Early Warning

Disease surveillance is an epidemiological practice by which the spread of disease is mentioned in order to establish patterns of progression. The main role of Priority Communicable Disease Surveillance (PCDS) is to predict, observe, and minimize the harm caused by outbreak, epidemic, and pandemic situations, as well as increase our knowledge to what factors might contribute to such circumstances. A key part of modern disease surveillance is the practice of disease case reporting.

Objective

Surveillance of priority communicable diseases started with a view to build up an early warning system for certain important public health important diseases in Bangladesh, namely: (1) Diarrheal disease (acute watery diarrhea and bloody dysentery); (2) Malaria; (3) Kala-azar; (4) Tuberculosis; (5) Leprosy; (6) Encephalitis; (7) Unknown diseases of public health concern.

It is admitted that real time surveillance system permits to reduce delay of outbreak detection, and preventive measures implementation. It is usually based on pre diagnostic numeric data collection and transmission. ASTER (Alerte et surveillance en temps reel) is a real time surveillance system for French Armed Forces deployed in French Guiana and Djibouti, constituted by 2 kinds of networks : several declaration networks and one analysis network. On June 2011, an outbreak occurred among a French Army Regiment in Djibouti, which has permitted to evaluate ASTER in real conditions.

Objective

To discuss advantages of real time surveillance system within Armed Forces, using a real outbreak case.

This paper describes the early warning that has been activated by the syndromic surveillance system installed within the Armed Forces in French Guiana and the consequences for Public Health decisions.

Effective communicable disease control through rapid detection and prompt response to outbreaks is one of the priorities during a humanitarian crisis, as communicable diseases can be a major cause of morbidity and mortality in emergencies, particularly in countries with poor disease surveillance mechanisms. Yemen is among many developing countries being hit by conflicts, displacement of population and disruption of basic services, where among other public health risks and threats the population is exposed to risks of several communicable diseases. Thus, effective preventive and control measures through early detection and rapid identification of infectious diseases and provision of a public health response to communicable disease outbreaks, a crucial priority health intervention, need to be directed towards diseases that are endemic and particularly those which can potentially cause excess numbers of mortality and morbidity within a short span of time.

Objective

The intended objective of the Electronic Disease Early Warning System (eDEWS) is to minimize morbidity and mortality due to communicable diseases through detection of potential outbreaks at their earliest possible stage using a novel modeling approach that mainly facilitates the transformation of data into actionable information.

Early warning surveillance (EWS) is a key factor in the fight against tropical infectious diseases(1). However, the process of carrying out EWS is complex as it involves several actors and requires the use of diverse human, material and technological resources for data collection, analysis, and diffusion(2). Modern EWS systems make use of state of the art technologies and technics which require much financial input and adequate technological expertise for the users. More so, the culture and habits of users in DCs make it very difficult to run such EWS systems in this milieu. In this paper, we propose a generic early warning surveillance architecture that tackles the stages from just after data collection, through data analysis to feedback and that is adapted to the context of limited resource countries.

Objective

Build a computer aided Early warning disease surveillance system adapted for Developing Countries (DCs) facing limited financial, human, intellectual, organizational, technological, and infrastructural resources.

Safe drinking water is essential for all communities. Intentional or unintentional contamination of drinking water requires water utilities and local public health to act quickly. The Water Security (WS) initiative of the U.S. Environmental Protection Agency is a multi-faceted approach involving water utilities and local public health officials (LPH) to identify, communicate, contain, and mitigate a drinking water contamination event. Components of WS include: online water quality monitoring, enhanced security monitoring, consumer complaint surveillance, and innovative uses of public health surveillance data streams. LPH already use multiple surveillance data systems to recognize disease events in a timely manner. However, few of these systems can be integrated or specifically designed for detection of drinking water contamination incidents.

Objective

This poster describes the integration of public health surveillance data as a component of an early warning system for detection of a drinking water contamination incident.

In 2004, the NSW Public Health Real-time Emergency Department Surveillance System operating in and around Sydney, Australia signalled a large-scale increase in Emergency Department (ED) visits for gastrointestinal illness (GI). A subsequent alarming state-wide rise in institutional gastroenteritis outbreaks was also seen through conventional outbreak surveillance.

Objectives

To examine the association between short-term variation in ED visits for GI with short-term variation in institutional gastroenteritis outbreaks and thus to evaluate whether syndromic surveillance of GI through EDs provides early warning for institutional gastroenteritis outbreaks.

Drug-related deaths have increased over the past decade throughout the United States. In New York City (NYC), every year there are approximately 900 psychoactive drug-related fatalities with the majority involving opioids. Unintentional drug overdose is the fourth leading cause of early adult death in NYC, and high rates of drug-related morbidity among drug users are evidenced by over 30,000 drug mentions in NYC emergency departments each year. Moreover, nonfatal overdose may be common among chronic drug users. Despite the relationship between fatal and non-fatal overdose clusters and continued increases in drug-related morbidity and mortality, no regular surveillance system currently exists. The implementation of a drug-related early warning system can inform and target a comprehensive public health response addressing the significant health problem of overdose morbidity and mortality.

Objective

This presentation describes how multiple syndromic data sources from emergency medical services ambulance dispatches and emergency department visits can be combined to routinely monitor citywide spatial patterns of adverse drug events and drug morbidity. This information can be used to target information, treatment and prevention services to drug “hotspots,” to provide early warning for drug-related morbidity, and to detect potential increased risk for overdose death.

If the next influenza pandemic emerges in Southeast Asia, the identification of early detection strategies in this region could enable public health officials to respond rapidly. Accurate, real-time influenza surveillance is therefore crucial. Novel approaches to the monitoring of infectious disease, especially respiratory disease, are increasingly under evaluation in an effort to avoid the cost- and timeintensive nature of active surveillance, as well as the processing time lag of traditional passive surveillance. In response to these issues, we have developed an indications and warning (I&W) taxonomy of pandemic influenza based on social disruption indicators reported in news media.

Objective

Our aim is to analyze news media for I&W of influenza to determine if the signals they create differ significantly between seasonal and pandemic influenza years.