General - ISDS

The APCC hotline fields daily calls regarding potential animal intoxications from the US, its territories, and Canada. We explored the value of these data for identifying increased occurrences of intoxications related to livestock and poultry species, toxicant product categories, clinical syndromes, and illness severity. These data proved valuable for identifying risks of toxicant exposures by species, product category, and season. In addition to identifying intoxication risks to animal health, these data could be used to monitor for infectious outbreaks that may initially be confused for intoxications.

Objective

To describe the value of the American Society for the Prevention of Cruelty to Animals (ASPCA) Poison Control Center (APCC) livestock animal calls as a passive data stream for biosurveillance of number of calls, species affected, toxicant exposures, and clinical syndromes.

Despite the steady increase in immunization coverage in Kenya, the most recent Kenya Demographic and Health Survey (KDHS) shows that there is still immunization inequality across the country. Nationally, 2 out of every 3 (66.67%) children has been fully immunized but only 2 out of every 5 (40%) children in the North Eastern region were fully vaccinated1. There is a need to identify the characteristics of the households with children who are not fully immunized for effective intervention.

Objective

Large scale surveys has been used extensively to monitor childhood immunization rates. The purpose of this research is to find measurable features that informs the state of immunization in Kenya.

Taking into account reporting delays in surveillance systems is not methodologically trivial. Consequently, most use the date of the reception of data, rather than the (often unknown) date of the health event itself. The main drawback of this approach is the resulting reduction in sensitivity and specificity1. Combining syndromic data from multiple data streams (most health events may leave a “signature” in multiple data sources) may be performed in a Bayesian framework where the result is presented in the form of a posterior probability for a disease2.

Objective

We apply an empirical Bayesian framework to perform change point analysis on multiple cattle mortality data streams, accounting for delayed reporting of syndromes.

Although significant progress has been made in tobacco control in the United States (US) over the past 50 years, more than 15% of the population currently use tobacco products.1 Tobacco use continues to be the leading cause of preventable death, contributing to over 480,000 deaths and about $300 billion in economic costs each year. To achieve the Healthy People 2020 (HP2020) objective of 12% national adult smoking rate by 2020, it is important to focus our tobacco control efforts on surveillance and addressing disparities in tobacco use prevalence and tobacco-induced diseases across different subpopulations and geographic areas.2 Utah reported the lowest prevalence rate (9.7% in 2014), while rates as high as 28% were identified in central Appalachia. Modern epidemiology is limited in its ability to explain patterns of tobacco use and tobacco-related interventions and policies in these highly prevalent, marginalized environments. Therefore, a combination of quantitative and community-based participatory research (CBPR), as proposed in Public Health 3.0, will expand the scope and reach to address all factors of tobacco use, including cross-sector collaboration and multi-level actions.3 This study aimed to comprehensively investigate counties in the Northeast Tennessee region where tobacco use prevalence is disproportionately highest, and to identify regional and culturally specific evidence-based practices for tobacco control. Additionally, the study examined how these practices can be scaled up to address similar high tobacco use and disadvantaged populations elsewhere in the US and worldwide.

Objective

To examine community engagement as a means to strengthen tobacco-related policies and programs use in marginalized populations.

When monitoring public health incidents using syndromic surveillance systems, Public Health England (PHE) uses the age of the presenting patient as a key indicator to further assess the severity, impact of the incident, and to provide intelligence on the likely cause. However the age distribution of cases is usually not considered until after unusual activity has been identified in the allages population data. We assessed whether monitoring specific age groups contemporaneously could improve the timeliness, specificity and sensitivity of public health surveillance.

Objective

To investigate whether aberration detection methods for syndromic surveillance would be more useful if data were stratified by age band.

Neill’s fast subset scan2 detects significant spatial patterns of disease by efficiently maximizing a log-likelihood ratio statistic over subsets of locations, but may result in patterns that are not spatially compact. The penalized fast subset scan (PFSS)3 provides a flexible framework for adding soft constraints to the fast subset scan, rewarding or penalizing inclusion of individual points into a cluster with additive point-specific penalty terms. We propose the support vector subset scan (SVSS), a novel method that iteratively assigns penalties according to distance from the separating hyperplane learned by a kernel support vector machine (SVM). SVSS efficiently detects disease clusters that are geometrically compact and irregular.

Objective

We present the support vector subset scan (SVSS), a new method for detecting localized and irregularly shaped patterns in spatial data. SVSS integrates the penalized fast subset scan3 with a kernel support vector machine classifier to accurately detect disease clusters that are compact and irregular in shape.

The Ministry of Health of Georgia accepted the Electronic Integrated Disease Surveillance System (EIDSS) as an official disease reporting system in 2012. The Georgian government adopted electronic reporting for both veterinary and human diseases in 2015. We conducted a comparative assessment of progress in the implementation of electronic reporting.

Objective

The objective of this study was to evaluate several aspects of the electronic disease reporting system and its abilities used in Georgia. Also, the study assessed if the system abilities are tailored to the national surveillance requirements. User attitudes (system strength and weaknesses) toward the system was also surveyed.

SOS Médecins France (SOS Med) is the first private and permanent network of general practitioners providing emergency care in France. Besides Hospital emergency departments (HED), SOS Med is therefore a major source of data for detecting and measuring nearreal-time health phenomena. The emergency services provided by the SOS Med have been subject to important changes in the recent years. Their services are enriched by a medical consultation center together with extended working hours. Besides, the south of the region is markedly affected by a declining number of medical practitioners This study was conducted to analyze the regional population coverage of emergency healthcare data provided by HED and SOS Med to the French syndromic surveillance system (SurSaUD®) taking into account distance, health care offer, demographic factors and ecological deprivation factors.

Objective

To analyse population coverage of syndromic surveillance(SS) based on emergency care data by studying i)the attractiveness of respectively SOS Médecins (Emergency care general practitioners) and Hospital emergency departments in the Centre-Val de Loire region and ii) the contribution of ecological deprivation factors in emergency access to healthcare.