Utilization of Google enterprise tools to georeference survey data among hard-to-reach groups: strategic application in international settings

Harnessing digital data and data science to achieve 90-90-90 goals to end the HIV epidemic

PURPOSE OF REVIEW

Effective public health interventions depend on timely, accurate surveillance. Harnessing digital data (including internet searches, social media, and online media) and data science is an emerging approach to complement traditional surveillance in public health but has been underutilized in HIV prevention and treatment.

RECENT FINDINGS

We highlight recent examples that illustrate how social media data can be applied to HIV surveillance and prevention interventions.

SUMMARY

To achieve 90-90-90 goals to end the HIV epidemic, we encourage traditional public health researchers to partner with data scientists to supplement HIV surveillance programs with social media analytics to refine estimates of HIV infections and key populations at risk and to identify subgroups and regions where prevention and treatment efforts need to be bolstered. We also encourage interdisciplinary teams to design interventions to promote HIV prevention and linkage to care by leveraging digital media, such as search engines and social media, that have the potential to reach millions of people instantaneously.

Using Google Earth™ and Geographical Information System data as method to delineate sample domains for an urban household surveys: the case of Maroua (Far North Region-Cameroon)

Background

Getting a random household sample during a survey can be expensive and very difficult especially in urban area and non-specialist. This study aimed to test an alternative method using freely available aerial imagery.

Methods

A gridded map and random selection method was used to select households for interviews. A hundred numbered of points were put along the edges of an updated map of Maroua. Then two numbers were randomly draw at a time and a line was drawn between those two numbers. A lot of different kinds of shapes of different sizes obtained were numbered. Ten shapes were randomly draw and the one selected were considered as ‘neighbourhoods’. A grid of 30 m × 30 m was drawn over each and then numbered. 202 grids considered here as households were randomly selected from the ten neighbourhoods for interviews.

Results

Out of 202 households visited, only 4 were found to be something other than a house. In addition, 30 sampled households (14.85%) were abandoned or the occupants had relocated elsewhere. This method resulted in an accuracy level of 72%, its advantage is the ability to generate efficient random sample at relatively low cost as well the time required.

Conclusions

The method proposed in this study was efficient and cost-effective when compared to the infield generation of a household inventory or Global Positioning System (GPS) tracking of households. It can then be used by researchers in low-incomes countries where funding for research is a challenge. However, this method needs to train the investigators on how to use the GPS.

Social Networks of Substance-Using Populations: Key Issues and Promising New Approaches for HIV

PURPOSE OF REVIEW

This paper presents recent literature on substance using networks and HIV, highlighting renewed and emerging themes in the field. The goal is to draw attention to research that holds considerable promise for advancing our understanding of the role of networks in shaping behaviors, while also providing critical information for the development of interventions, programs, and policies to reduce HIV and other drug-related harms.

RECENT FINDINGS

Recent research advances our understanding of networks and HIV, including among understudied populations, and provides new insight into how risk environments shape the networks and health of substance-using populations. In particular, the integration of network approaches with molecular epidemiology, research on space and place, and intervention methods provides exciting new avenues of investigation. Continued advances in network research are critical to supporting the health and rights of substance-using populations and ensuring the development of high-impact HIV programs and policies.

A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability

BACKGROUND

Commercial geospatial data resources are frequently used to understand healthcare utilisation. Although there is widespread evidence of a digital divide for other digital resources and infra-structure, it is unclear how commercial geospatial data resources are distributed relative to health need.

METHODS

To examine the distribution of commercial geospatial data resources relative to health needs, we assembled coverage and quality metrics for commercial geocoding, neighbourhood characterisation, and travel time calculation resources for 183 countries. We developed a country-level, composite index of commercial geospatial data quality/availability and examined its distribution relative to age-standardised all-cause and cause specific (for three main causes of death) mortality using two inequality metrics, the slope index of inequality and relative concentration index. In two sub-national case studies, we also examined geocoding success rates versus area deprivation by district in Eastern Region, Ghana and Lagos State, Nigeria.

RESULTS

Internationally, commercial geospatial data resources were inversely related to all-cause mortality. This relationship was more pronounced when examining mortality due to communicable diseases. Commercial geospatial data resources for calculating patient travel times were more equitably distributed relative to health need than resources for characterising neighbourhoods or geocoding patient addresses. Countries such as South Africa have comparatively high commercial geospatial data availability despite high mortality, whilst countries such as South Korea have comparatively low data availability and low mortality. Sub-nationally, evidence was mixed as to whether geocoding success was lowest in more deprived districts.

CONCLUSIONS

To our knowledge, this is the first global analysis of commercial geospatial data resources in relation to health outcomes. In countries such as South Africa where there is high mortality but also comparatively rich commercial geospatial data, these data resources are a potential resource for examining healthcare utilisation that requires further evaluation. In countries such as Sierra Leone where there is high mortality but minimal commercial geospatial data, alternative approaches such as open data use are needed in quantifying patient travel times, geocoding patient addresses, and characterising patients' neighbourhoods.

Impact of Public Safety Policies on Human Immunodeficiency Virus Transmission Dynamics in Tijuana, Mexico

Background

North Tijuana, Mexico is home to many individuals at high risk for transmitting and acquiring human immunodeficiency virus (HIV). Recently, policy shifts by local government impacted how these individuals were handled by authorities. Here we examined how this affected regional HIV transmission dynamics.

Methods

HIV pol sequences and associated demographic information were collected from 8 research studies enrolling persons in Tijuana and were used to infer viral transmission patterns. To evaluate the impact of recent policy changes on HIV transmission dynamics, qualitative interviews were performed on a subset of recently infected individuals.

Results

Between 2004 and 2016, 288 unique HIV pol sequences were obtained from individuals in Tijuana, including 46.4% from men who have sex with men, 42.1% from individuals reporting transactional sex, and 27.8% from persons who inject drugs (some individuals had >1 risk factor). Forty-two percent of sequences linked to at least 1 other sequence, forming 37 transmission clusters. Thirty-two individuals seroconverted during the observation period, including 8 between April and July 2016. Three of these individuals were putatively linked together. Qualitative interviews suggested changes in policing led individuals to shift locations of residence and injection drug use, leading to increased risk taking (eg, sharing needles).

Conclusions

Near real-time molecular epidemiologic analyses identified a cluster of linked transmissions temporally associated with policy shifts. Interviews suggested these shifts may have led to increased risk taking among individuals at high risk for HIV acquisition. With all public policy shifts, downstream impacts need to be carefully considered, as even well-intentioned policies can have major public health consequences.

Web-Based Survey Application to Collect Contextually Relevant Geographic Data With Exposure Times: Application Development and Feasibility Testing

Background

Although studies that characterize the risk environment by linking contextual factors with individual-level data have advanced infectious disease and substance use research, there are opportunities to refine how we define relevant neighborhood exposures; this can in turn reduce the potential for exposure misclassification. For example, for those who do not inject at home, injection risk behaviors may be more influenced by the environment where they inject than where they live. Similarly, among those who spend more time away from home, a measure that accounts for different neighborhood exposures by weighting each unique location proportional to the percentage of time spent there may be more correlated with health behaviors than one’s residential environment.

Objective

This study aimed to develop a Web-based application that interacts with Google Maps application program interfaces (APIs) to collect contextually relevant locations and the amount of time spent in each. Our analysis examined the extent of overlap across different location types and compared different approaches for classifying neighborhood exposure.

Methods

Between May 2014 and March 2017, 547 participants enrolled in a Baltimore HIV care and prevention study completed an interviewer-administered Web-based survey that collected information about where participants were recruited, worked, lived, socialized, injected drugs, and spent most of their time. For each location, participants gave an address or intersection which they confirmed using Google Map and Street views. Geographic coordinates (and hours spent in each location) were joined to neighborhood indicators by Community Statistical Area (CSA). We computed a weighted exposure based on the proportion of time spent in each unique location. We compared neighborhood exposures based on each of the different location types with one another and the weighted exposure using analysis of variance with Bonferroni corrections to account for multiple comparisons.

Results

Participants reported spending the most time at home, followed by the location where they injected drugs. Injection locations overlapped most frequently with locations where people reported socializing and living or sleeping. The least time was spent in the locations where participants reported earning money and being recruited for the study; these locations were also the least likely to overlap with other location types. We observed statistically significant differences in neighborhood exposures according to the approach used. Overall, people reported earning money in higher-income neighborhoods and being recruited for the study and injecting in neighborhoods with more violent crime, abandoned houses, and poverty.

Conclusions

This analysis revealed statistically significant differences in neighborhood exposures when defined by different locations or weighted based on exposure time. Future analyses are needed to determine which exposure measures are most strongly associated with health and risk behaviors and to explore whether associations between individual-level behaviors and neighborhood exposures are modified by exposure times.

A rural/urban comparison of privacy and confidentiality concerns associated with providing sensitive location information in epidemiologic research involving persons who use drugs

BACKGROUND

Analyses that link contextual factors with individual-level data can improve our understanding of the "risk environment"; however, the accuracy of information provided by participants about locations where illegal/stigmatized behaviors occur may be influenced by privacy/confidentiality concerns that may vary by setting and/or data collection approach.

METHODS

We recruited thirty-five persons who use drugs from a rural Appalachian town and a Mid-Atlantic city to participate in in-depth interviews. Through thematic analyses, we identified and compared privacy/confidentiality concerns associated with two survey methods that (1) collect self-reported addresses/cross-streets and (2) use an interactive web-based map to find/confirm locations in rural and urban settings.

RESULTS

Concerns differed more by setting than between methods. For example, (1) rural participants valued interviewer rapport and protections provided by the Certificate of Confidentiality more; (2) locations considered to be sensitive differed in rural (i.e., others' homes) and urban (i.e., where drugs were used) settings; and (3) urban participants were more likely to view providing cross-streets as an acceptable alternative to providing exact addresses for sensitive locations and to prefer the web-based map approach.

CONCLUSION

Rural-urban differences in privacy/confidentiality concerns reflect contextual differences (i.e., where drugs are used/purchased, population density, and prior drug-related arrests). Strategies to alleviate concerns include: (1) obtain a Certificate of Confidentiality, (2) collect geographic data at the scale necessary for proposed analyses, and (3) permit participants to provide intersections/landmarks in close proximity to actual locations rather than exact addresses or to skip questions where providing an intersection/landmark would not obfuscate the actual address.

Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California

Background

Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks.

Objectives

This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California.

Methods

From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities.

Results

The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles.

Conclusions

The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time.