Dengue Model Research Articles

Genetic algorithm to optimization mobility-based dengue mathematical model

<span lang="EN-US">Implementation of vaccines, mosquito repellents and several Wolbachia schemes have been proposed recently as strategies against dengue. Research showed that the use of vaccine and repellent is highly effective when implemented to individuals who are in area with high transmission rates, while the use of Wolbachia bacteria is strongly effective when implemented in area with low transmission rates. This research is to show a three-strategy combination to cope with the dengue using mathematical model. In dengue mathematical model construction, several parameters are not yet known, therefore a genetic algorithm method was used to estimate dengue model parameters. Numerical simulation results showed that the combination of three strategies were able to reduce the number of infected humans. The dynamic of the human population with the combination of three strategies on average was able to reduce the infected human population by 45.2% in immobility aspect. Furthermore, the mobility aspect in dengue model was presented by reviewing two areas; Yogyakarta and Semarang in Indonesia. The numerical solutions showed that the trend graph was almost similar between the two areas. With the maximum effort given, the combination control values decreased slowly until the 100<sup>th</sup> day.</span>

Analysis of Dengue Transmission Dynamic Model by Stability and Hopf Bifurcation with Two-Time Delays.

Mathematical models reflecting the epidemiological dynamics of dengue infection have been discovered dating back to 1970. The four serotypes (DENV-1 to DENV-4) that cause dengue fever are antigenically related but different viruses that are transmitted by mosquitoes. It is a significant global public health issue since 2.5 billion individuals are at risk of contracting the virus. The purpose of this study is to carefully examine the transmission of dengue with a time delay. A dengue transmission dynamic model with two delays, the standard incidence, loss of immunity, recovery from infectiousness, and partial protection of the human population was developed. Both endemic equilibrium and illness-free equilibrium were examined in terms of the stability theory of delay differential equations. As long as the basic reproduction number (R0) is less than unity, the illness-free equilibrium is locally asymptotically stable; however, when R0 exceeds unity, the equilibrium becomes unstable. The existence of Hopf bifurcation with delay as a bifurcation parameter and the conditions for endemic equilibrium stability were examined. To validate the theoretical results, numerical simulations were done. The length of the time delay in the dengue transmission epidemic model has no effect on the stability of the illness-free equilibrium. Regardless, Hopf bifurcation may occur depending on how much the delay impacts the stability of the underlying equilibrium. This mathematical modelling is effective for providing qualitative evaluations for the recovery of a huge population of afflicted community members with a time delay.

Deterministic and fractional analysis of a newly developed dengue epidemic model

This paper presents a new non-linear dengue epidemiological model with a new type of incidence rate called convex incidence rate. A qualitative study of the proposed model was conducted. Local and global stability and the threshold value are established. By using sensitivity analysis, the highly dominant parameters on the threshold value have been found. For numerical solutions, RK-4 and NSFD schemes are used. Moreover, the novel fractional-order operator created by Atangana-Baleanu for transmission dynamics of the Dengue epidemic model is considered in this paper. Assuming the importance of the non-local Atangana-Baleanu fractional-order approach, the transmission mechanism of Dengue has been investigated while taking into account different phases of infection and various transmission routes of the disease. To conduct the proposed study, first of all, By using the classical operator of ordinary derivatives, we will formulate the model. The fractional order derivative is used and We will expand the model to include fractional order derivatives. The operator being used is the fractional differential operator and has fractional order considered the process of Newton's polynomial for the proposed ABC model a new numerical scheme is developed which helped in presenting an iterative process. Using this scheme, for different values of sample curves are obtained and a pattern is established between the order of the derivative and the dynamics of the infection.

Simulation of Hemorrhage Pathogenesis in Mice through Dual Stimulation with Dengue Envelope Protein Domain III-Coated Nanoparticles and Antiplatelet Antibody.

Dengue hemorrhagic fever (DHF) is a severe form of dengue virus (DENV) infection that can lead to abnormal immune responses, endothelial vascular dysfunction, and hemorrhage pathogenesis. The virion-associated envelope protein domain III (EIII) is thought to play a role in the virulence of DENV by damaging endothelial cells. However, it is unclear whether EIII-coated nanoparticles simulating DENV virus particles could cause a more severe pathogenesis than soluble EIII alone. This study aimed to investigate whether EIII-coated silica nanoparticles (EIII-SNPs) could elicit greater cytotoxicity in endothelial cells and hemorrhage pathogenesis in mice compared to EIII or silica nanoparticles alone. The main methods included in vitro assays to assess cytotoxicity and in vivo experiments to examine hemorrhage pathogenesis in mice. EIII-SNPs induced greater endothelial cytotoxicity in vitro than EIII or silica nanoparticles alone. Two-hit combined treatment with EIII-SNPs and antiplatelet antibodies to simulate DHF hemorrhage pathogenesis during secondary DENV infections resulted in higher endothelial cytotoxicity than either treatment alone. In mouse experiments, two-hit combined treatment with EIII-SNPs and antiplatelet antibodies resulted in more severe hemorrhage pathogenesis compared to single treatments of EIII, EIII-SNPs, or antiplatelet antibodies alone. These findings suggest that EIII-coated nanoparticles are more cytotoxic than soluble EIII and could be used to develop a tentative dengue two-hit hemorrhage pathogenesis model in mice. Additionally, our results indicated that EIII-containing DENV particles could potentially exacerbate hemorrhage pathogenesis in DHF patients who have antiplatelet antibodies, highlighting the need for further research on the potential role of EIII in DHF pathogenesis.

Applying a multi-strain dengue model to epidemics data

Dengue disease transmission is a complex vector-borne disease, mainly due to the co-circulation of four serotypes of the virus. Mathematical models have proved to be a useful tool to understand the complexity of this disease. In this work, we extend the model studied by Esteva et al., 2003, originally proposed for two serotypes, to four circulating serotypes. Using epidemic data of dengue fever in Iquitos (Peru) and San Juan (Puerto Rico), we estimate numerically the co-circulation parameter values for selected outbreaks using a bootstrap method, and we also obtained the Basic Reproduction Number, R0, for each serotype, using both analytical calculations and numerical simulations. Our results indicate that the impact of co-circulation of serotypes in population dynamics of dengue infection is such that there is a reduced effect from DENV-3 to DENV-4 in comparison to no-cross effect for epidemics in Iquitos. Concerning San Juan epidemics, also comparing to no-cross effect, we also observed a reduced effect from the predominant serotype DENV-3 to both DENV-2 and DENV-1 epidemics neglecting the very small number of cases of DENV-4.

Mathematical analysis of the impact of community ignorance on the population dynamics of dengue

This study proposes a dengue spread model that considers the nonlinear transmission rate to address the level of human ignorance of dengue in their environment. The SIR − UV model has been proposed, where SIR denotes the classification of the human population and UV denotes the classification of the mosquito population. Assuming that the total human population is constant, and the mosquito population is already in its steady-state condition, using the Quasi-Steady State Approximation (QSSA) method, we reduce our SIR − UV model into a more simple IR-model. Our analytical result shows that a stable disease-free equilibrium exists when the basic reproduction number is <1. Furthermore, our model also shows the possibility of a backward bifurcation. The more ignorant the society is about dengue, the higher the possibility that backward bifurcation phenomena may appear. As a result, the condition of the basic reproduction number being <1 is insufficient to guarantee the extinction of dengue in a population. Furthermore, we found that increasing the recovery rate, reducing the waning immunity rate, and mosquito life expectancy can reduce the possibility of backward bifurcation phenomena. We use dengue incidence data from Jakarta to calibrate the parameters in our model. Through the fast Fourier transform analysis, it was found that dengue incidence in Jakarta has a periodicity of 52.4, 73.4, and 146.8 weeks. This result indicates that dengue will periodically appear at least every year in Jakarta. Parameter estimation for our model parameters was carried out by assuming the infection rate of humans as a sinusoidal function by determining the three most dominant frequencies. Numerical and sensitivity analyses were conducted to observe the impact of community ignorance on dengue endemicity. From the sensitivity analysis, we found that, although a larger community ignorance can trigger a backward bifurcation, this threshold can be minimized by increasing the recovery rate, prolonging the temporal immunity, or reducing the mosquito population. Therefore, to control dengue transmission more effectively, media campaigns undertaken by the government to reduce community ignorance should be accompanied by other interventions, such as a good treatment in the hospital or vector control programs. With this combination of interventions, it will be easier to achieve a condition of dengue-free population when the basic reproduction number is less than one.

Stability of periodic traveling fronts for a time–space periodic dengue transmission model

In this paper, we consider the periodic traveling waves for a time–space periodic and degenerate reaction–diffusion dengue model. By establishing two comparison theorems and using comparison methods, we prove the globally exponential stability of time–space periodic traveling fronts. Our result is a continuation of Fang et al. (2020).

Global dynamics of a dengue fever model incorporating transmission seasonality

The changes of seasons cause that the transmission of dengue fever is characterized by periodicity. We develop a dengue fever transmission model incorporating seasonal periodicity and spatial heterogeneity. Based on the well-posedness of solution for this model, we propose its basic reproduction number R0, and we discuss the properties of this number including its limiting form when the diffusion coefficients change. Moreover, the dynamical behavior of this model infers that if R0 ⩽ 1, then the disease-free periodic solution is globally asymptotically stable, and if R0 > 1, then the model possesses a positive periodic solution, which is globally asymptotically stable. These theoretical findings are further illustrated by the final numerical simulations. Additionally, we add that the similar problem has been investigated by M. Zhu and Y. Xu [A time-periodic dengue fever model in a heterogeneous environment, Math. Comput. Simul., 155:115–129, 2019] in which some dynamical results have been studied only on the cases R0 < 1 and R0 > 1. Our results not only include the scenario on the case R0 = 1, but also involve the more succinct conditions on the cases R0 < 1 and R0 > 1.

Solution of a dengue fever model via fractional natural decomposition and modified predictor–corrector methods

In this paper, we solved a model of a well-known infectious disease called dengue fever via fractional natural decomposition and modified Predictor–Corrector (PC) methods. A study of the dengue epidemic in the Cape Verde Islands off the coast of West Africa in 2009 has been resumed here for a better understanding of the results. The results are obtained using Liouville–Caputo and new generalized Caputo-type fractional derivatives. The numerical simulations are presented for various orders of given derivatives. Existence and uniqueness analysis of the given problem are also performed in the new generalized Caputo sense. The explored results are verified using figures. The main target of this paper is to explore the different dynamics of the given dengue fever model via two types of fractional numerical algorithms.

DDPM: A Dengue Disease Prediction and Diagnosis Model Using Sentiment Analysis and Machine Learning Algorithms

The aedes mosquito-borne dengue viruses cause dengue fever, an arboviral disease (DENVs). In 2019, the World Health Organization forecasts a yearly occurrence of infections from 100 million to 400 million, the maximum number of dengue cases ever testified worldwide, prompting WHO to label the virus one of the world's top ten public health risks. Dengue hemorrhagic fever can progress into dengue shock syndrome, which can be fatal. Dengue hemorrhagic fever can also advance into dengue shock syndrome. To provide accessible and timely supportive care and therapy, it is necessary to have indispensable practical instruments that accurately differentiate Dengue and its subcategories in the early stages of illness development. Dengue fever can be predicted in advance, saving one's life by warning them to seek proper diagnosis and treatment. Predicting infectious diseases such as dengue is difficult, and most forecast systems are still in their primary stages. In developing dengue predictive models, data from microarrays and RNA-Seq have been used significantly. Bayesian inferences and support vector machine algorithms are two examples of statistical methods that can mine opinions and analyze sentiment from text. In general, these methods are not very strong semantically, and they only work effectively when the text passage inputs are at the level of the page or the paragraph; they are poor miners of sentiment at the level of the sentence or the phrase. In this research, we propose to construct a machine learning method to forecast dengue fever.

The stability analysis of a co-circulation model for COVID-19, dengue, and zika with nonlinear incidence rates and vaccination strategies

This paper aims to study the impacts of COVID-19 and dengue vaccinations on the dynamics of zika transmission by developing a vaccination model with the incorporation of saturated incidence rates. Analyses are performed to assess the qualitative behavior of the model. Carrying out bifurcation analysis of the model, it was concluded that co-infection, super-infection and also re-infection with same or different disease could trigger backward bifurcation. Employing well-formulated Lyapunov functions, the model’s equilibria are shown to be globally stable for a certain scenario. Moreover, global sensitivity analyses are performed out to assess the impact of dominant parameters that drive each disease’s dynamics and its co-infection. Model fitting is performed on the actual data for the state of Amazonas in Brazil. The fittings reveal that our model behaves very well with the data. The significance of saturated incidence rates on the dynamics of three diseases is also highlighted. Based on the numerical investigation of the model, it was observed that increased vaccination efforts against COVID-19 and dengue could positively impact zika dynamics and the co-spread of triple infections.

Dynamical analysis of an age-structured dengue model with asymptomatic infection

In this paper, we propose a new mathematical model to investigate the transmission dynamics of dengue. The model is based on an age-structured system of differential and integral equations that couples the host and mosquito populations and that incorporates both symptomatic and asymptomatic infections. We derive the basic reproduction number and conduct a rigorous analysis on the local and global stabilities of the disease-free steady state. Meanwhile, we study the existence of the endemic steady states and explore conditions that could lead to the occurrence of a backward bifurcation. In addition, we establish the weak and strong uniform persistence properties of the system.

A novel mathematical analysis and threshold reinforcement of a stochastic dengue epidemic model with Lévy jumps

The aggressive re-emergence of dengue fever during the last decade made it a principal topic of several research fields, especially biomathematics. In this vein, mathematical modeling is commonly viewed as a great option to get an idea of this disease’s prevalence behavior. This work presents and analyzes a generalized stochastic dengue model that incorporates slight and huge environmental perturbations. In rigorous terms, our proposed model takes the form of a stochastic differential equations system that includes white noises and Lévy jumps. We first demonstrate its well-posedness then, and based on many novel analytical techniques, we provide some ameliorated necessary conditions for the extinction and the persistence in the mean. The theoretical findings show that the dynamics of our disturbed dengue model are mainly determined by the parameters related to the white noises and Lévy jumps intensities. In the end, certain numerical illustrative examples are depicted to confirm our findings and to highlight the effect of the adopted mathematical techniques on the results.

Small-Molecule Inhibitor of Flaviviral NS3-NS5 Interaction with Broad-Spectrum Activity and Efficacy In Vivo.

Every year, dengue virus (DENV) causes one hundred million infections worldwide that can result in dengue disease and severe dengue. Two other mosquito-borne flaviviruses, i.e., Zika virus (ZIKV) and West Nile virus (WNV), are responsible of prolonged outbreaks and are associated with severe neurological diseases, congenital defects, and eventually death. These three viruses, despite their importance for global public health, still lack specific drug treatments. Here, we describe the structure-guided discovery of small molecules with pan-flavivirus antiviral potential by a virtual screening of ~1 million structures targeting the NS3-NS5 interaction surface of different flaviviruses. Two molecules inhibited the interaction between DENV NS3 and NS5 in vitro and the replication of all DENV serotypes as well as ZIKV and WNV and exhibited low propensity to select resistant viruses. Remarkably, one molecule demonstrated efficacy in a mouse model of dengue by reducing peak viremia, viral load in target organs, and associated tissue pathology. This study provides the proof of concept that targeting the flaviviral NS3-NS5 interaction is an effective therapeutic strategy able to reduce virus replication in vivo and discloses new chemical scaffolds that could be further developed, thus providing a significant milestone in the development of much awaited broad-spectrum antiflaviviral drugs. IMPORTANCE More than one-third of the human population is at risk of infection by different mosquito-borne flaviviruses. Despite this, no specific antiviral drug is currently available. In this work, using a computational approach based on molecular dynamics simulation and virtual screening of ~1 million small-molecule structures, we identified a compound that targets the interaction between the two sole flaviviral enzymes, i.e., NS3 and NS5. This compound demonstrated pan-serotype anti-DENV activity and pan-flavivirus potential in infected cells, low propensity to select viral resistant mutant viruses, and efficacy in a mouse model of dengue. Broad-spectrum antivirals are much awaited, and this work represents a significant advance toward the development of therapeutic molecules with extended antiflavivirus potential that act by an innovative mechanism and could be used alone or in combination with other antivirals.

Control Design for Dengue Fever Model with Disturbance

A mathematical model has become a useful tool to predict and control dengue fever dynamics. In reality, the dynamic of dengue fever transmission can be disturbed by uncertainty measurements, so it is needed to consider the disturbance in the model. Then, dengue fever model with disturbance is constructed by using a gain matrix consisting a covariance matrix and random vector. As dengue vaccine has been challenging to reduce the pandemic, a dengue model with vaccination as control is constructed. The aim is to propose a feedback controller that can reduces the infected human (H2 control problem) and the uncertainty measurements (H∞ control problem). The control u denotes the proportion of susceptible humans that one decides to vaccinate at time t. A random mass vaccination with wanning immunity is chosen because vaccine still on development process. A Design of mixed H2 - H∞ control with State-dependent Riccati Equation (SDRE) approach is applied. The SDRE has been an effective method to solve for synthesizing nonlinear feedback controller by transforming the system to an State-dependent coefficient (SDC) form. By comparing the mixed scheme with basic H∞, numerical simulation shows that the control application effectively decreases the number of infected humans and reduces the disturbance.

Finite-time contraction stability of a stochastic reaction-diffusion dengue model with impulse and Markov switching.

From the perspective of prevention and treatment of dengue, it is important to minimize the number of infections within a limited time frame. That is, the study of finite time contraction stability (FTCS) of dengue system is a meaningful topic. This article proposes a dengue epidemic model with reaction-diffusion, impulse and Markov switching. By constructing an equivalent system, the well-posedness of the positive solution is proved. The main result is that sufficient conditions to guarantee the finite time contraction stability of the dengue model are acquired based on the average pulse interval method and the bounded pulse interval method. Furthermore, the numerical findings indicate the influences of impulse, control strategies and noise intensity on the FTCS.

Dynamic behavior of a reaction-diffusion dengue model with spatial heterogeneity

Dengue is one of the most prevalent vector-borne viral diseases, which is transmitted through the bite of Aedes mosquitoes (Aedes albopictus). In this study, using the global exponential attraction theory, the dynamic behavior of the dengue model in a spatially heterogeneous environment was studied. The existence and uniqueness of positive global solutions were proven using the semigroup theory. The basic reproduction number was defined using the spectral radius of the next-generation operator. Furthermore, a global exponential attractor set was given, and the results of globally asymptotically stable and disease uniform persistence were obtained for the dengue model. A numerical simulation showed the dynamic behavior and revealed that increasing the diffusion coefficient and spatial heterogeneity rate is beneficial for disease control.

Dynamical behavior and sensitivity analysis of a dengue reinfection model for vertical transmission incorporating multiple control strategies

Dynamical behavior and sensitivity analysis of a dengue reinfection model for vertical transmission incorporating multiple control strategies

A stability and optimal control analysis on a dengue transmission model with mosquito repellent

A stability and optimal control analysis on a dengue transmission model with mosquito repellent

Global dynamics of deterministic-stochastic dengue infection model including multi specific receptors via crossover effects

<abstract><p>Dengue viruses have distinct viral regularities due to the their serotypes. Dengue can be aggravated from a simple fever in an acute infection to a presumably fatal secondary pathogen. This article investigates a deterministic-stochastic secondary dengue viral infection (SDVI) model including logistic growth and a nonlinear incidence rate through the use of piecewise fractional differential equations. This framework accounts for the fact that the dengue virus can penetrate various kinds of specific receptors. Because of the supplementary infection, the system comprises both heterologous and homologous antibody. For the deterministic case, we determine the invariant region and threshold for the aforesaid model. Besides that, we demonstrate that the suggested stochastic SDVI model yields a global and non-negative solution. Taking into consideration effective Lyapunov candidates, the sufficient requirements for the presence of an ergodic stationary distribution of the solution to the stochastic SDVI model are generated. This report basically utilizes a novel idea of piecewise differentiation and integration. This method aids in the acquisition of mechanisms, including crossover impacts. Graphical illustrations of piecewise modeling techniques for chaos challenges are demonstrated. A piecewise numerical scheme is addressed. For various cases, numerical simulations are presented.</p></abstract>