Transmission Dynamics Of Tuberculosis Research Articles

Mathematical modeling of age-specific intervention strategies for latent tuberculosis infection

Tuberculosis (TB) remains a leading cause of death from a single infectious agent, with TB deaths in 2021 surpassing those from HIV/AIDS. In alignment with the WHO’s End TB strategy, South Korea launched a TB elimination plan in 2006. Recognizing the significance of age-dependent factors, we developed a comprehensive mathematical model to analyze the age-specific transmission dynamics of TB, including latent tuberculosis infection (LTBI), from 2012 to 2021. Our previous research focused on age-specific TB dynamics and the effects of various interventions on reducing active TB cases within different age groups. In this study, we enhance our model to include both short and long latent TB cases, allowing for a more detailed investigation of age-specific LTBI interventions and their impact on TB reduction. Utilizing the Markov Chain Monte Carlo (MCMC) method within a Bayesian inferential framework, we estimated model parameters that closely align with actual data with high accuracy. Our results revealed that non-elderly individuals are more responsive to transmission rates, whereas elderly individuals are more influenced by LTBI treatment. Strengthening LTBI treatment interventions significantly reduce TB infectious cases, particularly among those aged 65 and older. Detection and treatment strategies specifically targeting LTBI in the elderly population, along with primary TB treatments, are essential for TB control. The Korean government aims to reduce the TB incidence rate to below 20 cases per 100,000 by 2027. Our results indicate that this goal can be achieved by enhancing LTBI detection rates and treatment compliance levels. Specifically, our findings suggest that improving LTBI treatment interventions could lower the TB incidence to 10 cases per 100,000 by 2030. This underscores the critical importance of implementing age-specific LTBI detection and treatment interventions to effectively decrease TB incidence in South Korea.

Mathematical modeling of tuberculosis transmission dynamics with vaccination and two lines of treatments: a caputo fractional approach

Mathematical modeling of tuberculosis transmission dynamics with vaccination and two lines of treatments: a caputo fractional approach

Analysis of a fractional order epidemiological model for tuberculosis transmission with vaccination and reinfection

This study has been carried out using a novel mathematical model on the dynamics of tuberculosis (TB) transmission considering vaccination, endogenous re-activation of the dormant infection, and exogenous re-infection. We can comprehend the behavior of TB under the influence of vaccination from this article. We compute the basic reproduction number (R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {R}}_0$$\\end{document}) as well as the vaccination reproduction number (Rv\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {R}}_v$$\\end{document}) using the next-generation matrix (NGM) approach. The theoretical analysis demonstrates that the disease-free equilibrium point is locally asymptotically stable, and the fractional order system is Ulam–Hyers type stable. We perform numerical simulation of our model using the Adams-Bashforth 3-step method to verify the theoretical results and to show the model outputs graphically. By performing data fitting, we observe that our formulated model produces results that closely match real-world data. Our findings indicate that vaccinating a limited segment of the population can effectively eradicate the disease. The numerical simulations also show that vaccination can reduce the number of susceptible and infectious individuals in the population. Moreover, the graphical representations illustrate that the number of infected individuals rises due to both exogenous reinfection and endogenous reactivation.

Modeling and analysis of transmission dynamics of tuberculosis with preventive treatment and vaccination strategies in China

In China, approximately 350 million people with latent tuberculosis infection (LTBI) are the major source of new TB cases, meanwhile, BCG vaccination for newborns and children under five fails to fully arrest the TB epidemic due to the mechanisms of vaccine failure. It is expected that widespread TB preventive treatment (TPT) and new vaccination strategies may be solutions to end TB. This work allows for TPT and vaccination strategies in a nonlinear age-structured SVEIR model with nonexponential residence times to exploit the interventions for ending TB in China. Global stability analysis reveals that the target model preserves the threshold-value dynamics in terms of the basic reproduction number so that some existing results are extended, moreover, the model is applied to fit the data of TB cases in China. Furthermore, sensitivity analysis for endemic steady state suggests that four potentially feasible interventions (i.e., amplifying the inhibition effect of infectious individuals by limiting range of their mobility, shortening the treatment duration for patients, adopting BCG revaccination and enhancing the rate of TPT) can lower the steady level of infectious individuals at endemic steady state and delay its arrival time. Finally, several multifaceted strategies composed of these interventions are compared via emulational experiments. We conclude that the target of End TB Strategy by 2035 in China would be reached just by the multifaceted strategy with moderate intensity if BCG revaccination, the duration of TPT for 2 months and a 40% completion rate are realized. This investigation sheds light on the fantastic potential applications of new TPT and vaccination strategies.

Modeling tuberculosis transmission dynamics in Kazakhstan using SARIMA and SIR models

Tuberculosis (TB) is a highly contagious disease that remains a global concern affecting numerous countries. Kazakhstan has been facing considerable challenges in TB prevention and treatment for decades. This study aims to understand TB transmission dynamics by developing and comparing statistical and deterministic models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and the basic Susceptible-Infected-Recovered (SIR). TB data from 2014 to 2019 were collected from the Unified National Electronic Health System (UNEHS) using retrospective quantitative analysis. SARIMA models were able to capture seasonal variations, with Model 2 exhibiting superior predictive accuracy. Both models showed declining TB incidence and revealed a notable predictive performance evaluated by statistical metrics. In addition, the SIR model calculated the basic reproduction number (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R_0}$$\\end{document}) below 1, indicating a receding epidemic. Models proved the capability of each to accurately capture trends (SARIMA) and provide mathematical insights (SIR) into TB transmission dynamics. This study contributes to the general knowledge of TB transmission dynamics in Kazakhstan thus laying the foundation for more comprehensive studies on TB and control strategies.

Drug-resistance characteristics, genetic diversity, and transmission dynamics of multidrug-resistant or rifampicin-resistant Mycobacterium tuberculosis from 2019 to 2021 in Sichuan, China

BackgroundMultidrug- or rifampicin-resistant tuberculosis (TB; MDR/RR-TB) is a significant public health threat. However, the mechanisms involved in its transmission in Sichuan, China are unclear. To provide a scientific basis for MDR/RR-TB control and prevention, we investigated the drug-resistance characteristics, genetic diversity, and transmission dynamics and analyzed the demographic and clinical characteristics of patients to identify risk factors for the acquisition of MDR/RR-TB in Sichuan, Western China.MethodsWhole-genome sequencing was performed using a sample comprised of all MDR/RR-TB strains isolated from patients with pulmonary TB (≥ 15 years) at the 22 surveillance sites in Sichuan province between January 2019 and December 2021, to analyze genotypic drug resistance and genetic diversity. Moreover, we performed statistical analyses of the epidemiological characteristics and risk factors associated with the transmission dynamics of MDR/RR-TB.ResultsThe final analysis included 278 MDR/RR TB strains. Lineage 2.2, the major sub-lineage, accounted for 82.01% (228/278) of isolates, followed by lineage 4.5 (9.72%, 27/278), lineage 4.4 (6.83%, 19/278), and lineage 4.2 (1.44%, 4/278). The drug resistance rates, ranging from high to low, were as follows: isoniazid (229 [82.37%]), streptomycin (177 [63.67%]), ethambutol (144 [51.80%]), pyrazinamide (PZA, 119 [42.81%]), fluoroquinolones (FQs, 93 [33.45%]). Further, the clofazimine, bedaquiline, and delamanid resistance rates were 2.88, 2.88, and 1.04%, respectively. The gene composition cluster rate was 32.37% (90/278). In addition, 83.81% (233/278) of MDR/RR-TB cases were determined to be likely caused by transmission. Finally, patients infected with lineage two strains and strains with the KatG S315T amino acid substitution presented a higher risk of MDR/RR-TB transmission.ConclusionTransmission plays a significant role in the MDR/RR-TB burden in Sichuan province, and lineage 2 strains and strains harboring KatG S315T have a high probability of transmission. Further, high levels of FQ and PZA drug resistance suggest an urgent need for drug susceptibility testing prior to designing therapeutic regimens. New anti-TB drugs need to be used standardly and TB strains should be regularly monitored for resistance to these drugs.

Analysis and dynamical transmission of tuberculosis model with treatment effect by using fractional operator

ABSTRACT Each year, millions of people die from the airborne infectious illness tuberculosis (TB). Several drug-susceptible (DS) and drug-resistant (DR) forms of the causative agent, Mycobacterium tuberculosis (MTB), are currently common in the majority of affluent and developing nations, particularly in Bangladesh, and completely drug-resistant strains are beginning to arise. The main purpose of this research is to develop and examine a non-integer-order mathematical model for the dynamics of tuberculosis transmission using the fractal fractional operator. By demonstrating characteristics such as the boundedness of solutions, positivity, and reliance of the solution on the original data, the biological well-posedness of the mathematical model formulation was investigated for TB cases from 2002 to 2017 in KPK Pakistan. Ulam-Hyres stability is also used to assess both local and global aspects of TB bacterial infection. Sensitivity analysis of the TB model with therapy was also examined. The advanced numerical technique is used to find the solution of the fractional-order system to check the impact of fractional parameters. Simulation highlights that all classes have converging qualities and retain established positions with time, which shows the actual behavior of bacterial infection with TB.

Optimizing tuberculosis control: a comprehensive simulation of integrated interventions using a mathematical model

Tuberculosis (TB) remains a formidable global health challenge, demanding effective control strategies to alleviate its burden. In this study, we introduce a comprehensive mathematical model to unravel the intricate dynamics of TB transmission and assess the efficacy and cost-effectiveness of diverse intervention strategies. Our model meticulously categorizes the total population into seven distinct compartments, encompassing susceptibility, vaccination, diagnosed infectious, undiagnosed infectious, hospitalized, and recovered individuals. Factors such as susceptible individual recruitment, the impact of vaccination, immunity loss, and the nuanced dynamics of transmission between compartments are considered. Notably, we compute the basic reproduction number, providing a quantitative measure of TB transmission potential. Through this comprehensive model, our study aims to offer valuable insights into optimal control measures for TB prevention and control, contributing to the ongoing global efforts to combat this pressing health challenge.

Comparative Genomic Analysis of Mycobacterium tuberculosis Isolates Circulating in North Santander, Colombia.

Tuberculosis (TB) is an important infectious disease in relation to global public health and is caused species of the Mycobacterium tuberculosis complex (MTBC). In this study, we used whole-genome sequencing (WGS) and comparative genomics to investigate the genetic diversity of M. tuberculosis (Mtb) isolates circulating in North Santander (NS), Colombia. WGS was used for the phylogenetic and lineage characterization of 18 isolates of Mtb typed with orphan genotypes from 11 municipalities of NS between 2015 and 2018. The isolates studied were included in six sublineages from L4; the most frequent were 4.1.2.1, 4.3.3, and 4.3.4.2, corresponding to a proportion of 22.2%. The genome analysis conducted allowed the identification of a set of genetic variants mainly associated with determinants of virulence and evasion of the immune system (PPE34 and PE_PGRS2); adaptation and survival (PGL/p-HBAD); stress response (sigJ and sigM); geographic variability (PPE34); and carbohydrate and lipid metabolism (aldA, rocA, and cyp144). This is the first description of the molecular epidemiology of Mtb isolates circulating in NS achieved through WGS. It was possible to perform comparative genomics analyses between Mtb isolates against the universal reference H37Rv and Colombian UT205 genome, which can help us to understand the local genetic diversity and is relevant for epidemiological studies, providing insight into TB transmission dynamics in NS.

Transmission dynamics of tuberculosis in a high-burden area of China: An 8-year population-based study using whole genome sequencing

ObjectivesThis study investigated the transmission patterns of tuberculosis (TB) and its associated risk factors in Hunan province to inform the development of prevention and control strategies in the region. MethodsAn 8-year retrospective population-based genomic epidemiological study was conducted. Genomic clusters were defined using distance thresholds of 12-single-nucletide-polymorphisms. Risk factors associated with TB transmission were analyzed using logistic regression model. Kernel Density analysis was used to locate hotspots where transmission occurred. ResultsAmong 2649 TB cases included in this study, 275 clusters were identified, with an overall clustering rate of 24.7% (654/2649). Nearly 95% (620/654) of clustered strains were isolated from the same county. Of the 275 clusters, 23 (8.4%, 23/275) had differences in drug-resistant profiles, with FQs resistance mutations occurring most frequently (52.2%, 12/23). Multivariate analysis identified male TB patients, those aged 30-60 years, ethnic minorities, nonfarmers, retreated TB patients, and individuals infected with MDR/RR-TB as independent risk factors for TB transmission (P < 0.05). Kernel density analysis showed that among the 5 drug-resistant surveillance sites, Leiyang had the highest clustering rate, followed by Yongshun, Qidong, Hecheng, and Taojiang. ConclusionRecent transmission in the region is predominantly occurring within counties. The risk factors related to TB transmission and the hotspots where transmission occurs can provide a scientific basis for the formulation of targeted TB prevention and control strategies.

Toxin-antitoxin system gene mutations driving Mycobacterium tuberculosis transmission revealed by whole genome sequencing.

The toxin-antitoxin (TA) system plays a vital role in the virulence and pathogenicity of Mycobacterium tuberculosis (M. tuberculosis). However, the regulatory mechanisms and the impact of gene mutations on M. tuberculosis transmission remain poorly understood. To investigate the influence of gene mutations in the toxin-antitoxin system on M. tuberculosis transmission dynamics. We performed whole-genome sequencing on the analyzed strains of M. tuberculosis. The genes associated with the toxin-antitoxin system were obtained from the National Center for Biotechnology Information (NCBI) Gene database. Mutations correlating with enhanced transmission within the genes were identified by using random forest, gradient boosting decision tree, and generalized linear mixed models. A total of 13,518 M. tuberculosis isolates were analyzed, with 42.29% (n = 5,717) found to be part of genomic clusters. Lineage 4 accounted for the majority of isolates (n = 6488, 48%), followed by lineage 2 (n = 5133, 37.97%). 23 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, including vapB1 G34A, vapB24 A76C, vapB2 T171C, mazF2 C85T, mazE2 G104A, vapB31 T112C, relB T226A, vapB11 C54T, mazE5 T344C, vapB14 A29G, parE1 (C103T, C88T), and parD1 C134T. Six SNPs, including vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, Rv2653c A80C, and vapB22 C167T, were associated with transmission clades across different countries. Notably, our findings highlighted the positive association of vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, vapB19 C188T, and Rv2653c A80C with transmission clades across diverse regions. Furthermore, our analysis identified 32 SNPs that exhibited significant associations with clade size. Our study presents potential associations between mutations in genes related to the toxin-antitoxin system and the transmission dynamics of M. tuberculosis. However, it is important to acknowledge the presence of confounding factors and limitations in our study. Further research is required to establish causation and assess the functional significance of these mutations. These findings provide a foundation for future investigations and the formulation of strategies aimed at controlling TB transmission.

Effective Reproduction Number of Smear-Positive Pulmonary Tuberculosis in Iran: A Registry-Based Study (2011-2021).

Tuberculosis (TB) remains a major public health issue in Iran, especially smear-positive pulmonary tuberculosis (SPPTB), due to its high transmission rate. Examining the effective reproduction number(Rt ) of SPPTB and patient characteristics is crucial for crafting targeted TB control measures. This study aimed to assess the Rt of SPPTB in Iran from 2011 to 2021 and profile SPPTB patient demographics, initial smear bacilli density, diagnosis delays, and spatial distribution. Study Design: This is a historical cohort study. A time-dependent method was used to estimate Rt , and monthly data from the national TB registry were scrutinized from 2011 to 2021. A decline was observed in SPPTB incidence rates of 50909 SPPTB cases in Iran from 2011 to 2021. Approximately 29.1% of the cases were diagnosed within a month, while 44.5% experienced a one to three-month delay in diagnosis. The analysis revealed substantial heterogeneity in TB transmission dynamics across various provinces of Iran. Provinces such as Sistan and Baluchestan, Golestan, Guilan, Khuzestan, Tehran, and Khorasan Razavi exhibited the highest effective reproduction numbers. Additionally, there was a decreasing trend in the effective reproduction numbers across all provinces from 2011 to 2020. Effective reproduction numbers declined in most provinces from 2011 to 2020 but increased moderately after the COVID-19 pandemic, highlighting the need for targeted public health interventions. Although SPPTB incidence rates are declining nationally, elevated incidence rates and effective reproduction numbers in regions such as Sistan and Baluchestan, Golestan, Guilan, Khuzestan, Tehran, and Khorasan Razavi signify the need for persistent TB management efforts in Iran.

Epidemiology and molecular characterization of Mycobacterium tuberculosis including a drug-resistant strain associated with mortality of Asian elephants in Nepal 2019–2022

Tuberculosis (TB) is an emerging threat to the survival of elephants in Nepal. We investigated the lung tissue samples from nine elephants that died from 2019 to 2022 in Nepal using culture, conventional PCR, and loop-mediated isothermal amplification (LAMP) and then performed genotyping of five PCR-positive isolates to understand the possible transmission dynamics of Mycobacterium tuberculosis (Mtb). Results showed that two-thirds (6/9) of elephants were confirmed to be infected from Mtb by LAMP, 5/9 by PCR, and 4/9 by culture. Genotyping of Mtb isolates showed that elephants were infected with the Indo-Oceanic and Beijing lineages including an isoniazid-resistant Beijing lineage. MIRU-VNTR-based phylogeny, gyrA, and katG sequencing showed the possibility of ongoing transmission of Indo-Oceanic lineages and likely transmission of the drug-resistant Beijing lineage from human to elephant. Implementation of comprehensive surveillance and preventive measures are urgently needed to address this zoonotic disease and protect elephants from TB in Nepal.

Mathematical analysis of a novel fractional order vaccination model for Tuberculosis incorporating susceptible class with underlying ailment

ABSTRACT Tuberculosis (TB) is a communicable, airborne infection caused by the bacillus Mycobacterium tuberculosis. Pulmonary tuberculosis (PTB) is the most common presentation, although infection can spread anywhere to cause extra-pulmonary tuberculosis (EPTB). In this paper, a novel fractional order mathematical model is designed for the transmission dynamics of tuberculosis. Uninfected vulnerable individuals are categorized into the following: susceptible with underline ailment and susceptible without underline ailment. The research seeks to qualitatively and quantitatively analyze the proposed model and suggests comprehensive intervention measures for the control of tuberculosis among individuals with underline ailment. Some of the major highlights from the numerical investigation points out that TB vaccination is key to reducing the spread of TB among individuals with underline ailment. Furthermore, efforts to step down the spread of TB through awareness campaigns could significantly reduce the burden of the disease among individuals with co-morbidity.

On the Role of Early Case Detection and Treatment Failure in Controlling Tuberculosis Transmission: A Mathematical Modeling Study

Tuberculosis (TB) remains a pressing global health concern, demanding urgent attention to mitigate its spread and impact. In this study, we present a rigorous mathematical model of TB transmission that incorporates early case detection and addresses the critical issue of treatment failure. Through the development of a system of nonlinear ordinary differential equations, we conduct comprehensive analyses to assess the dynamics of TB transmission and the efficacy of intervention strategies. Our findings underscore the urgent need for effective TB control measures. Mathematical analyses reveal that the model exhibits a TB-free equilibrium, which is globally asymptotically stable only if the control reproduction number falls below one. However, we identify a concerning phenomenon: the model demonstrates a forward bifurcation when the control reproduction number equals one, suggesting that the disease-free equilibrium loses its stability, while simultaneously, the stable unique endemic equilibrium begins to emerge. Moreover, sensitivity analysis highlights the complex interplay between case detection rates, treatment failure probabilities, and TB transmission dynamics. Contrary to expectations, increasing case detection rates and minimizing treatment failure probabilities may not consistently reduce the basic reproduction number or the size of the infected population. Instead, there exists a critical threshold for intervention effectiveness, beyond which TB transmission can be significantly curtailed. Biologically, this phenomenon may occur if there is no balance between case detection and treatment efforts. If treatment quality does not improve, then case detection will not have a significant impact, and in the worst case scenario, it can exacerbate the intervention’s negative effects. These findings underscore the urgency of implementing targeted intervention strategies to combat TB transmission effectively. Failure to meet the critical intervention threshold risks undermining TB elimination efforts and exacerbating the global TB burden. Through numerical simulations, we elucidate potential intervention scenarios necessary for achieving TB elimination goals in human populations. In conclusion, our study highlights the urgent imperative for coordinated action to control TB transmission effectively. By elucidating the dynamics of TB spread and intervention efficacy, we provide valuable insights to inform evidence-based policy decisions and accelerate progress towards TB elimination on a global scale.

Dynamical System for Tuberculosis Outbreak with Vaccination Treatment and Different Interventions on the Burden of Drug Resistance

Tuberculosis, a highly contagious and lethal infectious disease, remains a global health concern with challenging treatment options. To combat its widespread impact, prevention strategies, such as vaccination, are imperative. This research focuses on developing a mathematical model with the addition of a vaccination compartment to understand the dynamics of tuberculosis transmission with vaccination. Subsequently, the study proceeds to identify the equilibrium points and calculate the basic reproduction number (ℜ0). Following this, a comprehensive stability analysis is conducted, and a numerical simulation is executed to observe the population dynamics. Furthermore, parameter sensitivity analysis is undertaken to assess the extent to which these parameters impact ℜ0. Preliminary analysis shows that the modified model has a solution that remains in the non-negative and bounded region. Furthermore, model analysis reveals two equilibrium points, namely the disease-free equilibrium and the endemic equilibrium. It is established that the disease-free equilibrium exhibits local asymptotic stability when ℜ0 1. Remarkably, the numerical simulation aligns with the analytical findings, reinforcing the robustness of the results. Analysis of the sensitivity of the parameter to ℜ0 shows that the parameter of the proportion of susceptible population entering the vaccination class has a significant effect on the value of ℜ0. The parameter of proportion of susceptible population entering the vaccination class has a negative effect on the number of populations with infection.

Modeling infectious respiratory diseases considering fear effect and latent period

This paper introduces a fractional-order (FO) SEIR epidemic model for respiratory diseases considering a non-human class P(t) for pathogens to study the effects of fear and awareness programs on disease dynamics. Further, using the basic reproduction number ℛ0α, the criteria for the extinction or persistence of the disease is established. Also, the conditions for Hopf bifurcation are derived, considering both FO (α) and rate of pathogens η as the bifurcation parameters. In addition, a detailed numerical simulation is performed to substantiate our theoretical results. The study of transmission dynamics of Tuberculosis (TB), a particular example of respiratory disease, is carried out in reference to the United States (US). Finally, we have estimated model parameters with the help of actual TB data from the US and then predicted the TB dynamics and disease control. It is pointed out that the fractional order can reduce the complexity of the model and better predict the dynamics of TB in the US than the integer order.

Genomic and spatial analysis reveal the transmission dynamics of tuberculosis in areas with high incidence of Zhejiang, China: A prospective cohort study

In the mountainous, rural regions of eastern China, tuberculosis (TB) remains a formidable challenge; however, the long-term molecular epidemiological surveillance in these regions is limited. This study aimed to investigate molecular and spatial epidemiology of TB in two mountainous, rural counties of Zhejiang Province, China, from 2015 to 2021, to elucidate the recent transmission and drug-resistance profiles. The predominant Lineage 2 (L2) Beijing family accounted for 80.1% of total 532 sequenced Mycobacterium tuberculosis (Mtb) strains, showing consistent prevalence over seven years. Gene mutations associated with drug resistance were identified in 19.4% (103/532) of strains, including 47 rifampicin or isoniazid-resistant strains, eight multi-drug-resistant (MDR) strains, and five pre-extensively drug-resistant (pre-XDR) strains. Genomic clustering revealed 53 distinct clusters with an overall transmission clustering rate of 23.9% (127/532). Patients with a history of retreatment and those infected with L2 strains had a higher risk of recent transmission. Spatial and epidemiological analysis unveiled significant transmission hotspots, especially in densely populated urban areas, involving various public places such as medical institutions, farmlands, markets, and cardrooms. The study emphasizes the pivotal role of Beijing strains and urban-based TB transmission in the western mountainous regions in Zhejiang, highlighting the urgent requirement for specific interventions to mitigate the impact of TB in these unique communities.

Modeling the Transmission Dynamics of Tuberculosis in Humans

Tuberculosis (TB) is a major threat to human health particularly in most of developing countries. In this article, we formulate and analyze a deterministic model for the transmission dynamics of pulmonary and extra-pulmonary tuberculosis. The next generation method is employed to find the basic reproduction number R0 which helps to determine whether TB clears or persists in the human population. Global stability of model equilibria is done through Lyapunov functions whereas the normalized forward sensitivity index method is adopted to determine parameters that drive tuberculosis. Analysis shows that both TB free and endemic equilibria exist. The TB free equilibrium is globally asymptotically stable whenever the basic reproduction number R0 &lt; 1 whereas the endemic equilibrium is globally asymptotically stable whenever R0 &gt; 1. Sensitivity analysis shows that the TB infection rate, the fraction of individuals who progress to pulmonary tuberculosis and its induced death drive TB. Numerical results indicate that when there are no interventions, susceptible humans decline significantly with time until when they are attracted to the steady state whereas latently infected, pulmonary and extra-pulmonary TB individuals increase until when they settle at the equilibrium states supporting the analytical results for existence of the endemic equilibrium. In light of these findings, we recommend treating humans infected with pulmonary TB who are carriers of the disease.

Causes of Backward Bifurcation in a Tuberculosis-Schistosomiasis Co-infection Dynamics

To obtain a thorough understanding of the influence of schistosomiasis infections on the transmission dynamics of tuberculosis, a deterministic mathematical model for the transmission dynamics of tuberculosis (TB) co-infection with schistosomiasis is created and examined. The aim of the research is to examine the reasons behind the backward bifurcation in the co-infection dynamics of tuberculosis and schistosomiasis. The backward bifurcation phenomena can be caused by the following parameters, according to the model's analysis (when the associated reproduction number is less than one), other than the well established route of exogeneous re-infection of latently infected TB individuals, the relative rates at which humans with latent schistosomiasis ($\eta_1$) and active schistosomiasis ($\eta_2$) are infected with TB, respectively, the lowered rate of reinfection with schistosomiasis ($\psi$), the fraction of individuals who experience fast progression to active TB ($p$), the adjustment parameter which accounts for the increased probability of infectiousness of humans with active TB and latent schistosomiasis ($\Pi_1$), the treatment rate of people infected with active TB exposed to schistosomiasis ($\zeta_{T1}$) and the rate of progression to active TB and exposed to schistosomiasis to active TB and active schistosomiasis ($\sigma$).