Bill and Melinda Gates Foundation.

BACKGROUND The End TB Strategy sets global goals of reducing TB incidence and mortality by 50% and 75% respectively by 2025. We assessed resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa. METHODS We examined intervention scenarios developed in consultation with country stakeholders, which scaled-up existing interventions to high but feasible coverage by 2025. Nine independent TB modelling groups collaborated to estimate policy outcomes, and we costed each scenario by synthesizing service utilization estimates, empirical cost data, and expert opinion on implementation strategies. We estimated health impact and resource implications for 2016–2035, including patient-incurred costs. To assess resource requirements and cost-effectiveness, we compared scenarios to a base case representing continued current practice. FINDINGS Incremental TB service costs differed by scenario and country, and in some cases more than doubled current funding needs. In general, expanding TB services substantially reduced patient-incurred costs; and in India and China this produced net cost-savings for most interventions under a societal perspective. In all countries, expanding TB care access produced substantial health gains. Compared to current practice, most intervention approaches appeared highly cost-effective when compared to conventional cost-effectiveness thresholds. INTERPRETATION Expanding TB services appears cost-effective for high-burden countries and could generate substantial health and economic benefits for patients, though funding needs challenge affordability. Further work is required to determine the optimal intervention mix for each country.

We have proposed and analyzed a nonlinear mathematical model for the spread of carrier dependent infectious diseases in a population with variable size structure including the role of vaccination. It is assumed that the susceptibles become infected by direct contact with infectives and/or by the carrier population present in the environment. The density of carrier population is assumed to be governed by a generalized logistic model and is dependent on environmental and human factors which are conducive to the growth of carrier population. The model is analyzed using stability theory of differential equations and numerical simulation. We have found a threshold condition, in terms of vaccine induced reproduction number R(φ) which is, if less than one, the disease dies out in the absence of carriers provided the vaccine efficacy is high enough, and otherwise the infection is maintained in the population. The model also exhibits backward bifurcation at R(φ) = 1. It is also shown that the spread of an infectious disease increases as the carrier population density increases. In addition, the constant immigration of susceptibles makes the disease more endemic.

SUMMARYBACKGROUND:There is an urgent need for improved estimations of the burden of tuberculosis (TB).OBJECTIVE:To develop a new quantitative method based on mathematical modelling, and to demonstrate its application to TB in India.DESIGN:We developed a simple model of TB transmission dynamics to estimate the annual incidence of TB disease from the annual risk of tuberculous infection and prevalence of smear-positive TB. We first compared model estimates for annual infections per smear-positive TB case using previous empirical estimates from China, Korea and the Philippines. We then applied the model to estimate TB incidence in India, stratified by urban and rural settings.RESULTS:Study model estimates show agreement with previous empirical estimates. Applied to India, the model suggests an annual incidence of smear-positive TB of 89.8 per 100 000 population (95%CI 56.8–156.3). Results show differences in urban and rural TB: while an urban TB case infects more individuals per year, a rural TB case remains infectious for appreciably longer, suggesting the need for interventions tailored to these different settings.CONCLUSIONS:Simple models of TB transmission, in conjunction with necessary data, can offer approaches to burden estimation that complement those currently being used.

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In this paper, the cumulative effect of ecological factors in the habitat on the spread of tuberculosis (TB) in human population is modeled and analyzed. The total human population is divided into two classes, susceptibles and infectives. It is assumed that TB is not only spread by direct contacts with infectives in the population but also indirectly by bacteria which are emitted by infectives in the habitat. It is assumed further that bacteria survive due to conducive ecological factors such as flower pots, plants, grasses, human clothes, etc. in the habitat. The cumulative density of ecological factors in the habitat is assumed to be governed by a population density dependent logistic model. The analysis of the model shows that as parameters governing the conducive ecological factors in the habitat increase, the spread of TB increases. The same result is also found with the increase in the parameter governing the survival and accumulation of bacteria in the habitat. It is further found that due to immigration of the population TB becomes more endemic. A numerical study of the model is also carried out to support the analytical results.

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Tuberculosis (TB) is returning to be a worldwide global public health threat. It is estimated that 9.6 million cases occurred in 2014, of which just two-thirds notified to public health authorities. The "missing cases" constitute a severe challenge for TB transmission control. TB is a severe disease in India, while, worldwide, the WHO estimates that one third of the entire world population is infected. Nowadays, incidence estimation relies increasingly more on notifications of new cases from routine surveillance. There is an urgent need for better estimates of the load of TB, in high-burden settings. We developed a simple model of TB transmission dynamics, using a dynamical system model, consisting of six classes of individuals. It contains the current medical epidemiologists' understanding of the spread of the Mycobacterium tuberculosis in humans, which is substantiated by field observations at the district level in India. The model incorporates the treatment options provided by the public and private sectors in India. Mathematically, an interesting feature of the system is that it exhibits a backward, or subcritical, bifurcation. One of the results of the investigation shows that the discrepancy between the diagnosis rates of the public and private sector does not seem to be the cause of the endemicity of the disease, and, unfortunately, even if they reached 100% of correct diagnosis, this would not be enough to achieve disease eradication. Several other approaches have been attempted on the basis of this model to indicate possible strategies that may lead to disease eradication, but the rather sad conclusion is that they unfortunately do not appear viable in practice.