Background : Increased need for Surveillance Platform to Efficiently Control the High-risk Pathogens
World has recently confronted critical challenges establishing the surveillance system to diagnose and manage the infection of high-risk pathogens because of the outbreak of pathogens such as COVID-19, SARS, Malaria.
WHO also emphasized on ‘dealing with data challenges’ and ‘high-quality health information and data’ as key messages in WHO health statistics 2020.
‘Investing in strengthening country health information systems to improve timeliness of data could have the greatest positive impact and is vital for countries to monitor progress towards SDGs (sustainable development goals)’
Situation in Korea : Challenges on Malaria diagnosis and surveillance in remote areas
In the case of life-threatening malaria infection in Korea, firstly, patients’ blood samples were screened at the local health centers/hospitals. In this first visit, it is crucial to detect malaria infection at the intial stage of infection to treat patients on time.
The microscopy test is the gold standard to confirm malaria infection and it needs fresh blood samples to clearly distinguish the typical morphology of infected cells. Therefore, it is best to confirm if the patient is positive to malaria at the first moment of suspected patient’s visit to hospitals/local health centers.
However, if the malaria infected RBCs are quite low at the initial stage of the infection, for example 2-3 among 200,000 RBCs, it is very difficult to find them in microscopy even if microscopy experts are working on it. Other diagnostic kits such as RDT and PCR are also not accurate in this level.
miLab Platform and its benefit: Noul is developing the digitalized miLab platform for real-time diagnosis and analysis for malaria.
miLab platform is the best solution for this situation.
miLab platform can be the surveillance and diagnostic platform by providing the digitalized images and accurate AI analysis for malaria from automated sample preparation and scanning. For surveillance, Korea Disease Control and Prevention Agency (KCDA) can remotely evaluate the digitalized images and AI analysis results.
Currently, Noul is performing a digitalization project of malaria (plasmodium vivax)-infected samples from blood smear tests, funded by KCDA. By using miLab, the malaria-suspected blood samples in KCDA and 3 local health centres in Paju, Gangwha, and Kimpo are automatically smeared and scanned for digitalization for more than 200,000 RBCs per one sample. The malaria-infected RBCs are annotated for AI-learning process. This project will help to increase the accuracy of AI malaria diagnostics for plasmodium vivax by miLab too.
From the year 2021, as a second step, miLab platforms will be set up in more than 10 hospitals/local health centers selected by KCDA to achieve more digtal images and help to confirm the malaria infection by experts.
miLab platform clearly improves the accessibility of digtalized results to control malaria and strong advantage to detect the potential malaria-infected RBCs in high-throughput scanning (more than 200,000 RBCs).