MétaCan
Menu
Retour à la cohorte
Enregistrement W4411326575 · doi:10.1093/acrefore/9780190632366.013.173

Sexually Transmitted Infections: Old Foe, New Opportunities for Control

2025· reference-entry· en· W4411326575 sur OpenAlexaff
Francis Ndowa, Suzanne M. Garland, Remco P. H. Peters, Laith J. Abu-Raddad

Notice bibliographique

RevueOxford Research Encyclopedia of Global Public Health · 2025
Typereference-entry
Langueen
DomaineMedicine
ThématiqueSyphilis Diagnosis and Treatment
Établissements canadiensSKiN Health
Organismes subventionnairesnon disponible
Mots-clésControl (management)BiologyMedicineComputer scienceArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

Abstract More than 30 pathogens, including bacteria, viruses, protozoa, and ectoparasites, cause sexually transmitted infections (STIs). Approximately 1 million curable STIs, comprising Neisseria gonorrhoeae, Chlamydia trachomatis, Treponema pallidum, and Trichomonas vaginalis, are acquired everyday worldwide. The most common of the treatable STIs is a protozoon, T. vaginalis, causing approximately 156 million new infections in 2020. Sexually transmitted viral infections are also prevalent worldwide, of which the most important are the human immunodeficiency virus (HIV), herpes simplex virus types 1 and 2, and the human papillomavirus (HPV). STIs impact people’s lives through their impact on reproductive health and child health, as well as through the facilitation of sexual transmission of HIV infection and, with some, such as HPV, as precursors of anogenital cancers. People face enormous challenges with access to health services for STI care. Furthermore, some STIs commonly exist as asymptomatic infections, particularly among adolescents. In addition, even with symptoms, some individuals have difficulty accessing affordable healthcare services because of anticipated stigma. The epidemiology of STIs is influenced by an interplay of the determinants of spread of infections and human behavior. At the individual level, determinant factors include ignorance of STIs, sexual behavior, sexual preferences, sexual networks, sex work, healthcare-seeking behaviors, and whether or not use is made of old and newer biomedical HIV and STI prevention interventions, such as condoms, medical male circumcision, and pre-exposure prophylaxis (e.g., PrEP for HIV); availability of, and access to, post-exposure prophylaxis; and prophylactic STI vaccines. At the population level, the determinants include demographic factors, socioeconomic factors, geographical settings, cultural ramifications, political commitment and health system responses. STIs can be prevented through modification of sexual behavior toward “safer sex.” The interventions implemented by countries, to varying degrees of coverage, include behavioral interventions, promotion of use of barrier methods, vaccinations, screening for STIs, and case-finding in people attending healthcare services for conditions other than for STI care. In persons with established infections, the focus is on averting short-term and long-term sequelae of untreated STIs, such as pelvic inflammatory disease, tubal-factor infertility, adverse pregnancy outcomes, and cervical cancer. This includes screening for asymptomatic STIs, cervical cancer, and the early diagnosis and treatment of HIV infection. Regular screening has been shown to reduce the population prevalence of STIs, prevention of some adverse outcomes such as congenital syphilis, and improved prognosis in such cases as early treatment of HPV-associated cervical cancer. The evidence and cost-effectiveness of screening for C. trachomatis and N. gonorrhoeae to prevent infertility and improve pregnancy outcomes is limited. Also, screening programs result in increased use of antibiotics in certain population groups, with concerns of increase in the development of antimicrobial resistance, especially in N. gonorrhoeae. The detection and management of STIs has been revolutionized since the 1990s by the development of molecular detection tests, the advent of STI vaccines, and the advent of new treatment molecules, such as antiretroviral treatments, which have facilitated timely diagnosis of both symptomatic and asymptomatic infections and converted some fatal infections into manageable chronic infections.

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)0,003
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,723
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
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 Opus0,158
Tête enseignante GPT0,416
Écart entre enseignants0,258 · 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.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

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

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueOxford Research Encyclopedia of Global Public HealthMême sujetSyphilis Diagnosis and TreatmentTravaux en français237 207