However, this reflects a limitation within our current surveillance systems and one that school attendance data has the potential to rectify. Future work should consider the feasibility of collecting symptom-specific absence information from schools to enhance the specificity of the data and support the syndromic surveillance of a broader range of childhood infectious disease.
Health Protection Research Unit
infectious intestinal disease
lower super output area
National Institute for Health Research
Public Health England
This research was funded by the National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Gastrointestinal Infections at University of Liverpool in partnership with Public Health England, in collaboration with University of East Anglia, University of Oxford, and the Quadram Institute (grant NIHR HPRU 2012-10038). DH is funded by an NIHR Post-doctoral Fellowship (PDF-2018-11-ST2-006). IH is supported by the UK Research and Innovation through the JUNIPER modeling consortium (grant MR/V038613/1). The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, the Department of Health and Social Care, or Public Health England.
ALD, JPH, RV, DH, and SJO all contributed to the study design. IH contributed to the statistical methods. ALD wrote the first draft of the manuscript. All authors read and approved the final manuscript.
DH report grants on the topic of rotavirus vaccines, outside of the submitted work, from GlaxoSmithKline Biologicals, Sanofi Pasteur, and Merck and Co (Kenilworth, NJ) after the closure of Sanofi Pasteur-MSD in December 2016. RV report grants on the topic of rotavirus vaccines, outside of the submitted work, from GlaxoSmithKline Biologicals. ALD, JPH, IH, and SJO have nothing to disclose.