School-based surveillance of acute infectious disease in children: a systematic review

A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases

BACKGROUND

The early identification of outbreaks of both known and novel influenza-like illnesses is an important public health problem.

OBJECTIVE

The design and testing of a tool that detects and tracks outbreaks of both known and novel influenza-like illness, such as the SARS-CoV-19 worldwide pandemic, accurately and early.

METHODS

This paper describes the ILI Tracker algorithm that first models the daily occurrence of a set of known influenza-like illnesses in hospital emergency departments in a monitored region using findings extracted from patient care reports using natural language processing. We then show how the algorithm can be extended to detect and track the presence of an unmodeled disease which may represent a novel disease outbreak.

RESULTS

We include results based on modeling the diseases influenza, respiratory syncytial virus, human metapneumovirus, and parainfluenza for five emergency departments in Allegheny County Pennsylvania from June 1, 2014 through May 31, 2015. We also include the results of detecting the outbreak of an unmodeled disease, which in retrospect was very likely an outbreak of the enterovirus EV-D68.

CONCLUSIONS

The results reported in this paper provide support that ILI Tracker was able to track well the incidence of four modeled influenza-like diseases over a one-year period, relative to laboratory confirmed cases, and it was computationally efficient in doing so. The system was alsoable to detect a likely novel outbreak of the enterovirus D68 early in an outbreak that occurred in Allegheny County in 2014, as well as clinically characterize that outbreak disease accurately.

CLINICALTRIAL

Descriptive Epidemiology of Pathogens Associated with Acute Respiratory Infection in a Community-Based Study of K-12 School Children (2015-2023)

School-based outbreaks often precede increased incidence of acute respiratory infections in the greater community. We conducted acute respiratory infection surveillance among children to elucidate commonly detected pathogens in school settings and their unique characteristics and epidemiological patterns. The ORegon CHild Absenteeism due to Respiratory Disease Study (ORCHARDS) is a longitudinal, laboratory-supported, school-based, acute respiratory illness (ARI) surveillance study designed to evaluate the utility of cause-specific student absenteeism monitoring for early detection of increased activity of influenza and other respiratory viruses in schools from kindergarten through 12th grade. Eligible participants with ARIs provided demographic, epidemiologic, and symptom data, along with a nasal swab or oropharyngeal specimen. Multipathogen testing using reverse-transcription polymerase chain reaction (RT-PCR) was performed on all specimens for 18 respiratory viruses and 2 atypical bacterial pathogens (Chlamydia pneumoniae and Mycoplasma pneumoniae). Between 5 January 2015 and 9 June 2023, 3498 children participated. Pathogens were detected in 2455 of 3498 (70%) specimens. Rhinovirus/enteroviruses (36%) and influenza viruses A/B (35%) were most commonly identified in positive specimens. Rhinovirus/enteroviruses and parainfluenza viruses occurred early in the academic year, followed by seasonal coronaviruses, RSV, influenza viruses A/B, and human metapneumovirus. Since its emergence in 2020, SARS-CoV-2 was detected year-round and had a higher median age than the other pathogens. A better understanding of the etiologies, presentations, and patterns of pediatric acute respiratory infections can help inform medical and public health system responses.

Predicting Norovirus in England Using Existing and Emerging Syndromic Data: Infodemiology Study

BACKGROUND

Norovirus is associated with approximately 18% of the global burden of gastroenteritis and affects all age groups. There is currently no licensed vaccine or available antiviral treatment. However, well-designed early warning systems and forecasting can guide nonpharmaceutical approaches to norovirus infection prevention and control.

OBJECTIVE

This study evaluates the predictive power of existing syndromic surveillance data and emerging data sources, such as internet searches and Wikipedia page views, to predict norovirus activity across a range of age groups across England.

METHODS

We used existing syndromic surveillance and emerging syndromic data to predict laboratory data indicating norovirus activity. Two methods are used to evaluate the predictive potential of syndromic variables. First, the Granger causality framework was used to assess whether individual variables precede changes in norovirus laboratory reports in a given region or an age group. Then, we used random forest modeling to estimate the importance of each variable in the context of others with two methods: (1) change in the mean square error and (2) node purity. Finally, these results were combined into a visualization indicating the most influential predictors for norovirus laboratory reports in a specific age group and region.

RESULTS

Our results suggest that syndromic surveillance data include valuable predictors for norovirus laboratory reports in England. However, Wikipedia page views are less likely to provide prediction improvements on top of Google Trends and Existing Syndromic Data. Predictors displayed varying relevance across age groups and regions. For example, the random forest modeling based on selected existing and emerging syndromic variables explained 60% variance in the ≥65 years age group, 42% in the East of England, but only 13% in the South West region. Emerging data sets highlighted relative search volumes, including "flu symptoms," "norovirus in pregnancy," and norovirus activity in specific years, such as "norovirus 2016." Symptoms of vomiting and gastroenteritis in multiple age groups were identified as important predictors within existing data sources.

CONCLUSIONS

Existing and emerging data sources can help predict norovirus activity in England in some age groups and geographic regions, particularly, predictors concerning vomiting, gastroenteritis, and norovirus in the vulnerable populations and historical terms such as stomach flu. However, syndromic predictors were less relevant in some age groups and regions likely due to contrasting public health practices between regions and health information-seeking behavior between age groups. Additionally, predictors relevant to one norovirus season may not contribute to other seasons. Data biases, such as low spatial granularity in Google Trends and especially in Wikipedia data, also play a role in the results. Moreover, internet searches can provide insight into mental models, that is, an individual's conceptual understanding of norovirus infection and transmission, which could be used in public health communication strategies.

Monitoring School Absenteeism for Influenza-Like Illness Surveillance: Systematic Review and Meta-analysis

Background

Influenza causes considerable disease burden each year, particularly in children. Monitoring school absenteeism has long been proposed as a surveillance tool of influenza activity in the community, but the practice of school absenteeism could be varying, and the potential of such usage remains unclear.

Objective

The aim of this paper is to determine the potential of monitoring school absenteeism as a surveillance tool of influenza.

Methods

We conducted a systematic review of the published literature on the relationship between school absenteeism and influenza activity in the community. We categorized the types of school absenteeism and influenza activity in the community to determine the correlation between these data streams. We also extracted this correlation with different lags in community surveillance to determine the potential of using school absenteeism as a leading indicator of influenza activity.

Results

Among the 35 identified studies, 22 (63%), 12 (34%), and 8 (23%) studies monitored all-cause, illness-specific, and influenza-like illness (ILI)–specific absents, respectively, and 16 (46%) used quantitative approaches and provided 33 estimates on the temporal correlation between school absenteeism and influenza activity in the community. The pooled estimate of correlation between school absenteeism and community surveillance without lag, with 1-week lag, and with 2-week lag were 0.44 (95% CI 0.34, 0.53), 0.29 (95% CI 0.15, 0.42), and 0.21 (95% CI 0.11, 0.31), respectively. The correlation between influenza activity in the community and ILI-specific absenteeism was higher than that between influenza activity in community all-cause absenteeism. Among the 19 studies that used qualitative approaches, 15 (79%) concluded that school absenteeism was in concordance with, coincided with, or was associated with community surveillance. Of the 35 identified studies, only 6 (17%) attempted to predict influenza activity in the community from school absenteeism surveillance.

Conclusions

There was a moderate correlation between school absenteeism and influenza activity in the community. The smaller correlation between school absenteeism and community surveillance with lag, compared to without lag, suggested that careful application was required to use school absenteeism as a leading indicator of influenza epidemics. ILI-specific absenteeism could monitor influenza activity more closely, but the required resource or school participation willingness may require careful consideration to weight against the associated costs. Further development is required to use and optimize the use of school absenteeism to predict influenza activity. In particular, the potential of using more advanced statistical models and validation of the predictions should be explored.

Estonian Parents' Awareness of Pediculosis and Its Occurrence in Their Children

Background and Objectives: Pediculosis, or head lice infestation, is a widespread health problem that can affect anyone, regardless of gender, age, or social background. The purpose of this study was to clarify the occurrence of pediculosis among Estonian preschool- and primary school-aged children according to their parents and the parent’s awareness of pediculosis and related behaviors. Materials and Methods: An online questionnaire was completed by the parents of the preschool children (n = 1141) in 2019 and the parents of the elementary school children (n = 362) in 2021. For the descriptive data, t-test, Mann−Whitney or χ2 test, linear regression, and logistic regression analyses were applied. Results: According to the parents, pediculosis had occurred in 34.7% of the children, and more than one-third of pediculosis patients had experienced it more than twice. Lice were mainly acquired from elementary school or preschool and less often from friends, relatives, or training environments. Parents’ knowledge of head lice was rather good; the average score of the correct answers was 14.0 ± 3.4 (max. 20). In the multivariate analysis, higher age (coefficient 0.07, p < 0.001), healthcare education (coefficient 1.19, p < 0.001), and a previous occurrence of pediculosis in a family (coefficient 1.95; p < 0.001) were factors influencing better knowledge. In order to treat the infestation, antilice shampoo and combing were the most often used methods. Conclusion: Despite parents’ awareness, pediculosis infestations continue to be common among our children.

A Pilot Influenza Syndromic Surveillance System Based on Absenteeism and Temperature in China: Development and Usability (Preprint)

Background

Shortcomings of the current school-based infectious disease syndromic surveillance system (SSS) in China include relying on school physicians to collect data manually and ignoring the health information of students in attendance.

Objective

This study aimed to design and implement an influenza SSS based on the absenteeism (collected by face recognition) and temperature of attending students (measured by thermal imaging).

Methods

An SSS was implemented by extending the functionality of an existing application. The system was implemented in 2 primary schools and 1 junior high school in the Yangtze River Delta, with a total of 3535 students. The examination period was from March 1, 2021, to January 14, 2022, with 174 effective days. The daily and weekly absenteeism and fever rates reported by the system (DAR1 and DFR; WAR1 and WFR) were calculated. The daily and weekly absenteeism rates reported by school physicians (DAR2 and WAR2) and the weekly positive rate of influenza virus (WPRIV, released by the Chinese National Influenza Center) were used as standards to evaluate the quality of the data reported by the system.

Results

Absenteeism reported by school physicians (completeness 86.7%) was 36.5% of that reported by this system (completeness 100%), and a significant positive correlation between them was detected (r=0.372, P=.002). When the influenza activity level was moderate, DAR1s were significantly positively correlated among schools (r_ab=0.508, P=.004; r_bc=0.427, P=.02; r_ac=0.447, P=.01). During the influenza breakout, the gap of DAR1s widened. WAR1 peaked 2 weeks earlier in schools A and B than in school C. Variables significantly positively correlated with the WPRIV were the WAR1 and WAR2 of school A, WAR1 of school C, and WFR of school B. The correlation between the WAR1 and WPRIV was greater than that between the WAR2 and WPRIV in school A. Addition of the WFR to the WAR1 of school B increased the correlation between the WAR1 and WPRIV.

Conclusions

Data demonstrated that absenteeism calculation based on face recognition was reliable, but the accuracy of the temperature recorded by the infrared thermometer should be enhanced. Compared with similar SSSs, this system has superior simplicity, cost-effectiveness, data quality, sensitivity, and timeliness.

Head Lice Infestation in Schoolchildren, in Poland-Is There a Chance for Change?

Pediculosis capitis is a current and neglected health issue worldwide. The lack of screening programs contributes to the marginalization of the problem and delays therapeutic measures. Our study aimed to analyze the occurrence of this parasitosis in primary schools in Poland and to determine factors contributing to the persistence of its foci. The research tools were two questionnaires: one for primary school children and the other for school managers. While children answered questions about the epidemiology of pediculosis capitis and expressed their opinion on the hygienic condition of infested persons, the school directors were asked about the occurrence of head lice in schools, preventive measures, and institutions supporting schools in combating the infestation. The survey covered the period 2014–2018. Pediculosis capitis was reported in 87.5% of the schools. The greatest number of cases was reported in the group of 6–9 year-olds (68%). Among 4970 children, 16.7% had no knowledge of head lice; however, 57.1% wanted to increase their awareness of the problem. Campaigns on lice were conducted mainly as a result of emerging pediculosis capitis cases, and most schools could not rely on institutional support. Screening programs and preventive educational campaigns should be part of pediculosis capitis control in Poland.