Browsing by Author "Distiller, Greg B"

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    Substance abuse and HIV risk behaviours amongst primary health care service users in Cape Town
    (2005) Flisher, Alan J; Bresick, Graham F; Sterling, Stacy A; Bresick, Graham F; Sterling, Stacy A; Distiller, Greg B; Weisner, Constance M; Ward, Catherine L; Mertens, Jennifer R
    Objective: To document prevalence of, and association between, substance use and HIV risk behaviours among primary care patients.Method: Cross-sectional survey. Four primary care clinics in Cape Town. We selected clinics using stratified sampling, and systematically selected 131 patients from attendance logs. We assessed substance use with the Alcohol, Smoking and Substance Involvement Screening Test, and HIV risk with items addressing injection drug use, blood-sharing rituals, and sexual risk behaviours. Results: Substances most used at hazardous levels were tobacco (28.2%) and alcohol (14.8%). Among possible HIV risk factors, highest prevalence was participation in blood-sharing rituals (25%), and having had an STI (19.8%). An association between substance use and sexual risk behaviours was only found among those aged 18-24. Conclusion: In younger patients, presence of substance use or HIV risk behaviours increases the probability that the other is present.
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    Using mark-recapture methods to estimate population size and survival of pyjama sharks (Poroderma africanum) in Mossel Bay, South Africa
    (2017) Grusd, Samantha; Gennari, Enrico; Moloney, Coleen L; Distiller, Greg B
    Sharks are vulnerable to exploitation as a result of their biological characteristics. Markrecapture models were applied to conventional tag recapture data and acoustic telemetry data to estimate abundance, apparent survival, recapture probability and temporary emigration for the pyjama shark, Poroderma africanum in Mossel Bay, South Africa over a five-year period. This study applied Pollock's robust design (with the conventional tag data) and Cormack-Jolly-Seber (CJS) models (with the acoustic tag data) to analyze the mark-recapture data. In addition, a von Bertalanffy model was fit to the data to estimate individual growth. The best-fit robust design model showed the population as having no temporary emigration, survival probability that is dependent on the length at first capture, and time-constant capture probabilities. The best-fit CJS model showed the population also having time-constant survival, but sex dependent capture probabilities. Robust design abundance estimates (with 95% C.I.) in Mossel Bay varied from 279 (102-787) sharks to 733 (320-1777) sharks, although confidence intervals were quite large. CJS apparent annual survival (95% C.I.; CJS) was estimated to be 0.271 year⁻¹ (0.04 to 0.56) and annual recapture probability (95% C.I.) was estimated to be 0.008 year⁻¹ (0.003-0.20), indicating that survival and recaptures for this endemic species are relatively low. Annual somatic growth rate (k) was estimated to be 0.213 year⁻¹, indicating that this population is slow growing, a characteristic common in most shark species. Overall, the results in this study provide baseline knowledge on this population in Mossel Bay and can be used to implement proper management techniques. This knowledge can be further expanded upon to give a more in-depth understanding of all size and age classes in the population and the role that the environment and anthropogenic activities play in the population structure.