P1-S4.13 Mapping high risk activities of HIV/AIDS in Gaoxin and Yantan District of Zigong City
Notice bibliographique
Résumé
Background Zigong is located in the south of Sichuan Province of China. As a key area with a large number of migrants, Zigong has long been confronting the danger of HIV/AIDS. The goal of “Zigong geographic mapping on HIV/AIDS high-risk population” research project is to provide information on the location, type and volume of the female sex workers (FSWs) in Gaoxin (urban) and Yantan District (rural) to provide baseline information for HIV/AIDS prevention policy and programs in future. Methods This study adopted a “geographical approach” to map the location and spots of the activities of sex trade and estimated the number of FSWs involved in the activities. This included two sequential steps: 1) Systematic information gathering from key informants (KI) suggested the locations (“hot spots”) where FSWs congregate. 2) The “hot spots” were validated through site visit and insiders; the information about the number and characteristics of FSWs in each spot were collected. Results In Gaoxin District: 59 high-risk spots were confirmed and 16 clusters were marked in 10 zones. The most common type of sex trade spots was hair salon/massage room/foot massage room. 72.9% of the spots were both “seeking risk” and “taking risk”, while 22.0% and 3.4% were only “seeking risk” and “taking risk” respectively. 39.0% of the spots had more than three clients per FSW per day. The estimated number of total FSWs in this urban area was 303. 38.5% of FSWs were in hotel/small lodge, while 29.3% and 27.3% were in small tea house/bar/KTV and hair salon/massage room/foot massage room respectively. The peak season, peak date and peak time of the most spots was summer, the whole week, afternoon and night. In Yantan District: 12 high-risk spots were confirmed and half were concentrated in Yantan Town. The most common type was small tea house/bar/KTV. Nine spots were both “seeking risk” and “taking risk”, while three were “taking risk” only. Five spots had more than three clients per day for each FSW. The estimated number of FSWs was 42, and 74.4% worked in the small tea house/bar/KTV. The peak season, peak date and peak time of the most spots was spring and summer, the whole week, and night, respectively. Conclusions The mapping approach provided direct and visible geographic distribution information, which enables a quick mastery of the distribution of high risk spots and the number of high risk population, for public health intervention planning and program implementation.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».