Social media has become an integral part of our day to day activities and we use it to stay in touch with friends, read the news, and find information. Internet activity is easily tracked and freely available data on trending topics can be used to the benefit of many fields, including public health. A new study published in Environmental Health shows that the number of heat-related illnesses are closely related with social media information, particularly with user tweets and Google searches. The study also found that internet search activity for protective behaviors decreased the number of heat-related illnesses.
In contrast to other natural hazards such as hurricanes, tornadoes and floods, heat waves are hard to visualize. This may partially explain why extreme heat events are the leading cause of weather-related human illnesses. Currently, there are an estimated 1,300 deaths every year due to extreme heat in the U.S. This number soars when we experience hotter, longer lasting, and frequent heat events. One of the worst heat waves occurred in 2003 resulting in more than 70,000 excess deaths in Europe. To protect human health from heat waves, many governments currently run heat wave warning systems.
Problems of current heat wave warning systems
Many current warning systems only consider environmental factors such as air temperature and humidity. These systems, however, have several problems. The systems are solely based on outdoor environments instead of indoor conditions where people spend most of their time. They do not consider an individual’s health risk of becoming ill from extreme heat, their health status, thermal comfort, and clothing choices.
These problems could be partially solved by using data from social media and internet search engines. People may tend to express their direct feelings and thoughts on the internet in real time. For example, we find more people complaining about the weather when temperatures are too high on social media. This research tried to check if this information is scientifically valid and useful for improving current warning systems.
Relating web data to illnesses
We hypothesized that there are more patients with heat-related illnesses when there are more frequent Twitter tweets or Google search results mentioning heat-related keywords. The study collected Twitter messages that mentioned “air conditioning (AC)” and “heat” and Google search data that included weather (heat wave, hot weather), medical (heat exhaustion, heat stroke), recreational (drink, beer, park, pool, swim, water), and adaptation information (AC repair) from May 7 to November 3, 2014, focusing on the state of Florida, U.S. We then tried to find the association between these web data and five emergency room or hospital admission disease categories (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease).
If there are more people posting heat-related tweets or searching for heat-related keywords, there are more heat-related illness and dehydration cases
The results show that the number of heat-related illness and dehydration cases exhibited a significant positive relationship with web data. Specifically, heat-related illness cases showed positive associations with tweets (heat, AC) and web searches (drink, heat stroke, park, swim, and tired). In addition, terms such as park, pool, swim, and water tended to show a consistent positive relationship with dehydration cases. Furthermore, the research suggests that tweets and Google searches related to activity patterns such as swimming or going to the park or pool, are positively associated with heat-related illness and dehydration cases. We found inconsistent relationships for renal illnesses and were not able to find any associations between web data and cardiovascular and respiratory illness.
This result tells us that if there are more people posting heat-related tweets or searching for heat-related keywords, there are more heat-related illness and dehydration cases. This suggests that web data could be used as a good index for measuring the risk of heat-related health problems. Currently, Europe experiences record-breaking heat waves in 2019. We believe this type of web data could benefit regions without warning systems and persistently hot and humid climates where warning systems may be less effective.