About: The potential impact of preventive therapy against tuberculosis in the WHO South-East Asian Region: a modelling approach

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About: The potential impact of preventive therapy against tuberculosis in the WHO South-East Asian Region: a modelling approach Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	The potential impact of preventive therapy against tuberculosis in the WHO South-East Asian Region: a modelling approach
Creator	Arinaminpathy, Nimalan Bhatia, Vineet Mandal, Partha Mandal, Sandip Sharma, Mukta
topic	covid:89e2d929820c60c27316237262275377438333c1#this
Source	PMC
abstract	BACKGROUND: The prevention of tuberculosis (TB) is key for accelerating current, slow declines in TB burden. The 2018 World Health Organization (WHO) guidelines on eligibility for preventive therapy to treat latent TB infection (LTBI) include people living with human immunodeficiency virus (PLHIV), household contacts of TB patients including children, and those with clinical conditions including silicosis, dialysis, transplantation, etc. and other country-specific groups. We aimed to estimate the potential impact of full implementation of these guidelines in the WHO South-East Asian (SEA) Region, which bears the largest burden of TB and LTBI amongst the WHO regions. METHODS: We developed mathematical models of TB transmission dynamics, calibrated individually to each of the 11 countries in the region. We modelled preventive therapy in the absence of other TB interventions. As an alternative comparator, reflecting ongoing developments in TB control in the region, we also simulated improvements in the treatment cascade for active TB, including private sector engagement and intensified case-finding. Relative to both scenarios, for each country in the region, we projected TB cases and deaths averted between 2020 and 2030, by full uptake of preventive therapy, defined as comprehensive coverage amongst eligible populations as per WHO guidelines, and assuming outcomes consistent with clinical trials. We also performed sensitivity analysis to illustrate impact under less-than-optimal conditions. RESULTS: At the regional level, full uptake of preventive therapy amongst identified risk groups would reduce annual incidence rates in 2030 by 8.30% (95% CrI 6.48–10.83) relative to 2015, in the absence of any additional interventions. If implemented against a backdrop of improved TB treatment cascades, preventive therapy would achieve an incremental 6.93 percentage points (95% CrI 5.81–8.51) of reduction in annual incidence rates, compared to 2015. At the regional level, the numbers of individuals with latent TB infection that need to be treated to avert 1 TB case is 64 (95% CrI 55–74). Sensitivity analysis illustrates that results for impact are roughly proportional to ‘effective coverage’ (the product of actual coverage and effectiveness of the regimen). CONCLUSIONS: Full implementation of WHO guidelines is important for ending TB in the SEA Region. Although future strategies will need to be expanded to the population level, to achieve large declines in TB incidence, the uptake of current tools can offer a valuable step in this direction.
has issue date	2020-07-20(xsd:dateTime)
bibo:doi	10.1186/s12916-020-01651-5
has license	cc-by
sha1sum (hex)	89e2d929820c60c27316237262275377438333c1
schema:url	https://doi.org/10.1186/s12916-020-01651-5
resource representing a document's title	The potential impact of preventive therapy against tuberculosis in the WHO South-East Asian Region: a modelling approach
has PubMed Central identifier	PMC7369473
schema:publication	BMC Med
resource representing a document's body	covid:89e2d929820c60c27316237262275377438333c1#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/89e2d929820c60c27316237262275377438333c1
is schema:about of	named entity 'consistent' named entity 'therapy' named entity 'product' named entity '2018 World' named entity 'alternative' named entity 'improved' named entity 'actual' named entity 'bears' named entity 'cases' named entity 'tuberculosis' named entity 'Region' named entity 'developed' named entity 'performed' named entity 'burden' named entity 'comparator' named entity 'incidence' named entity 'Results' named entity 'cascade' named entity 'Relative' named entity 'calibrated' named entity 'full' named entity 'conditions' named entity 'backdrop' named entity 'level' named entity 'incidence' named entity 'human immunodeficiency virus' named entity 'populations' named entity 'preventive' named entity 'latent TB' named entity 'clinical trials' named entity 'WHO' named entity 'World Health Organization' named entity 'infection' named entity 'PLHIV' named entity 'preventive therapy' named entity 'World Health Organization' named entity 'sensitivity analysis' named entity 'TB treatment' named entity 'silicosis' named entity 'tuberculosis' named entity '1, 2' named entity 'compartmental models' named entity 'HIV' named entity 'isoniazid' named entity 'preventive therapy' named entity 'Sensitivity analysis' named entity 'high-risk groups' named entity 'extrapulmonary' named entity 'posterior distribution' named entity 'preventive therapy' named entity 'PLHIV' named entity 'HIV' named entity 'preventive therapy' named entity 'PLHIV' named entity 'latent TB' named entity 'status quo' named entity 'infection' named entity 'epidemiological' named entity 'Nepal' named entity 'HIV' named entity 'WHO' named entity 'preventive therapy' named entity 'mortality rate' named entity 'DPR Korea' named entity 'credible intervals' named entity 'preventive therapy' named entity 'incidence rate' named entity 'public health' named entity 'WHO' named entity 'WHO' named entity 'preventive therapy' named entity 'Bangladesh' named entity 'PLHIV' named entity 'East Asian' named entity 'preventive therapy' named entity 'sensitivity analysis' named entity 'coinfection'

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