Rapid Plasma Reagin Test Market Size

Global Rapid Plasma Reagin Test Market size was valued at USD 2.8 billion in 2023 and is poised to grow from USD 3.09 billion in 2024 to USD 6.77 billion by 2032, growing at a CAGR of 10.3% during the forecast period (2025-2032).

Surge in syphilis incidence, advancements in rapid plasma reagin test technologies, government initiatives for sexually transmitted infection (STI) screening, growing emphasis on preventive healthcare, and high demand from emerging countries.

The global surge in syphilis cases, notably among high-risk groups such as men who have sex with men and pregnant women, is propelling the demand for rapid plasma reagin tests. Automated rapid plasma reagin test systems streamline sample processing, reduce manual errors, and increase throughput, making them ideal for high-volume laboratories. Government-led programs aimed at STI prevention and control are also expected to play a crucial role in rapid plasma reagin test market growth. High preference for point-of-care (POC) testing due to their rapid results is also expected to favor the adoption of rapid plasma reagin test in the long run. Developing countries are also expected to influentially boost sales of rapid plasma reagin tests owing to growing awareness regarding syphilis and other STIs.

On the contrary, limited access in low-resource settings, competition from alternative diagnostics, false-positive results, and regulatory and quality control issues are estimated to limit the global rapid plasma reagin test market penetration through 2032 and beyond.

What Role does AI play in Rapid Plasma Reagin Tests?

Artificial Intelligence (AI) and machine learning are being increasingly applied in RPR test interpretation to reduce human error and improve diagnostic accuracy. Automated image analysis software can objectively evaluate RPR card reactions, enhancing consistency and reliability, especially in high-volume laboratories or remote screening programs. AI tools can also integrate with digital health platforms to store, analyze, and share data across networks, enabling real-time disease surveillance. This trend supports early outbreak detection and resource optimization. As diagnostic laboratories adopt smart systems, the use of AI is expected to play a pivotal role in standardizing and scaling up RPR test operations.