Surveillance Systems

Epidemiologists, public health agencies and scientists increasingly augment traditional surveillance systems with alternative data sources such as, digital surveillance systems utilizing news reports and social media, over-the-counter medication sales, and school absenteeism. Similar to school absenteeism, an increase in reservation cancellations could serve as an early indicator of social disruption including a major public health event. In this study, we evaluated whether a rise in restaurant table availabilities could be associated with an increase in disease incidence.

Objective

The objective of this study is to evaluate whether trends in online restaurant table reservations can be used as an early indicator for a disease outbreak.

The Triple-S project (Syndromic Surveillance Systems in Europe, www.syndromicsurveillance.eu), co-financed by the European Commission and involving twenty four organizations from fourteen countries was launched in September 2010 with the following objectives 1) performing an inventory of existing or planned SyS systems in Europe both in animal and public health, 2) building a network of experts involved in SyS 3) producing guidelines to implement SyS systems, 4) developing synergies between human and animal health SyS systems. The project is based on a cooperation between human and animal health experts, as supported by the One Health initiative [1].

Objective: 

The objective of this study, based on the Triple-S project outputs, was to present the existing synergies between human and animal health syndromic surveillance (SyS) systems in Europe and a proposal to enhance this kind of collaboration.

 

Hospital acquired infections are a major cause of morbidity, mortality and increased resource utilization. CDC estimates that in the US alone, over 2 million patients are affected by nosocomial infections costing approximately $34.7 billion to $45 billion annually (1). The existing process of detection and reporting relies on time consuming manual processing of records and generation of alerts based on disparate definitions that are not comparable across institutions or even physicians.

Objective:

Our objective was to conduct surveillance of nosocomial infections directly from multiple EMR data streams in a large multi-location Canadian health care facility. The system developed automatically triggers bed-day-level-location-aware reports and detects and tracks the incidents of nosocomial infections in hospital by ward.

The U.S. Environmental Protection Agency (EPA) designed a program to pilot multi-component contamination warning systems (CWSs), known as the “Water Security initiative (WSi).” The Cincinnati pilot has been fully operational since January 2008, and an additional four pilot utilities will have their own, custom CWSs by the end of 2012. A workshop amongst the pilot cities was conducted in May 2012 to discuss lessons learned from the design, implementation, operation, maintenance, and evaluation of each city’s PHS component.

Objective

This paper describes the lessons learned from operation and maintenance of the public health surveillance (PHS) component of five pilot city drinking water contamination warning systems (CWS) including: Cincinnati, New York, San Francisco, Philadelphia, and Dallas.

In July 2012, the 54 children infected with enterovirus-71(EV71) were died in Cambodia. The media called it as mystery illness and made Asian parents worried. In fact, the severe epidemics of enterovirus occurred frequently in Asia, including Malaysia, Singapore, Taiwan and China. The clinical severity varied from asymptomatic to mild (hand-foot-mouth disease and herpangina) and severe pulmonary edema/hemorrhage and encephalitis. Up to now, the development of vaccine for EV-71 and the more effective antiviral drug was still ongoing. Therefore, surveillance for monitoring the enterovirus activity and understanding the epidemiological characteristics between mild and severe enterovirus cases was crucial.

Objective

This study was to elucidate the spatio-temporal correlations between the mild and severe enterovirus cases through integrating enterovirus-related three surveillance systems in Taiwan. With these fully understanding epidemiological characteristics, hopefully, we can develop better measures and indicators from mild cases to provide early warning signals and thus minimizing subsequent numbers of severe cases.

Over the last decade, the application of syndromic surveillance systems has expanded beyond early event detection to include longterm disease trend monitoring. However, statistical methods employed for analyzing syndromic data tend to focus on early event detection. Generalized linear mixed models (GLMMs) may be a useful statistical framework for examining long-term disease trends because, unlike other models, GLMMs account for clustering common in syndromic data, and GLMMs can assess disease rates at multiple spatial and temporal levels (1). We show the benefits of the GLMM by using a GLMM to estimate asthma syndrome rates in New York City from 2007 to 2012, and to compare high and low asthma rates in Harlem and the Upper East Side (UES) of Manhattan.

Objective:

Show the benefits of using a generalized linear mixed model (GLMM) to examine long-term trends in asthma syndrome data.

 

Maine has been conducting syndromic surveillance since 2007 using the Early Aberration Reporting System (EARS). An evaluation of the syndromic surveillance system was conducted to determine if system objectives are being met, assess the system’s usefulness, and identify areas for improvement. According to CDC’s Guidelines for Evaluating Public Health Surveillance Systems, a surveillance system is useful if it contributes to the timely prevention and control of adverse health events. Acceptability includes the willingness of participants to report surveillance data; participation or reporting rate; and completeness of data.

Objective:

To assess the usefulness and acceptability of Maine’s syndromic surveillance system among hospitals who currently participate.

 

So as to develop more effective countermeasures against influenza, timely and precise information about influenza activity at schools, kindergartens, and nursery schools may be helpful. At the Infectious Diseases Surveillance Center of the National Institute of Infectious Diseases, a School Absenteeism Surveillance System (SASSy) has been in operation since 2009. SASSy monitors the activity of varicella, mumps, mycoplasma pneumonia, pharyngoconjunctival fever, hand-foot-mouth disease, influenza, and many other infectious diseases in schools. In 2010, SASSy was extended to the Nursery School Absenteeism Surveillance System (NSASSy). These systems record the number of absentees due to infectious diseases in each class of all grades of schools every day. As a powerful countermeasure to the pandemic flu of 2009, SASSy was activated in 9 prefectures, in which included more than 6000 schools, and it is gradually being adopted in other prefectures. As of February 2012, 18 prefectures and 4 big cities, which together comprised 15,700 schools (about 35% of all schools in Japan), utilized SASSy. NSASSy is used in more than 4100 nursery schools, which is about 18% of all nursery schools in Japan. Some studies of similar systems were performed in the UK (1), Hong Kong (2), and the USA (3,4), examined surveillance systems for monitoring infectious disease incidence, but the systems to construct in those studies do not operate nationwide like SASSy or NSASSy, and they cannot provide influenza incidence rates in children.

Objective: 

So far, it is difficult to show the incidence rate of influenza in the official sentinel surveillance in Japan. Hence we construct the system which record infectious diseases at schools, kindergartens, and nursery schools, and then can show the accurate incidence rate of influenza in children by age/grade.