Distribution and transmission of <i>M. tuberculosis</i> in a high-HIV prevalence city in Malawi: a genomic and spatial analysis
Notice bibliographique
Résumé
Abstract Background Delays in identifying and treating individuals with infectious tuberculosis (TB) contribute to poor health outcomes and allow ongoing community transmission of M. tuberculosis ( Mtb ). Current recommendations for screening for tuberculosis specify community characteristics (e.g., areas with high local tuberculosis prevalence) that can be used to target screening within the general population. However, areas of higher tuberculosis burden are not necessarily areas with higher rates of transmission. We investigated the genomic diversity and transmission of Mtb using high-resolution surveillance data in Blantyre, Malawi. Methods and Findings We extracted and performed whole genome sequencing on mycobacterial DNA from cultured M. tuberculosis isolates obtained from culture-positive tuberculosis cases at the time of tuberculosis (TB) notification in Blantyre, Malawi between 2015-2019. We constructed putative transmission networks identified using TransPhylo and investigated individual and pair-wise demographic, clinical, and spatial factors associated with person-to-person transmission. We found that 56% of individuals with sequenced isolates had a probable direct transmission link to at least one other individual in the study. We identified thirteen putative transmission networks that included five or more individuals. Five of these networks had a single spatial focus of transmission in the city, and each focus centered in a distinct neighborhood in the city. We also found that approximately two-thirds of inferred transmission links occurred between individuals residing in different geographic zones of the city. Conclusion While the majority of detected tuberculosis transmission events in Blantyre occurred between people living in different zones, there was evidence of distinct geographical concentration for five transmission networks. These findings suggest that targeted interventions in areas with evidence of localized transmission may be an effective local tactic, but will likely need to be augmented by city-wide interventions to improve case finding and to address social determinants of tuberculosis to have sustained impact. Author Summary Why was this study done? – Tuberculosis (TB) is a major global health threat and a leading cause of death due to infectious disease. Rapid diagnosis and treatment of individuals with TB is vital to reduce the spread of disease. – If public health programs can identify areas with ongoing TB transmission, resources might be directed toward intervening in those areas to interrupt transmission chains. However, in settings where many people have TB, it is often difficult to differentiate areas with high rates of disease from areas with high rates of local transmission. What did the researchers do and find? – We used whole genome sequencing data to infer networks of TB transmission in Blantyre, Malawi. We used individual residence data to identify whether transmission networks were concentrated in specific parts of the city and to describe the amount of transmission that occurred between vs. within distinct parts of the city. – We found that most TB transmission in Blantyre occurred between individuals who did not live near each other. We also identified five transmission networks which had strong local foci of transmission. What do these findings mean? – Because most TB transmission in Blantyre does not occur in concentrated areas, city-wide interventions, such as improving access to TB care services and addressing social determinants of TB, may be needed to improve TB control. – For areas where there is evidence of local concentrated transmission, additional resources and strategies, such as targeted active case finding, may help to more rapidly reduce transmission and TB incidence.
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 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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 ».