Programmatic Mapping to Estimate Size, Distribution, and Dynamics of Key Populations in Kosovo
Bibliographic record
Abstract
BACKGROUND: The burden of an HIV epidemic in Kosovo lies among the key populations (KPs) of female sex workers (FSWs), men who have sex with men (MSM), and people who inject drugs (PWIDs). The available interventions for KPs are fragmented and lack sufficient and appropriate granularity of information needed to develop large-scale outreach programs. OBJECTIVE: The aim of this study was to estimate the size and distribution of these populations to create evidence for developing action plans for HIV prevention. METHODS: The programmatic mapping approach was used to collect systematic information from key informants, including geographic and virtual locations in 26 municipalities of Kosovo between February to April 2016. In level 1, information was gathered about KPs' numbers and locations through 1537 key informant interviews within each municipality. Level 2 involved validating these spots by conducting another 976 interviews with KPs congregating at those spots. Population size estimates were calculated for each spot, and finally a national-level estimate was developed, which was corrected for duplication and overlaps. RESULTS: Of the estimated 6814 MSM (range: 6445 to 7117), nearly 4940 operate through the internet owing to the large stigma and discrimination against same-sex relationships. Geo-based MSM (who operate through physical spots) congregate at a few spots with large spot sizes (13.3 MSM/spot). Three-fourths of the MSM are distributed in 5 major municipalities. Fridays and Saturdays are the peak days of operation; however, the number only increases by 5%. A significant number are involved in sex work, that is, provide sex to other men for money. PWIDs are largely geo-based; 4973 (range: 3932 to 6015) PWIDs of the total number of 5819 (range: 4777 to 6860) visit geographical spots, with an average spot size of 7.1. In smaller municipalities, they mostly inject in residential locations. The numbers stay stable during the entire week, and there are no peak days. Of the 5037 (range: 4213 to 5860) FSWs, 20% use cell phones, whereas 10% use websites to connect with clients. The number increases by 25% on weekends, especially in larger municipalities where sex work is mostly concentrated. Other than a few street-based spots, most spots are establishments run by pimps, which is reflective of the highly institutionalized, structured, and organized FSW network. CONCLUSIONS: This study provides valuable information about the population size estimates as well as dynamics of each KP, which is the key to developing effective HIV prevention strategies. The information should be utilized to develop microplans and effectively provide HIV prevention services to various KPs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".