118 research outputs found
Assessing sexual risk behavior among men who have sex with men in Vietnam : development and use of a new Internet-based sampling method
Background: Men who have sex with men (MSM) are at high risk of HIV infection
in all regions globally. Surveys among MSM in Hanoi and Ho Chi Minh City in
Vietnam have shown prevalence rates of 15% and 17% respectively. Representative
data about MSM and other hidden populations are extremely difficult to collect, due
to stigma. Much available data may thus not be representative of the MSM
population as a whole, preventing an evidence-based response to the HIV epidemic.
Respondent-driven sampling (RDS) was developed to enable representative
sampling of hidden groups but relies on untested assumptions. In addition, an
Internet-based version of RDS (webRDS) can potentially improve several key
limitations of the RDS method.
Aims: To develop a webRDS system for representative sampling of internet-using
MSM in Vietnam and to increase knowledge about sexual risk behavior for HIV
among MSM in Vietnam.
Methods: RDS studies were simulated on anonymized data from a large webcommunity
for lesbian, gay, bisexual and transgender persons. The assumptions
under which RDS is known to be unbiased were systematically violated and the
effects were studied. In-depth interviews (IDIs) were performed with 17 purposively
sampled MSM in Hanoi, Vietnam and latent content analysis was used. A webRDS
system, designed for MSM in Vietnam, was developed and used in two crosssectional
surveys in Vietnam.
Results: Simulations indicate that bias using RDS is large if respondents choose to
invite people based on characteristics that are correlated with study outcomes. Bias
and variance increased if participants preferentially invited frequent contacts. Diverse
seed selection was highly beneficial. IDIs showed that male-male relationships were
perceived to be short and unstable. Faithfulness was highly valued but largely seen as
unobtainable. The webRDS system enabled sustained recruitment of 676 and 983
submissions respectively in the two surveys. Maximum wave length was 29 waves
and equilibrium was reached for all but one variable. The sample was younger and of
higher education than the Vietnamese average. Thirty-six percent (CI: 32-42%) of
MSM in the second webRDS survey had unprotected anal sex (UAS) at least once
during the last three months. Thirty-six percent (CI: 32-41%) had ever taken an HIV
test and received the result. Ninety-two percent of all UAS acts were reported to have
taken place with non-casual partners. The numbers of UAS partners and UAS acts
were positively correlated. Modeling showed that this sexual behavior pattern is
likely to lead to explosive HIV transmission.
Conclusions: Simulations showed that RDS is relatively robust but empirical studies
of non-random recruitment and a better understanding of real-life variance is needed.
WebRDS is a highly promising method. Further evaluation and development is
warranted. HIV prevention services niched for MSM needs to be aggressively scaled
up in Vietnam
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Digital Epidemiology
Mobile, social, real-time: the ongoing revolution in the way people communicate has given rise to a new kind of epidemiology. Digital data sources, when harnessed appropriately, can provide local and timely information about disease and health dynamics in populations around the world. The rapid, unprecedented increase in the availability of relevant data from various digital sources creates considerable technical and computational challenges
Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen
Implementation of Web-Based Respondent-Driven Sampling among Men who Have Sex with Men in Vietnam
Objective: Lack of representative data about hidden groups, like men who have
sex with men (MSM), hinders an evidence-based response to the HIV epidemics.
Respondent-driven sampling (RDS) was developed to overcome sampling challenges
in studies of populations like MSM for which sampling frames are absent.
Internet-based RDS (webRDS) can potentially circumvent limitations of the
original RDS method. We aimed to implement and evaluate webRDS among a hidden
population.
Methods and Design: This cross-sectional study took place 18 February to 12
April, 2011 among MSM in Vietnam. Inclusion criteria were men, aged 18 and
above, who had ever had sex with another man and were living in Vietnam.
Participants were invited by an MSM friend, logged in, and answered a survey.
Participants could recruit up to four MSM friends. We evaluated the system by
its success in generating sustained recruitment and the degree to which the
sample compositions stabilized with increasing sample size.
Results: Twenty starting participants generated 676 participants over 24
recruitment waves. Analyses did not show evidence of bias due to ineligible
participation. Estimated mean age was 22 year and 82% came from the two large
metropolitan areas. 32 out of 63 provinces were represented. The median number
of sexual partners during the last six months was two. The sample composition
stabilized well for 16 out of 17 variables.
Conclusion: Results indicate that webRDS could be implemented at a low cost
among Internet-using MSM in Vietnam. WebRDS may be a promising method for
sampling of Internet-using MSM and other hidden groups.
Key words: Respondent-driven sampling, Online sampling, Men who have sex with
men, Vietnam, Sexual risk behavio
Census-derived migration data as a tool for informing malaria elimination policy
Background: Numerous countries around the world are approaching malaria elimination. Until global eradication is achieved, countries that successfully eliminate the disease will contend with parasite reintroduction through international movement of infected people. Human-mediated parasite mobility is also important within countries near elimination, as it drives parasite flows that affect disease transmission on a subnational scale.Methods: Movement patterns exhibited in census-based migration data are compared with patterns exhibited in a mobile phone data set from Haiti to quantify how well migration data predict short-term movement patterns. Because short-term movement data were unavailable for Mesoamerica, a logistic regression model fit to migration data from three countries in Mesoamerica is used to predict flows of infected people between subnational administrative units throughout the region.Results: Population flows predicted using census-based migration data correlated strongly with mobile phone-derived movements when used as a measure of relative connectivity. Relative population flows are therefore predicted using census data across Mesoamerica, informing the areas that are likely exporters and importers of infected people. Relative population flows are used to identify community structure, useful for coordinating interventions and elimination efforts to minimize importation risk. Finally, the ability of census microdata inform future intervention planning is discussed in a country-specific setting using Costa Rica as an example.Conclusions: These results show long-term migration data can effectively predict the relative flows of infected people to direct malaria elimination policy, a particularly relevant result because migration data are generally easier to obtain than short-term movement data such as mobile phone records. Further, predicted relative flows highlight policy-relevant population dynamics, such as major exporters across the region, and Nicaragua and Costa Rica’s strong connection by movement of infected people, suggesting close coordination of their elimination efforts. Country-specific applications are discussed as well, such as predicting areas at relatively high risk of importation, which could inform surveillance and treatment strategies.<br/
Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen
Large-scale data from digital infrastructure, like mobile phone networks, provides rich information on the behavior of millions of people in areas affected by climate stress. Using anonymized data on mobility and calling behavior from 5.1 million Grameenphone users in Barisal Division and Chittagong District, Bangladesh, we investigate the effect of Cyclone Mahasen, which struck Barisal and Chittagong in May 2013. We characterize spatiotemporal patterns and anomalies in calling frequency, mobile recharges, and population movements before, during and after the cyclone. While it was originally anticipated that the analysis might detect mass evacuations and displacement from coastal areas in the weeks following the storm, no evidence was found to suggest any permanent changes in population distributions. We detect anomalous patterns of mobility both around the time of early warning messages and the storm’s landfall, showing where and when mobility occurred as well as its characteristics. We find that anomalous patterns of mobility and calling frequency correlate with rainfall intensity (r = .75, p < 0.05) and use calling frequency to construct a spatiotemporal distribution of cyclone impact as the storm moves across the affected region. Likewise, from mobile recharge purchases we show the spatiotemporal patterns in people’s preparation for the storm in vulnerable areas. In addition to demonstrating how anomaly detection can be useful for modeling human adaptation to climate extremes, we also identify several promising avenues for future improvement of disaster planning and response activities
Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and the Netherlands using respondent-driven sampling
Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in the Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in the Netherlands and Thailand
Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti
Linus Bengtsson and colleagues examine the use of mobile phone positioning data to monitor population movements during disasters and outbreaks, finding that reports on population movements can be generated within twelve hours of receiving data
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