MalariaSpot: Gamified App For Malaria Diagnosis

MalariaSpot: Gamified App For Malaria Diagnosis


How Gamification in a Mobile App Could Help Improve Malaria Diagnosis

The competitive nature of people brought out by playing games has a new application in training people how to diagnose the disease malaria. It’s a game called MalariaSpot and it’s an example of how gamification in mobile apps is bringing new ways to improve health care.

Malaria is caused by a parasite that is transmitted to humans by mosquito bites. The World Health Organization estimates that there are more than 200 million cases of malaria annually that kill about 627,000 each year. The standard practice for diagnosing malaria consists of detecting the parasites, then counting the number of parasites in a blood smear sample.

Malaria diagnosis is done through a microscope – the greater the number of parasites counted, the more severe the infection. Medical professionals view approximately 100 images to do this count, a lengthy and tedious process. The more times a specialist does this diagnosis, the better he or she gets at the process. But studying these images to diagnose malaria can take specialists up to half an hour. With gamification, MalariaSpot aims to shave the diagnosing time down to minutes.

Smartphones are becoming ubiquitous. MalariaSpot aims to tap the wisdom of crowds. By turning malaria diagnosis into a game easily accessed and played on a smartphone, MalariaSpot’s developers aim to distribute malaria images globally so that people can play a game that allows people to see images and count the parasites.

The malaria images players see are real; they were provided by the National Institute for Communicable Disease in Johannesburg, South Africa. The concept for MalariaSpot came from Dr. Miguel Luengo-Oroz, a researcher from the Universidad Politenica de Madrid, in Spain. The game measures the accurate counts and the mistakes, and tracks a player’s scores. The game also tracks the speed and accuracy of players overall. The goal is to use knowledge gleaned from the analysis of non-diagnostic experts to help the diagnostic experts improve the way that they do their malaria analysis.

If MalariaSpot works, it could drive development of artificial intelligence engines that helps diagnostic experts make better and faster diagnosis of malaria.

Image credit: Wikimedia


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