Agent-based modelling study of antimicrobial-resistant Neisseria gonorrhoeae transmission in men who have sex with men: towards individualised diagnosis and treatment.

Background Antimicrobial-resistant (AMR) gonorrhoea is a global public health threat. Discriminatory point-of-care tests (POCT) to detect drug sensitivity are under development, enabling individualised resistance-guided therapy. METHODS: An individual-based dynamic transmission model of gonorrhoea infection in MSM living in London has been developed, incorporating ciprofloxacin-sensitive and resistant strains. The time-dependent sexual contact network is captured by periodically restructuring active connections to reflect the transience of contacts. Different strategies to improve treatment selection were explored, including discriminatory POCT and selecting partner treatment based on either the index case or partner susceptibility. Outcomes included population prevalence of gonorrhoea and drug dose counts. RESULTS: It is shown that using POCT to detect ciprofloxacin-sensitive infections could result in a large decrease in ceftriaxone doses (by 70% compared with the reference case in the simulations of this study). It also suggests that ceftriaxone use can be reduced with existing technologies, albeit to a lesser degree; either using index case sensitivity profiles to direct treatment of partners, or testing notified partners with strain discriminatory laboratory tests before treatment, reduced ceftriaxone use in our model (by 27% and 47% respectively). CONCLUSIONS: POCT to detect ciprofloxacin-sensitive gonorrhoea are likely to dramatically reduce reliance on ceftriaxone, but requires the implementation of new technology. In the meantime, the proportion of unnecessary ceftriaxone treatment by testing partners before treatment could be reduced significantly. Alternatively, index case sensitivity profiles could be used to select effective treatments for partners.

Data-driven modelling of social forces and collective behaviour in zebrafish.

Zebrafish are rapidly emerging as a powerful model organism in hypothesis-driven studies targeting a number of functional and dysfunctional processes. Mathematical models of zebrafish behaviour can inform the design of experiments, through the unprecedented ability to perform pilot trials on a computer. At the same time, in-silico experiments could help refining the analysis of real data, by enabling the systematic investigation of key neurobehavioural factors. Here, we establish a data-driven model of zebrafish social interaction. Specifically, we derive a set of interaction rules to capture the primary response mechanisms which have been observed experimentally. Contrary to previous studies, we include dynamic speed regulation in addition to turning responses, which together provide attractive, repulsive and alignment interactions between individuals. The resulting multi-agent model provides a novel, bottom-up framework to describe both the spontaneous motion and individual-level interaction dynamics of zebrafish, inferred directly from experimental observations.

Web-Based Activity Within a Sexual Health Economy: Observational Study.

BACKGROUND: Regular testing for sexually transmitted infections (STIs) is important to maintain sexual health. Self-sampling kits ordered online and delivered in the post may increase access, convenience, and cost-effectiveness. Sexual health economies may target limited resources more effectively by signposting users toward Web-based or face-to-face services according to clinical need. OBJECTIVE: The aim of this paper was to investigate the impact of two interventions on testing activity across a whole sexual health economy: (1) the introduction of open access Web-based STI testing services and (2) a clinic policy of triage and signpost online where users without symptoms who attended clinics for STI testing were supported to access the Web-based service instead. METHODS: Data on attendances at all specialist public sexual health providers in an inner-London area were collated into a single database. Each record included information on user demographics, service type accessed, and clinical activity provided, including test results. Clinical activity was categorized as a simple STI test (could be done in a clinic or online), a complex visit (requiring face-to-face consultation), or other. RESULTS: Introduction of Web-based services increased total testing activity across the whole sexual health economy by 18.47% (from 36,373 to 43,091 in the same 6-month period-2014-2015 and 2015-2016), suggesting unmet need for testing in the area. Triage and signposting shifted activity out of the clinic onto the Web-based service, with simple STI testing in the clinic decreasing from 16.90% (920/5443) to 12.25% (511/4172) of total activity, P<.001, and complex activity in the clinic increasing from 69.15% (3764/5443) to 74.86% (3123/4172) of total activity, P<.001. This intervention created a new population of online users with different demographic and clinical profiles from those who use Web-based services spontaneously. Some triage and signposted users (29.62%, 375/1266) did not complete the Web-based testing process, suggesting the potential for missed diagnoses. CONCLUSIONS: This evaluation shows that users can effectively be transitioned from face-to-face to Web-based services and that this introduces a new population to Web-based service use and changes the focus of clinic-based activity. Further development is underway to optimize the triage and signposting process to support test completion.