Enhancing tuberculosis case notifications through mapping sales of medicine in the private sector: a quasi-experimental study in Punjab province, Pakistan
Notice bibliographique
Résumé
In Pakistan, almost one-third of people who develop tuberculosis (TB) are missed by the National TB Program (NTP). A considerable number of people with TB receive treatment in the private sector but remain unnotified. This study documents the outcomes of an intervention to identify people with TB through private pharmacy engagement, building on mapping TB medicine sales in Punjab Province. A comprehensive intervention was carried out in four districts of Punjab with high anti-TB drug sales, comprising a policy change requiring mandatory notification of TB medication sales, mapping and engaging pharmacies selling anti-TB drugs, reporting through a novel ‘eTB’ mobile application and providing support via a call center. We collected both historical and prospective TB notification data from the intervention and control districts. The primary outcome was the change in TB notifications during the intervention period compared with historical and control notifications. Over the 12-month intervention period, 15,669 people with TB were reported from 2,943 pharmacies in four districts. Among the people identified, 88% were male (n = 13,673), 95% had pulmonary disease (n = 14,969), and 4,256 (27%) were bacteriologically confirmed. Chain pharmacies (n = 14) contributed to 39% of the yield. TB notifications increased by 17,462 (+ 34%) over the baseline period compared with an 8% increase in the control districts. The number of bacteriologically confirmed notifications increased by 32% compared with 16% in the control districts. The proportion of bacteriological confirmation was similar before and during the intervention. The results of the largest TB intervention with pharmacies globally showed incredible potential to link people with TB who are receiving care in the private sector. Mapping TB medicine sales in the private sector with tailored interventions can contribute to closing the gap in notifications where anti-TB drug sales in the private sector are prevalent. What is already known on this topic? A significant number of people with TB receive care in the private sector as evidenced by the significant volumes of anti-TB medicines sold, particularly in countries with substantive private TB drug markets like Pakistan. However, there is still a gap in notifications, particularly from small scale private pharmacies. Most pharmacy-based TB interventions have been done at a small scale and have engaged pharmacies to refer people with TB-related symptoms for testing thus creating a potentially perverse economic incentive for participation. What this study adds • Using TB drug sales data can help target interventions engaging private pharmacies at a large scale. Enormous numbers of people with TB can be captured in the public notification system to close the existing notification gap. • Private sector engagement approaches that support existing business models are more likely to create buy-in and more successful in increasing collaboration. • In many countries, men with TB are missed more often than women, and this type of private sector intervention has the potential to bring the gap in TB notifications among men. How this study might affect research, practice or policy • A combination of regulatory approaches and enablers applied by NTPs could be useful in engaging with private sector, particularly for-profit private pharmacies in identifying people with TB who are currently missed. • There is potential to improve case identification and management through enhanced data sharing between private pharmacies and public health authorities supported by intermediary agencies.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».