Transmission Dynamics Of Tuberculosis Research Articles

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.

Tuberculosis in Prisons: Importance of Considering the Clustering in the Analysis of Cross-Sectional Studies

The level of clustering and the adjustment by cluster-robust standard errors have yet to be widely considered and reported in cross-sectional studies of tuberculosis (TB) in prisons. In two cross-sectional studies of people deprived of liberty (PDL) in Medellin, we evaluated the impact of adjustment versus failure to adjust by clustering on prevalence ratio (PR) and 95% confidence interval (CI). We used log-binomial regression, Poisson regression, generalized estimating equations (GEE), and mixed-effects regression models. We used cluster-robust standard errors and bias-corrected standard errors. The odds ratio (OR) was 20% higher than the PR when the TB prevalence was >10% in at least one of the exposure factors. When there are three levels of clusters (city, prison, and courtyard), the cluster that had the strongest effect was the courtyard, and the 95% CI estimated with GEE and mixed-effect models were narrower than those estimated with Poisson and binomial models. Exposure factors lost their significance when we used bias-corrected standard errors due to the smaller number of clusters. Tuberculosis transmission dynamics in prisons dictate a strong cluster effect that needs to be considered and adjusted for. The omission of cluster structure and bias-corrected by the small number of clusters can lead to wrong inferences.

Is bovine density and ownership associated with human tuberculosis in India?

Zoonotic tuberculosis in humans is caused by infection with bacteria of the Mycobacterium tuberculosis complex acquired from animals, most commonly cattle. India has the highest burden of human tuberculosis in the world and any zoonotic risk posed by tuberculosis in bovines needs to be managed at the source of infection as a part of efforts to end human tuberculosis. Zoonotic tuberculosis in humans can be severe and is clinically indistinguishable from non-zoonotic tuberculosis. As a consequence, zoonotic tuberculosis remains under-recognised and the significance of its contribution to human tuberculosis is poorly understood. This study aimed to explore any association between bovine density, bovine ownership, and human tuberculosis reporting in India using self-reported tuberculosis data in households and officially reported tuberculosis cases while controlling for common confounders for human tuberculosis. We find an association between human tuberculosis reporting, bovine density and bovine ownership in India. Buffalo density was significantly associated with an increased risk of self-reported tuberculosis in households (odds ratio (OR) = 1.23 (95% credible interval (CI): 1.10-1.39) at household level; incidence rate ratio (IRR) = 1.17 (95% CI: 1.04-1.33) at district level), while cattle density (OR = 0.80, 95% CI: 0.71-0.89; IRR = 0.78, 95% CI: 0.70-0.87) and ownership of bovines in households (OR = 0.94, 95% CI: 0.9-0.99; IRR = 0.67, 95% CI: 0.57-0.79) had a protective association with tuberculosis reporting. It is unclear whether this relates to differences in tuberculosis transmission dynamics, or perhaps an association between bovines and other unexplored confounders for tuberculosis reporting in humans. Our study highlights a need for structured surveillance to estimate the prevalence of tuberculosis in cattle and buffaloes, characterisation of Mycobacterium tuberculosis complex species present in bovines and transmission analyses at the human-animal interface to better assess the burden and risk pathways of zoonotic tuberculosis in India.

Sensitivity and Stability Analysis of Tuberculosis Disease with Infectious Latent

Tuberculosis (TB) is a dangerous contagious disease which can even lead to death if no control measure is applied. The disease is caused by mycobacterium which generally affects lungs and other related organs such as lymph gland, intestine, kidneys, uterus, bone and brain. The spread of TB occurs via the bacteria contaminated air which is inhaled into the lungs. Cough, chest pain, shortness of breath, appetite loss, weight loss, fever, cold and fatigue are some of the symptoms of TB. However, we proposed a mathematical model to investigate the transmission dynamics of tuberculosis and it is investigated analytically that the endemic equilibrium point is stable with the help of Routh-Hurwitz criteria. The sensitivity analysis shows that there would be an epidemic if and only if β≈β^1, where β^1≤0.1. Finally, using Matlab, it is shown that the disease free equilibrium is unstable which the endemic equilibrium becomes stable beyond 60 days. In addition, the recovered population increased rapidly while the exposed population decreased steeply in the disease-free equilibrium. It is an indication that there will be no outbreak of the tuberculosis infection. Besides, an increased in the effective contact rate increases both the infected population and recovered population. It is equally inferred that the recovered population do not show a trend pattern as ∝ increases while the susceptible and infected populations increased and decreased respectively as ∝ is increased. The recovered population showed no response pattern for ∝ since recovered individuals do not obtain permanent immunity.

The Evolution and Transmission Dynamics of Multidrug-Resistant Tuberculosis in an Isolated High-Plateau Population of Tibet, China.

On the Tibetan Plateau, most tuberculosis is caused by indigenous Mycobacterium tuberculosis strains with a monophyletic structure and high-level drug resistance. This study investigated the emergence, evolution, and transmission dynamics of multidrug-resistant tuberculosis (MDR-TB) in Tibet. The whole-genome sequences of 576 clinical strains from Tibet were analyzed with the TB-profiler tool to identify drug-resistance mutations. The evolution of the drug resistance was then inferred based on maximum-likelihood phylogeny and dated trees that traced the serial acquisition of mutations conferring resistance to different drugs. Among the 576 clinical M. tuberculosis strains, 346 (60.1%) carried at least 1 resistance-conferring mutation and 231 (40.1%) were MDR-TB. Using a pairwise distance of 50 single nucleotide polymorphisms (SNPs), most strains (89.9%, 518/576) were phylogenetically separated into 50 long-term transmission clusters. Eleven large drug-resistant clusters contained 76.1% (176/231) of the local multidrug-resistant strains. A total of 85.2% of the isoniazid-resistant strains were highly transmitted with an average of 6.6 cases per cluster, of which most shared the mutation KatG Ser315Thr. A lower proportion (71.6%) of multidrug-resistant strains were transmitted, with an average cluster size of 2.9 cases. The isoniazid-resistant clusters appear to have undergone substantial bacterial population growth in the 1970s to 1990s and then subsequently accumulated multiple rifampicin-resistance mutations and caused the current local MDR-TB burden. These findings highlight the importance of detecting and curing isoniazid-resistant strains to prevent the emergence of endemic MDR-TB. IMPORTANCE Emerging isoniazid resistance in the 1970s allowed M. tuberculosis strains to spread and form into large multidrug-resistant tuberculosis clusters in the isolated plateau of Tibet, China. The epidemic was driven by the high risk of transmission as well as the potential of acquiring further drug resistance from isoniazid-resistant strains. Eleven large drug-resistant clusters consisted of the majority of local multidrug-resistant cases. Among the clusters, isoniazid resistance overwhelmingly evolved before all the other resistance types. A large bacterial population growth of isoniazid-resistant clusters occurred between 1970s and 1990s, which subsequently accumulated rifampicin-resistance-conferring mutations in parallel and accounted for the local multidrug-resistant tuberculosis burden. The results of our study indicate that it may be possible to restrict MDR-TB evolution and dissemination by prioritizing screening for isoniazid (INH)-resistant TB strains before they become MDR-TB and by adopting measures that can limit their transmission.

New insights on tuberculosis transmission dynamics and drug susceptibility profiles among the prison population in Southern Brazil based on whole-genome sequencing.

The rate of tuberculosis (TB) infection among the prison population (PP) in Brazil is 28 times higher than that in the general population, and prison environment favors the spread of TB. To describe TB transmission dynamics and drug resistance profiles in PP using whole-genome sequencing (WGS). This was a retrospective study of Mycobacterium tuberculosis cultivated from people incarcerated in 55 prisons between 2016 and 2019; only one isolate per prisoner was included. Information about movement from one prison to another was tracked. Clinical information was collected, and WGS was performed on isolates obtained at the time of TB diagnosis. Among 134 prisoners included in the study, we detected 16 clusters with a total of 58 (43%) cases of M. tuberculosis. Clusters ranged from two to seven isolates with five or fewer single nucleotide polymorphism (SNP) differences, suggesting a recent transmission. Six (4.4%) isolates were resistant to at least one anti-TB drug. Two of these clustered together and showed resistance to rifampicin, isoniazid, and fluoroquinolones, with 100% concordance between WGS and phenotypic drug-susceptibility testing. Prisoners with clustered isolates had a high amount of movement between prisons (two to eight moves) during the study period. WGS demonstrated the recent transmission of TB within prisons in Brazil. The high movement among prisoners seems to be related to the transmission of the same M. tuberculosis strain within the prison system. Screening for TB before and after the movement of prisoners using rapid molecular tests could play a role in reducing transmission.

Mathematical modelling and analysis of COVID-19 and tuberculosis transmission dynamics

In this paper, a mathematical model for assessing the impact of COVID-19 on tuberculosis disease is proposed and analysed. There are pieces of evidence that patients with Tuberculosis (TB) have more chances of developing the SARS-CoV-2 infection. The mathematical model is qualitatively and quantitatively analysed by using the theory of stability analysis. The dynamic system shows endemic equilibrium point which is stable when R0<1 and unstable when R0>1. The global stability of the endemic point is analysed by constructing the Lyapunov function. The dynamic stability also exhibits bifurcation behaviour. The optimal control theory is used to find an optimal solution to the problem in the mathematical model. The sensitivity analysis is performed to clarify the effective parameters which affect the reproduction number the most. Numerical simulation is carried out to assess the effect of various biological parameters in the dynamic of both tuberculosis and COVID-19 classes. Our simulation results show that the COVID-19 and TB infections can be mitigated by controlling the transmission rate γ.

Stability Analysis of Mathematical Modeling on the Spread of Tuberculosis Case Detection

In this study, a mathematical model on the transmission dynamics of tuberculosis was formulated and analyzed. The basic reproduction number ( ) for each model is calculated and determined using the next generation method and condition for elimination (disease free equilibrium) or persistence (endemic equilibrium) in a population. Stability analysis shows that disease free equilibrium is locally asymptotically stable whenever the reproduction is less than unity. Furthermore, tuberculosis case detection continued to persist whenever the reproduction number exceeds unity. However, the models consisting of system of first order nonlinear differential equations.

Dynamical aspects of a tuberculosis transmission model incorporating vaccination and time delay

To explore transmission dynamics of tuberculosis, a tuberculosis transmission model with vaccination and time delay is developed in current paper. Positivity and boundedness are analyzed. Local stability of tuberculosis-free equilibrium in respect of the time delay due to latent period of tuberculosis is analyzed and we have found threshold value of the time delay for the local stability of tuberculosis-free equilibrium. Then, local stability of tuberculosis-existence equilibrium following exhibition of Hopf bifurcation at the crucial value of the time delay due to latent period of tuberculosis is derived. It is shown that the developed model undergoes a Hopf bifurcation around the tuberculosis-existence when the time delay due to latent period of tuberculosis passes through the threshold value. Direction and stability of the Hopf bifurcation are investigated with the help of the normal form method and center manifold theory. Finally, numerical simulations are carried out in the justification of obtained analytical findings. The results obtained provide significant information for tuberculosis disease controlling.

A Mathematical Model of the Transmission Dynamics of Tuberculosis with Exogenous Reinfection in the Infection-Free State

A Mathematical Model of the Transmission Dynamics of Tuberculosis with Exogenous Reinfection in the Infection-Free State

The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities.

Social network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies. We assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social network structure and characteristics of first-degree contacts (sex, human immunodeficiency virus [HIV] status, tuberculosis infection) were associated with revalent tuberculosis infection (positive tuberculin skin test [TST] result) after adjusting for individual-level risk factors (age, sex, HIV status, tuberculosis contact, wealth, occupation, and Bacillus Calmette-Guérin [BCG] vaccination) with targeted maximum likelihood estimation. Among 3 335 residents sampled for TST, 32% had a positive TST results and 4% reported a tuberculosis contact. The social network contained 15 328 first-degree contacts. Persons with the most network centrality (top 10%) (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.1]) and the most (top 10%) male contacts (1.5 [1.3-1.9]) had a higher risk of prevalent tuberculosis, than those in the remaining 90%. People with ≥1 contact with HIV (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.6]) and ≥2 contacts with tuberculosis infection were more likely to have tuberculosis themselves (2.6 [ 95% confidence interval: 2.2-2.9]). Social networks with higher centrality, more men, contacts with HIV, and tuberculosis infection were positively associated with tuberculosis infection. Tuberculosis transmission within measurable social networks may explain prevalent tuberculosis not associated with a household contact. Further study on network-informed tuberculosis case finding interventions is warranted.

Demographic Control Measure Implications of Tuberculosis Infection for Migrant Workers across Taiwan Regions.

A sharp increase in migrant workers has raised concerns for TB epidemics, yet optimal TB control strategies remain unclear in Taiwan regions. This study assessed intervention efforts on reducing tuberculosis (TB) infection among migrant workers. We performed large-scale data analyses and used them to develop a control-based migrant worker-associated susceptible–latently infected–infectious–recovered (SLTR) model. We used the SLTR model to assess potential intervention strategies such as social distancing, early screening, and directly observed treatment, short-course (DOTS) for TB transmission among migrant workers and locals in three major hotspot cities from 2018 to 2023. We showed that social distancing was the best single strategy, while the best dual measure was social distancing coupled with early screening. However, the effectiveness of the triple strategy was marginally (1–3%) better than that of the dual measure. Our study provides a mechanistic framework to facilitate understanding of TB transmission dynamics between locals and migrant workers and to recommend better prevention strategies in anticipation of achieving WHO’s milestones by the next decade. Our work has implications for migrant worker-associated TB infection prevention on a global scale and provides a knowledge base for exploring how outcomes can be best implemented by alternative control measure approaches.

Transmission Dynamics of Tuberculosis with Age-specific Disease Progression.

Demographic structure and latent phenomenon are two essential factors determining the rate of tuberculosis transmission. However, only a few mathematical models considered age structure coupling with disease stages of infectious individuals. This paper develops a system of delay partial differential equations to model tuberculosis transmission in a heterogeneous population. The system considers demographic structure coupling with the continuous development of disease stage, which is crucial for studying how aging affects tuberculosis dynamics and disease progression. Here, we determine the basic reproduction number, and several numerical simulations are used to investigate the influence of various progression rates on tuberculosis dynamics. Our results support that the aging effect on the disease progression rate contributes to tuberculosis permanence.

Asymptotic behavior of Tuberculosis between smokers and non-smokers

Tuberculosis (TB) is an ailment caused by Mycobacterium tuberculosis. So, by the continuous spread of TB, this study presents a new mathematical model of TB that investigates the impact of smoking and contact rate on the transmission dynamics of the disease in a population. The basic reproduction number R 0 , of the model, is computed by employing the next generation matrix approach and the dynamical behavior of the model is explored in detail. Mathematical analysis reveals that the disease-free equilibrium solution is globally asymptotically stable when the associated basic reproduction number is less than unity. It is further shown that the model has a unique endemic equilibrium point, which is proved to exist when R 0 > 1 . The global asymptotic stability of the unique endemic equilibrium, when the associated basic reproduction number exceeds unity, is investigated through numerical simulations. Sensitivity analysis is carried out to identify key parameters that have the greatest influence on the transmission dynamics of TB in the population. The sensitivity results show that the top four parameters of the model, that have the most influence on R 0 of the model are the recruitment rate of smokers into the population, contact rate, progression rate to latent TB stage, and recovery rate of infectious individuals, with other key parameters influencing the outcome of the other output responses. Numerical experiments are performed to support the analytical findings. Numerical simulation of the model shows that, if the contact rate α = 0 . 001 , then R 0 is estimated to be 0.4611, which shows that TB dies out of the population. It further shows that, if the contact rate α = 0 . 005 , R 0 is estimated to be 2.3058, which indicates that TB establishes itself in the population. We observed from the above results that the smoking habit should be discouraged in society to reduce the prevalence of TB in the population.

Emergence of multi-drug-resistant Mycobacterium tuberculosis in Niger: A snapshot based on whole-genome sequencing.

BackgroundAmong other West African countries experiencing the high endemicity of deadly tuberculosis, the situation in Niger is poorly evidenced by microbiological investigations.Methodology/Principal findingsThe study of 42 isolates of Mycobacterium tuberculosis from Niger by whole genome sequencing using Illumina iSeq technology yielded four M. tuberculosis lineages: Indo-Oceanic L1 (n = 1) (2.3%), East-Asian (n = 1) (2.3%), East-African Indian L3 (n = 2) (4.7%) and Euro-American L4 (n = 38) (90.4%). The sub-lineage L4.1.3 comprising 18 isolates (47.3%) was predominant, followed by the L4.6.2.2 sub-lineage (Cameroon genotype, n = 13 isolates) (34.2%). Investigating drug resistance profile for 12 antibiotics found 8/42 (19%) pan-susceptible isolates and 34/42 (81%) resistant isolates; with 40/42 (95.2%) isolates being susceptible to clofazimine-bedaquiline.Conclusions/SignificanceThese unprecedented data from Niger highlight the dynamics of tuberculosis transmission and drug resistance in Niger and may assist tuberculosis control in this country which continues to support a high burden of tuberculosis.

A diffusive tuberculosis model with early and late latent infections: New Lyapunov function approach to global stability

This paper formulates a diffusive tuberculosis (TB) model with early and late latent infections, vaccination and treatment that may more properly describe the slow and fast dynamics of TB transmission. We develop a new concise approach to determine the combination coefficients in the Lyapunov function candidate for the model and its time derivative in the case that both are the linear combinations of several Volterra-type functions, which highly simplifies the computations in global dynamical analysis for the nonlinear high-dimensional model. Based on the TB case data reported in China, the parameter values of the model are estimated. We further predict the TB prevalence trend in China. Sensitivity analysis for the control reproduction number and endemic equilibrium is conducted to seek some effective interventions that can significantly reduce initial TB transmission and lower TB prevalence levels in China. In the end, numerical simulations show that the bigger diffusive rates pick up the speeds of convergence to the equilibria of the model.

Characterizing tuberculosis transmission dynamics in high-burden urban and rural settings

Mycobacterium tuberculosis transmission dynamics in high-burden settings are poorly understood. Growing evidence suggests transmission may be characterized by extensive individual heterogeneity in secondary cases (i.e., superspreading), yet the degree and influence of such heterogeneity is largely unknown and unmeasured in high burden-settings. We conducted a prospective, population-based molecular epidemiology study of TB transmission in both an urban and rural setting of Botswana, one of the highest TB burden countries in the world. We used these empirical data to fit two mathematical models (urban and rural) that jointly quantified both the effective reproductive number, R, and the propensity for superspreading in each population. We found both urban and rural populations were characterized by a high degree of individual heterogeneity, however such heterogeneity disproportionately impacted the rural population: 99% of secondary transmission was attributed to only 19% of infectious cases in the rural population compared to 60% in the urban population and the median number of incident cases until the first outbreak of 30 cases was only 32 for the rural model compared to 791 in the urban model. These findings suggest individual heterogeneity plays a critical role shaping local TB epidemiology within subpopulations.

Mathematical Modeling and Analysis of TB and COVID-19 Coinfection

Tuberculosis (TB) and coronavirus (COVID-19) are both infectious diseases that globally continue affecting millions of people every year. They have similar symptoms such as cough, fever, and difficulty breathing but differ in incubation periods. This paper introduces a mathematical model for the transmission dynamics of TB and COVID-19 coinfection using a system of nonlinear ordinary differential equations. The well-posedness of the proposed coinfection model is then analytically studied by showing properties such as the existence, boundedness, and positivity of the solutions. The stability analysis of the equilibrium points of submodels is also discussed separately after computing the basic reproduction numbers. In each case, the disease-free equilibrium points of the submodels are proved to be both locally and globally stable if the reproduction numbers are less than unity. Besides, the coinfection disease-free equilibrium point is proved to be conditionally stable. The sensitivity and bifurcation analysis are also studied. Different simulation cases were performed to supplement the analytical results.

Drug-Resistant Characteristics, Genetic Diversity, and Transmission Dynamics of Rifampicin-Resistant Mycobacterium tuberculosis in Hunan, China, Revealed by Whole-Genome Sequencing.

ABSTRACTTo gain a deep insight into the additional drug-resistant profiles, genetic diversity, and transmission dynamics of rifampicin-resistant tuberculosis (RR-TB) circulating in Hunan province, drug susceptibility testing and whole-genome-sequencing were performed among RR-TB strains collected from Jan. 2013 to Jun. 2018 in Hunan province. A total of 124 RR-TB strains were recovered successfully and included into the final analysis. Lineage 2.2.1 was the dominant sublineage, accounting for 72.6% (90/124), followed by lineage 4.5 (11.3%, 14/124), lineage 4.4 (8.1%, 10/124), lineage 4.2 (6.5%, 8/124) and lineage 2.2.2 (1.6%, 2/124). Overall, 83.1% (103/124) and 3.2% (4/124) of RR-TB were MDR-TB and XDR-TB, respectively. Nearly 30% of RR-TB isolates were resistant to fluoroquinolones, and 26.6% (33/124) were pre-XDR-TB. Moreover, 30.6% (38/124) of RR-TB strains were identified as phenotypically resistance to pyrazinamide. Totally, 17 clusters containing 48 (38.7%, 48/124) RR-TB strains were identified, ranging in size from 2 to 10 isolates. No significant difference was detected in clustering rate between lineage 2 and lineage 4 (χ2 = 0.027, P = 0.870). Our study revealed the complexity of RR-TB strains circulating in Hunan province with complex additional drug-resistant profile and relatively higher clustering rates. Comprehensive information based on WGS should be used to guide the design of treatment regimens and tailor public interventions.IMPORTANCE Comprehensive information such as genetic background and drug-resistant profile of MTB strains could help to tailor public interventions. However, these data are limited in Hunan province, one of the provinces with high-TB burden in China. So, this study aimed to provide us with deep insight into the molecular epidemiology of RR-TB isolates circulating in Hunan province by combining phenotypic drug susceptibility testing and whole-genome sequencing. To our knowledge, this is the first study to use whole-genome sequencing data of RR-TB strains spanning more than 5 years for molecular epidemiology analysis in Hunan province, which allows us to identify genetic background information and clustered strains more accurately. Our study revealed the complexity of RR-TB strains circulating in Hunan province with complex additional drug-resistant profile and relatively higher clustering rates. Comprehensive information based on WGS should be used to guide the design of treatment regimens and tailor public interventions.