Brownstein John

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 incidence of dengue fever (DF) has increased 30 fold between 1960 and 2010. The literature suggests that temperature plays a major role in the life cycle of the mosquito vector and in turn, the timing of DF outbreaks. We use real-time data from GDT and real-time temperature estimates from NASA Earth observing systems to examine the relationship between dengue and climate in 17 Mexican states from 2003–2011. For the majority of states, we predict that a warming climate will increase the number of days the minimum temperature is within the risk range for dengue.

Objective

To evaluate the association between Dengue Fever and climate in Mexico with real-time data from Google Dengue Trends and climate data from NASA Earth observing systems.

Previous studies have documented significant lags in official reporting of outbreaks compared to unofficial reporting (1,2). MoH+ provides an additional tool to analyze this issue, with the unique advantage of actively gathering a wide range of streamlined official communication, including formal publications, online press releases, and social media updates.

Objective:

To introduce MoH+, HealthMap’s (HM) real-time feed of official government sources, and demonstrate its utility in comparing the timeliness of outbreak reporting between official and unofficial sources.

 

The emergence of new influenza strains including H1N1, H5N1, H3N2v as well as other respiratory pathogens such as SARS, along with generally weak information about household and community transmission of influenza, enforce the need for augmented influenza surveillance. At the same time, Internet penetration and access has grown, with 82% of American adults using the Internet, enabling transfer and communication of information that can be collected and aggregated in near real-time. Surveillance targeted towards influenza in other countries, and towards malaria in India, has previously been executed with good user engagement. In this study, we created an online participatory influenza surveillance tool in the United States, called Flu Near You.

Objective

To develop a participatory system for monitoring the activity of influenza-like-illness among the United States general population.

In the South East Asia Region (SEAR), infectious disease continues to be a leading cause of death. SEAR countries, like Vietnam, are also at risk for outbreaks of emerging diseases due to high population density, proximity to animals and deforestation. Given Vietnam’s location in SEAR and its recurrent outbreaks of zoonotic diseases— timely surveillance in Vietnam is critical to global public health. Online news sources have been recognized as potential sources for early detection of emerging disease outbreaks, as was the case with SARS.  HealthMap, an innovative disease surveillance system developed at Boston Children’s Hospital, leverages the expediency of online news media by using text-mining technology to monitor and map global disease outbreaks reported by news sources.

Objective

To present the development of a surveillance system utilizing online Vietnamese language media sources to detect disease events in Vietnam and the South East Asian Region.

The purpose of this work was to develop a novel method of estimating the amount of influenza-like illness (ILI) in a population, in near-real time, by using a source of information that is completely open to the public and free to access. We investigated the usefulness of data gathered from Wikipedia to estimate the prevalence of ILI in the United States, using data from the Centers for Disease Control and Prevention (CDC) as well as Google Flu Trends.

Introduction

Each year, there are an estimated 250,000–500,000 deaths worldwide that are attributed to seasonal influenza, with anywhere between 3,000–50,000 deaths occurring in the United States of America (US). In the US, the Centers for Disease Control and Prevention (CDC) continuously monitors the level of influenza-like illness (ILI) circulating in the population. While the CDC ILI data is considered to be a useful indicator of influenza activity, its availability has a known lag-time of between 7–14 days. To appropriately distribute vaccines, staff, and other healthcare commodities, it is critical to have up-to-date information about the prevalence of ILI in a population. To this end, we have created a method of estimating current ILI activity in the US by gathering information on the number of times particular Wikipedia articles have been viewed. Not only is the information held within Wikipedia articles very useful on its own, but statistics and trends surrounding the amount of usage of particular articles, frequency of article edits, region specific statistics, and countless other factors make the Wikipedia environment an area of interest for researchers. Furthermore, Wikipedia makes all of this information public and freely available, greatly increasing and expediting any potential research studies that aim to make use of their data.

Traditional surveillance systems only capture a fraction of the estimated 48 million yearly cases of foodborne illness in the United States due to few affected individuals seeking medical care and lack of reporting to appropriate authorities. Non-traditional disease surveillance approaches could be used to supplement foodborne illness surveillance systems.

Objective

We assessed whether foodservice reviews on Yelp.com (a business review site) can be used to support foodborne illness surveillance efforts.

The influenza A(H7N9) virus emerged in early 2013 in China, with more than 130 laboratory-confirmed cases identified within a short period of about three months. Evidence-based public health response is essential for effective control of the disease, which relies on epidemiological and clinical data with good quality and timeliness. Publicly available information from sources such as official health website, online news, blogs or social media has the potential of rapid sharing of data to a wide community of experts for more comprehensive analyses. In our study we described the strength and limitation of these data for various types of epidemiological inferences.

Objective

This study described the strength and limitation of using line lists that built on publicly available data in various types of epidemiological inferences during the H7N9 epidemic in China, 2013.

The success of public health campaigns in decreasing or eliminating the burden of vaccine-preventable diseases can be undermined by media content influencing vaccine hesitancy in the population. A tool for tracking and describing the ever-growing platforms for such media content can help decide how and where to invest in campaigns to increase public confidence in vaccines. The Vaccine Sentimeter, developed from the Healthmap project, aims to assist public health practitioners in maintaining or improving vaccine coverage through a real-time, online visualization tool of global media content on vaccines.

Objective The current analysis describes the scope and trends in United States content from the Vaccine Sentimeter’s results, while seeking to examine any possible links between media content, vaccine coverage, and reported vaccine adverse events in the country.