METHODS: Data were derived from a respondent-driven survey sample (RDS) collected during 2010 of 460 PWID in greater Kuala Lumpur. Analysis focused on socio-demographic, clinical, behavioural, and network information. Spatial probit models were developed based on a distinction between the influence of peers (individuals nominated through a recruitment network) and neighbours (residing a close distance to the individual). The models were expanded to account for the potential influence of the network formation.
RESULTS: Recruitment patterns of HIV-infected PWID clustered both spatially and across the recruitment networks. In addition, HIV-infected PWID were more likely to have peers and neighbours who inject with clean needles were HIV-infected and lived nearby (<5km), more likely to have been previously incarcerated, less likely to use clean needles (26.8% vs 53.0% of the reported injections, p<0.01), and have fewer recent injection partners (2.4 vs 5.4, p<0.01). The association between the HIV status of peers and neighbours remained significantly correlated even after controlling for unobserved variation related to network formation and sero-sorting.
CONCLUSION: The relationship between HIV status across networks and space in Kuala Lumpur underscores the importance of these factors for surveillance and prevention strategies, and this needs to be more closely integrated. RDS can be applied to identify injection network structures, and this provides an important mechanism for improving public health surveillance, accessing high-risk populations, and implementing risk-reduction interventions to slow HIV transmission.
METHODOLOGY/PRINCIPAL FINDINGS: For eight destination countries (Indonesia, Philippines, Thailand, India, Malaysia, Vietnam, Sri Lanka, and Singapore), we collected age-dependent seroepidemiological data. We also retrieved the number of imported cases, who were notified to the Japanese government, as well as the total number of travelers to each destination. Using a mathematical model, we estimated the force of infection in each destination country with seroepidemiological data while jointly inferring the reporting coverage of DENV infections among Japanese travelers from datasets of imported cases and travelers. Assuming that travelers had a risk of infection that was identical to that of the local population during travel, the reporting coverage of dengue appeared to range from 0.6% to 4.3%. The risk of infection per journey ranged from 0.02% to 0.44%.
CONCLUSIONS/SIGNIFICANCE: We found that the actual number of imported cases of DENV infection among Japanese travelers could be more than 20 times the notified number of imported cases. This finding may be attributed to the substantial proportion of asymptomatic and under-ascertained infections.