Potential use of school absenteeism record for disease surveillance in developing countries, case study in rural Cambodia

Cost-effectiveness analysis of (Nursery) School Absenteeism Surveillance System

BACKGROUND

Our earlier report reported that the (Nursery) School Absenteeism Surveillance System ((N)SASSy) can decrease numbers of patients. This study evaluates (N)SASSy's cost-effectiveness.

METHODS

A social perspective is taken for economic evaluation. For simplicity, 8,000 yen is assumed for direct medical costs. We assume the home health care duration to be 6 days, with 30 000 yen as the indirect opportunity cost of family nursing. Benefit-cost ratios are used as indicators of cost-effectiveness.

RESULTS

By multiplying the disease burden per patient by the reduced number of patients, the (N)SASSy effect was estimated as 206.9 billion yen, with 95% confidence interval of [67.3,346.6] billion yen. The total cost attributable to (N)SASSy throughout Japan is expected to be 2.63 billion yen. The benefit-cost ratio is expected to be approximately 60.

CONCLUSIONS

The estimated benefit-cost ratio is much higher than that for the routine immunization of children.

Infection Control in Nursery Schools and Schools Using a School Absenteeism Surveillance System

Infection control in nursery schools and schools is important for community health and the health of children. In Japan, caregivers of children or students usually report the absence due to illness to their attending nurseries or schools, including symptoms and diagnosed diseases. The (Nursery) School Absenteeism Surveillance System, (N)SASSy, covers about 60% of schools and 40% of nurseries in Japan. In this paper, we evaluated the benefits of (N)SASSy as an infection control measure by a public health center. Mito Public Health Center (MPHC) covers 58 nurseries and 186 schools, as of May 2015, and called the nurseries and/or schools to confirm the situation, in case of aberration detected through (N)SASSy. The outcome was defined as the proportion of cluster avoidance by advice from MPHC. A cluster was identified, when the number of patients at the same facility with the same symptom or diagnosed disease was greater than ten during the prior seven days. During the study period (April 2015-March 2016), MPHC advised 85 times, and clusters were avoided 82 times (96.5%). The proportion of cluster avoidance was 100% for fever, enterohemorrhagic Escherichia coli infection, respiratory syncytial virus infection, or streptococcal pharyngitis infection. The proportion of cluster avoidance for diarrhea, vomiting or gastroenteritis infection, mumps, hand-foot-mouth disease (HFMD), and influenza was 78.8, 50.0, 20.0, and 6.7%, respectively. In conclusion, advice from a public health center given by phone based on information from (N)SASSy will be helpful for reducing the number of clusters of infectious diseases, except for HFMD and influenza.

Association of influenza outbreak in each nursery school and community in a ward in Tokyo, Japan

In nursery schools, influenza outbreaks have occurred every year. However, influenza characteristics of its diffusion among nursery schools, within each nursery school, and among classes of different ages in nursery schools remains unclear. This paper presents an examination of these matters using the Nursery School Absenteeism Surveillance System (NSASSy). All nursery schools in ward A in Tokyo introduced to the NSASSy in 2015. The study period was November 2015 through March 2016. The data of influenza patients were extracted from NSASSy. We examined four definitions of 'starting date of community outbreak' (SDCO) of influenza: 1) the first recorded day of influenza patients (SDCO1), 2) the last day of influenza patients recorded for two consecutive days (SDCO2), 3) three consecutive days (SDCO3), and 4) four consecutive days (SDCO4). We evaluated those four definitions by duration of the initial case at each nursery school from SDCO and evaluated the proportion of nursery schools at which the initial case occurred before SDCO. The average durations of initial cases at respective nursery schools from SDCO1-4 were 40.3, 26.3, 23.1 and 13.3 days. The respective proportions of nursery schools at which the initial case occurred before SDCO1-4 were 3.1%, 6.4%, 9.4% and 40.6%. Results demonstrate that SDCO3 is an appropriate definition of SDCO. Robustness checks for other areas, seasons, and population size constitute the next challenge for research in this area.

Applying the zero-inflated Poisson model with random effects to detect abnormal rises in school absenteeism indicating infectious diseases outbreak

Records of absenteeism from primary schools are valuable data for infectious diseases surveillance. However, the analysis of the absenteeism is complicated by the data features of clustering at zero, non-independence and overdispersion. This study aimed to generate an appropriate model to handle the absenteeism data collected in a European Commission granted project for infectious disease surveillance in rural China and to evaluate the validity and timeliness of the resulting model for early warnings of infectious disease outbreak. Four steps were taken: (1) building a 'well-fitting' model by the zero-inflated Poisson model with random effects (ZIP-RE) using the absenteeism data from the first implementation year; (2) applying the resulting model to predict the 'expected' number of absenteeism events in the second implementation year; (3) computing the differences between the observations and the expected values (O-E values) to generate an alternative series of data; (4) evaluating the early warning validity and timeliness of the observational data and model-based O-E values via the EARS-3C algorithms with regard to the detection of real cluster events. The results indicate that ZIP-RE and its corresponding O-E values could improve the detection of aberrations, reduce the false-positive signals and are applicable to the zero-inflated data.

Asthma-Related School Absenteeism, Morbidity, and Modifiable Factors

INTRODUCTION

Asthma is a leading cause of chronic disease-related school absenteeism. Few data exist on how information on absenteeism might be used to identify children for interventions to improve asthma control. This study investigated how asthma-related absenteeism was associated with asthma control, exacerbations, and associated modifiable risk factors using a sample of children from 35 states and the District of Columbia.

METHODS

The Behavioral Risk Factor Surveillance System Child Asthma Call-back Survey is a random-digit dial survey designed to assess the health and experiences of children aged 0-17 years with asthma. During 2014-2015, multivariate analyses were conducted using 2006-2010 data to compare children with and without asthma-related absenteeism with respect to clinical, environmental, and financial measures. These analyses controlled for sociodemographic and clinical characteristics.

RESULTS

Compared with children without asthma-related absenteeism, children who missed any school because of asthma were more likely to have not well controlled or very poorly controlled asthma (prevalence ratio=1.50; 95% CI=1.34, 1.69) and visit an emergency department or urgent care center for asthma (prevalence ratio=3.27; 95% CI=2.44, 4.38). Mold in the home and cost as a barrier to asthma-related health care were also significantly associated with asthma-related absenteeism.

CONCLUSIONS

Missing any school because of asthma is associated with suboptimal asthma control, urgent or emergent asthma-related healthcare utilization, mold in the home, and financial barriers to asthma-related health care. Further understanding of asthma-related absenteeism could establish how to most effectively use absenteeism information as a health status indicator.

The usefulness of school-based syndromic surveillance for detecting malaria epidemics: experiences from a pilot project in Ethiopia

Background

Syndromic surveillance is a supplementary approach to routine surveillance, using pre-diagnostic and non-clinical surrogate data to identify possible infectious disease outbreaks. To date, syndromic surveillance has primarily been used in high-income countries for diseases such as influenza -- however, the approach may also be relevant to resource-poor settings. This study investigated the potential for monitoring school absenteeism and febrile illness, as part of a school-based surveillance system to identify localised malaria epidemics in Ethiopia.

Methods

Repeated cross-sectional school- and community-based surveys were conducted in six epidemic-prone districts in southern Ethiopia during the 2012 minor malaria transmission season to characterise prospective surrogate and syndromic indicators of malaria burden. Changes in these indicators over the transmission season were compared to standard indicators of malaria (clinical and confirmed cases) at proximal health facilities. Subsequently, two pilot surveillance systems were implemented, each at ten sites throughout the peak transmission season. Indicators piloted were school attendance recorded by teachers, or child-reported recent absenteeism from school and reported febrile illness.

Results

Lack of seasonal increase in malaria burden limited the ability to evaluate sensitivity of the piloted syndromic surveillance systems compared to existing surveillance at health facilities. Weekly absenteeism was easily calculated by school staff using existing attendance registers, while syndromic indicators were more challenging to collect weekly from schoolchildren. In this setting, enrolment of school-aged children was found to be low, at 54 %. Non-enrolment was associated with low household wealth, lack of parental education, household size, and distance from school.

Conclusions

School absenteeism is a plausible simple indicator of unusual health events within a community, such as malaria epidemics, but the sensitivity of an absenteeism-based surveillance system to detect epidemics could not be rigorously evaluated in this study. Further piloting during a demonstrated increase in malaria transmission within a community is recommended.

Estimating the effectiveness of early control measures through school absenteeism surveillance in observed outbreaks at rural schools in Hubei, China

BACKGROUND

School absenteeism is a common data source in syndromic surveillance, which allows for the detection of outbreaks at an early stage. Previous studies focused on its correlation with other data sources. In this study, we evaluated the effectiveness of control measures based on early warning signals from school absenteeism surveillance in rural Chinese schools.

METHODS

A school absenteeism surveillance system was established in all 17 primary schools in 3 adjacent towns in the Chinese region of Hubei. Three outbreaks (varicella, mumps, and influenza-like illness) were detected and controlled successfully from April 1, 2012, to January 15, 2014. An impulse susceptible-exposed-infectious-recovered model was used to fit the epidemics of these three outbreaks. Moreover, it simulated the potential epidemics under interventions resulting from traditional surveillance signals. The effectiveness of the absenteeism-based control measures was evaluated by comparing the simulated datasets.

RESULTS

The school absenteeism system generated 52 signals. Three outbreaks were verified through epidemiological investigation. Compared to traditional surveillance, the school absenteeism system generated simultaneous signals for the varicella outbreak, but 3 days in advance for the mumps outbreak and 2-4 days in advance for the influenza-like illness outbreak. The estimated excess protection rates of control measures based on early signals were 0.0%, 19.0-44.1%, and 29.0-37.0% for the three outbreaks, respectively.

CONCLUSIONS

Although not all outbreak control measures can benefit from early signals through school absenteeism surveillance, the effectiveness of early signal-based interventions is obvious. School absenteeism surveillance plays an important role in reducing outbreak spread.