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Enregistrement W2603430634 · doi:10.1371/journal.pntd.0005475

Dengue seroprevalence, seroconversion and risk factors in Dhaka, Bangladesh

2017· article· en· W2603430634 sur OpenAlexafffund
Parnali Dhar‐Chowdhury, Kishor Kumar Paul, C. Emdad Haque, Shakhawat Hossain, L. Robbin Lindsay, Antonia Dibernardo, W. Abdullah Brooks, Michael Drebot

Notice bibliographique

RevuePLoS neglected tropical diseases · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueMosquito-borne diseases and control
Établissements canadiensUniversity of WinnipegUniversity of ManitobaPublic Health Agency of Canada
Organismes subventionnairesInternational Development Research CentrePublic Health AgencyPublic Health Agency of CanadaManitoba Health Research Council
Mots-clésSeroprevalenceDengue feverSeroconversionDengue virusMedicinePopulationSerologyEnvironmental healthDemographyVirologyImmunologyVirusAntibody

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Dengue virus (DENV) activity has been reported in Dhaka, Bangladesh since the early 1960s with the greatest burden of dengue fever and dengue hemorrhagic fever cases observed in 2000. Since this time, the intensity of dengue activity has varied from year to year, and its determining factors remained relatively unknown. In light of such gaps in knowledge, the main objectives of this study were to determine the magnitude of seroprevalence and seroconversion among the surveyed population, and establish the individual/household level risk factors for the presence of DENV antibodies among all age groups of target populations in the city of Dhaka. METHODOLOGY/PRINCIPAL FINDINGS: Considering the lack of fine scale investigations on the factors driving dengue activity in Bangladesh, a prospective cohort study involving serological surveys was undertaken with participant interviews and blood donation across the city of Dhaka in 2012. Study participants were recruited from 12 of 90 wards and blood samples were collected during both the pre-monsoon (n = 1125) and post-monsoon (n = 600) seasons of 2012. The findings revealed that the seroprevalence in all pre-monsoon samples was 80.0% (900/1125) while the seropositivity in the pre-monsoon samples that had paired post-monsoon samples was 83.3% (503/600). Of the 97 paired samples that were negative at the pre-monsoon time point, 56 were positive at the post-monsoon time point. This resulted in a seroprevalence of 93.2% (559/600) among individuals tested during the post-monsoon period. Seroprevalence trended higher with age with children exhibiting a lower seropositivity as compared to adults. Results from this study also indicated that DENV strains were the only flaviviruses circulating in Dhaka in 2012. A multivariate analysis revealed that age, possession of indoor potted plants, and types of mosquito control measures were significant factors associated with DENV seroprevalence; while attendance in public/mass gatherings, and use of mosquito control measures were significantly associated with DENV seroconversion after adjusting for all other variables. CONCLUSIONS/SIGNIFICANCE: Our study suggests that there is a high level of endemic dengue virus circulation in the city of Dhaka which has resulted in significant DENV seroprevalence among its residents. Seropositivity increased with age, however, a substantial proportion of children are at risk for DENV infections. Our serological analysis also documents considerable DENV seroconversion among study participants which indicates that a large proportion of the population in the city of Dhaka were newly exposed to DENV during the study period (pre-and post-monsoon 2012). High levels of seroconversion suggest that there was an intense circulation of DENV in 2012 and this may have resulted in a significant risk for viral associated illness. Findings of our study further indicated that home-based interventions, such as removing indoor potted plants and increased bed net use, in addition to vector control measures in public parks, would reduce exposure to DENV and further decrease risk of viral associated disease.

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)0,000
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 enseignants0,004
Score d'incertitude au seuil0,847

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
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)0,0010,000

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 Opus0,013
Tête enseignante GPT0,251
Écart entre enseignants0,238 · 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

Citations100
Publié2017
Routes d'admission2
Résumé présentoui

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