Estimating typhoid incidence from community-based serosurveys: A multicohort study in Bangladesh, Nepal, Pakistan and Ghana
Notice bibliographique
Résumé
Abstract Background The incidence of enteric fever, an invasive bacterial infection caused by typhoidal Salmonellae , is largely unknown in regions lacking blood culture surveillance. New serologic markers have proven accurate in diagnosing enteric fever, but whether they could be used to reliably estimate population-level incidence is unknown. Methods We collected longitudinal blood samples from blood culture-confirmed enteric fever cases enrolled from surveillance studies in Bangladesh, Nepal, Pakistan, and Ghana and conducted cross-sectional serosurveys in the catchment areas of each surveillance site. We used ELISAs to measure quantitative IgA and IgG antibody responses to Hemolysin E (HlyE) and S . Typhi lipopolysaccharide (LPS). We used Bayesian hierarchical models to fit two-phase power-function decay models to the longitudinal antibody responses among enteric fever cases and used the joint distributions of the peak antibody titers and decay rate to estimate population-level incidence rates from cross-sectional serosurveys. Findings The longitudinal antibody kinetics for all antigen-isotypes were similar across countries and did not vary by clinical severity. The seroincidence of typhoidal Salmonella infection among children <5 years ranged between 58.5 per 100 person-years (95% CI: 42.1 - 81.4) in Dhaka, Bangladesh to 6.6 (95% CI: 4.3-9.9) in Kavrepalanchok, Nepal, and followed the same rank order as clinical incidence estimates. Interpretation The approach described here has the potential to expand the geographic scope of typhoidal Salmonella surveillance and generate incidence estimates that are comparable across geographic regions and time. Funding This work was supported by the Bill and Melinda Gates Foundation (INV-000572). Research in context Evidence before this study Previous studies have identified serologic responses to two antigens (Hemolysin E [HlyE] and Salmonella lipopolysaccharide [LPS]) as promising diagnostic markers of acute typhoidal Salmonella infection. We reviewed the evidence for seroepidemiology tools for enteric fever available as of November 01, 2021, by searching the National Library of Medicine article database and medRxiv for preprint publications, published in English, using the terms “enteric fever”, “typhoid fever”, “ Salmonella Typhi”, “ Salmonella Paratyphi”, “typhoidal Salmonella ”, “Hemolysin E”, “ Salmonella lipopolysaccharide”, “seroconversion”, “serosurveillance”, “seroepidemiology”, “seroprevalence” and “seropositivity.” We found no studies using HlyE or LPS as markers to measure the incidence or prevalence of enteric fever in a population. Anti-Vi IgG responses were used as a marker of population seroprevalence in cross-sectional studies conducted in South Africa, Fiji, and Nepal, but were not used to calculate population-based incidence estimates. Added value of this study We developed and validated a method to estimate typhoidal Salmonella incidence in cross-sectional population samples using antibody responses measured from dried blood spots. First, using longitudinal dried blood spots collected from over 1400 blood culture-confirmed cases in four countries, we modeled the longitudinal dynamics of antibody responses for up to two years following infection, accounting for heterogeneity in antibody responses and age-dependence. We found that longitudinal antibody responses were highly consistent across four countries on two continents and did not differ by clinical severity. We then used these antibody kinetic parameters to estimate incidence in population-based samples in six communities across the four countries, where concomitant population-based incidence was measured using blood cultures. Seroincidence estimates were much higher than blood-culture-based case estimates across all six sites, suggestive of a high incidence of asymptomatic or unrecognized infections. Still, the rank order of seroincidence and culture-based incidence rates were the same, with the highest rates in Bangladesh and lowest in Ghana. Implications of all the available evidence Many at-risk low- and middle-income countries lack data on typhoid incidence needed to inform and evaluate vaccine introduction. Even in countries where incidence estimates are available, data are typically geographically and temporally sparse due to the resources necessary to initiate and sustain blood culture surveillance. We found that typhoidal Salmonella infection incidence can be estimated from community-based serosurveys using dried blood spots, representing an efficient and scalable approach for generating the typhoid burden data needed to inform typhoid control programs in resource-constrained settings.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».