Transmission Dynamics Research Articles

Species Composition and Feeding Behaviors of Vector Mosquitoes of Avian Infectious Diseases at a Wild Bird Rehabilitation Facility in Japan.

Although wild bird rehabilitation facilities are important for the conservation of wild species, individuals may be kept within the facilities for long periods, consequently posing a risk for the bird to be infected with pathogens to which they are not naturally exposed. In turn, novel pathogens may be introduced through rescued migratory species. Avian malaria and West Nile fever are important avian diseases transmitted by mosquitoes. To understand the transmission dynamics of such diseases at rehabilitation facilities, the ecology of vector mosquitoes, including species composition, seasonality, and feeding behaviors, were explored. Mosquitoes were collected at a wild bird rehabilitation facility and wildlife sanctuary in Japan from 2019 to 2020 using mouth aspirators, sweep nets, and light traps. A total of 2,819 mosquitoes of 6 species were captured, all of which are potential vectors of avian diseases. Culex pipiens pallens and Cx. pipiens form molestus were the dominant species (82.9% of all collected mosquitoes). Density and seasonality differed between sampling locations, presumably because of differences in mosquito behaviors including feeding preferences and responses to climatic factors. Blood-fed Culex mosquitoes fed solely on birds, and many mosquito species are thought to have fed on birds within the facility. Particularly, Cx. pipiens group probably fed on both rescued and free-living birds. The rehabilitation facility may be an important site for the introduction and spread of pathogens because 1) numerous mosquitoes inhabit the hospital and its surroundings; 2) blood-fed mosquitoes are caught within the hospital; 3) there is direct contact between birds and mosquitoes; 4) both birds within the hospital and wild birds are fed upon. Furthermore, blood-fed Cx. pipiens form molestus were observed in the winter, suggesting that pathogens might be transmitted even during the winter when other mosquito species are inactive.

Global Dynamics of a Social Hierarchy-Stratified Malaria Model: Insight from Fractional Calculus

In this study, a mathematical model for the transmission dynamics of malaria among different socioeconomic groups in the human population interacting with a susceptible-infectious vector population is presented and analysed using a fractional-order derivative of the Caputo type. The total human population is stratified into two distinguished classes of lower and higher income individuals, with each class further subdivided into susceptible, infectious, and recovered populations. The socio hierachy-structured fractional-order malaria model is analyzed through the application of different dynamical system tools. The theory of positivity and boundedness based on the generalized mean value theorem is employed to investigate the basic properties of solutions of the model, while the Banach fixed point theory approach is used to prove the existence and uniqueness of the solution. Furthermore, unlike the existing related studies, comprehensive global asymptotic dynamics of the fractional-order malaria model around both disease-free and endemic equilibria are explored by generalizing the usual classical methods for establishing global asymptotic stability of the steady states. The asymptotic behavior of the trajectories of the system are graphically illustrated at different values of the fractional (noninteger) order.

Fractional-order rat bite fever model: a mathematical investigation into the transmission dynamics

Fractional-order rat bite fever model: a mathematical investigation into the transmission dynamics

Optimal emergency hospitals construction in an unexpected epidemic with considering the interactive effect

AbstractConstructing emergency hospitals is one of the most critical measures to defeat an unexpected epidemic. However, existing operations research (OR) studies rarely consider the interactive effect between the construction of emergency hospitals and the dynamics of epidemic transmission. Inspired by this gap, we propose a new modeling framework for decision‐making in emergency hospital construction. In our optimization model, we address the pandemic evolution functions as constraints. We also consider the heterogeneity among infected individuals, distinguishing between those with mild and severe symptoms, each requiring treatment in different types of emergency hospitals. We formulate the problem as a mixed integer nonlinear programming model. Our model can envision the current and future evolution of the epidemic and the impact of different decisions regarding emergency hospital construction on epidemic development. Simultaneously, it provides the optimal strategy to build hospitals and minimize the total number of untreated patients due to the disease. The proposed model is tested using the Covid‐19 outbreak case in Wuhan. The results can provide precise guidelines for emergency hospitals construction, including timing and capacity, and offer decision boundaries for policymakers considering the uncertainty of disease transmission. Furthermore, our decision‐making framework is general and can be adapted to study other epidemics.

Untangling the stranglehold through mathematical modelling of Streptococcus equi subspecies equi transmission

Strangles, a disease caused by infection with Streptococccus equi subspecies equi (S. equi), is endemic worldwide and one of the most frequently diagnosed infectious diseases of horses. Recent work has improved our knowledge of key parameters of transmission dynamics, but important knowledge gaps remain. Our aim was to apply mathematical modelling of S. equi transmission dynamics to prioritise future research areas, and add precision to estimates of transmission parameters thereby improving understanding of S. equi epidemiology and quantifying the control effort required. A compartmental deterministic model was constructed. Parameter values were estimated from current literature wherever possible. We assessed the sensitivity of estimates for the basic reproduction number on the population scale to varying assumptions for the unknown or uncertain parameters of: (mean) duration of carriership (1∕γC), relative infectiousness of carriers (f), proportion of infections that result in carriership (p), and (mean) duration of immunity after natural infection (1∕γR). Available incidence and (sero-)prevalence data were compared to model outputs to improve point estimates and ranges for these currently unknown or uncertain transmission-related parameters. The required vaccination coverage of an ideal vaccine to prevent major outbreaks under a range of control scenarios was estimated, and compared available data on existing vaccines. The relative infectiousness of carriers (as compared to acutely ill horses) and the duration of carriership were identified as key knowledge gaps. Deterministic compartmental simulations, combined with seroprevalence data, suggest that 0.05<fˆ<0.5 and that the duration of protective immunity after infection is likely 4–6 years. The presence of carriers alone may suffice to keep S. equi endemic in a population, implying that carriers cannot be ignored in control efforts. Weekly screening of herds for signs of strangles could be sufficient to ensure R < 1, provided all horses are screened for carriership post-infection. In some of worst-case scenarios, vaccination alone would not suffice to prevent major outbreaks from occurring. A stochastic agent-based model was also constructed and validated, and used to simulate a remount depot, to evaluate whether historical incidence data of recurrence of strangles within individuals could be explained without the assumption that one in four horses fail to mount a lasting immune response. These simulations demonstrated that the observed data could have occurred without that assumption.

Learning from the Past, Looking to Resilience: Housing in Serbia in the Post-Pandemic Era

The COVID-19 pandemic has profoundly reshaped life across the globe, significantly influencing the future of housing. The enactment and densification of diverse activities within one place have resulted in varying degrees of conflict between the built and social environment. This conflict is directly related to the degree of housing adaptability to new life, work, and leisure conditions. Movement restrictions and distance learning have significantly impacted the young population, which is susceptible to ‘enforced togetherness’ conditions. However, studies on post-pandemic housing in Serbia are rare. This paper investigates the relationship between the built and social environment, focusing on current trends in multi-family housing from the perspective of the progressive change of life standards in the post-pandemic era. It also includes a survey of the living conditions of architecture students in Serbia during lockdown and distance learning, offering insights into the impact of the physical environment on virus transmission and social dynamics. The main objective of this study is to formulate guidelines for developing a resilient housing model in Serbia that will address both current and future crises. From the findings, it can be concluded that radical changes in housing policy are necessary to enable less interdependence among layers within the system striving to be resilient.

Genomic insights unveil the plasmid transfer mechanism and epidemiology of hypervirulent Klebsiella pneumoniae in Vietnam.

Hypervirulent Klebsiella pneumoniae (hvKp) is a significant cause of severe invasive infections in Vietnam, yet data on its epidemiology, population structure and dynamics are scarce. We screened hvKp isolates from patients with bloodstream infections (BSIs) at a tertiary infectious diseases hospital in Vietnam and healthy individuals, followed by whole genome sequencing and plasmid analysis. Among 700 BSI-causing Kp strains, 100 (14.3%) were hvKp. Thirteen hvKp isolates were identified from 350 rectal swabs of healthy adults; none from 500 rectal swabs of healthy children. The hvKp isolates were genetically diverse, encompassing 17 sequence types (STs), predominantly ST23, ST86 and ST65. Among the 113 hvKp isolates, 14 (12.6%) carried at least one antimicrobial resistance (AMR) gene, largely mediated by IncFII, IncR, and IncA/C plasmids. Notably, the acquisition of AMR conjugative plasmids facilitated horizontal transfer of the non-conjugative virulence plasmid between K. pneumoniae strains. Phylogenetic analysis demonstrated hvKp isolates from BSIs and human carriage clustered together, suggesting a significant role of intestinal carriage in hvKp transmission. Enhanced surveillance is crucial to understand the factors driving intestinal carriage and hvKp transmission dynamics for informing preventive measures. Furthermore, we advocate the clinical use of our molecular assay for diagnosing hvKp infections to guide effective management.

Bayesian inference for the onset time and epidemiological characteristics of emerging infectious diseases

BackgroundEmerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging.MethodsWe introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable.ResultsTo validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature.ConclusionThis study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.

Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years

Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.

Mathematical modeling of SARS-CoV-2 variant substitutions in European countries: transmission dynamics and epidemiological insights

BackgroundCountries across Europe have faced similar evolutions of SARS-CoV-2 variants of concern, including the Alpha, Delta, and Omicron variants.Materials and methodsWe used data from GISAID and applied a robust, automated mathematical substitution model to study the dynamics of COVID-19 variants in Europe over a period of more than 2 years, from late 2020 to early 2023. This model identifies variant substitution patterns and distinguishes between residual and dominant behavior. We used weekly sequencing data from 19 European countries to estimate the increase in transmissibility (Δβ) between consecutive SARS-CoV-2 variants. In addition, we focused on large countries with separate regional outbreaks and complex scenarios of multiple competing variants.ResultsOur model accurately reproduced the observed substitution patterns between the Alpha, Delta, and Omicron major variants. We estimated the daily variant prevalence and calculated Δβ between variants, revealing that: (i) Δβ increased progressively from the Alpha to the Omicron variant; (ii) Δβ showed a high degree of variability within Omicron variants; (iii) a higher Δβ was associated with a later emergence of the variant within a country; (iv) a higher degree of immunization of the population against previous variants was associated with a higher Δβ for the Delta variant; (v) larger countries exhibited smaller Δβ, suggesting regionally diverse outbreaks within the same country; and finally (vi) the model reliably captures the dynamics of competing variants, even in complex scenarios.ConclusionThe use of mathematical models allows for precise and reliable estimation of daily cases of each variant. By quantifying Δβ, we have tracked the spread of the different variants across Europe, highlighting a robust increase in transmissibility trend from Alpha to Omicron. Additionally, we have shown that the geographical characteristics of a country, as well as the timing of new variant entrances, can explain some of the observed differences in variant substitution dynamics across countries.

SEIR Model on the Review Impact of Social Distancing for COVID-19 Transmission Dynamics

The COVID-19 pandemic has had a huge influence on world health, with many countries enacting lockdowns and social distancing measures to help reduce transmission. However, the efficiency of these efforts is questionable, particularly in locations like as North East Nigeria, where specific socioeconomic and demographic characteristics can alter virus transmission dynamics. In this paper, we assess the pandemic in North East Nigeria by modifying the SIR to SEIR compartmental model, which incorporates data from the National Centre for Disease Control. We exposed that social distancing techniques like face masks, hand washing, and avoiding big gatherings are more successful than lockdowns in slowing the spread of COVID-19 in the region. Our findings suggest that future pandemic response plans should concentrate on social distancing measures that are both effective and feasible while avoiding the economic and social disruptions caused by lockdowns. Our work emphasizes the significance of specialized approaches to pandemic control in varied situations, including North East Nigeria.

Next generation sequencing improves the resolution of detecting mixed host blood meal sources in field collected arboviral mosquito vectors.

Accurate knowledge of blood meal hosts of different mosquito species is critical for identifying potential vectors and establishing the risk of pathogen transmission. We compared the performance of Miseq next generation sequencing approach relative to conventional Sanger sequencing approach in identification of mosquito blood meals using genetic markers targeting the 12S rRNA and cytochrome oxidase I (COI) genes. We analysed the blood meals of three mosquito vector species (Aedes aegypti, Aedes simpsoni s.l. and Culex pipiens s.l.) collected outdoors, and compared the frequency of single- versus multiple-blood feeding. Single host blood meals were mostly recovered for Sanger-based sequencing of the mitochondrial 12S rRNA gene, whereas Miseq sequencing employing this marker and the COI marker detected both single and multiple blood meal hosts in individual mosquitoes. Multiple blood meals (two or more hosts) which mostly included humans were detected in 19%-22.7% of Ae. aegypti samples. Most single host blood meals for this mosquito species were from humans (47.7%-57.1%) and dogs (9.1%-19.0%), with livestock, reptile and rodent hosts collectively accounting for 4.7%-28.9% of single host blood meals. The frequency of two or more host blood meals in Ae. simpsoni s.l. was 26.3%-45.5% mostly including humans, while single host blood meals were predominantly from humans (31.8%-47.4%) with representation of rodent, reptile and livestock blood meals (18.2%-68.2%). Single host blood meals from Cx. pipiens s.l. were mostly from humans (27.0%-39.4%) and cows (11.5%-27.36%). Multiple blood meal hosts that mostly included humans occurred in 21.2%-24.4% of Cx. pipiens s.l. samples. Estimated human blood indices ranged from 53%-76% for Ae. aegypti, 32%-82% for Ae. simpsoni s.l. and 26%-61% for Cx. pipiens s.l. and were consistently lower for Sanger-based sequencing approach compared to Miseq-based sequencing approach. These findings demonstrate that Miseq sequencing approach is superior to Sanger sequencing approach as it can reliably identify mixed host blood meals in a single mosquito, improving our ability to understand the transmission dynamics of mosquito-borne pathogens.

Typing of Treponema pallidum in a Brazilian sample and follow-up of treatment using molecular assays.

Syphilis remains a significant public health concern, with serological assays being the primary method for diagnosis. However, molecular techniques have proven to be reliable tools for the diagnosis and understanding of the transmission dynamics of Treponema pallidum infection. This study aimed to evaluate the efficacy of syphilis treatment using molecular assays, perform Enhanced Centers for Disease Control and Prevention (ECDC) typing, and analyze resistance (macrolide and doxycycline) in the T. pallidum isolate. PCR assay amplified treponemal DNA only from the lesion sample, whereas qPCR was able to amplify DNA in both lesion and blood samples before treatment. Throughout the treatment follow-up, qPCR effectively did not identify treponemal DNA in the blood for up to one to two weeks after treatment. ECDC typing revealed the genotype 14 e/g in the Brazilian T. pallidum isolate, and the presence of the A2058G mutation in 23S rRNA gene, indicating macrolide resistance. Although, the G1058C mutation in 16S rRNA gene was not detected. Notably, qPCR demonstrated its potential for diagnosing T. pallidum in blood samples, even when the treponemal DNA levels were low, enabling more accurate and sensitive diagnosis and guiding better syphilis therapy. In addition, to the best of our knowledge, this study represents the first identification of subtype 14 e/g and azithromycin resistance in a Brazilian T. pallidum isolate.

Epidemic characteristics of local HIV-2 transmission across Hunan province, China

ObjectiveTo elucidate the epidemiological features of HIV-2 in Hunan Province, China, utilizing sequence analysis. MethodsThirteen individuals diagnosed with HIV-2 infection in Hunan Province, China, from 2017 to 2023 were included in this study. Amplification of HIV-2 env and pol regions was conducted, followed by Sanger sequencing. Phylogenetic and molecular transmission network analyses were performed to delineate molecular features and transmission dynamics. ResultsAll 14 individuals contracted HIV-2 through heterosexual intercourse, comprising 7 males and 7 females, with a median age of 58 years. Among them, three couples (HN001 and HN013, HN010 and HN011, HN008 and HN009) were identified, along with commercial sexual activity engagement reported for subject HN004. Notably, subjects HN001, HN003, HN008, and HN010 engaged in commercial sexual activities at the same location as subject HN004. Phylogenetic analysis of the pol gene revealed close proximity of sequences from all subjects to reference sequences from Gambia (Sub-type A). Employing a genetic distance threshold of 1.5 %, eight out of the 14 subjects formed a molecular transmission network, with HN002 and HN004 identified as central nodes. ConclusionFrom 2017 to 2023, all HIV-2-infected individuals in Hunan Province, China, acquired the virus through identifiable routes, indicating transmission of similar HIV-2 strains among them.

Rabies and the Arctic Fox (Vulpes lagopus): A Review.

The Arctic fox (Vulpes lagopus) is the primary infection reservoir of Arctic rabies, the dynamics of which are poorly understood and subject to significant spatiotemporal variation. Although rabies presence has been documented in the region since the mid-19th century, there is currently no evidence of rabies impacting Arctic fox population size. Under the influence of climate change in a rapidly changing Arctic ecosystem, changes in transmission dynamics are predicted, with implications for this species. Concurrently, the World Health Organization leads the United Against Rabies collective in the aim of elimination of dog-mediated rabies by 2030, and although efforts have justifiably been directed to tropical regions, elimination will require a good understanding of rabies in the Arctic. Therefore, this review aimed to provide an overview of current Arctic rabies understanding, while identifying the key knowledge gaps. The review covered spatiotemporal trends in rabies populations, population dynamics of the host species, and current theories about Arctic rabies persistence. It is still unclear how Arctic rabies can persist under low host densities, which has led to several hypotheses in recent years. Creation of high animal density "hotspots" caused by heterogenic fox distribution and multispecies congregations in response to food availability, extensive Arctic fox migration patterns, and the potential evolution to a less lethal variant of rabies may all be part of the explanation. Evidence for these theories by using recent genetic and modeling studies was evaluated within the review. There is currently insufficient evidence about the efficacy and feasibility of vaccines against Arctic rabies. Key knowledge gaps need addressing to enable future control campaigns.

Corruption dynamics: a mathematical model and analysis

This study proposes and analyzes a deterministic mathematical model to describe the dynamics of corruption transmission. We began by proving that the solution to the model is bounded and positive. The next-generation matrix approach is used to compute the basic reproduction number (R0) in relation to corruption-free equilibrium. The Jacobian and Lyapunov functions are used to show that corruption-free equilibrium is asymptotically stable in both locally and globally when R0&lt;1, and otherwise, an endemic corruption equilibrium develops. Furthermore, the sensitivity of the model's parameters was investigated. The findings demonstrate that religious precepts govern public education. The two sectors most susceptible to corruption control are education and corrections. The study recommends investing more in the provision of public education to citizens by creating awareness among all and including it in the education curriculum and religious leaders to teach their followers seriously about the impact of corruption as well as the use of jail as punishment. The numerical simulation results agreed with the analytical results.

Linking Spontaneous Behavioral Changes to Disease Transmission Dynamics: Behavior Change Includes Periodic Oscillation.

Behavior change significantly influences the transmission of diseases during outbreaks. To incorporate spontaneous preventive measures, we propose a model that integrates behavior change with disease transmission. The model represents behavior change through an imitation process, wherein players exclusively adopt the behavior associated with higher payoff. We find that relying solely on spontaneous behavior change is insufficient for eradicating the disease. The dynamics of behavior change are contingent on the basic reproduction number corresponding to the scenario where all players adopt non-pharmaceutical interventions (NPIs). When , partial adherence to NPIs remains consistently feasible. We can ensure that the disease stays at a low level or maintains minor fluctuations around a lower value by increasing sensitivity to perceived infection. In cases where oscillations occur, a further reduction in the maximum prevalence of infection over a cycle can be achieved by increasing the rate of behavior change. When , almost all players consistently adopt NPIs if they are highly sensitive to perceived infection. Further consideration of saturated recovery leads to saddle-node homoclinic and Bogdanov-Takens bifurcations, emphasizing the adverse impact of limited medical resources on controlling the scale of infection. Finally, we parameterize our model with COVID-19 data and Tokyo subway ridership, enabling us to illustrate the disease spread co-evolving with behavior change dynamics. We further demonstrate that an increase in sensitivity to perceived infection can accelerate the peak time and reduce the peak size of infection prevalence in the initial wave.

COVID-19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy.

Mathematical models are vital tools to understand transmission dynamics and assess the impact of interventions to mitigate COVID-19. However, historically, their use in Africa has been limited. In this scoping review, we assess how mathematical models were used to study COVID-19 vaccination to potentially inform pandemic planning and response in Africa. We searched six electronic databases: MEDLINE, Embase, Web of Science, Global Health, MathSciNet and Africa-Wide NiPAD, using keywords to identify articles focused on the use of mathematical modelling studies of COVID-19 vaccination in Africa that were published as of October 2022. We extracted the details on the country, author affiliation, characteristics of models, policy intent and heterogeneity factors. We assessed quality using 21-point scale criteria on model characteristics and content of the studies. The literature search yielded 462 articles, of which 32 were included based on the eligibility criteria. Nineteen (59%) studies had a first author affiliated with an African country. Of the 32 included studies, 30 (94%) were compartmental models. By country, most studies were about or included South Africa (n = 12, 37%), followed by Morocco (n = 6, 19%) and Ethiopia (n = 5, 16%). Most studies (n = 19, 59%) assessed the impact of increasing vaccination coverage on COVID-19 burden. Half (n = 16, 50%) had policy intent: prioritising or selecting interventions, pandemic planning and response, vaccine distribution and optimisation strategies and understanding transmission dynamics of COVID-19. Fourteen studies (44%) were of medium quality and eight (25%) were of high quality. While decision-makers could draw vital insights from the evidence generated from mathematical modelling to inform policy, we found that there was limited use of such models exploring vaccination impacts for COVID-19 in Africa. The disparity can be addressed by scaling up mathematical modelling training, increasing collaborative opportunities between modellers and policymakers, and increasing access to funding.

Mathematical Modeling of the Transmission Dynamics of Gumboro Disease

Gumboro disease is a viral poultry disease that causes immune suppression on the infected birds leading to poor production, mortality, and exposure to secondary infections, hence a major threat in the poultry industry worldwide. A mathematical model of the transmission dynamics of Gumboro disease is developed in this paper having four compartments of chicken population and one compartment of Gumboro pathogen population. The basic reproduction number Rog is derived, and the dynamical behaviors of both the disease-free equilibrium (DFE) and endemic equilibrium are analyzed using the ordinary differential equation theory. From the analysis, we found that the system exhibits an asymptotic stable DFE whenever Rog&lt;1 and an asymptotic stable EE whenever Rog&gt;1. The numerical simulation to verify the theoretical results was carried out using MATLAB ode45 solver, and the results were found to be consistent with the theoretical findings.

A model for the control of transmission dynamics of human monkeypox disease in Sub-Saharan Africa

The Human Monkeypox virus has received significant research interest in recent times. While few researchers have studied the effects of vaccination on human-to-animal or animal-to-human Monkeypox transmission, others just studied the effects of treatment on human Monkeypox. In this article, we made the proposition of a deterministic vaccine model that deals with the dynamics of the effects of vaccination and treatment on human Monkeypox in sub-Saharan Africa. We investigated the effects of vaccination on the various epidemiological classes qualitatively. The findings from the analysis of the model are that the model possesses two equilibria, locally asymptotically stable disease-free equilibrium (DFE) when an epidemiological threshold - the effective reproductive number is less than unity, and locally asymptotically stable endemic equilibrium when the number is greater than unity. We then corroborated the theoretical findings with numerical simulations, which reveal that when the rate of vaccination is increased resulting in many newly born persons in the populace being vaccinated, the prevalence of the deadly scourge is significantly reduced, while newly born individuals that miss vaccination experience a drastic torment of the deadly disease that often occasion death. Further revelation from the simulations is that when greater efforts