Mathematical modeling of mpox: A scoping review

Risk of evolution driven population-wide emergence of mpox: The paradoxic effect of moderate interventions

BACKGROUND

The global mpox outbreak in 2022 was declared a public health emergency of international concern. While in non-endemic countries disease spread remained limited mostly to a high risk group, a main public health concern is that through evolution, mpox gains the ability to widely spread in the entire population.

METHODS

We construct a stochastic epidemiological model of SEIR type, to investigate the spread of mpox primarily propagating within a core population - consisting of MSM individuals having multiple sexual partners - before affecting the general population. We examine how effective various intervention strategies are in preventing this from happening. These non-pharmaceutical interventions include reducing disease transmission in the core population, in the general population, or in both. Our analysis encompasses the optimal timing for these interventions, considering the effects of early versus late intervention and the potential impact of different mutation patterns on disease spread.

RESULTS

Our findings highlight that effective early intervention can be achieved with lower intensity, while delayed intervention requires stronger measures. Notably, our results reveal an intriguing phenomenon where moderate intervention could lead to worse outcome than no intervention. This counterintuitive outcome arises because moderate reductions may prolong transmission chains within the core group, leading to more opportunities for the pathogen to acquire mutations resulting in higher transmission potential in the general population.

CONCLUSIONS

A comprehensive understanding of the role of the core group in disease dynamics and the mutation patterns are crucial for developing tailored and effective public health strategies. The moderate intervention paradox suggests that to minimize the risk of population-wide emergence, it must be ensured that targeted interventions are highly efficient.

The effect of heterogeneity of relative vaccine costs on the mean population vaccination rate with mpox as an example

Mpox (formerly known as monkeypox) is a neglected tropical disease that became notorious during its 2022-2023 worldwide outbreak. The vaccination was available, but there were inequities in vaccine access. In this paper, we extend existing game-theoretic models to study a population that is heterogeneous in the relative vaccination costs. We consider a population with two groups. We determine the Nash equilibria (NE), i.e., optimal vaccination rates, for each of the groups. We show that the NE always exists and that, for a narrow range of parameter values, there can be multiple NEs. We focus on comparing the mean optimal vaccination rate in the heterogeneous population with the optimal vaccination rate in the corresponding homogeneous population. We show that there is a critical size for the group with lower relative costs and the mean optimal vaccination in the heterogeneous population is more than in the homogeneous population if and only if the group is larger than the critical size.

Mpox-XDE: an ensemble model utilizing deep CNN and explainable AI for monkeypox detection and classification

The daily surge in cases in many nations has made the growing number of human monkeypox (Mpox) cases an important global concern. Therefore, it is imperative to identify Mpox early to prevent its spread. The majority of studies on Mpox identification have utilized deep learning (DL) models. However, research on developing a reliable method for accurately detecting Mpox in its early stages is still lacking. This study proposes an ensemble model composed of three improved DL models to more accurately classify Mpox in its early phases. We used the widely recognized Mpox Skin Images Dataset (MSID), which includes 770 images. The enhanced Swin Transformer (SwinViT), the proposed ensemble model Mpox-XDE, and three modified DL models-Xception, DenseNet201, and EfficientNetB7-were used. To generate the ensemble model, the three DL models were combined via a Softmax layer, a dense layer, a flattened layer, and a 65% dropout. Four neurons in the final layer classify the dataset into four categories: chickenpox, measles, normal, and Mpox. Lastly, a global average pooling layer is implemented to classify the actual class. The Mpox-XDE model performed exceptionally well, achieving testing accuracy, precision, recall, and F1-score of 98.70%, 98.90%, 98.80%, and 98.80%, respectively. Finally, the popular explainable artificial intelligence (XAI) technique, Gradient-weighted Class Activation Mapping (Grad-CAM), was applied to the convolutional layer of the Mpox-XDE model to generate overlaid areas that effectively highlight each illness class in the dataset. This proposed methodology will aid professionals in diagnosing Mpox early in a patient's condition.

"Mpox in MSM: Tackling stigma, minimizing risk factors, exploring pathogenesis, and treatment approaches"

Mpox is a zoonotic disease caused by the monkeypox virus (MPV), primarily found in Central and West African countries. The typical presentation of the disease before the 2022 mpox outbreak includes a febrile prodrome 5-13 days post-exposure, accompanied by lymphadenopathy, malaise, headache, and muscle aches. Unexpectedly, during the 2022 outbreak, several cases of atypical presentations of the disease were reported, such as the absence of prodromal symptoms and the presence of genital skin lesions suggestive of sexual transmission. As per the World Health Organization (WHO), as of March 20, 2024, 94,707 cases of mpox were reported worldwide, resulting in 181 deaths (22 in African endemic regions and 159 in non-endemic countries). The United States Centers for Disease Control and Prevention (CDC) reports a total of 32,063 cases (33.85% of total cases globally), with 58 deaths (32.04% of global deaths) due to mpox. Person-to-person transmission of mpox can occur through respiratory droplets and sustained close contact. However, during the 2022 outbreak of mpox, a high incidence of anal and perianal lesions among MSMs indicated sexual transmission of MPV as a major route of transmission. Since MSMs are disproportionately at risk for HIV transmission. In this review, we discusses the risk factors, transmission patterns, pathogenesis, vaccine, and treatment options for mpox among MSM and people living with HIV (PLWH). Furthermore, we provide a brief perspective on the evolution of the MPV in immunocompromised people like PLWH.

Mpox Virus as a Global Public Health Emergency: A Scoping Review

The monkeypox (Mpox) virus has emerged as a global public health emergency of international concern recently. The virus that was endemic in West and Central Africa has now been reported with chains of global transmission to several countries. A scoping review was carried out from the relevant literature available from PubMed, Scopus and Web of Science. This comprehensive analysis describes the virus epidemiology, pathogenesis, clinical manifestations, complications including secondary bacterial infections, diagnosis, treatment and vaccination. The article underscores the significance of key viral and immune mediators of infection and discusses updated recommendations on therapeutic strategies and vaccination.

Assessment of MPOX infection-related knowledge levels, concerns, and associated factors: a community-based cross-sectional study

BACKGROUND

MPOX (Monkeypox) is a zoonotic disease of increasing global concern due to its re-emergence and potential for human-to-human transmission. Effective public health interventions rely on understanding socio-demographic determinants of knowledge and perceptions of the disease. This study aimed to investigate MPOX-related knowledge and concerns among a diverse sample in Türkiye, identifying key factors influencing knowledge levels.

METHODS

A cross-sectional study was conducted with 509 participants aged 18-73 years (mean age: 33.8 ± 15.6) in all settlements of Türkiye. Socio-demographic data were collected, and MPOX knowledge and concerns were assessed using a structured data form. To assess knowledge levels regarding MPOX, 15 questions were defined with 1 point given for each correct answer, and these questions were then categorized as high knowledge (≥ 10 correct answers) and low knowledge (< 10 correct answers). Univariable and multivariable binary logistic regression analyses were conducted to identify factors associated with knowledge levels. Trust and reliance on information sources were also evaluated. The data form was distributed to participants via social media platforms.

RESULTS

The majority of participants (97.1%) were aware of MPOX, but only 6.5% believed adequate precautions were in place. The mean knowledge score was 7.6 ± 3.7, with 37.7% demonstrating high knowledge. In terms of concerns about MPOX, only 31.6% of participants were identified as concerned, whereas the majority (68.4%) of the participants reported no significant concerns. The most trusted source of information about MPOX among the participants was medical doctors and healthcare professionals, as indicated by 53.63% of respondents. Low knowledge was significantly associated with older age (p = 0.015), female gender (p = 0.002), lower education levels (p < 0.001), non-medical fields (p < 0.001), and lower income (p < 0.001). Social media (53.11%) was the most common information source, yet healthcare professionals (53.63%) were the most trusted. Multivariable logistic regression confirmed that being in non-medical fields (OR = 2.858, 95% CI: 1.809-4.515, p < 0.001), lower income (OR = 3.141, 95% CI: 2.015-4.896, p < 0.001), and perceived low immunity (OR = 2.264, 95% CI: 1.350-3.797, p = 0.002) independently predicted lower knowledge.

CONCLUSIONS

Despite high awareness, significant gaps in MPOX knowledge exist, particularly among older adults, females, non-medical professionals, and those with low income. Public health strategies should prioritize these groups, leveraging trusted sources like healthcare professionals while improving the reliability of digital information platforms.

Modelling vaccination approaches for mpox containment and mitigation in the Democratic Republic of the Congo

BACKGROUND

Mpox was first identified in the Democratic Republic of the Congo (DRC) in 1970. In 2023, a historic outbreak of mpox occurred in the country, continuing into 2024. Over 14 000 cases and 600 deaths were reported in 2023 alone, representing a major increase from previous outbreaks. The modified vaccinia Ankara vaccine (brand names JYNNEOS, Imvamune, and Imvanex) was used in the 2022 mpox outbreak in the USA and Europe. However, at the time of the study, vaccination had not been made available in the DRC. We aimed to inform policy and decision makers on the potential benefits of, and resources needed, for mpox vaccination campaigns in the DRC by providing counterfactual scenarios evaluating the short-term effects of various vaccination strategies on mpox cases and deaths, if such a vaccination campaign had been undertaken before the 2023-24 outbreak.

METHODS

A dynamic transmission model was used to simulate mpox transmission in the DRC, stratified by age (<5, 5-15, and >15 years) and province. The model was used to simulate potential vaccination strategies, varying by age and region (endemic provinces, non-endemic provinces with historic cases, and all provinces) assessing the effect the strategies would have on deaths and cases in an epidemic year similar to 2023. In addition, we estimated the number of vaccine doses needed to implement each strategy.

FINDINGS

Without vaccination, our model predicted 14 700 cases and 700 deaths from mpox over 365 days. Vaccinating 80% of all children younger than 5 years in endemic regions led to a 27% overall reduction in cases and a 43% reduction in deaths, requiring 10·5 million vaccine doses. Vaccinating 80% of all children younger than 5 years in all regions led to a 29% reduction in cases and a 43% reduction in deaths, requiring 33·1 million doses. Vaccinating 80% of children aged 15 years or younger in endemic provinces led to a 54% reduction in cases and a 71% reduction in deaths, requiring 26·6 million doses.

INTERPRETATION

When resources are limited, vaccinating children aged 15 years or younger, or younger than 5 years, in endemic regions of the DRC would be the most efficient use of vaccines. Further research is needed to explore long-term effects of a one-time or recurrent vaccination campaign.

FUNDING

Canadian Institutes of Health Research, Canadian International Development Research Centre, US Department of Defense (Defense Threat Reduction Agency, Mpox Threat Reduction Network), Global Affairs Canada (Weapons Threat Reduction Program), US Department for Agriculture (Agriculture Research Service, Non-Assistance Cooperative Agreement).

The Peculiar Emergence of Mpox (Monkeypox): Directions for the Search for the Natural Reservoir and Vaccination Strategies

Background/Objectives: Mpox (monkeypox) is a zoonosis with origins in a currently unknown African reservoir. The first epidemiological accounts of mpox date back to the early 1980s, yet mpox only emerged as a pandemic threat in 2022-2023, more than 40 years later. This scenario is very different from those of other emerging diseases such as HIV and SARS, which immediately spread globally, in fully susceptible populations, starting from patients zero. Methods: We use mathematical modeling to illustrate the dynamics of mpox herd immunity in small communities in touch with the mpox natural reservoir. In particular, we employ an SEIR stochastic model. Results: The peculiar emergence of mpox can be explained by its relationship with smallpox, which was eradicated through universal mass vaccination in 1980. Mpox first emerged in small rural communities in touch with mpox's animal reservoir and then spread globally. The relative isolation of these communities and their herd-immunity dynamics against mpox worked to delay the introduction of mpox in large urban centers. Conclusions: Mathematical modeling suggests that the search for the mpox animal reservoir would be most fruitful in communities with high mpox seroprevalence and small outbreaks. These are communities is tight contact with the mpox natural reservoir. We propose vaccinating individuals in communities in these communities to severely reduce the importation of cases elsewhere.

Exploring the dynamics of monkeypox transmission with data-driven methods and a deterministic model

Introduction

Mpox (formerly monkeypox) is an infectious disease that spreads mostly through direct contact with infected animals or people's blood, bodily fluids, or cutaneous or mucosal lesions. In light of the global outbreak that occurred in 2022-2023, in this paper, we analyzed global Mpox univariate time series data and provided a comprehensive analysis of disease outbreaks across the world, including the USA with Brazil and three continents: North America, South America, and Europe. The novelty of this study is that it delved into the Mpox time series data by implementing the data-driven methods and a mathematical model concurrently-an aspect not typically addressed in the existing literature. The study is also important because implementing these models concurrently improved our predictions' reliability for infectious diseases.

Methods

We proposed a traditional compartmental model and also implemented deep learning models (1D- convolutional neural network (CNN), long-short term memory (LSTM), bidirectional LSTM (BiLSTM), hybrid CNN-LSTM, and CNN-BiLSTM) as well as statistical time series models: autoregressive integrated moving average (ARIMA) and exponential smoothing on the Mpox data. We also employed the least squares method fitting to estimate the essential epidemiological parameters in the proposed deterministic model.

Results

The primary finding of the deterministic model is that vaccination rates can flatten the curve of infected dynamics and influence the basic reproduction number. Through the numerical simulations, we determined that increased vaccination among the susceptible human population is crucial to control disease transmission. Moreover, in case of an outbreak, our model showed the potential for epidemic control by adjusting the key epidemiological parameters, namely the baseline contact rate and the proportion of contacts within the human population. Next, we analyzed data-driven models that contribute to a comprehensive understanding of disease dynamics in different locations. Additionally, we trained models to provide short-term (eight-week) predictions across various geographical locations, and all eight models produced reliable results.

Conclusion

This study utilized a comprehensive framework to investigate univariate time series data to understand the dynamics of Mpox transmission. The prediction showed that Mpox is in its die-out situation as of July 29, 2023. Moreover, the deterministic model showed the importance of the Mpox vaccination in mitigating the Mpox transmission and highlighted the significance of effectively adjusting key epidemiological parameters during outbreaks, particularly the contact rate in high-risk groups.

Supercritical and homogenous transmission of monkeypox in the capital of China

Starting from May 31, 2023, the local transmission of monkeypox (Mpox) in mainland China began in Beijing. Till now, the transmission characteristics have not been explored. Based on the daily Mpox incidence data in the first 3 weeks of Beijing (from May 31 to June 21, 2023), we employed the instant-individual heterogeneity transmission model to simultaneously calculate the effective reproduction number (Re ) and the degree of heterogeneity (k) of the Beijing epidemic. We additionally simulated the monthly infection size in Beijing from July to November and compared with the reported data to project subsequent transmission dynamics. We estimated Re to be 1.68 (95% highest posterior density [HPD]: 1.12-2.41), and k to be 2.57 [95% HPD: 0.54-83.88], suggesting the transmission of Mpox in Beijing was supercritical and didn't have considerable transmission heterogeneity. We projected that Re fell in the range of 0.95-1.0 from July to November, highlighting more efforts needed to further reduce the Mpox transmissibility. Our findings revealed supercritical and homogeneous transmission of the Mpox epidemic in Beijing. Our results could serve as a reference for understanding and predicting the ongoing Mpox transmission in other regions of China and evaluating the effect of control measures.

A hybrid forecasting technique for infection and death from the mpox virus

Objectives

The rising of new cases and death counts from the mpox virus (MPV) is alarming. In order to mitigate the impact of the MPV it is essential to have information of the virus's future position using more precise time series and stochastic models. In this present study, a hybrid forecasting system has been developed for new cases and death counts for MPV infection using the world daily cumulative confirmed and death series.

Methods

The original cumulative series was decomposed into new two subseries, such as a trend component and a stochastic series using the Hodrick-Prescott filter. To assess the efficacy of the proposed models, a comparative analysis with several widely recognized benchmark models, including auto-regressive (AR) model, auto-regressive moving average (ARMA) model, non-parametric auto-regressive (NPAR) model and artificial neural network (ANN), was performed.

Results

The introduction of two novel hybrid models, HPF 1 1 and HPF 3 4 , which demonstrated superior performance compared to all other models, as evidenced by their remarkable results in key performance indicators such as root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE), is a significant advancement in disease prediction.

Conclusion

The new models developed can be implemented in forecasting other diseases in the future. To address the current situation effectively, governments and stakeholders must implement significant changes to ensure strict adherence to standard operating procedures (SOPs) by the public. Given the anticipated continuation of increasing trends in the coming days, these measures are essential for mitigating the impact of the outbreak.