Risk assessment strategies for early detection and prediction of infectious disease outbreaks associated with climate change.

A new generation of surveillance strategies is being developed to help detect emerging infections and to identify the increased risks of infectious disease outbreaks that are expected to occur with climate change. These surveillance strategies include event-based surveillance (EBS) systems and risk modelling. The EBS systems use open-source internet data, such as media reports, official reports, and social media (such as Twitter) to detect evidence of an emerging threat, and can be used in conjunction with conventional surveillance systems to enhance early warning of public health threats. More recently, EBS systems include artificial intelligence applications such machine learning and natural language processing to increase the speed, capacity and accuracy of filtering, classifying and analysing health-related internet data. Risk modelling uses statistical and mathematical methods to assess the severity of disease emergence and spread given factors about the host (e.g. number of reported cases), pathogen (e.g. pathogenicity) and environment (e.g. climate suitability for reservoir populations). The types of data in these models are expanding to include health-related information from open-source internet data and information on mobility patterns of humans and goods. This information is helping to identify susceptible populations and predict the pathways from which infections might spread into new areas and new countries. As a powerful addition to traditional surveillance strategies that identify what has already happened, it is anticipated that EBS systems and risk modelling will increasingly be used to inform public health actions to prevent, detect and mitigate the climate change increases in infectious diseases.

Big Data and the Global Public Health Intelligence Network (GPHIN).

BACKGROUND: Globalization and the potential for rapid spread of emerging infectious diseases have heightened the need for ongoing surveillance and early detection. The Global Public Health Intelligence Network (GPHIN) was established to increase situational awareness and capacity for the early detection of emerging public health events. OBJECTIVE: To describe how the GPHIN has used Big Data as an effective early detection technique for infectious disease outbreaks worldwide and to identify potential future directions for the GPHIN. FINDINGS: Every day the GPHIN analyzes over more than 20,000 online news reports (over 30,000 sources) in nine languages worldwide. A web-based program aggregates data based on an algorithm that provides potential signals of emerging public health events which are then reviewed by a multilingual, multidisciplinary team. An alert is sent out if a potential risk is identified. This process proved useful during the Severe Acute Respiratory Syndrome (SARS) outbreak and was adopted shortly after by a number of countries to meet new International Health Regulations that require each country to have the capacity for early detection and reporting. The GPHIN identified the early SARS outbreak in China, was credited with the first alert on MERS-CoV and has played a significant role in the monitoring of the Ebola outbreak in West Africa. Future developments are being considered to advance the GPHIN's capacity in light of other Big Data sources such as social media and its analytical capacity in terms of algorithm development. CONCLUSION: The GPHIN's early adoption of Big Data has increased global capacity to detect international infectious disease outbreaks and other public health events. Integration of additional Big Data sources and advances in analytical capacity could further strengthen the GPHIN's capability for timely detection and early warning.

An overview of internet biosurveillance.

Internet biosurveillance utilizes unstructured data from diverse web-based sources to provide early warning and situational awareness of public health threats. The scope of source coverage ranges from local media in the vernacular to international media in widely read languages. Internet biosurveillance is a timely modality that is available to government and public health officials, healthcare workers, and the public and private sector, serving as a real-time complementary approach to traditional indicator-based public health disease surveillance methods. Internet biosurveillance also supports the broader activity of epidemic intelligence. This overview covers the current state of the field of Internet biosurveillance, and provides a perspective on the future of the field.

Landscape of international event-based biosurveillance.

Event-based biosurveillance is a scientific discipline in which diverse sources of data, many of which are available from the Internet, are characterized prospectively to provide information on infectious disease events. Biosurveillance complements traditional public health surveillance to provide both early warning of infectious disease events and situational awareness. The Global Health Security Action Group of the Global Health Security Initiative is developing a biosurveillance capability that integrates and leverages component systems from member nations. This work discusses these biosurveillance systems and identifies needed future studies.

Injury surveillance in construction: eye injuries.

Occupational eye injuries are both common and preventable. About 20% of occupational eye injuries occur in construction. To investigate the nature of eye injuries among construction workers, we analyzed a large data set of construction worker injuries. In addition, we interviewed 62 workers with eye injuries to further explore circumstances of eye injury and workers' attitudes and behavior toward the use of eye protection. Eleven percent (363 cases) of the 3,390 construction workers in our data set were treated for eye injuries. Welders, plumbers, insulators, painters/glaziers, supervisors, and electricians had a higher proportion of all injuries due to eye injuries than other trades. Nearly half of the diagnoses were abrasions (46%) followed by foreign objects or splash in the eye (29%), conjunctivitis (10%), and burns (5%). In the interviews with 62 workers, we found that employers very frequently required eye protection for all tasks or for high-risk tasks, and workers report wearing eye protection regularly. However, most did not wear eye protection with top and side shields; if we believe the injuries occurred because a particle or liquid passed between the glasses and the workers' faces, increased use of goggles or full shields would have prevented two-thirds of this group of injuries.

Surveillance of construction worker injuries: the utility of trade-specific analysis.

Construction is a dangerous industry, with high rates of both fatal and nonfatal injuries. To learn more about the causes of nonfatal construction worker injuries, and to identify injury cases for further work site-based investigations or prevention programs, we established an emergency department-based surveillance program in November 1990. This article describes circumstances of injury, diagnoses, and demographic characteristics of injured construction workers for 2,791 cases identified through mid-August, 1997. Lacerations and strains and sprains were the most frequent diagnoses; cutting and piercing objects were the leading causes of injury among all construction workers, followed by falls and overexertion. Because of the variety of work performed in this industry, more detailed injury descriptions, by trade, are most useful for thinking about injury prevention. To illustrate this, we profile injury patterns among workers from four specific trades: carpenters, electricians, plumbers, and ironworkers. Areas of concern highlighted by the trade-specific analyses include eye injuries among plumbers; falls from ladders among electricians and plumbers; slips, trips, and falls on the same level among ironworkers; electrical exposure among electricians; and, amputations among carpenters.