Eradicate Malaria from an entire Island in Indonesia

3.3 billion people live at risk of malaria across 106 malaria-endemic countries. Although the risk is widespread, cases and deaths are concentrated in third world countries. Children are the first to suffer.

No parent should lose their child to a disease that can be diagnose, prevented or treated.

Prompt diagnosis and effective treatment are the cornerstones of malaria case management; patients recover rapidly if diagnosed and treated early.

We have launched a program to eradicate Malaria one island at a time in Indonesia and this is the first one. BANGKA ISLAND

Here is the technical description of the project (led by Dr. David Mendel / University of Jakarta) This project introduces the study of a novel automated detection method in four remote villages located in Bangka Island, Indonesia. The method automates the classic optical microscopy protocol by making use of a bespoke image analysis treatment on an iPhone. It is based on a complex combination of color filters, morphological filters, and artificial intelligence. The resulting software, packaged as a mobile app, leverages advantageously several functions of the iPhone. First, both cameras are used: the back camera, with its high definition, is used to capture the micro graphs of blood samples. The front camera is used to identify the patient (photograph of his/her portrait and facial recognition to identify his/her presence in the database). The GPS and internal clock are used to tag the results with location and an unambiguous time stamp. The method has been demonstrated, in the laboratory, to be extremely effective at detecting both p. falciparum and p. vivax, and is now ready for field testing. In this study, we will deploy one complete kit in remote, endemic areas in Bangka Island, Indonesia. Repeated testing over a period of 3 full months during the high season of malaria will enable us to determine the suitability of the test and its accuracy in the field, the selectivity of the test, the influence of the operator, the quality of the training given to the operator, and the influence of regional data.