Viral Load Tests as Predictive Tools for Mpox Severity Amid Outbreak

In August 2024, the World Health Organization (WHO) declared a second 'Public Health Emergency of International Concern' for mpox, highlighting the urgent need for effective predictive measures as outbreaks escalate, particularly in Africa. The current outbreak is primarily driven by the clade I variant, which has led to multiple countries reporting their first-ever cases of this more severe strain.

Researchers from Nagoya University, in collaboration with international colleagues, have made significant strides in understanding how viral load tests can serve as predictive tools for the severity of mpox symptoms when skin lesions first appear. Their recent study, titled "Modeling lesion transition dynamics to clinically characterize patients with clade I mpox in the Democratic Republic of the Congo," was published in the journal Science Translational Medicine on July 2, 2025. This research reveals that measuring the viral load in the blood at the onset of skin lesions provides critical insights into the potential progression of the disease, thus aiding in more effective treatment strategies.

The study utilized medical records from clade Ia mpox patients in the Democratic Republic of the Congo—one of the countries most affected by this outbreak—between 2007 and 2011. According to Dr. Shingo Iwami, Professor at the Nagoya University Graduate School of Science and co-lead author of the study, a viral load exceeding 40,000 copies per milliliter of blood when skin lesions appear correlates with a higher risk of developing severe and prolonged symptoms. This finding is particularly crucial, given that the clade Ia variant has a mortality rate of approximately 10%, a significant increase compared to the 1% mortality rate associated with the clade IIb variant observed during the 2022 global outbreak.

The implications of this research are manifold. Early identification of patients likely to experience severe symptoms could facilitate more intensive treatment and monitoring protocols, ultimately leading to improved patient outcomes. Dr. Iwami asserts, "If this method can be applied to current circulating mpox strains, we can move toward more personalized, data-driven medicine. For patients and their families, this could provide clearer expectations about recovery timelines and reassurance through more precise medical predictions after a frightening diagnosis."

The study's findings underscore the importance of understanding viral load dynamics in the context of mpox transmission and progression. The researchers employed a combination of mathematical modeling and machine learning techniques to classify patients based on their symptom severity and the duration of skin lesion healing. The results indicate a natural division among patients into two distinct groups: those who recover quickly with mild symptoms and those who endure severe symptoms, including persistent skin lesions.

This ongoing outbreak, which extends from the Democratic Republic of the Congo to neighboring countries, is notably complicated by the presence of clade Ib, in addition to clade Ia. Future research will focus on testing the predictive method on this clade Ib variant, which poses a distinct challenge in managing the outbreak effectively.

As the WHO continues to monitor the situation, the development of predictive tools like viral load testing may play a pivotal role in shaping public health responses to emerging infectious diseases. By enhancing the ability of healthcare providers to predict disease severity and tailor treatment approaches, these advancements could significantly alter the trajectory of mpox management in affected regions. The integration of such data-driven methodologies into clinical practice emphasizes the evolving landscape of infectious disease management as it intersects with technological innovations in health science.

For additional insights, please refer to the original study by Takara Nishiyama et al., published in Science Translational Medicine (2025). DOI: 10.1126/scitranslmed.ads4773.