Estimating tuberculosis incidence from primary survey data: a mathematical modeling approach

Pandey, Surabhi; Chadha, V. K.; Laxminarayan, Ramanan; Arinaminpathy, Nimalan

doi:10.5588/ijtld.16.0182

Cited by 31 publications

(17 citation statements)

References 19 publications

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“…In this paper we present a model for the disease situation in India, one of the countries in which the disease is endemic. This work is an extension of previous results, [3,15,18] and in particular of the work in progress [19], in that we account for the diagnostic system to be partioned into the public and private sectors, contrary to what was assumed in the earlier works.…”

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confidence: 87%

A TB model: Is disease eradication possible in India?

Pandey¹,

Venturino²

2017

MBE

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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.

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confidence: 87%

A TB model: Is disease eradication possible in India?

Pandey¹,

Venturino²

2017

MBE

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“…We also neglect HIV/TB coinfection, which accounts for an estimated 3% of TB burden in India [3]. We calibrated the model to: pooled subnational prevalence surveys from India [14,15]; estimates of the annual risk of infection from nationally representative infection surveys [16]; and WHO estimates for the proportion of cases that have rifampicin-or multi-drug resistance [3]. Each of these inputs has uncertainty attached.…”

Section: Plos Onementioning

confidence: 99%

The potential deployment of a pan-tuberculosis drug regimen in India: A modelling analysis

et al. 2020

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There is increasing interest in future, highly-potent 'pan-TB' regimens against tuberculosis (TB), that may be equally effective in both drug-susceptible and rifampicin-resistant (RR) forms of TB. Taking the example of India, the country with the world's largest burden of TB, we show that adoption of these regimens could be: (i) epidemiologically impactful, and (ii) cost-saving to the national TB programme, even if the regimen itself is more costly than current TB treatment. Mathematical modelling suggests that deployment of a pan-TB regimen in 2022 would reduce the annual incidence of TB in 2030 by 23.9% [95% Bayesian credible intervals [CrI] 17.6-30.8%] if used to treat all TB cases, and by 2.30% [95% CrI 1.57-3.48%] if used to treat only RR-TB. Notably, with a regimen costing less than USD 359 (95% CrI 287-441), treating all diagnosed TB cases with the pan-TB regimen yielded greater cost-savings than treating just those diagnosed with RR-TB. One limitation of our approach is that it does not capture the risk of resistance to the new regimen. We discuss ways in which this risk could be mitigated using modern adherence support mechanisms, as well as drug sensitivity testing at the point of TB diagnosis, to prevent new resistant forms from becoming established. A combination of such approaches would be important for maximising the useful lifetime of any future regimen.

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“…This approach implies that all pulmonary TB patients are equally infectious, while all extrapulmonary patients are entirely non-infectious, and so does not capture the heterogeneity among pulmonary patients. Other TB models have considered sputum smear status as a factor in stratifying patients' levels of infectiousness, considering both smear-negative and smearpositive pulmonary TB to be infectious, with the relative infectiousness of smear-negative patients compared to smear-positive typically set between 15 and 25% [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. While stratifying pulmonary TB patients based on smear status captures an additional clinical attribute that is important in determining infectiousness, even these models still do not capture the full picture of TB patients' infectiousness variation, since several behavioural and demographic factors other than smear status can affect the level of infectiousness [5].…”

Section: Introductionmentioning

confidence: 99%