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Dengue fever is a major cause of morbidity and mortality in the Republic of the Philippines (RP) and across the world. Early identification of geographic outbreaks can help target intervention campaigns and mitigate the severity of outbreaks. Electronic disease surveillance can improve early identification but, in most dengue endemic areas data pre-existing digital data are not available for such systems. Data must be collected and digitized specifically for electronic disease surveillance. Twitter, however, is heavily used in these areas; for example, the RP is among the top 20 producers of tweets in the world. If social media could be used as a surrogate data source for electronic disease surveillance, it would provide an inexpensive pre-digitized data source for resource-limited countries. This study investigates whether Twitter extracts can be used effectively as a surrogate data source to monitor changes in the temporal trend of dengue fever in Cebu City and the National Capitol Region surrounding Manila (NCR) in the RP.

Objective:

To determine whether Twitter data contains information on dengue-like illness and whether the temporal trend of such data correlates with the incidence dengue or dengue-like illness as identified by city and national health authorities.

 

Submitted by Magou on

The Connecticut Department of Public Health (DPH), like all public health agencies, is constantly challenged by new health threats and emerging diseases. A major responsibility of these agencies is the rapid and effective communication of information on emerging threats to members of the public who may be potentially exposed. This responsibility for effective risk communication is critical when the public perception of risk is high. The September 11, 2001 terrorist attacks and subsequent anthrax mail attacks (Amerithrax) resulted in a new era of public risk perception and concern. Many new and advanced surveillance systems, developed in response to these events, have increased the need for effective risk communication. For example, the DPH developed its first syndromic surveillance system in September 2001 to monitor for possible bioterrorism events and emerging infections. This resulted in the implementation of a number of risk communication and response protocols. These and other protocols were tested in responding to the recent anthrax contamination of a drum maker’s residence and a multistate rash outbreak.

 

Objective

This paper describes various risk communications techniques used in Connecticut to provide health information to the public following surveillance signal alerts. The use of hotlines and contemporary social networking systems to quickly communicate with targeted populations are compared to the use of news releases and other traditional approaches.

Referenced File
Submitted by elamb on

While traditional means of surveillance by governments, multi-national agencies, and institutional networks assist in reporting and confirming infectious disease outbreaks, these formal sources of information are limited by their geographic coverage and timeliness of information flow. In contrast, rapid global reach of electronic communication has resulted in the advent of informal sources of information on outbreaks. Informal resources include discussion sites, online news media, individual and organization reports and even individual search records. The earliest descriptions of the severe acute respiratory syndrome outbreak in Guangdon Province, south China came from informal reports. However, system development to date has been geared toward knowledge management and strategies for interpreting these data are underdeveloped. There is a need to move from simple knowledge reorganization to an analytic approach for disseminating timely yet specific signals.

 

Objective

Internet-based resources such as discussion sites and online news sources have become invaluable sources for a new wave of surveillance systems. The WHO relies on these informal sources for about 65% of their outbreak investigations. Despite widespread use of unstructured information there has been little, if any, data evaluation.

Referenced File
Submitted by elamb on

An increasing amount of global discourse reporting has migrated to the online space, in the form of publicly accessible social media outlets, blogs, wikis, and news feeds. Social media also presents pub- licly available and highly accessible information about individual, real-time activity that can be leveraged to detect, monitor, and more efficiently respond to biological events.

Objective

We propose a cloud-based Open Source Health Intelligence (OS- HINT) system that uses open source media outlets, such as Twitter and RSS feeds, to automatically characterize foodborne illness events in real-time. OSHINT also forecasts response requirements, through predictive models, to allow more efficient use of resources, person- nel, and countermeasures in biological event response.

Submitted by dbedford on

Presented May 24, 2018.

Mauricio Santillana, MS, PhD describes machine learning methodologies that leverage Internet-based information from search engines, twitter microblogs, crowd-sourced disease surveillance systems, electronic medical records, and historical synchronicities in disease activity across spatial regions, to successfully monitor and forecast disease outbreaks in multiple locations around the globe in near real-time.

Presenter

User-generated content enabled by social media tools provide a stream of data that augment surveillance data. Current use of social media data focuses on identification of disease events. However, once identification occurs, the leveraging of social media in monitoring disease events remains unclear. To clarify this, we constructed a framework mapped to the surveillance cycle, to understand how social media can improve public health actions.

Objective

Recent scholarship has focused on using social media (e.g., Twitter, Facebook) as a secondary data stream for disease event detection. However, reported implementations such as (4) underscore where the real value may lie in using social media for surveillance. We provide a framework to illuminate uses of social media beyond passive observation, and towards improving active responses to public health threats.

Submitted by teresa.hamby@d… on

The explosive use of social media sites presents a unique opportunity for developing alternative methods for understanding the health of the public. The near ubiquity of smartphones has further increased the volume and resolution of data that is shared through these sites. The emerging field of digital epidemiology has focused on methods to analyze and use this “digital exhaust” to augment traditional epidemiologic methods. When applied to the task of disease detection they often detect outbreaks 1-2 weeks earlier than their traditional counterpart. Many of these approaches successfully employ data mining techniques to detect symptoms associated with influenza-like illness. Others can identify the appearance of novel symptom patterns, allowing the ability to detect the emergence of a new illness in a population. However, behaviors that lead to increased risk for disease have not yet received this treatment.

Objective

Create an analysis pipeline that can detect the behavioral determinants of disease in the population using social media data.

Submitted by teresa.hamby@d… on

The use of social media as a syndromic sentinel for diseases is an emerging field of growing relevance as the public begins to share more online, particularly in the area of influenza. Several applications have been developed to predict or monitor influenza activity using publicly posted or self-reported online data; however, few have prioritized accuracy at the local level. In 2016, the Cook County Department of Public Health (CCDPH) collected localized Twitter information to evaluate its utility as a potential influenza sentinel data source. Tweets from MMWR week 40 through MMWR week 20 indicating influenza-like illness (ILI) in our jurisdiction were collected and analyzed for correlation with traditional surveillance indicators. Social media has the potential to join other sentinels, such as emergency room and outpatient provider data, to create a more accurate and complete picture of influenza in Cook County.

Objective:

To determine if social media data can be used as a surveillance tool for influenza at the local level.

Submitted by elamb on

In recent years, individuals have been using social network sites like Facebook, Twitter, and Reddit to discuss health-related topics. These social media platforms consequently became new avenues for research and applications for researchers, for instance disease surveillance. Reddit, in particular, can potentially provide more in-depth contextual insights compared to Twitter, and Reddit members discuss potentially more diverse topics than Facebook members. However, identifying relevant discussions remains a challenge in large datasets like Reddit. Thus, much previous research using Reddit data focused on selected few topically-oriented sub-communities. Although such approach allows for topically focused datasets, a large portion of related data can be missed. In this research, we examine all sub-communities in which members are discussing e-cigarettes in order to determine if investigating these other sub-communities could result in a better smoking surveillance system.

Objective:

We aim to explore how to effectively leverage social media for vaping electronic cigarette (e-cigarette) surveillance. This study examines how members of a social media platform called Reddit utilize topically-oriented sub-communities for e-cigarette discussions.

Submitted by elamb on

Nearly 100 people per day die from opioid overdose in the United States. Further, prescription opioid abuse is assumed to be responsible for a 15-year increase in opioid overdose deaths. However, with increasing use of social media comes increasing opportunity to seek and share information. For instance, 80% of Internet users obtain health information online, including popular social interaction sites like Reddit (http://www.reddit.com), which had more than 82.5 billion page views in 20153. In Reddit, members often share information, and include URLs to supplement the information. Understanding the frequency of URL sharing and types of shared URLs can improve our knowledge of information seeking/sharing behaviors as well as domains of shared information on social media. Such knowledge has the potential to provide opportunities to improve public health surveillance practice. We use Reddit to track opioid related discussions and then investigate types of shared URLs among Reddit members in those discussions.

Objective:

We aim to understand (1) the frequency of URL sharing and (2) types of shared URLs among opioid related discussions that take place in the social media platform called Reddit.

Submitted by elamb on
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