Monkeypox lineages amid the ongoing COVID-19 pandemic: A global public health concern - Correspondence

Knowledge and attitude of human monkeypox among university students and staff in Tehran, Iran

Background

Effective control of any disease, including Monkey pox (mpox), is highly dependent on public knowledge and adherence to preventive measures. This cross-sectional study was conducted with the aim of investigating the knowledge of students and staff of Baqiyatallah University about the origin of mpox and its symptoms, transmission, prevention, and management.

Methods

In the current cross-sectional study, the data was collected from Aug 5, 2024 to Sep 5, 2024. The target population consisted of students, teachers, and the staff of Baqiyatallah University, aged 18 or above. Multiple Logistic regressions were employed to assess the association between participants' overall knowledge about human mpox as well as their attitude and their demographic data. Data was analyzed using IBM SPSS statistics version 23.0 (IBM Corp., Armonk, NY, USA) and subsequently coded and labeled. The statistical significance level was set at 5%.

Results

The overall mean score of participants' knowledge and attitude was 6.37 ± 2.20 and 4.24 ± 1.71, respectively. Based on Bloom's cut-off points, 458 (84.3%), 78 (14.4%), and 7 (1.3%) of the participants had low, moderate, and high knowledge levels, respectively and, 279 (51.4%), 221 (40.7%), and 43 (7.9%) of the participants had low, moderate, and high attitude levels, respectively. Logistic regression analysis showed that job status(OR: 9.6, 95% CI: 1.3-66.4), major(OR: 4.3, 95% CI: 1.3-14), and higher educational level (OR: 7.6, 95% CI: 1.03-61.8), was significantly associated with participants' knowledge about mpox.

Conclusion

This study showed that university students and staff in Iran do not have enough knowledge about mpox, including its symptoms, preventive measures, and treatment, with a good understanding of local and international health authorities in the control of emerging mpox. People with higher education tend to have better knowledge, which indicates that access to reliable information sources is necessary to acquire accurate knowledge.

In silico evidence of monkeypox F14 as a ligand for the human TLR1/2 dimer

Recent emergence of zoonotic monkeypox virus (Mpox) in human has triggered the virologists to develop plausible preventive measures. Hitherto, our understanding on the mechanism of immunopathogenesis of Mpox infection is elusive. However, available experimental evidences suggest induction of inflammation as the main cause of pathogenesis. Toll-like receptors (TLRs) are critical in initiating and modulating the host immune response to pathogens. Inflammatory responses observed in various poxvirus infections have, in fact, been shown to be mediated through TLR activation. Therefore, by in silico approaches, this study seeks to identify the Mpox antigen(s) (MAg) that are most likely to interact with human cell-surface TLRs. The Mpox proteomics data available in UniProt database contain 174 protein sequences, among which 105 immunoreactive proteins were modeled for 3D structure and examined for comparative protein-protein interactions with the TLRs through molecular docking and molecular dynamics simulation. F14, an 8.28 kDa infective protein of Mpox, was found to exhibit strong binding affinity (ΔG=-12.5 Kcal mol-1) to TLR1/2 dimer to form a compact thermodynamically stable protein complex. Interestingly, a significant level of conformational change was also observed in both F14 and TLR6 while forming F14-TLR1/2 complex. Based on these data we propose F14 as a putative ligand of human TLR1/2 to initiate proinflammatory signaling in the Mpox-infected host.

Transmission dynamics, complications and mitigation strategies of the current mpox outbreak: A comprehensive review with bibliometric study

As the mankind counters the ongoing COVID-19 pandemic by the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), it simultaneously witnesses the emergence of mpox virus (MPXV) that signals at global spread and could potentially lead to another pandemic. Although MPXV has existed for more than 50 years now with most of the human cases being reported from the endemic West and Central African regions, the disease is recently being reported in non-endemic regions too that affect more than 50 countries. Controlling the spread of MPXV is important due to its potential danger of a global spread, causing severe morbidity and mortality. The article highlights the transmission dynamics, zoonosis potential, complication and mitigation strategies for MPXV infection, and concludes with suggested 'one health' approach for better management, control and prevention. Bibliometric analyses of the data extend the understanding and provide leads on the research trends, the global spread, and the need to revamp the critical research and healthcare interventions. Globally published mpox-related literature does not align well with endemic areas/regions of occurrence which should ideally have been the scenario. Such demographic and geographic gaps between the location of the research work and the endemic epicentres of the disease need to be bridged for greater and effective translation of the research outputs to pubic healthcare systems, it is suggested.

Perceptions and Knowledge of Public Towards Emerging Human Monkeypox in Yemen: A Cross-Sectional Study

Background

The spread of monkeypox (mpox) worldwide poses a severe threat to human life. This virus leads to a disease with symptoms similar to smallpox in humans. To combat this threat, improving public knowledge and perception toward mpox is vital for public health preventive measures.

Methods

A cross-sectional survey was carried out in Yemen from December 2022 to March 2023 to investigate public perception and knowledge of mpox. Individuals were approached through social media platforms using a convenient sampling approach. Linear regression was used to determine the association between participants' knowledge (dependent variable) and explanatory variables.

Results

A total of 853 individuals consented to take part in the study. A significant proportion of respondents had a low knowledge level (N=572, 67.06%). Most participants knew about the nature of the diseases (75%, n=641), transmission mode (78.1%, n=668), hand sanitizer preventive measures, and skin- related symptoms. However, only 20.8% (n= 178) knew that diarrhea is not a symptom, and 25.4% (n= 217) knew antibiotics are unnecessary for mpox management. A proportion of 57.7% (n=492) of the participants feared human mpox, and 47.7% (n= 407) thought it was a conspiracy. Most participants had a good perception of local and international health authorities controlling the disease. Age, education level, having a health-related certificate, and receiving a 2-dose vaccination for COVID-19 had statistically significant associations with mpox knowledge level (P < 0.05). Social media platforms were the most often used information source about mpox (78.3%, n= 668), followed by articles (41.1%, n=351).

Conclusion

The study reveals a low public knowledge about mpox in Yemen, emphasizing the need for targeted educational campaigns, especially via social media, to strengthen public health measures and disease control. Addressing Knowledge gaps and correcting misconceptions is crucial for improving preparedness and response to the disease.

Deep and Transfer Learning Approaches for Automated Early Detection of Monkeypox (Mpox) Alongside Other Similar Skin Lesions and Their Classification

The world faces multiple public health emergencies simultaneously, such as COVID-19 and Monkeypox (mpox). mpox, from being a neglected disease, has emerged as a global threat that has spread to more than 100 nonendemic countries, even as COVID-19 has been spreading for more than 3 years now. The general mpox symptoms are similar to chickenpox and measles, thus leading to a possible misdiagnosis. This study aimed at facilitating a rapid and high-brevity mpox diagnosis. Reportedly, mpox circulates among particular groups, such as sexually promiscuous gay and bisexuals. Hence, selectively vaccinating, isolating, and treating them seems difficult due to the associated social stigma. Deep learning (DL) has great promise in image-based diagnosis and could help in error-free bulk diagnosis. The novelty proposed, the system adopted, and the methods and approaches are discussed in the article. The present work proposes the use of DL models for automated early mpox diagnosis. The performances of the proposed algorithms were evaluated using the data set available in public domain. The data set adopted for the study was meant for both training and testing, the details of which are elaborated. The performances of CNN, VGG19, ResNet 50, Inception v3, and Autoencoder algorithms were compared. It was concluded that CNN, VGG19, and Inception v3 could help in early detection of mpox skin lesions, and Inception v3 returned the best (96.56%) classification accuracy.