Missouri K-12 school collection and reporting of school-based syndromic surveillance data: a cross sectional study.
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ABSTRACT:
SUBMITTER: Rebmann T
PROVIDER: S-EPMC4736256 | biostudies-other | 2016 Feb
REPOSITORIES: biostudies-other
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Project description:BackgroundSyndromic surveillance through web or phone-based polling has been used to track the course of infectious diseases worldwide. Our study objective was to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada.MethodsThis was a cross-sectional study using three distinct Canada-wide web-based surveys, and phone polling in Ontario. All three sources contained self-reported information on COVID-19 symptoms and testing. In addition to describing respondent characteristics, we examined symptom frequency and the testing rate among the symptomatic, as well as rates of symptoms and testing across respondent groups.ResultsWe found that over March- April 2020, 1.6% of respondents experienced a symptom on the day of their survey, 15% of Ontario households had a symptom in the previous week, and 44% of Canada-wide respondents had a symptom in the previous month. Across the three surveys, SARS-CoV-2-testing was reported in 2-9% of symptomatic responses. Women, younger and middle-aged adults (versus older adults) and Indigenous/First nations/Inuit/Métis were more likely to report at least one symptom, and visible minorities were more likely to report the combination of fever with cough or shortness of breath.InterpretationThe low rate of testing among those reporting symptoms suggests significant opportunity to expand testing among community-dwelling residents of Canada. Syndromic surveillance data can supplement public health reports and provide much-needed context to gauge the adequacy of SARS-CoV-2 testing rates.
| S-EPMC7531838 | biostudies-literature
Project description:Delayed reporting of health data may hamper the early detection of infectious diseases in surveillance systems. Furthermore, combining multiple data streams, e.g. aiming at improving a system's sensitivity, can be challenging. In this study, we used a Bayesian framework where the result is presented as the value of evidence, i.e. the likelihood ratio for the evidence under outbreak versus baseline conditions. Based on a historical data set of routinely collected cattle mortality events, we evaluated outbreak detection performance (sensitivity, time to detection, in-control run length) under the Bayesian approach among three scenarios: presence of delayed data reporting, but not accounting for it; presence of delayed data reporting accounted for; and absence of delayed data reporting (i.e. an ideal system). Performance on larger and smaller outbreaks was compared with a classical approach, considering syndromes separately or combined. We found that the Bayesian approach performed better than the classical approach, especially for the smaller outbreaks. Furthermore, the Bayesian approach performed similarly well in the scenario where delayed reporting was accounted for to the scenario where it was absent. We argue that the value of evidence framework may be suitable for surveillance systems with multiple syndromes and delayed reporting of data.
| S-EPMC5430846 | biostudies-literature
Project description: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.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.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.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.
| S-EPMC4707000 | biostudies-other
Project description:School-based influenza-like-illness (ILI) syndromic surveillance can be an important part of influenza community surveillance by providing early warnings for outbreaks and leading to a fast response. From September 2012 to December 2014, syndromic surveillance of ILI was carried out in 4 county-level schools. The cumulative sum methods(CUSUM) was used to detect abnormal signals. A susceptible-exposed-infectious/asymptomatic-recovered (SEIAR) model was fit to the influenza outbreak without control measures and compared with the actual influenza outbreak to evaluate the effectiveness of early control efforts. The ILI incidence rates in 2014 (14.51%) was higher than the incidence in 2013 (5.27%) and 2012 (3.59%). Ten school influenza outbreaks were detected by CUSUM. Each outbreak had high transmissibility with a median Runc of 4.62. The interventions in each outbreak had high effectiveness and all Rcon were 0. The early intervention had high effectiveness within the school-based ILI syndromic surveillance. Syndromic surveillance within schools can play an important role in controlling influenza outbreaks.
| S-EPMC5590954 | biostudies-literature
Project description:BackgroundSoil Transmitted Helminths (STH) infect over 1.5 billion people globally and are associated with anemia and stunting, resulting in an annual toll of 1.9 million Disability-Adjusted Life Years (DALYs). School-based deworming (SBD), via mass drug administration (MDA) campaigns with albendazole or mebendazole, has been recommended by the World Health Organization to reduce levels of morbidity due to STH in endemic areas. DeWorm3 is a cluster-randomized trial, conducted in three study sites in Benin, India, and Malawi, designed to assess the feasibility of interrupting STH transmission with community-wide MDA as a potential strategy to replace SBD. This analysis examines data from the DeWorm3 trial to quantify discrepancies between school-level reporting of SBD and gold standard individual-level survey reporting of SBD.Methodology/principal findingsPopulation-weighted averages of school-level SBD calculated at the cluster level were compared to aggregated individual-level SBD estimates to produce a Mean Squared Error (MSE) estimate for each study site. In order to estimate individual-level SBD coverage, these MSE values were applied to SBD estimates from the control arm of the DeWorm3 trial, where only school-level reporting of SBD coverage had been collected. In each study site, SBD coverage in the school-level datasets was substantially higher than that obtained from individual-level datasets, indicating possible overestimation of school-level SBD coverage. When applying observed MSE to project expected coverages in the control arm, SBD coverage dropped from 89.1% to 70.5% (p-value < 0.001) in Benin, from 97.7% to 84.5% (p-value < 0.001) in India, and from 41.5% to 37.5% (p-value < 0.001) in Malawi.Conclusions/significanceThese estimates indicate that school-level SBD reporting is likely to significantly overestimate program coverage. These findings suggest that current SBD coverage estimates derived from school-based program data may substantially overestimate true pediatric deworming coverage within targeted communities.Trial registrationNCT03014167.
| S-EPMC10118084 | biostudies-literature
Project description:Qualitative methods are increasingly being used in emergency care research. Rigorous qualitative methods can play a critical role in advancing the emergency care research agenda by allowing investigators to generate hypotheses, gain an in-depth understanding of health problems or specific populations, create expert consensus, and develop new intervention and dissemination strategies. In Part I of this two-article series, we provided an introduction to general principles of applied qualitative health research and examples of its common use in emergency care research, describing study designs and data collection methods most relevant to our field (observation, individual interviews, and focus groups). Here in Part II of this series, we outline the specific steps necessary to conduct a valid and reliable qualitative research project, with a focus on interview-based studies. These elements include building the research team, preparing data collection guides, defining and obtaining an adequate sample, collecting and organizing qualitative data, and coding and analyzing the data. We also discuss potential ethical considerations unique to qualitative research as it relates to emergency care research.
| S-EPMC4560670 | biostudies-literature
Project description:The availability of weekly Web-based participatory surveillance data on self-reported influenza-like illness (ILI), defined here as self-reported fever and cough/sore throat, over several influenza seasons allows for estimation of the incidence of influenza infection in population cohorts. We demonstrate this using syndromic data reported through the Influenzanet surveillance platform in the Netherlands. We used the 2011-2012 influenza season, a low-incidence season that began late, to assess the baseline rates of self-reported ILI during periods of low influenza circulation, and we used ILI rates above that baseline level from the 2012-1013 season, a major influenza season, to estimate influenza attack rates for that period. The latter conversion required estimates of age-specific probabilities of self-reported ILI given influenza (Flu) infection (P(ILI | Flu)), which were obtained from separate data (extracted from Hong Kong, China, household studies). For the 2012-2013 influenza season in the Netherlands, we estimated combined influenza A/B attack rates of 29.2% (95% credible interval (CI): 21.6, 37.9) among survey participants aged 20-49 years, 28.3% (95% CI: 20.7, 36.8) among participants aged 50-60 years, and 5.9% (95% CI: 0.4, 11.8) among participants aged ?61 years. Estimates of influenza attack rates can be obtained in other settings using analogous, multiseason surveillance data on self-reported ILI together with separate, context-specific estimates of P(ILI | Flu).
| S-EPMC4036214 | biostudies-literature
Project description:BackgroundSurveillance of univariate syndromic data as a means of potential indicator of developing public health conditions has been used extensively. This paper aims to improve the performance of detecting outbreaks by using a background forecasting algorithm based on the adaptive recursive least squares method combined with a novel treatment of the Day of the Week effect.MethodsPrevious work by the first author has suggested that univariate recursive least squares analysis of syndromic data can be used to characterize the background upon which a prediction and detection component of a biosurvellance system may be built. An adaptive implementation is used to deal with data non-stationarity. In this paper we develop and implement the RLS method for background estimation of univariate data. The distinctly dissimilar distribution of data for different days of the week, however, can affect filter implementations adversely, and so a novel procedure based on linear transformations of the sorted values of the daily counts is introduced. Seven-days ahead daily predicted counts are used as background estimates. A signal injection procedure is used to examine the integrated algorithm's ability to detect synthetic anomalies in real syndromic time series. We compare the method to a baseline CDC forecasting algorithm known as the W2 method.ResultsWe present detection results in the form of Receiver Operating Characteristic curve values for four different injected signal to noise ratios using 16 sets of syndromic data. We find improvements in the false alarm probabilities when compared to the baseline W2 background forecasts.ConclusionThe current paper introduces a prediction approach for city-level biosurveillance data streams such as time series of outpatient clinic visits and sales of over-the-counter remedies. This approach uses RLS filters modified by a correction for the weekly patterns often seen in these data series, and a threshold detection algorithm from the residuals of the RLS forecasts. We compare the detection performance of this algorithm to the W2 method recently implemented at CDC. The modified RLS method gives consistently better sensitivity at multiple background alert rates, and we recommend that it should be considered for routine application in bio-surveillance systems.
| S-EPMC2639573 | biostudies-literature
Project description:INTRODUCTION:Despite interventions by low and middle-income countries toward the achievement of the global Sustainable Development Goal (SDG) on promoting mental health and well-being of their populace by the year 2030, suicidal behaviours continue to be major causes of premature mortality, especially among young people. This study examined the prevalence and predictors of suicidal behaviours among in-school adolescents in Mozambique. MATERIALS AND METHODS:This was a cross-sectional study of 1918 in-school adolescents using data from the 2015 Global School-based Health Survey (GSHS) of Mozambique. The outcome variables (suicidal ideation, suicidal plan, and suicidal attempt) were measured with single items in the survey. Both bivariate and multivariate analyses were performed using chi-square test of independence and binary logistic regression respectively. Results are presented as Adjusted Odds Ratios for the binary logistic regression analysis. Statistical significance was set at p<0.05. RESULTS:The prevalence of suicidal behaviours 12 months prior to the survey were 17.7%, 19.6% and 18.5% for suicidal ideation, suicidal plan, and suicidal attempt respectively. Adolescents who experienced anxiety had higher odds of suicidal ideation [AOR = 1.616, 95%CI = 1.148-2.275], suicidal plan [AOR = 1.507, 95%CI = 1.077-2.108], and suicidal attempt [AOR = 1.740, 95%CI = 1.228-2.467]. Adolescents who were physically attacked in school were also more likely to ideate [AOR = 1.463, 95%CI = 1.115-1.921], plan [AOR = 1.328, 95%CI = 1.020-1.728], and attempt [AOR = 1.701, 95%CI = 1.306-2.215] suicide. Having close friends was, however, an important protective factor against suicidal ideation [AOR = 0.694, 95%CI = 0.496-0.971], plan [AOR = 0.625, 95%CI = 0.455-0.860], and attempt [AOR = 0.529, 95%CI = 0.384-0.729]. Peer support also reduced the risk of suicidal ideation [AOR = 0.704, 95%CI = 0.538,0.920] and plan [AOR = 0.743, 95%CI = 0.572,0.966] among the in-school adolescents. CONCLUSION:Suicidal behaviours constitute major public health challenges among in-school adolescents in Mozambique. The behaviours are predominant among adolescents who are physically attacked and those who experience anxiety. Conversely, having close friends serves as a protective factor against suicidal behaviours. To ensure that Mozambique meets the SDG target of promoting the mental health of all by the year 2030, the Government of Mozambique and educational authorities should urgently design and implement innovative interventions and strengthen existing ones that seek to address physical attacks and anxiety among in-school adolescents. School administrations should also incorporate programmes that seek to congregate students and offer platforms for social interaction and cohesion.
| S-EPMC7380623 | biostudies-literature
Project description:BACKGROUND:Cannabis use can have serious detrimental effects in children and adolescents. It is therefore important to continually assess the use of cannabis among young people in order to inform prevention efforts. We assessed the prevalence of cannabis use among middle and high school students in Ontario and examined its association with demographic and behavioural factors. METHODS:Data were obtained from the 2015 Ontario Student Drug Use and Health Survey, a province-wide school-based survey of students in grades 7 through 12. Analyses included a representative sample of 9920 middle and high school students. Bivariate cross-tabulations and logistic regression analyses were used to investigate the factors associated with cannabis use. RESULTS:Overall, 21.5% and 13.9% of students reported using cannabis in the previous year and previous month, respectively. The conditional probability that an adolescent who reported cannabis use in the previous year would report daily use was 12.5%. There was a significant dose-response gradient with age, with older students being more likely to use cannabis than younger students. In multivariable analyses, being in grades 10 through 12 (odds ratios [ORs] ranged from 3.71 to 3.85), being black (OR 2.67 [95% confidence interval (CI) 1.76-4.05]), using tobacco cigarettes (OR 10.10 [95% CI 8.68-13.92]) and being an occasional (OR 5.35 [95% CI 4.01-7.13]) or regular (OR 14.6 [95% CI 10.8-19.89]) alcohol user were associated with greater odds of cannabis use. Being an immigrant was associated with lower odds of cannabis use (OR 0.55 [95% CI 0.39-0.78]). INTERPRETATION:The findings suggest that cannabis use is prevalent among middle and high school students in Ontario and is strongly associated with tobacco cigarette smoking and alcohol consumption. Future research should document trends in cannabis use over time, including its risks, especially when the legalization of recreational cannabis comes into effect.
| S-EPMC5878957 | biostudies-literature