Transmission Dynamics Of Tuberculosis Research Articles

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 < 1 whereas the endemic equilibrium is globally asymptotically stable whenever R0 > 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 ($\sigma$).

A caputo fractional-order model of tuberculosis incorporating enlightenment and therapy using the Laplace-Adomian decomposition method

ABSTRACT In this study, we used a deterministic model to investigate tuberculosis transmission dynamics while considering control measures. We analyzed four compartmental models representing susceptible, latent, infected, and recovered populations. To assess the potential spread of the disease, we calculated the basic reproduction number using the next-generation matrix after establishing a disease-free equilibrium. Additionally, we explored the endemic equilibrium, as well as local and global stabilities. To obtain numerical solutions, we employed the Laplace-Adomian decomposition method. For constructing the model, we utilized Maple 18 software and varied the order (0 < ψ < 1) to examine the impact of enlightenment and therapy. Graphical representations were used to analyze the effects of non-integer order Caputo derivative parameters on the susceptible, latent, infected, and recovered populations over time. Our detailed discussion highlights the crucial role of mathematical models based on Caputo fractional derivatives in effectively controlling and eradicating tuberculosis from society. These findings contribute valuable insights to inform strategies for combating the disease and promoting public health initiatives.

Whole Genome Sequence-Based Analyses of Drug Resistance Characteristics, Genetic Diversity, and Transmission Dynamics of Drug-Resistant Mycobacterium tuberculosis in Urumqi City.

This study aims to analyze the drug resistance spectrum, genetic diversity, and transmission dynamics to provide a basis for the prevention and control of drug-resistant (DR) tuberculosis (TB) epidemics. This retrospective study is based on routine national drug resistance surveillance. The demographic, epidemiological, and clinical information on DR-TB patients from 2016 to 2021 was collected and used for phenotypic drug susceptibility testing and whole-genome sequencing. It was indicated that L2.2.1 was the dominant lineage in Urumqi. The drug resistance spectrum in Urumqi was narrow, which means more drug combinations can be used for clinical treatment. Furthermore, mutations identification of drug-resistance gene katG, rpoB, embA/B, rrs, rpsL, eis, gyrA/B, folC and tryA are important for clinical drug use. However, mutations in cross-resistance genes rrs have limited guidance for clinical selection of KM, CPM and AK. Moreover, there is an increased risk of cluster transmission of DR-TB, and the difference in clustering rate among L2, L3, and L4 was not statistically significant (χ2 = 2.6410, p = 0.2670). In the Urumqi, DR-TB has a complex prevalence state, a narrow drug resistance spectrum, and a high clustering rate and burden of drug resistance. To reduce the burden of DR-TB, related research should be strengthened, and the development of prevention, control, and treatment strategies should be accelerated.

Transmission dynamics of drug-resistant tuberculosis in Ningbo, China: an epidemiological and genomic analysis.

Tuberculosis (TB), particularly drug-resistant TB (DR-TB), remains a significant public health concern in Ningbo, China. Understanding its molecular epidemiology and spatial distribution is paramount for effective control. From December 24, 2020, to March 12, 2023, we collected clinical Mycobacterium tuberculosis (MTB) strains in Ningbo, with whole-genome sequencing performed on 130 MTB strains. We analyzed DR-related gene mutations, conducted phylogenetic and phylodynamic analyses, identified recent transmission clusters, and assessed spatial distribution. Among 130 DR-TB cases, 41% were MDR-TB, 36% pre-XDR-TB, 19% RR-TB, and 3% HR-TB. The phylogenetic tree showed that 90% of strains were Lineage 2 (Beijing genotype), while remaining 10% were Lineage 4 (Euro-American genotype). The spatial analysis identified hotspots of DR-TB in Ningbo's northern region, particularly in traditional urban centers. 31 (24%) of the DR-TB cases were grouped into 7 recent transmission clusters with a large outbreak cluster containing 15 pre-XDR-TB patients. Epidemiological analyses suggested a higher risk of recent DR-TB transmission among young adult patients who frequently visited Internet cafes, game rooms, and factories. Our study provides comprehensive insights into the epidemiology and genetics of DR-TB in Ningbo. The presence of genomic clusters highlights recent transmission events, indicating the need for targeted interventions. These findings are vital for informing TB control strategies in Ningbo and similar settings.

A mathematical model based on ABC fractional order for TB transmission with treatment interruptions in case of Bule Hora town, Ethiopia

In this study, we introduce a novel fractional-order model enriched with the Atangana-Baleanu-Caputo derivative to explore the dynamics of TB transmission in developing nations, where tuberculosis (TB) remains a pressing public health concern requiring urgent attention. We outline the methodology employed, emphasizing key aspects such as solution existence, uniqueness, Hyers-Ulam stability, and numerical simulations. Equilibrium points of the system, including the Disease-Free Equilibrium (DFE) and the Endemic Equilibrium (EE), are revealed through adopted mathematical manupulations. Following rigorous numerical simulations employing the Euler approach and a meticulously crafted scheme, the study illustrates compartmental solutions across a spectrum of fractional orders. This approach provides a comprehensive understanding of the model’s behavior and its responsiveness to different parameter configurations. Remarkably, as the fractional order tends towards one, our findings align closely with those of traditional integer-order models, offering insightful parallels into the model’s dynamics. Additionally, our work emphasizes the pivotal role of vaccination as a preventive measure, elucidating its profound impact on reducing tuberculosis incidence within communities. The promotion of widespread access to TB vaccines emerges as a potent strategy in curtailing the disease’s prevalence, underscoring the significance of proactive vaccination initiatives. As conclusion, this study presents a comprehensive examination of TB dynamics through a fractional-order modeling approach. Our results pave the way for further exploration, including the investigation of alternative fractional-order derivatives and exploration of theoretical and numerical stability. These endeavors will enhance our understanding of TB dynamics and inform more effective strategies for disease control and prevention.

Dynamics and optimal control of tuberculosis model with the combined effects of vaccination, treatment and contaminated environments

&lt;abstract&gt;&lt;p&gt;Tuberculosis has affected human beings for thousands of years, and until today, tuberculosis still ranks third among 29 infectious diseases in China. However, most of the existing mathematical models consider a single factor, which is not conducive to the study of tuberculosis transmission dynamics. Therefore, this study considers the combined effects of vaccination, treatment, and contaminated environments on tuberculosis, and builds a new model with seven compartments of $ SVEITRW $ based on China's tuberculosis data. The study shows that when the basic reproduction number $ R_{0} $ is less than 1, the disease will eventually disappear, but when $ R_{0} $ is greater than 1, the disease may persist. In the numerical analysis part, we use Markov-chain Monte-Carlo method to obtain the optimal parameters of the model. Through the next generation matrix theory, we calculate that the $ R_{0} $ value of tuberculosis in China is $ 2.1102 $, that is, if not controlled, tuberculosis in China will not disappear over time. At the same time, through partial rank correlation coefficients, we find the most sensitive parameter to the basic reproduction number $ R_{0} $. On this basis, we combine the actual prevalence of tuberculosis in China, apply Pontryagin's maximum principle, and perform cost-effectiveness analysis to obtain the conditions required for optimal control. The analysis shows that four control strategies could effectively reduce the prevalence of TB, and simultaneously controlling $ u_{2}, u_{3}, u_{4} $ is the most cost-effective control strategy.&lt;/p&gt;&lt;/abstract&gt;

Genomic analysis of lineage-specific transmission of multidrug resistance tuberculosis in China

ABSTRACT Objectives We investigated the genetic diversities and lineage-specific transmission dynamics of multidrug-resistant tuberculosis (MDR-TB), with the goal of determining the potential factors driving the MDR epidemics in China. Methods We curated a large nationwide Mycobacterium tuberculosis (M. tuberculosis) whole genome sequence data set, including 1313 MDR strains. We reconstructed the phylogeny and mapped the transmission networks of MDR-TB across China using Bayesian inference. To identify drug-resistance variants linked to enhanced transmissibility, we employed ordinary least-squares (OLS) regression analysis. Result The majority of MDR-TB strains in China belong to lineage 2.2.1. Transmission chain analysis has indicated that the repeated and frequent transmission of L2.2.1 plays a central role in the establishment of MDR epidemic in China, but no occurrence of a large predominant MDR outbreak was detected. Using OLS regression, the most common single nucleotide polymorphisms (SNPs) associated with resistance to isoniazid (katG_p.Ser315Thr and katG_p.Ser315Asn) and rifampicin (rpoB_p.Ser450Leu, rpoB_p.His445Tyr, rpoB_p.His445Arg, rpoB_p.His445Asp, and rpoB_p.His445Asn) were more likely to be found in L2 clustered strains. Several putative compensatory mutations in rpoA, rpoC, and katG were significantly associated with clustering. The eastern, central, and southern regions of China had a high level of connectivity for the migration of L2 MDR strains throughout the country. The skyline plot showed distinct population size expansion dynamics for MDR-TB lineages in China. Conclusion MDR-TB epidemic in China is predominantly driven by the spread of highly transmissible Beijing strains. A range of drug-resistance mutations of L2 MDR-TB strains displayed minimal fitness costs and may facilitate their transmission.

Genomic transmission clusters and circulating lineages of Mycobacterium tuberculosis among refugees residing in refugee camps in Ethiopia

BackgroundUnderstanding the transmission dynamics of Mycobacterium tuberculosis (Mtb) could benefit the design of tuberculosis (TB) prevention and control strategies for refugee populations. Whole Genome Sequencing (WGS) has not yet been used to document the Mtb transmission dynamics among refugees in Ethiopia. We applied WGS to accurately identify transmission clusters and Mtb lineages among TB cases in refugee camps in Ethiopia. Method and designWe conducted a cross-sectional study of 610 refugees in refugee camps in Ethiopia presenting with symptoms of TB. WGS data of 67 isolates was analyzed using the Maximum Accessible Genome for Mtb Analysis (MAGMA) pipeline; iTol and FigTree were used to visualize phylogenetic trees, lineages, and the presence of transmission clusters. ResultsMtb culture-positive refugees originated from South Sudan (52/67, 77.6%), Somalia (9/67, 13.4%). Eritrea (4/67, 6%), and Sudan (2/67, 3%). The majority (52, 77.6%) of the isolates belonged to Mtb lineage (L) 3, and one L9 was identified from a Somalian refugee. The vast majority (82%) of the isolates were pan-susceptible Mtb, and none were multi-drug-resistant (MDR)-TB. Based on the 5-single nucleotide polymorphisms cutoff, we identified eight potential transmission clusters containing 23.9% of the isolates. Contact investigation confirmed epidemiological links with either family or social interaction within the refugee camps or with neighboring refugee camps. ConclusionFour lineages (L1, L3, L4, and L9) were identified, with the majority of strains being L3, reflecting the Mtb L3 dominance in South Sudan, where the majority of refugees originated from. Recent transmission among refugees was relatively low (24%), likely due to the short study period. The improved understanding of the Mtb transmission dynamics using WGS in refugee camps could assist in designing effective TB control programs for refugees.

A STOCHASTIC DIFFERENTIAL EQUATION (SDE) BASED MODEL FOR THE SPREAD OF TUBERCULOSIS

Understanding dynamics of an infectious disease helps in designing appropriate strategies for containing its spread in a population. In this work, a deterministic and stochastic model of the transmission dynamics of Tuberculosis is developed and analyzed. The models involve the Susceptible, Exposed, Infectious and Recovered individuals. We computed the basic reproduction number and showed that for, the disease-free equilibrium is globally asymptotically stable. The resulting deterministic model was transformed into an equivalent stochastic model resulting in stochastic differential equation. The drift coefficient, the covariance matrix and the diffusion matrix were determined using the method proposed by Allen et al. (2008).

Mycobacterium tuberculosis epidemiology in Oman: whole-genome sequencing uncovers transmission pathways.

Tuberculosis (TB) originating from expatriates that hail from high TB-burden countries is hypothesized to play a role in continued TB transmission in Oman. Here, we used whole-genome sequencing (WGS) to assess national TB transmission dynamics. The annual incidence per 100,000 population per year was calculated for nationals and expatriates. A convenience sample of Mycobacterium tuberculosis (MTB) isolates from 2018 to 2019 was sequenced and analyzed with publicly available TB sequences from Bangladesh, Tanzania, the Philippines, India, and Pakistan. Relatedness was assessed by generating core-genome single nucleotide polymorphism (SNP) distances. The incidence of TB was five cases per 100,000 persons in 2018 and seven cases per 100,000 persons in 2020 (R2 = 0.34, P = 0.60). Incidence among nationals was 3.9 per 100,000 persons in 2018 and 3.5 per 100,000 persons in 2020 (R2 = 0.20, P = 0.70), and incidence among expatriates was 7.2 per 100,000 persons in 2018 and 12.7 per 100,000 persons in 2020 (R2 = 0.74, P = 0.34). Sixty-eight local MTB isolates were sequenced and analyzed with 393 global isolates. Isolates belonged to nine distinct spoligotypes. Two isolates, originating from an expatriate and an Omani national, were grouped into a WGS-based cluster (SNP distance < 12), which was corroborated by an epidemiological investigation. Relatedness of local and global isolates (SNP distance < 100) was also seen. The relatedness between MTB strains in Oman and those in expatriate countries of origin can aid inform TB control policy. Our results provide evidence that WGS can complement epidemiological analysis to achieve the End TB strategy goal in Oman. IMPORTANCE Tuberculosis (TB) incidence in Oman remains above national program control targets. TB transmission originating from expatriates from high TB-burden countries has been hypothesized to play a role. We used whole-genome sequencing (WGS) to assess TB transmission dynamics between expatriates and Omani nationals to inform TB control efforts. Available Mycobacterium tuberculosis isolates from 2018 to 2019 underwent WGS and analysis with publicly available TB sequences from Bangladesh, the Philippines, India, and Pakistan to assess for genetic relatedness. Our analysis revealed evidence of previously unrecognized transmission between an expatriate and an Omani national, which was corroborated by epidemiological investigation. Analysis of local and global isolates revealed evidence of distant relatedness between local and global isolates. Our results provide evidence that WGS can complement classic public health surveillance to inform targeted interventions to achieve the End TB strategy goal in Oman.

A fractional-order tuberculosis model with efficient and cost-effective optimal control interventions

This study is concerned with applying fractional calculus in modelling tuberculosis (TB) transmission dynamics. A new six-dimensional fractional-order mathematical model in the sense of the Caputo derivative operator is formulated to capture memory effects in the spread process of tuberculosis. Some key features such as vaccination, forces of TB infection, and exogenous re-infection by two actively infectious classes are considered. Banach fixed point theory is employed to prove the existence and uniqueness of a solution for the fractional-order model. Equilibrium points and effective reproduction number of the model are determined. Analysis reveals that the model exhibits backward bifurcation where stable TB-free and TB-present equilibrium points co-exist when the effective reproduction number is below unity. Some sensitive parameters of the model are identified to help design intervention measures against the disease. Hence, four time-dependent controls, namely advocacy effort against infection and re-infection, vaccination control, prophylaxis against latent infection, and treatment control, are considered to form a fractional-order optimal control model. The controls are characterized using Pontryagin’s maximum principle. Efficiency and cost-effectiveness assessments are conducted to quantify the most efficient and cost-effective intervention plan to minimize TB spread in the population. Behaviours of the fractional-order TB model at varying values of the order of the Caputo derivative are extensively explored to show memory effects in the transmission dynamics of the disease.

Global behaviour of a tuberculosis model with difference in awareness and treatment adherence levels

The treatment adherence level of tuberculosis patients is critically related to their awareness level about tuberculosis and anti-tuberculosis therapy. Tuberculosis is always spreading if the community has low level of awareness. In this article a mathematical model describing the impact of treatment adherence and difference in awareness level on tuberculosis transmission dynamics is investigated. It is assumed that the detected infectious individuals with low level of awareness after treatment may enter either the recovered compartment due to treatment adherence or the latent compartment due to lack of adherence. We compute the epidemic threshold parameter, Rb, to study its role on the dynamics and stability of the proposed model. Mathematical analyses of this model reveal that treatment nonadherence of individuals with active tuberculosis may lead to relapse. Analysis of the epidemic threshold parameter shows that increase in awareness level, treatment and adherence to medication has a positive effect on tuberculosis control. Whereas, decrease in effective contact rate and endogenous reactivation rate help to reduce tuberculosis infection. The numerical simulations of the model illustrate the feasibility of our analytical conclusions.

Comparative whole-genome sequence analysis of Mycobacterium tuberculosis isolated from pulmonary tuberculosis and tuberculous lymphadenitis patients in Northwest Ethiopia.

Tuberculosis (TB), caused by the Mycobacterium tuberculosis complex (MTBC), is a chronic infectious disease with both pulmonary and extrapulmonary forms. This study set out to investigate and compare the genomic diversity and transmission dynamics of Mycobacterium tuberculosis (Mtb) isolates obtained from tuberculous lymphadenitis (TBLN) and pulmonary TB (PTB) cases in Northwest Ethiopia. A facility-based cross-sectional study was conducted using two groups of samples collected between February 2021 and June 2022 (Group 1) and between June 2020 and June 2022 (Group 2) in Northwest Ethiopia. Deoxyribonucleic acid (DNA) was extracted from 200 heat-inactivated Mtb isolates. Whole-genome sequencing (WGS) was performed from 161 isolates having ≥1 ng DNA/μl using Illumina NovaSeq 6000 technology. From the total 161 isolates sequenced, 146 Mtb isolates were successfully genotyped into three lineages (L) and 18 sub-lineages. The Euro-American (EA, L4) lineage was the prevailing (n = 100; 68.5%) followed by Central Asian (CAS, L3, n = 43; 25.3%) and then L7 (n = 3; 2.05%). The L4.2.2.ETH sub-lineage accounted for 19.9%, while Haarlem estimated at 13.7%. The phylogenetic tree revealed distinct Mtb clusters between PTB and TBLN isolates even though there was no difference at lineages and sub-lineages levels. The clustering rate (CR) and recent transmission index (RTI) for PTB were 30 and 15%, respectively. Similarly, the CR and RTI for TBLN were 31.1 and 18 %, respectively. PTB and TBLN isolates showed no Mtb lineages and sub-lineages difference. However, at the threshold of five allelic distances, Mtb isolates obtained from PTB and TBLN form distinct complexes in the phylogenetic tree, which indicates the presence of Mtb genomic variation among the two clinical forms. The high rate of clustering and RTI among TBLN implied that TBLN was likely the result of recent transmission and/or reactivation from short latency. Hence, the high incidence rate of TBLN in the Amhara region could be the result of Mtb genomic diversity and rapid clinical progression from primary infection and/or short latency. To validate this conclusion, a similar community-based study with a large sample size and better sampling technique is highly desirable. Additionally, analysis of genomic variants other than phylogenetic informative regions could give insightful information. Combined analysis of the host and the pathogen genome (GXG) together with environmental (GxGxE) factors could give comprehensive co-evolutionary information.

Genotypic and spatial analysis of transmission dynamics of tuberculosis in Shanghai, China: a 10-year prospective population-based surveillance study

With improved tuberculosis (TB) control programs, the incidence of TB in China declined dramatically over the past few decades, but recently the rate of decrease has slowed, especially in large cities such as Shanghai. To help formulate strategies to further reduce TB incidence, we performed a 10-year study in Songjiang, a district of Shanghai, to delineate the characteristics, transmission patterns, and dynamic changes of the local TB burden. We conducted a population-based study of culture-positive pulmonary TB patients diagnosed in Songjiang during 2011-2020. Genomic clusters were defined with a threshold distance of 12-single-nucleotide-polymorphisms based on whole-genome sequencing, and risk factors for clustering were identified by logistic regression. Transmission inference was performed using phybreak. The distances between the residences of patients were compared to the genomic distances of their isolates. Spatial patient hotspots were defined with kernel density estimation. Of 2212 enrolled patients, 74.7% (1652/2212) were internal migrants. The clustering rate (25.2%, 558/2212) and spatial concentrations of clustered and unclustered patients were unchanged over the study period. Migrants had significantly higher TB rates but less clustering than residents. Clustering was highest in male migrants, younger patients and both residents and migrants employed in physical labor. Only 22.1% of transmission events occurred between residents and migrants, with residents more likely to transmit to migrants. The clustering risk decreased rapidly with increasing distances between patient residences, but more than half of clustered patient pairs lived ≥5km apart. Epidemiologic links were identified for only 15.6% of clustered patients, mostly in close contacts. Although some of the TB in Songjiang's migrant population is caused by strains brought by infected migrants, local, recent transmission is an important driver of the TB burden. These results suggest that further reductions in TB incidence require novel strategies to detect TB early and interrupt urban transmission. Shanghai Municipal Science and Technology Major Project (ZD2021CY001), National Natural Science Foundation of China (82272376), National Research Council of Science and Technology Major Project of China (2017ZX10201302-006).

The influence of ambient air pollution on the transmission of tuberculosis in Jiangsu, China.

In this paper, based on the statistical data, we investigate the effects of long-term exposure to ambient particulate air pollution on the transmission dynamics of tuberculosis (TB) in Jiangsu, China by studying the threshold dynamics of the TB epidemic model via the statistical data analytically and numerically. The basic reproduction number reveals that TB in Jiangsu, China is an endemic disease and will persist for a long time. And the numerical results show that, in order to control the TB in Jiangsu effectively, we must decrease the depuration coefficient of PM10 in the body, the proportion of TB symptomatic infectious by direct transmission, the reactivation rate of the pre-symptomatic infectious and the effect coefficient of PM10 and MTB inhaled of TB transmission, and increase the uptake coefficient, the recovery rate of the symptomatic/pre-symptomatic infectious and the influence coefficient of PM10 on the body of mortality. Our study shows that PM10 is closely related to the incidence of TB, and the effective control efforts are suggested to focus on increasing close-contact distance and wearing protective mask to decrease the influence of PM10 on the TB transmission, which may shed a new light on understanding the environmental drivers to TB.

On mathematical modeling of fractional-order stochastic for tuberculosis transmission dynamics

Tuberculosis remains one of the most dangerous diseases globally and has affected many people in Sub-Saharan Africa. In this paper, a fractional stochastic model of tuberculosis disease was formulated and analyzed. The existence and uniqueness of solutions are presented in the new approach far from the deterministic fractional operators. We carry out numerical simulations of the model using three fractional operators. Our numerical results suggest that the Caputo–Fabrizio operator has a more random effect among the three different operators than the Atangana–Baleanu and the Caputo operators. Further, it is envisaged that the fractional-order derivatives significantly impact the dynamics of the disease.

Transition dynamics between a novel coinfection model of fractional-order for COVID-19 and tuberculosis via a treatment mechanism.

In this paper, a fractional-order coinfection model for the transmission dynamics of COVID-19 and tuberculosis is presented. The positivity and boundedness of the proposed coinfection model are derived. The equilibria and basic reproduction number of the COVID-19 sub-model, Tuberculosis sub-model, and COVID-19 and Tuberculosis coinfection model are derived. The local and global stability of both the COVID-19 and Tuberculosis sub-models are discussed. The equilibria of the coinfection model are locally asymptotically stable under certain conditions. Later, the impact of COVID-19 on TB and TB on COVID-19 is analyzed. Finally, the numerical simulation is carried out to assess the effect of various biological parameters in the transmission dynamics of COVID-19 and Tuberculosis coinfection.

Treatment strategies for the latent tuberculosis infections.

This study investigates the dynamics of tuberculosis transmission through mathematical modeling, incorporating exogenous reinfections and different treatment approaches for latent tuberculosis infections. We examine three types of treatment rates: saturated, unsaturated, and mass screening-then-treatment. Our results reveal that both saturated treatment and mass screening-then-treatment can lead to a backward bifurcation, while unsaturated treatment does not. To determine the global dynamics of the models, we employ a persistent approach that avoids classifying the steady mode. By applying the models to China, we demonstrate that the data favors the use of unsaturated treatment. If unsaturated treatment is not feasible, the optimal strategy is to screen high-risk groups, identify LTBIs, and administer unsaturated treatment. Saturated treatments are not recommended.