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Enregistrement W2892565614 · doi:10.1016/s2214-109x(18)30313-9

Preventing tuberculosis among high-risk workers

2018· article· en· W2892565614 sur OpenAlexaboutno aff
Perry Gottesfeld, Michael Reid, Eric Goosby

Notice bibliographique

RevueThe Lancet Global Health · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueTuberculosis Research and Epidemiology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTuberculosisSilicosisEnvironmental healthMedicineTuberculosis preventionGovernment (linguistics)Gold miningIncidence (geometry)BusinessPathology

Résumé

récupéré en direct d'OpenAlex

Tuberculosis control programmes focus on case identification and treatment. Therefore, opportunities to prevent disease onset are often overlooked. New strategies are needed to further reduce global incidence and mortality of tuberculosis to achieve the visionary goal of a tuberculosis-free world. Prevention of tuberculosis among miners and other workers exposed to silica offers one such opportunity. The UN is holding its first high-level meeting on tuberculosis in the General Assembly this year to focus on solutions. Heads of state should therefore embrace strategies to prevent tuberculosis before it occurs by controlling risk factors. Primary prevention to reduce exposure to silica dust in the workplace should be considered an important tool in responding to this epidemic, particularly among individuals working in dusty environments. Workplace dust controls and appropriate regulations can be implemented without taking away resources from conventional approaches. While the price of gold and other precious metals has more than doubled in the past 15 years, mining employment has grown substantially. Much of this growth has been in the informal sector, in what WHO classifies as countries with a high burden of tuberculosis. Mining communities, and other occupations with elevated exposure to silica dust, in these countries often have the highest reported incidence of tuberculosis. For more than 100 years, studies have linked silica dust in the workplace with increased risk of tuberculosis.1Miners' Phthisis Prevention CommitteeThe prevention of silicosis in the mines of Witwatersrand. Government Printer, Pretoria1937Google Scholar Beyond mining, workers in construction, pottery, marble stone industries, and sand extraction have high rates of tuberculosis. For individuals with confirmed silicosis, the risk of active tuberculosis increases by more than three-fold, whereas for individuals with HIV, the risk increases by five-fold. Among workers with HIV and silicosis, the risk increases synergistically by more than 15 times making this one of the deadliest combinations in high-burden countries.2Corbett EL Churchyard GJ Clayton TC et al.HIV infection and silicosis: the impact of two potent risk factors on the incidence of mycobacterial disease in South African miners.AIDS. 2000; 14: 2759-2768Crossref PubMed Scopus (147) Google Scholar A legal settlement in South Africa costing US$400 million highlighted the impact of silica dust exposures in compensating miners and former miners with tuberculosis and not just silicosis. Tuberculosis programmes are investing billions of dollars annually to identify and treat individuals with active tuberculosis. Despite these investments, tuberculosis incidence is declining slowly in many countries. Ministries of Health and their donor partners should develop new mechanisms to address determinants of tuberculosis to reduce disease incidence. Few strategies prevent active tuberculosis, but studies done in the USA, Italy, and South Africa have shown a decrease in tuberculosis incidence among workers after dust exposures were reduced.1Miners' Phthisis Prevention CommitteeThe prevention of silicosis in the mines of Witwatersrand. Government Printer, Pretoria1937Google Scholar, 3Cocco PL Carta P Belli S Picchiri GF Flore MV Mortality of Sardinian lead and zinc miners: 1960–88.Occup Environ Med. 1994; 51: 674-682Crossref PubMed Scopus (34) Google Scholar, 4Costello J Graham WG Vermont granite workers' mortality study.Am J Ind Med. 1988; 13: 483-497Crossref PubMed Scopus (63) Google Scholar Even in low-resource settings, hazards from respirable silica dust can be reduced by 80% with wet spray misting.5Gottesfeld P Nicas M Kephart JW Balakrishnan K Rinehart R Reduction of respirable silica following the introduction of water spray applications in Indian stone crusher mills.Int J Occup Environ Health. 2008; 14: 94-103Crossref PubMed Scopus (18) Google Scholar At no additional cost, these investments have the potential to reduce the incidence of silicosis, lung cancer, and other diseases in mining communities worldwide. Engineering controls to reduce silica dust exposures have been shown to be the most cost-effective measures to prevent disease in the workplace, even without the benefits of reducing tuberculosis and lung cancer incidence.6Lahiri S Levenstein C Nelson DI Rosenberg BJ The cost effectiveness of occupational health interventions: prevention of silicosis.Am J Ind Med. 2005; 48: 503-514Crossref PubMed Scopus (51) Google Scholar The rate of return for investments in primary prevention (eg, workplace dust controls) is higher than for secondary prevention programmes that identify and treat cases of tuberculosis—interventions that prevent exposures before they cause disease have clear benefits (ie, improved ventilation).7Hunchangsith P Barendregt JJ Vos T Bertram M Cost-effectiveness of various tuberculosis control strategies in Thailand.Value Health. 2012; 15: S50-S55Summary Full Text Full Text PDF PubMed Scopus (15) Google Scholar, 8Disease Control Priorities ProjectDisease control priorities in developing countries.second edition. The World Bank and Oxford University Press, Washington DC and New York2006Google Scholar More than 230 million individuals are exposed to silica in the workplace. When calculating the public health impact, it is important to consider that many workers migrate to job sites and return home with tuberculosis and therefore pose a disseminating threat to millions more.9Murie F Building safety—an international perspective.Int J Occup Environ Health. 2007; 13: 5-11Crossref PubMed Scopus (58) Google Scholar, 10Intergovernmental Forum on Mining, Minerals, Metals and Sustainable DevelopmentGlobal trends in artisanal and small-scale mining (ASM): a review of key numbers and issues. International Institute for Sustainable Development, Winnipeg2017Google Scholar Because silica exposures in mining and other occupations substantially impact public health worldwide, global health funders should develop action plans to reduce exposure to silica dust in high-risk communities. Governments should adopt regulations to control silica dust and, along with multilateral aid agencies, include silica dust control plans in public sector infrastructure programmes. The International Commission on Occupational Health has outlined comprehensive recommendations to implement these measures.11International Commission of Occupational HealthPreventing tuberculosis among Silica-exposed workers.http://www.icohweb.org/site/multimedia/news/pdf/1-ICOH-Statement-on-Preventing-TB-among-Silica-exposed-Workers-Final-2018.pdfDate: April 28, 2018Date accessed: May 30, 2018Google Scholar Tuberculosis disproportionately affects the poorest and most vulnerable populations, including individuals with the highest dust exposures in the workplace. Without waiting on any new treatments or technology, a key risk factor for tuberculosis (ie, silica dust exposure) can be substantially reduced. By investing in simple dust control measures, high-burden countries and their donor partners can save thousands of lives and millions of dollars. We declare no competing interests.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,183
Score d'incertitude au seuil0,987

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,036
Tête enseignante GPT0,390
Écart entre enseignants0,354 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations14
Publié2018
Routes d'admission1
Résumé présentoui

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