Health and Medical News and Resources

General interest items edited by Janice Flahiff

[Press release] Model predicts public response to disease outbreaks

Model predicts public response to disease outbreaks

From the 14 January 2015  press release

David L. Chandler | MIT News Office
January 14, 2015

Sometimes the response to the outbreak of a disease can make things worse — such as when people panic and flee, potentially spreading the disease to new areas. The ability to anticipate when such overreactions might occur could help public health officials take steps to limit the dangers.

Now a new computer model could provide a way of making such forecasts, based on a combination of data collected from hospitals, social media, and other sources. The model was developed by researchers at MIT, Draper Laboratory, and Ascel Bio, and is described in a paper published in the journal Interface.

The research grew out of earlier studies of how behavior spreads through social networks, explains co-author Marta Gonzalez, an assistant professor of civil and environmental engineering at MIT. The spread of information — and misinformation — about disease outbreaks “had not been studied, and it’s hard to get detailed information on the panic reactions,” Gonzalez says. “How do you quantify panic?”

One way of analyzing those reactions is by studying news reporting on outbreaks, as well as messages posted on social media, and comparing those with data from hospital records about the actual incidence of the disease.

In many cases, the reaction to an outbreak can cause more harm than the disease itself: For example, the researchers say, curtailing travel and distribution of goods can create economic damage, or even lead to rioting and other behavior that can exacerbates a disease’s spread. Wide publicity of an outbreak can also cause health care facilities to be overrun by people concerned about minor symptoms, potentially making it difficult for those affected by the disease to obtain the care they need, the researchers add.

To study the phenomenon, the team looked at data from three disease outbreaks: the 2009 spread of H1N1 flu in both Mexico and in Hong Kong, and the 2003 spread of SARS in Hong Kong. The model they developed could accurately reproduce the population-level behavior that accompanied those outbreaks.

In these cases, public response was often disproportionate to actual risk; in general, the research showed, diseases that are rare or unusual frequently receive attention that far outpaces the true risk. For example, the SARS outbreak in Hong Kong produced a much stronger public response than H1N1, even though the rate of infection with H1N1 was hundreds of times greater than that of SARS.

This analysis did not specifically address the ongoing Ebola epidemic in West Africa — but once again, Gonzalez says, “The response [is] just not justified by the extent of the disease.”

 

January 27, 2015 Posted by | Public Health | , , , , , , , | Leave a comment

Could Social Media Be Used to Detect Disease Outbreaks?

From the 1 November 2011 Science Daily article

New research has looked at whether social media could be used to track an event or phenomenon, such as flu outbreaks and rainfall rates. The study by academics at the University of Bristol‘s Intelligent Systems Laboratory is published online in ACM Transactions on Intelligent Systems and Technology.

Social networks, such as Facebook and microblogging services like Twitter, have only been around for a short time but in that time they have provided shapshots of real life by forming, electronically, public expression and interaction.

The research by Professor Nello Cristianini and Vasileios Lampos in the University’s Intelligent Systems Laboratory, geo-tagged user posts on the microblogging service of Twitter as their input data to investigate two case studies.

The first case study looked at levels of rainfall in a given location and time using the content of tweets. The second case study collected regional flu-like illness rates from tweets to find out if an epidemic was emerging.

The study builds on previous research that reported a methodology that used tweets to track flu-like illness rates in several UK regions. The research also demonstrated a tool, the Flu Detector, which uses the content of Twitter to map current flu rates in several UK regions.

Professor Nello Cristianini, speaking about the research, said: “Twitter, in particular, encouraged their 200 million users worldwide to make their posts, commonly known as tweets, publicly available as well as tagged with the user’s location. This has led to a new wave of experimentation and research using an independent stream of information.

“Our research has demonstrated a method, by using the content of Twitter, to track an event, when it occurs and the scale of it. We were able to turn geo-tagged user posts on the microblogging service of Twitter to topic-specific geolocated signals by selecting textual features that showed the content and understanding of the text.”…

Read the entire article

December 2, 2011 Posted by | Public Health | , , , | Leave a comment

Why Physicians Are Reluctant to Share Patient Data: Fine Line Between Protecting Privacy and Public Health

Conversation between doctor and patient/consumer.

Image via Wikipedia

From the 7 July Science News Today article

 

Family doctors are reluctant to disclose identifiable patient information, even in the context of an influenza pandemic, mostly in an effort to protect patient privacy. A recently published study by Dr. Khaled El Emam the Canada Research Chair in Electronic Health Information at the University of Ottawa and the Children’s Hospital of Eastern Ontario Research Institute recently found that during the peak of the H1N1 pandemic in 2009, there was still reluctance to report detailed patient information for public health purposes.

These results are important today, so we can learn from that experience and prepare for the inevitable next pandemic.

“There is a perceived tradeoff between the public good and individual privacy. If we sway too much on the public good side, then all people’s health data would be made available without conditions,” explained Dr. El Emam. “If we sway too much on the individual privacy side then no health data would be shared without consent, but then this would potentially increase public health risks. Physicians are important gatekeepers of patient information, so we need to better understand the conditions under which they are willing to provide patient data so that everyone wins; we do not need to make these tradeoffs….

July 7, 2011 Posted by | Public Health | , , , , | Leave a comment

Hospital Preparedness Checklist for Pandemic Influenza

Hospital Preparedness Checklist for Pandemic Influenza (with a 2009 focus)  aims to help “enhance the readiness of the health facilities to cope with the challenges of an epidemic, a pandemic or any other emergency or disaster, hospital managers need to ensure the initiation of relevant generic priority action. [The document]  aims to provide a checklist of the key action to carry out in the context of a continuous hospital emergency preparedness process.”

This 32 page PDF document includes checklists in the areas of incident command, communication, continuity of essential services, surge capacity, human resources, logistics, and supply management (including pharmaceuticals), infection prevention and control, case management, surveillance, and laboratory services.

 

October 28, 2010 Posted by | Professional Health Care Resources | , , , , | 1 Comment

   

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