Phones could be the next big technological application in public health. Public health researchers could potentially predict disease outbreaks by studying cell services providers ‘ data base , calls, text messages including routing towers. This information can be useful in estimation of morbidity, and mortality by making inferences as on travel patterns and thus be able to predict ways of disease spread. A good example is the Ebola (hemorrhagic fever ) disease. Using mobile phones , suspected patients can be traces using the routing towers and the chain of disease spreads can be tracked. Cell phones have also reenergized public health research through phone surveys. Phone surveys are cheap and easy to implement . Health care advice can be shared via cell phone , especially emergencies and follow ups.
Mobile phone case study in Kenya: Rural hospitals in Kenya always run out of blood in case of increased demand ( motor vehicle accidents, clashes, hemorrhagic fevers). Most of these hospitals are in remote places with no land line telephone communications. A mobile phone intervention led to massive change in the blood supply chain to these rural hospitals. Nurses were advised to call in advance in situations they though blood could be needed in large quantities, The mobile phone technology has saved many patients to date.
mobile hone have also being used it predicting malaria spread pattern in Kenya. Researchers analyze the time and duration of calls , where calls are placed from , and where they are connecting to. From this inferences are drawn about travel patters in future of people from high malaria infection zones to low malaria infection zones. This is very useful information in decision making and predicting future malaria spread pattern. The same model can be applied to track down Ebola patients.
In other studies , researches have used mobile phone tracking to study the likelihood of people who have stopped smoking relapsing due to certain behaviors. In New York, researches examined the association between certain habits- going to bars, hanging out with other smokers , or going out on Fridays nights and relapse. This was done by examining behavioral data recorded by special smart phones given to smokers in the study. This was used to develop a probability model of determining the possibility of a smoker relapsing based on certain habits.
All the above example demonstrate the role of mobile phones in public health research and health communication. It is the next main thing to explore.