School-based influenza surveillance has been considered for real-time monitoring of influenza, as children 5-17 years old play an important role in community-level transmission.
Objective
To determine if all-cause and cause-specific school absences improve predictions of virologically confirmed influenza in the community.
ARIs have epidemic and pandemic potential. Prediction of presence of ARIs from individual signs and symptoms in existing studies have been based on clinically-sourced data. Clinical data generally represents the most severe cases, and those from locations with access to healthcare institutions. Thus, the viral information that comes from clinical sampling is insufficient to either capture disease incidence in general populations or its predictability from symptoms. Participatory data — information that individuals today can produce on their own — enabled by the ubiquity of digital tools, can help fill this gap by providing self-reported data from the community. Internet-based participatory efforts such as Flu Near You have augmented existing ARI surveillance through early and widespread detection of outbreaks and public health trends.
Objective
To evaluate prediction of laboratory diagnosis of acute respiratory infection (ARI) from participatory data using machine learning models
Despite the significance of disease reporting to any health system, Grenada like most countries struggle with underreporting of notifiable diseases by physicians. In order to improve the national disease surveillance system in Grenada, it is critical understand the reasons for any underreporting. The study was conducted to determine physicians’ knowledge of notifiable reporting and to identify the barriers to reporting.
Objective
The study was carried out to determine physicians’ knowledge of notifiable reporting and to identify the barriers to reporting in Grenada
Visceral leishmaniasis (VL) is a zoonotic, protozoal infection that is endemic in Georgia, which commonly affects young children. In recent years, the incidence of VL has increased sharply and the geographic distribution has increased. Recently, VL moved to highly populated areas as new foci appeared from 2010-2015, during which, 610 laboratory confirmed cases of VL were registered in Georgia. The majority of cases were found in East Georgia (94.2%) and 5.8% of cases in West Georgia (representing new foci of VL in Georgia).
Objective
The purpose of this study was to describe the epidemiology of visceral leishmaniasis in Georgia and to define new control measures.
The 2016 U.S. Olympic Track and Field Team Trials were held July 1-10 in Eugene, OR. This mass gathering included over 1,000 athletes, 1,500 volunteers, and 175,000 spectators. The Oregon Public Health Division (PHD) and Lane County Public Health (LCPH) participated in pre-event planning and collaborated to produce a daily epidemiology report for the Incident Management Team (IMT) during the event. The state and county public health agencies had collaborated on surveillance for prior mass gatherings, including the 2012 Trials. However, 2016 was the first opportunity to use complete state and county syndromic surveillance data.
Objective
To streamline production of a daily epidemiology report including syndromic surveillance, notifiable disease, and outbreak data during a mass gathering.
There is no safe level of lead in the body, and elevated lead in children can lead to decreased Intelligence Quotients (IQ) and behavioral problems. The American Academy of Pediatrics recommends lead testing of children with a positive risk assessment. Children who live in low socioeconomic areas may be at higher risk for lead exposure. As recent events have shown, having an elevated lead poisoning surveillance system can be critical to ensure that there is not a community-wide lead exposure. To reach the children that may not have been screened by a primary care physician, on March 1, 2016 the Sedgwick County Health Department Women, Infants, and Children (WIC) program began offering lead screenings to all children in the WIC program and their mothers. Per Centers for Disease Control and Prevention (CDC) guidelines, the Sedgwick County Health Department Epidemiology program (Epi) investigates anyone who has an elevated blood lead test (5 μg/dL or greater). There are two types of lead tests – screening (capillary finger stick) and confirmatory (venous blood draw).
The Florida Department of Health in Hillsborough County (FDOH- Hillsborough) conducts enhanced syndromic surveillance on a daily basis. The Electronic Surveillance System for the Early Notification of Community-based Epidemics in Florida (ESSENCE-FL) is the syndromic surveillance system used by epidemiologists within the Florida Department of Health (FDOH). During the time of this study, ESSENCE-FL receives data from 210 of emergency departments (ED) and 33 urgent care centers (UCC) throughout the state of Florida, including 12 EDs and 3 UCCs in Hillsborough County. In 2014, the ESSENCE-FL system added a feature that delivers an automatic daily email to designated primary ESSENCE-FL users in each county containing all visits which have been detected by the state’s visits of interest (VOI) query. The email contains all visits which have been detected by the visits of interest (VOI) query for each ESSENCE-FL users designated county. The VOI query utilizes the combined chief complaint and discharge diagnosis (CCDD) field of a visit for keywords related to reportable diseases and exposures of public health interest. In addition to this VOI email, Hillsborough County analyzes time of arrival alerts, specialized emerging infectious disease queries, poison information center data, and volume levels of syndromes and subsyndromes predetermined by ESSENCE-FL. A daily summary report of the enhanced daily surveillance analysis is then provided to area public health officials within FDOH-Hillsborough and the surrounding counties. This study examines how visits requiring additional investigation are detected and the resources required to complete the investigation.
Objective
Enhanced daily surveillance is used to identify reportable diseases, outbreaks, and clusters and provides situational awareness. This project examines how health care visits requiring additional information are detected using enhanced syndromic surveillance and the resources required from detection through completion.
Zika virus spread quickly through South and Central America in 2015. The City of Houston saw its first travel-related Zika cases in December of 2015. On January 29th, the City held the first planning meeting with regional partners from healthcare, blood banks, petrochemical companies, mosquito control, and others. Additionally the City activated Incident Command Structure (ICS) and designated the Public Health Authority as the Incident Commander.
Initial steps taken by HHD included expanding the capability and capacity of the public health laboratory to test for Zika virus; expand surveillance efforts; created an educational campaign around the “3Ds” of Zika defense (Drain, Dress, DEET) which were then disseminated through several means, including a mass mailing with water bills; and provided DEET to mothers through the WIC program.
The Houston Health Department took the lead in authoring the City’s Zika Action Plan. In this 3 goals and 6 strategies were identified. Goals included 1) Keep Houstonians and visitors aware of the threat of Zika; 2) minimize the spread of the virus; and 3) protect pregnant women from the virus. The 6 strategies employed were to A) develop preparedness plans; B) implement ICS within the City; C) ensure situational awareness through surveillance; D) Increase community awareness; E) reduce opportunities for Zika mosquito breeding grounds; and F) provide direct intervention to reduce the threat of Zika.
HHD was responsible for many of the action items within the plan. We conducted several community outreach events, where we disseminated educational materials, t-shirts, DEET, and other give- aways. These events allowed frequent engagement with the public for bidrectional communication on how to approach the threat.
Objective
This session will explore the role of the Houston Health Department (HHD) in the City of Houston’s response to the threat of Zika. The panelists will provide perspective from the roles of Bureau Chief, informatician, and epidemiologist and provide insight into lessons learned and strategic successes.
Hand-foot-mouth disease (HFMD) is a common childhood illness and the drivers of HFMD incidence are still not clear [1]. In mainland China, continuing and increasing HFMD epidemics have been recorded since 2008, causing millions of infections and hundreds of deaths annually. In Beijing, 28,667 cases were reported in 2015 and the incidence was 133.28/100,000. The variations in Beijing HFMD epidemics over population, space, and time that have been revealed [2] emphasize the need for further research about risk factors of HFMD occurrence. This study aims to explore local effects on HFMD incidence led by potential factors.
Objective
HFMD incidence varies between geographic regions at the township in Beijing. The objective of this study was to examine spatial heterogeneity for the association between HFMD incidence and demographic and socioeconomic factors.
Every year nearly 12 million new cases of syphilis in the world are registered. Currently, in many countries of the world the stabilization or even reduction of the incidence of syphilis is marked, but this does not apply to Ukraine. The current stage of development of the syphilis problem in Ukraine is characterized by not only high morbidity, but also the fact that in the overwhelming number of cases, we are talking about the latent forms and atypical manifestations of the disease and resistance to therapy [1]. Preventive and prophylactic measures are important in maintaining the public health. Predicting the dynamics of disease spreading allows developing appropriate countermeasures and ensuring rational use of human and material resources. Qualitative forecast of syphilis spreading is possible to implement by means of mathematical modeling.