Usefulness of Non-Skin Samples in the PCR Diagnosis of Mpox (Monkeypox)

MPXV DNA kinetics in bloodstream and other body fluids samples

Since spring 2022, the global epidemiology of the monkeypox virus (MPXV) has changed. The unprecedented increase of human clade II MPXV cases worldwide heightened concerns about this emerging zoonotic disease. We analysed the positivity rates, viral loads, infectiousness, and persistence of MPXV DNA for up to 4 months in several biological samples from 89 MPXV-confirmed cases. Our data showed that viral loads and positivity rates were higher during the first two weeks of symptoms for all sample types. Amongst no-skin-samples, respiratory specimens showed higher MPXV DNA levels and median time until viral clearance, suggesting their usefulness in supporting MPXV diagnosis, investigating asymptomatic patients, and monitoring viral shedding. Infectious virus was cultured from respiratory samples, semen, and stools, with high viral loads and collected within the first 10 days. Notably, only one saliva and one semen were found positive for viral DNA after 71 and 31 days from symptoms, respectively. The focus on bloodstream samples showed the best testing sensitivity in plasma, reporting the overall highest MPXV DNA detection rate and viral loads during the 3-week follow-up as compared to serum and whole-blood. The data here presented can be useful for MPXV diagnostics and a better understanding of the potential alternative routes of its onward transmission.

Mpox-AISM: AI-mediated super monitoring for mpox and like-mpox

Swift and accurate diagnosis for earlier-stage monkeypox (mpox) patients is crucial to avoiding its spread. However, the similarities between common skin disorders and mpox and the need for professional diagnosis unavoidably impaired the diagnosis of earlier-stage mpox patients and contributed to mpox outbreak. To address the challenge, we proposed "Super Monitoring", a real-time visualization technique employing artificial intelligence (AI) and Internet technology to diagnose earlier-stage mpox cheaply, conveniently, and quickly. Concretely, AI-mediated "Super Monitoring" (mpox-AISM) integrates deep learning models, data augmentation, self-supervised learning, and cloud services. According to publicly accessible datasets, mpox-AISM's Precision, Recall, Specificity, and F1-score in diagnosing mpox reach 99.3%, 94.1%, 99.9%, and 96.6%, respectively, and it achieves 94.51% accuracy in diagnosing mpox, six like-mpox skin disorders, and normal skin. With the Internet and communication terminal, mpox-AISM has the potential to perform real-time and accurate diagnosis for earlier-stage mpox in real-world scenarios, thereby preventing mpox outbreak.

A study on the recognition of monkeypox infection based on deep convolutional neural networks

Introduction

The World Health Organization (WHO) has assessed the global public risk of monkeypox as moderate, and 71 WHO member countries have reported more than 14,000 cases of monkeypox infection. At present, the identification of clinical symptoms of monkeypox mainly depends on traditional medical means, which has the problems of low detection efficiency and high detection cost. The deep learning algorithm is excellent in image recognition and can extract and recognize image features quickly and reliably.

Methods

Therefore, this paper proposes a residual convolutional neural network based on the λ function and contextual transformer (LaCTResNet) for the image recognition of monkeypox cases.

Results

The average recognition accuracy of the neural network model is 91.85%, which is 15.82% higher than that of the baseline model ResNet50 and better than the classical convolutional neural networks models such as AlexNet, VGG16, Inception-V3, and EfficientNet-B5.

Discussion

This method realizes high-precision identification of skin symptoms of the monkeypox virus to provide a fast and reliable auxiliary diagnosis method for monkeypox cases for front-line medical staff.

A Case of Mistaken Identity: Varicella Zoster and Monkeypox

Mpox, previously referred to as monkeypox, is a zoonotic virus originally endemic to West Africa which has recently garnered significant attention due to a global outbreak. It remains a challenging diagnosis due to varying clinical presentations and similarities with other infectious pathogens. While diligent monitoring of its prevalence remains crucial, clinicians should combat recency bias when forming differentials for viral illnesses with similar presentations. Here, we discuss the case of an immigrant child with self-reported vaccination history of Varicella Zoster who was diagnosed with Mpox in the emergency department but was subsequently found to have Varicella Zoster after further testing. To effectively manage outbreaks and provide optimal care, healthcare professionals should stay up to date on the latest advancements in diagnostic techniques and available interventions.