ArticleScientific reports2017
An Immunization Strategy for Hidden Populations.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Non-selective distribution of infectious disease prevention may outperform risk-based targeting.Nature communications · 2022Article
- Network centrality for the identification of biomarkers in respondent-driven sampling datasets.PloS one · 2021Article
- Location inference for hidden population with online text analysis.International journal of health geographics · 2020Article
- Immunization strategies in networks with missing data.PLoS computational biology · 2020Article
- HIV control strategies for sex worker-client contact networks.Journal of the Royal Society, Interface · 2019Article
- Inferring the Population Mean with Second-Order Information in Online Social Networks.Entropy (Basel, Switzerland) · 2018Article
- Analyzing hidden populations online: topic, emotion, and social network of HIV-related users in the largest Chinese online community.BMC medical informatics and decision making · 2018Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hidden populations, such as injecting drug users (IDUs), sex workers (SWs) and men who have sex with men (MSM), are considered at high risk of contracting and transmitting infectious diseases such as AIDS, gonorrhea, syphilis etc. However, public health interventions to such groups are prohibited due to strong privacy concerns and lack of global information, which is a necessity for traditional strategies such as targeted immunization and acquaintance immunization. In this study, we introduce an innovative intervention strategy to be used in combination with a sampling approach that is widely used for hidden populations, Respondent-driven Sampling (RDS). The RDS strategy is implemented in two steps: First, RDS is used to estimate the average degree (personal network size) and degree distribution of the target population with sample data. Second, a cut-off threshold is calculated and used to screen the respondents to be immunized. Simulations on model networks and real-world networks reveal that the efficiency of the RDS strategy is close to that of the targeted strategy. As the new strategy can be implemented with the RDS sampling process, it provides a cost-efficient and feasible approach for disease intervention and control for hidden populations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.