COVID-19 Diagnostics: A Panoramic View on Its Present Scenario, Challenges and Solutions

Area of Science:

• Medical Diagnostics
• Infectious Disease Research
• Public Health

Background:

• Effective control of COVID-19 relies heavily on early diagnosis and quarantine measures.
• Current diagnostic approaches include AI/ML imaging and laboratory-based methods, each with distinct efficiencies and applications.
• Limitations in sensitive assays for detecting low viral titers pose challenges for early COVID-19 detection.

Purpose of the Study:

• To provide a comprehensive overview of diagnostic techniques for COVID-19.
• To analyze the advantages and disadvantages of various COVID-19 detection methods.
• To identify key challenges and potential improvements in diagnostic strategies for SARS-CoV-2.

Main Methods:

• Review of existing literature on COVID-19 diagnostic methods.
• Comparison of AI/ML-based imaging techniques with laboratory diagnostic approaches.
• Evaluation of methods including RT-PCR, Serum Viral Neutralization (SVN) assays, and other emerging techniques.

Main Results:

• RT-PCR is considered the benchmark for rapid and efficient SARS-CoV-2 detection.
• AI/ML imaging is useful for late-stage patients but requires lung imaging.
• SVN assays show lower efficiency compared to RT-PCR, and sensitivity for low viral loads remains a challenge.

Conclusions:

• Accurate and timely diagnosis is paramount for managing COVID-19 outbreaks.
• RT-PCR remains a highly effective method, while AI/ML and other techniques offer complementary roles.
• Further development of sensitive assays is needed to overcome limitations in early detection of low viral titers.