Reproduction Number Research Articles

Global stability and modeling with a non-singular kernel for fractional order heroin epidemic model: Insights from different population studies

There has been a worldwide epidemic of heroin that has affected people, families, societies, and cultures across the world. Now, the heroin epidemic has transitioned from heroin abuse to the overuse of synthetic narcotics, which are widely accessible and inexpensively produced. In this work, a novel mathematical approach is applied to investigate the dynamics of the heroin epidemic model and its harmful effect on society with different population data. A heroin model has been constructed with the importance of a non-singular kernel in the sense of a generalized Mittag-Leffler kernel. The well-possedness of the proposed model is proven via fixed-point theory. To examine the heroin model, two equilibrium states have been determined. These equilibrium states are proven to be locally and globally asymptotically stable. To analyze the behavior of heroin, a basic reproduction number and sensitivity analysis are used to determine the impact of different parameters mathematically as well as through simulations. To find the approximate solution, we implement the Toufik-Atangana numerical method at different fractional order values. The sensitivity of the heroin model is carried out, and 3-D graphs show the significance of the parameter involved in the model. Finally, the numerical outcomes are presented with different values of fractional parameters.

Decoding the origins, spread, and global risks of mcr-9 gene

The global spread of the plasmid-mediated mcr (mobilized colistin resistance) gene family presents a significant threat to the efficacy of colistin, a last-line defense against numerous Gram-negative pathogens. The mcr-9 is the second most prevalent variant after mcr-1. A dataset of 698 mcr-9-positive isolates from 44 countries is compiled. The historical trajectory of the mcr-9 gene is reconstructed using Bayesian analysis. The effective reproduction number is used innovatively to study the transmission dynamics of this mobile-drug-resistant gene. Our investigation traces the origins of mcr-9 back to the 1960s, revealing a subsequent expansion from Western Europe to the America and East Asia in the late 20th century. Currently, its transmissibility remains high in Western Europe. Intriguingly, mcr-9 likely emerged from human-associated Salmonella and exhibits a unique propensity for transmission within the Enterobacter. Our research provides a new perspective that this host preference may be driven by codon usage biases in plasmids. Specifically, mcr-9-carrying plasmids prefer the nucleotide C over T compared to mcr-1-carrying plasmids among synonymous codons. The same bias is seen in Enterobacter compared to Escherichia (respectively as their most dominant genus). Furthermore, we uncovered fascinating patterns of coexistence between different mcr-9 subtypes and other resistance genes. Characterized by its low colistin resistance, mcr-9 has used this seemingly benign feature to silently circumnavigate the globe, evading conventional detection methods. However, colistin-resistant Enterobacter strains with high mcr-9 expression have emerged clinically, implying a strong risk of mcr-9 evolving into a global "true-resistance-gene". This study explores the mcr-9 gene, emphasizing its origin, adaptability, and dissemination potential. Given the high mcr-9 expression colistin-resistant strains was observed in clinically the prevalence of mcr-9 poses a significant challenge to drug resistance prevention and control within the One Health framework. This work was partially supported by the National Natural Science Foundation of China (Grant No. 32141001 and 81991533).

Mathematical modelling and transmission dynamic of SEIRVQD model for epidemic diseases

In this paper, we construct and formulate a new mathematical model for the spread of epidemic diseases with vaccination. The proposed model is composed of eight compartments, namely susceptible (S), exposed (E), infected (I), recovered (R), vaccinated (V ), quarantined (Q) and died (D). We prove the existence of a unique solution. Additionally, the region of the feasibility of the system and equilibrium points are presented. In order to indicate the level of viral invasion and demonstrate the ability of infection transmission, we calculate the basic reproduction number ( R 0 ) by the next generation matrix method. Furthermore, the sensitivity of the basic reproduction number ( R 0 ) concerning the fluctuations of the biological parameters of the presented model has been investigated. Finally, Numerical simulations are performed using MATLAB to illustrate and validate the efficiency of the proposed model and its accordance using real data for Chinese measles and Portugal's COVID-19 outbreaks.

Effect of vaccine dose intervals: Considering immunity levels, vaccine efficacy, and strain variants for disease control strategy

In this study, we present an immuno-epidemic model to understand mitigation options during an epidemic break. The model incorporates comorbidity and multiple-vaccine doses through a system of coupled integro-differential equations to analyze the epidemic rate and intensity from a knowledge of the basic reproduction number and time-distributed rate functions. Our modeling results show that the interval between vaccine doses is a key control parameter that can be tuned to significantly influence disease spread. We show that multiple doses induce a hysteresis effect in immunity levels that offers a better mitigation alternative compared to frequent vaccination which is less cost-effective while being more intrusive. Optimal dosing intervals, emphasizing the cost-effectiveness of each vaccination effort, and determined by various factors such as the level of immunity and efficacy of vaccines against different strains, appear to be crucial in disease management. The model is sufficiently generic that can be extended to accommodate specific disease forms.

Predictive modeling of hepatitis B viral dynamics: a caputo derivative-based approach using artificial neural networks

A fractional model for the kinetics of hepatitis B transmission was developed. The hepatitis B virus significantly affects the world’s economic and health systems. Acute and chronic carrier phases play a crucial part in the spread of the HBV infection. The Hepatitis B infection can be spread by chronic carriers even though they show no symptoms. In this article, we looked into the Hepatitis B virus’s various stages of infection-related transmission and built a nonlinear epidemic. Then, a fractional hepatitis B virus model using a Caputo derivative and vaccine effects is created. First, we determined the proposed model’s essential reproductive value and equilibria. With the aid of Fixed Point Theory, a qualitative analysis of the problem’s approximative root has been produced. The Adams-Bashforth predictor-corrector scheme is used to aid in the iterative approximate technique’s evaluation of the fractional system under consideration that has the Caputo derivative. In the final section, a graphical representation compares various noninteger orders and displays the discovered scheme findings. In this study, we’ve utilized Artificial Neural Network (ANN) techniques to partition the dataset into three categories: training, testing, and validation. Our analysis delves deep into each category, comprehensively examining the dataset’s characteristics and behaviors within these divisions. The study comprehensively analyzes the fractional HBV transmission model, incorporating both mathematical and computational approaches. The findings contribute to a better understanding of the dynamics of HBV infection and can inform the development of effective public health interventions.

Bifurcation Analysis and Optimal Control of an SEIR Model with Limited Medical Resources and Media Impact on Heterogeneous Networks

The spread of epidemic diseases is often considered to be bound up with human behavior. Both treatment and awareness-raising are seen as important preventive measures during an outbreak. In this paper, an SEIR model on heterogeneous network containing saturated treatment function with media information variable is constructed. Through mathematical analysis, the basic reproduction number and equilibriums of the system are derived. The global stability of disease-free equilibrium is further proved based on LaSalle’s invariant principle. It is also found that with a gradual increase of the delayed treatment parameter, the system exhibits a transition from forward bifurcation to backward bifurcation with the variation of the basic reproduction number. Finally, an optimal control problem is formulated with both treatment rate and media information dissemination rate as control variables and solved using the Pontryagin’s maximum principle. All the above results are verified by numerical experiments.

Collective exploitation of large prey by group foraging shapes aggregation and fitness of cnidarian polyps

Group living is widespread and beneficial to metazoans. It improves protection and survival opportunities, reinforcing interspecific competitiveness. Benthic cnidarians often colonize large surfaces. Evidence of collective capture and exploitation of large prey by small, clumped polyps suggests that aggregation is functional to access food resources hardly achievable by isolated individuals. In turn, the chance to catch large prey may represents a driver of aggregation in polyps, whether beneficial to their fitness. Here, the effects of group foraging on aggregation, asexual reproduction, and growth rates of Aurelia coerulea von Lendenfeld 1884 polyps were experimentally tested by providing them with either small or large prey, or a mix of both to simulate the co-occurrence of preys at sea. As expected, some polyps were not able to reach the large prey. Hence, the population was a posteriori divided into group-foragers and solitary-feeders. In general, the large prey diet resulted in higher population fitness and when simultaneously supplied with the small prey represented an energetic booster resulting beneficial for all group-members. The decrease of interindividual distances was reported among group-foragers, that converged towards each other. Cnidarians are basal in metazoan evolution, and the comprehension of their collective foraging behavior, as well as the processes leading to the selective feature driving them to forage in group or not, may be essential to better understand the evolution and spread of social foraging in animals. Moreover, the access to large prey by sessile polyps of Aurelia coerulea could be pivotal in determining the increase in abundance of adult bloom-forming medusae.

Influences of Salt Stress on Cotton Metabolism and Its Consequential Effects on the Development and Fecundity of Aphis gossypii Glover

The degree of global soil salinization is gradually deepening, which will inevitably affect agricultural ecology. It has been found that salt stress induces the resistance of host plants to phytophagous pests. However, little is known about the effects of salt-stressed cotton plants on the fitness of cotton aphids (Aphis gossypii Glover). In this study, we investigated the differences between cotton metabolomes under mild (75 mM NaCl) and moderate (150 mM NaCl) salinity conditions and their effects on the fitness of cotton aphids. The results showed that 49 metabolites exhibited significant upregulation, while 86 metabolites were downregulated, with the increasing NaCl concentration. The duration of nymphal aphids under 150 mM NaCl significantly extended to 6.31 days when compared with the control (0 mM NaCl, 4.10 days). Meanwhile, the longevity of adult aphids decreased significantly under 75 and 150 mM NaCl, with an average of 10.38 days (0 mM NaCl) reduced to 8.55 and 4.89 days, respectively. Additionally, the total reproduction number of single females decreased from 31.31 (0 mM NaCl) to 21.13 (75 mM NaCl) and 10.75 (150 mM NaCl), whereas the survival rate of aphids decreased from 81.25% (0 mM NaCl) to 56.25% (75 mM NaCl) and 34.38% (150 mM NaCl) on the 12th day. These results support the hypothesis that plants growing under salt stress are better defended against herbivores. Furthermore, 49 differential metabolites were found to be negatively correlated with the longevity and fecundity of adult aphids, while 86 different metabolites showed the opposite trend. These results provide insights into the occurrence and control of cotton aphids amidst the escalating issue of secondary salinization.

A Modified SIVR Mathematical Model of Covid-19 Post-vaccination Stability Analysis in Kenya

In this paper, the study focused on carrying out a stability analysis on a modified SIR model for the COVID-19 pandemic for the period after vaccination in Kenya. The purpose of the work was to show that whereas the rate and the extent of disease spread amongst the Kenyan people was not as wide spread as happened in other parts of the world, it was necessary for government and policy makers to roll out a robust civic education to convince the majority of the Kenyan population to embrace vaccination as a major containment measure in curbing the spread of COVID-19 and other infectious diseases since the study revealed that the infections drastically reduced to near zero after vaccination except for a few isolated cases that were and still continue to exhibit mild symptoms to none at all. This was attributed to the development of the vaccine which upon a massive campaign by the Kenyan government, led into a significant portion of the population being vaccinated. It is believed this vaccination drive enhanced herd immunity amongst the population. This development has had a significant effect in the control of more recent COVID-19 variants like JN-1 that have remained largely mild and undetected in the country. Both local and global post vaccination stabilities were analyzed for the system using the Lyapunov function. The main objective of the study was therefore to carry out a post vaccination stability analysis by estimating key parameters such as the basic reproduction number, ( R0) and herd immunity threshold (HIT) for infectious diseases by fitting data into the model to enable predictions of future dynamics of the disease. The study used the Next Generation matrix and the least square method besides the Python software to solve generated differential equations of the model for and HIT parameters. Results obtained showed that, there was a significant reduction in infections due to enhanced herd immunity attributed largely to the roll out of vaccination.

Cumulative and interannual effects of reproduction in eastern grey kangaroos.

Reproduction can reduce energy allocation to other life-history traits such as survival and growth. Resource constraints give rise to (co)variation in life-history traits and to heterogeneity in energy acquisition and allocation. At each reproductive opportunity, females face a choice between allocation to current reproduction or to maintenance. Many studies compare reproductive trade-offs between two consecutive years, but few account for the cumulative effects of reproduction over multiple years, a crucial factor in understanding life-history evolution in long-lived iteroparous species. We compared short- (interannual) and long-term (cumulative) reproductive trade-offs with a 14-year capture-mark-recapture study of eastern grey kangaroos, where females can have substantial skeletal growth for several years after maturation. We used a multivariate approach to compare how interannual and multi-annual cumulative reproduction affected growth (n = 378 measurements), mass change (n = 376 measurements) and subsequent reproduction (n = 388 measurements), and to quantify (co)variation between these traits among individuals (n = 107) and years (n = 14). Interannually, young females that reproduced experienced decreased skeletal growth compared to young females that did not reproduce. Reproductive females of all ages experienced reduced mass gain and weaning probability in the following year. The cumulative effects of multiple reproductions included decreased skeletal growth, mass gain and weaning probability in the following year. These effects increased with age and reproductive rate. We found positive trait correlations between mass change, leg growth and subsequent reproduction among individuals and years, though weaker at the cumulative than interannual level. Females experience dynamic interannual and cumulative trade-offs. Our analyses of cumulative costs of reproduction revealed long-term trade-offs as well as cumulative costs that were not apparent when estimating interannual costs. Trait correlations suggested heterogeneity in growth and reproduction among females. Years of increased growth were followed by years of increased reproduction, and years of poor growth were followed by years of poor reproduction. Our exploration of both interannual and cumulative costs of reproduction underscores the need to account for long-term reproductive histories to better understand reproductive trade-offs in long-lived iteroparous species.

Efficacy of Noval Nematicide on Root-knot Nematode, Meloidogyne javanica and Establishment of Recommended Dose in Mung Bean (Vigna radiata L.)

The study was carried out to efficacy of newer nematicide (fluensulfone 2% GR) at different doses under field conditions on mung bean. Total seven treatments were used with different doses of fluensulfone 2% GR i.e., T1 - fluensulfone 2% GR 10 kg/ha., T2 - fluensulfone 2% GR 12 kg/ha., T3 - fluensulfone 2% GR 14 kg/ha., T4 - fluensulfone 2% GR 16 kg/ha., T5- fluensulfone 2% GR 18 kg/ha., T6- fluensulfone 2% GR 20 kg/ha., T7 - carbofuran 3G 50 kg/ha and T8 - untreated check (control) maintained for comparison. The observations were recorded on plant growth characters (shoot length (cm), shoot weight (gm), root length (cm), and root weight (gm)) and nematode reproduction (number of galls per plant, number of egg mass per plant, number of eggs per egg mass, nematode juveniles per 200 cc soil and final nematode population). Treated plant with fluensulfone 2% GR with the dose of 20kg/ha found to be the best to given the maximum plant growth characters and minimized nematode reproduction.

Analyzing the dynamics and optimal control of a vector-borne model with dual vertical transmission and multiple serotypes

Abstract Transmission and contact patterns have an important influence on the intensity and trend of disease transmission. Taking into account two different serotypes and the vertical transmission of the disease in both humans and mosquitoes, this paper proposes a novel vector-borne disease model. In order to explore the evolution mechanisms of the model and the impacts of contact pattern on disease transmission. The basic regeneration number of the proposed model is obtained via the next-generation matrix approach. Subsequently, we analyze the conditions of the stabilities and existences of the equilibrium points. Further, the sensitivity of the parameters is studied using numerical simulations. It is observe that the increase of vertical transmission rate of mosquitoes leads to the increase of the basic reproduction number. In addition, we develop vaccination and insecticide control strategies and derive the existence and expression of the optimal solution. Our numerical results show that vaccination has a little effect on preventing the spread of disease among mosquitoes. However, insecticide spraying is effective in reducing the spread of disease between humans and mosquitoes.

Threshold dynamics of a degenerated diffusive incubation period host–pathogen model with saturation incidence rate

In this paper, we consider an incubation period host–pathogen system with degenerated diffusion. The global compact attractor of the solution of the model is investigated using the κ-contraction method. Furthermore, the basic reproduction number is defined, and we discuss the dynamic analysis of a degenerated diffusion model. The obtained theoretical results are nontrivial and can be considered a continuation of the work by Wang et al. in 2022.

Sensitivity analysis and global stability of epidemic between Thais and tourists for Covid -19

This study employs a mathematical model to analyze and forecast the severe outbreak of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), focusing on the socio-economic ramifications within the Thai population and among foreign tourists. Specifically, the model examines the impact of the disease on various population groups, including susceptible (S), exposed (E), infected (I), quarantined (Q), and recovered (R) individuals among tourists visiting the country. The stability theory of differential equations is utilized to validate the mathematical model. This involves assessing the stability of both the disease-free equilibrium and the endemic equilibrium using the basic reproduction number. Emphasis is placed on local stability, the positivity of solutions, and the invariant regions of solutions. Additionally, a sensitivity analysis of the model is conducted. The computation of the basic reproduction number (R0) reveals that the disease-free equilibrium is locally asymptotically stable when R0 is less than 1, whereas the endemic equilibrium is locally asymptotically stable when R0 exceeds 1. Notably, both equilibriums are globally asymptotically stable under the same conditions. Through numerical simulations, the study concludes that the outcome of COVID-19 is most sensitive to reductions in transmission rates. Furthermore, the sensitivity of the model to all parameters is thoroughly considered, informing strategies for disease control through various intervention measures.

Modeling different strategies towards control of lung cancer: leveraging early detection and anti-cancer cell measures

The global population has encountered significant challenges throughout history due to infectious diseases. To comprehensively study these dynamics, a novel deterministic mathematical model, TCD I L 2 Z, is developed for the early detection and treatment of lung cancer. This model incorporates I L 2 cytokine and anti-PD-L1 inhibitors, enhancing the immune system’s anticancer response within five epidemiological compartments. The TCD I L 2 Z model is analyzed qualitatively and quantitatively, emphasizing local stability given the limited data-a critical component of epidemic modeling. The model is systematically validated by examining essential elements such as equilibrium points, the reproduction number ( R 0 ), stability, and sensitivity analysis. Next-generation techniques based on R 0 that track disease transmission rates across the sub-compartments are fed into the system. At the same time, sensitivity analysis helps model how a particular parameter affects the dynamics of the system. The stability on the global level of such therapy agents retrogrades individuals with immunosuppression or treated with I L 2 and anti-PD-L1 inhibitors admiring the Lyapunov functions’ applications. NSFD scheme based on the implicit method is used to find the exact value and is compared with Euler’s method and RK4, which guarantees accuracy. Thus, the simulations were conducted in the MATLAB environment. These simulations present the general symptomatic and asymptomatic consequences of lung cancer globally when detected in the middle and early stages, and measures of anticancer cells are implemented including boosting the immune system for low immune individuals. In addition, such a result provides knowledge about real-world control dynamics with I L 2 and anti-PD-L1 inhibitors. The studies will contribute to the understanding of disease spread patterns and will provide the basis for evidence-based intervention development that will be geared toward actual outcomes.

Epidemiological characteristics and transmission dynamics of dengue fever in China

China has experienced successive waves of dengue epidemics over the past decade. Nationwide data on 95,339 dengue cases, 89 surveillance sites for mosquito density and population mobility between 337 cities during 2013-20 were extracted. Weekly dengue time series including time trends and harmonic terms were fitted using seasonal regression models, and the amplitude and peak timing of the annual and semiannual cycles were estimated. A data-driven model-inference approach was used to simulate the epidemic at city-scale and estimate time-evolving epidemiological parameters. We found that the geographical distribution of dengue cases was expanding, and the main imported areas as well as external sources of imported cases changed. Dengue cases were predominantly concentrated in southern China and it exhibited an annual peak of activity, typically peaking in September. The annual amplitude of dengue epidemic varied with latitude (F = 19.62, P = 0.0001), mainly characterizing by large in southern cities and small in northern cities. The effective reproduction number Reff across cities is commonly greater than 1 in several specific months from July to November, further confirming the seasonal fluctuations and spatial heterogeneity of dengue epidemics. The results of this national study help to better informing interventions for future dengue epidemics in China.

Research on safety strategies for nucleic acid testing in sudden epidemic conditions based on a SEIARD dynamic model

Infectious diseases have caused enormous disasters in human society, and asymptomatic carriers are an important challenge in our epidemic prevention and control process. Nucleic acid testing has played an important role in rapid testing for asymptomatic individuals. How to carry out nucleic acid testing in a scientific manner is a practical problem encountered in normal production and life. Based on the real COVID-19 epidemic data from Shanghai, we established a susceptible-exposed-infected-asymptomatic-recovered-death (SEIARD) dynamic model. The least squares method was used to fit the data and estimate the unknown parameters β and E(0) in the model, and MATLAB software was employed to simulate the development of the epidemic. The data fitting results indicated that the SEIARD model can better describe the early development patterns of the epidemic (R2 = 0.98; MAPE = 2.54%). We calculated the basic reproduction number of the Shanghai epidemic as R0 = 2.86. As the frequency of nucleic acid testing increased, the basic reproduction number R0 continued to decrease. When there is one latent carrier and one asymptomatic carrier in the nucleic acid testing team, the number of queues is directly proportional to the number of infected individuals, the nucleic acid testing team increases by 50 people, and the number of new asymptomatic cases increases by approximately 4 people. If both susceptible individuals (S) and asymptomatic patients (A) are not wearing masks, the infection rate reaches approximately 7%; after wearing masks, the final infection rate is less than 1% at 1.5 m between two people. The queue spacing is inversely proportional to the number of infected individuals. With a distance of d = 1 m, a nucleic acid testing team of 100 people added 8% of the infected individuals; when d = 1.5 m, fewer than 2% of the newly infected individuals. The results confirmed that controlling the queue size for nucleic acid testing, strictly wearing masks, and maintaining a queue spacing of more than 1.5 m are safe and effective nucleic acid testing strategies. Our findings are also applicable to the prevention of other newly emerging infectious diseases.

Sublethal and transgenerational effects of tetraniliprole on the tomato pinworm Phthorimaea (=Tuta) absoluta (Lepidoptera: Gelechiidae)

Invasive pest species of economic importance often require intensive pesticide use, leading to recurrent problems of pesticide resistance. Such is the case with the tomato pinworm, Phthorimaea (=Tuta) absoluta (Meyrick) (Lepidoptera: Gelechiidae), requiring the use of new insecticidal compounds for their management. Tetraniliprole, a novel insecticide effective against lepidopteran, coleopteran, and dipteran pests, is a potential alternative against the tomato pinworm. This study investigates the sublethal effects of tetraniliprole on the development and reproduction of the parental (F0) and progeny (F1) generations of P. absoluta while exploring the underlying mechanisms. Sublethal tetraniliprole exposure extended larval duration and reduced pupation rate, emergence rate, hatchability, and fecundity in both the F0 and F1 of P. absoluta. Additionally, the life-table parameters of the F1 generation were significantly altered, with decreases in net reproductive rate (R0) and increases in the mean generation time (T), leading to decreases in the intrinsic rate of population growth (r). The relative fitness of F1 insects exposed to tetraniloprole was reduced compared to unexposed insects (0.63 and 0.49, respectively). Furthermore, the mRNA expression levels of reproduction-related genes such as TaVg and TaVgR were down-regulated in the tetraniliprole-exposed insects. Finally, insect exposure to tetraniloprole increases the activity of the antioxidant enzymes such as glutathione S-transferase (GSTs), catalase (CAT), and superoxide dismutase (SOD). Taken together, these findings suggest that sublethal concentrations of tetraniloprole adversely affect both the development and reproduction of P. absoluta, providing a foundation for optimizing pest control strategies.

Assessing the impact of disease incidence and immunization on the resilience of complex networks during epidemics

Disease severity through an immunized population ensconced on a physical network topology is a key technique for preventing epidemic spreading. Its influence can be quantified by adjusting the common (basic) methodology for analyzing the percolation and connectivity of contact networks. Stochastic spreading properties are difficult to express, and physical networks significantly influence them. Visualizing physical networks is crucial for studying and intervening in disease transmission. The multi-agent simulation method is useful for measuring randomness, and this study explores stochastic characteristics of epidemic transmission in various homogeneous and heterogeneous networks. This work thoroughly explores stochastic characteristics of epidemic propagation in homogeneous and heterogeneous networks through extensive theoretical analysis (positivity and boundedness of solutions, disease-free equilibrium point, basic reproduction number, endemic equilibrium point, stability analysis) and multi-agent simulation approach using the Gilespie algorithm. Results show that Ring and Lattice networks have small stochastic variations in the ultimate epidemic size, while BA-SF networks have disease transmission starting before the threshold value. The theoretical and deterministic aftermaths strongly agree with multi-agent simulations (MAS) and could shed light on various multi-dynamic spreading process applications. The study also proposes a novel concept of void nodes, Empty nodes and disease severity, which reduces the incidence of contagious diseases through immunization and topologies.

Modeling environmental-born melioidosis dynamics with recurrence: An application of optimal control

Melioidosis is a significant health problem in tropical and subtropical regions, especially in Southeast Asia and Northern Australia. Recurrent melioidosis is a major obstacle to eliminating the disease from the community in these nations. This work aims to propose and analyze a human melioidosis model with recurrent phenomena and an optimal control model by incorporating time-dependent control functions. The basic reproduction number (R0) of the uncontrolled model is derived using the method of the next-generation matrix. Using the construction of a Lyapunov functional, we present the global asymptotic dynamics of the autonomous model in the presence of recurrent for both disease-free and endemic equilibria. The global asymptotic stability of the model’s equilibria shows the absence of a backward bifurcation for the model in both cases, whether in the absence or presence of relapse. The sensitivity analysis aims to identify the parameters that have the most significant impact on the model’s dynamics. Furthermore, qualitative analysis of the model’s global dynamics and the changing effect of the most influential parameters on R0 are supported by numerical experiments, with the results being illustrated graphically. The model with time-dependent controls is analyzed using optimal control theory to assess the impact of various intervention strategies on the spread of the epidemic. The numerical results of the optimality system are carried out using the Forward–Backward Sweep method in Matlab. We also conducted a cost-effectiveness analysis using two approaches: the average cost-effectiveness ratio and the incremental cost-effectiveness ratio.