Malaria refers to a mosquito-borne disease that can be contracted by humans as well as animals. Its symptoms generally consist of tiredness, headaches, fever, vomiting, etc. In some severe cases, it has also caused individuals to appear yellow, have seizures, go into a coma, or even death.
Malaria is known to be the leading reason for mortality in the world. As per WHO (World Health Organization), a child dies every two minutes due to malaria. In current times, malaria diagnosis entails physically counting the parasites in infected red blood cell smear samples. The process is essential to determine the best possible treatment for individual patients. However, the process comes with several limitations. It requires manual labor resulting in millions of blood smear samples waiting too long to be diagnosed. On top of this, the process is also time-consuming and costly. Manual inspection of samples also makes it prone to human error.
Some recent research and projects have paved the way for overcoming the shortcomings mentioned above and further adding growth to the Malaria Diagnostic Market. This may be ensured with the new app that is likely to make malaria diagnosis much more reliable while also reducing the cost of diagnosis.
A group of researchers has developed an automated algorithm that has the ability to assist microscopists in the field assisting with a better reading of blood smears and supplying better and faster results. It provides primary care in situations wherein resources are available in low quality and quantity.
The technology consists of a dual deep learning framework that can effectively calculate cells in thin blood smears with the help of advanced imaging. The team also constructed a mobile application that can attach itself to a microscope and then use the phone camera to capture blood smears images.
Another project with the name Mobile Malaria Project has started its second phase in some parts of Africa. The team is involved in testing the feasibility of mobile genetic sequencing technology. The data produced by this technology is vital in Malaria Diagnosis. It helps to determine which drugs to use and how to assess if such medications are working or not.
The team brought forward that there was a possibility that DNA data on genes could be generated. Those genes are involved in resisting anti-material drugs with the help of this compact and portable equipment price.
The machine in question has the ability to collect small blood samples from individuals suffering from malaria. Lab tests, then extract and amplify the DNA from any malaria parasite. After which specific genes inside the DNA are cut out and placed into machines for analysis.
The team has started the second phase with three objectives. Firstly, to reduce the price of the genetic sequencing technology while also making it easier to use, secondly, building the capacity of the machine to analyze genetic data, and lastly, to communicate this data to policymakers in Zambia.
With this technology's help, scientists can also deduce different parasites that might be present in the sample. This helps in determining how much malaria is present in a particular area. Rapid diagnostics tests are used in Africa usually and conclude the presence of malaria by looking for a specific protein produced by the parasites. The parasites have developed the ability to hide from such tests; genetic technology can help identify how many parasites have developed this ability and its effect on tests done.