Full project title:
Network Canvas: Development, Hardening, and Dissemination of a Software Suite for the Collection of Complex Network and Contextual Data in HIV and Drug Research
A thorough understanding of population dynamics is vital for reducing the spread of infectious and for informing disease control. This is particularly true with HIV, due to its high transmission dependence on drug and sexual network dynamics. For stigmatised populations with large disparities in the prevalence of HIV, structural determinants (e.g. poverty, access to care, stigma – the context surrounding the population) also drive disease. Therefore, the collection of network and contextual data is a high priority for researchers, but one that unfortunately poses enormous methodological challenges. In particular, the nature of these data has introduced new complexities in data collection, processing, and storage, limiting accessibility to only those who possess the strong technical expertise and resources necessary to create bespoke solutions.
Given these challenges, and fuelled by lower costs and easier access to ‘big data,’ some health and HIV researchers have turned to trace data (e.g. Twitter, Facebook) to facilitate their work. Yet, these approaches cannot replace data collected directly from individuals, since the network structure through which HIV is transmitted, the relevant behavioural data (e.g. condomless anal sex, injection drug use), and an individual’s disease status (e.g. HIV, gonorrhoea) are not readily obtainable from social media sites.
Benefiting from recent convergences in technologies, and responding to the clear need within the research community, the project researchers have already developed a software tool (netCanvas-R) that can quickly and accurately capture complex network and contextual data directly from a participant. This project seeks to build upon this work by evolving this novel and highly effective data collection and management tool (which was originally optimised for a single study) into a standalone software suite. This suite will ensure accessibility to all researchers, particularly HIV and drug researchers, who are interested in the capture of complex network and contextual data.
To extend and harden existing capabilities and build a standalone Network Canvas software suite. This will provide researchers with a user-friendly, generalizable, and customizable tool that will facilitate the efficient capture, storage, monitoring, and export of complex network, longitudinal, geospatial, contextual and behavioural data.
To ensure the sustainability of the Network Canvas software suite. Promotional work, engagement activities, and the production of strong documentation, tutorials, and training materials will build a community that will sustain the open source and freely available software suite.
Strictly Necessary Cookies
moove_gdrp_popup - a cookie that saves your preferences for cookie settings. Without this cookie, the screen offering you cookie options will appear on every page you visit.
This cookie remains on your computer for 365 days, but you can adjust your preferences at any time by clicking on the "Cookie settings" link in the website footer.
Please note that if you visit the Oxford University website, any cookies you accept there will appear on our site here too, this being a subdomain. To control them, you must change your cookie preferences on the main University website.
This website uses Google Tags and Google Analytics to collect anonymised information such as the number of visitors to the site, and the most popular pages. Keeping these cookies enabled helps the OII improve our website.
Enabling this option will allow cookies from:
Google Analytics - tracking visits to the ox.ac.uk and oii.ox.ac.uk domains
These cookies will remain on your website for 365 days, but you can edit your cookie preferences at any time via the "Cookie Settings" button in the website footer.
Please enable Strictly Necessary Cookies first so that we can save your preferences!