Browsing by Author "Van Schalkwyk, C."
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- ItemBED estimates of HIV incidence : resolving the differences, making things simpler(PLOS, 2012-01) Hargrove, J.; Van Schalkwyk, C.; Eastwood, H.Objective: Develop a simple method for optimal estimation of HIV incidence using the BED capture enzyme immunoassay. Design: Use existing BED data to estimate mean recency duration, false recency rates and HIV incidence with reference to a fixed time period, T. Methods: Compare BED and cohort estimates of incidence referring to identical time frames. Generalize this approach to suggest a method for estimating HIV incidence from any cross-sectional survey. Results: Follow-up and BED analyses of the same, initially HIV negative, cases followed over the same set time period T, produce estimates of the same HIV incidence, permitting the estimation of the BED mean recency period for cases who have been HIV positive for less than T. Follow-up of HIV positive cases over T, similarly, provides estimates of the false-recent rate appropriate for T. Knowledge of these two parameters for a given population allows the estimation of HIV incidence during T by applying the BED method to samples from cross-sectional surveys. An algorithm is derived for providing these estimates, adjusted for the false-recent rate. The resulting estimator is identical to one derived independently using a more formal mathematical analysis. Adjustments improve the accuracy of HIV incidence estimates. Negative incidence estimates result from the use of inappropriate estimates of the false-recent rate and/or from sampling error, not from any error in the adjustment procedure. Conclusions: Referring all estimates of mean recency periods, false-recent rates and incidence estimates to a fixed period T simplifies estimation procedures and allows the development of a consistent method for producing adjusted estimates of HIV incidence of improved accuracy. Unadjusted BED estimates of incidence, based on life-time recency periods, would be both extremely difficult to produce and of doubtful value.
- ItemExtracellular polymer production and potential for aggregate formation by classical propionibacteria(2003) Van Schalkwyk, C.; Joubert, H.; Britz, T.J.; Van Schalkwyk, C.; Joubert, H.; Britz, T.J.Nineteen Propionibacterium strains were screened for extracellular polymer (ECP) production. The best producer, P. jensenii S1, was introduced into two different media, Yeast Extract Lactate (YEL)-medium and Apricot Effluent (AE)-medium. The YEL medium samples were incubated in different mixing systems (a roller-table and a linear shaking platform) for 24 days at 35°C. According to the volatile fatty acids and pH profiles, no real differences could be detected between the two mixing systems. Bacterial aggregates were, however, only observed in the roller-table samples. The process was repeated with AE-medium on the roller-table. Larger and more stable flocs were observed in the AE-medium samples. Scanning electron microscopy and PCR analysis confirmed the presence of propionibacteria in these flocs even after 5 months of storage at 4°C. It was concluded that ECP-producing Propionibacterium strains could be manipulated to form bacterial flocs under certain environmental conditions, which might be enhanced in the presence of fibrous material occurring naturally in food industry effluents.
- ItemHow should we best estimate the mean recency duration for the BED method?(PLOS, 2012-11-16) Hargrove, J.; Eastwood, H.; Mahiane, G.; Van Schalkwyk, C.BED estimates of HIV incidence from cross-sectional surveys are obtained by restricting, to fixed time T, the period over which incidence is estimated. The appropriate mean recency duration (VT) then refers to the time where BED optical density (OD) is less than a pre-set cut-off C, given the patient has been HIV positive for at most time T. Five methods, tested using data for postpartum women in Zimbabwe, provided similar estimates of VT for C = 0.8: i) The ratio (r/s) of the number of BED-recent infections to all seroconversions over T = 365 days: 192 days [95% CI 168–216]. ii) Linear mixed modeling (LMM): 191 days [95% CI 174–208]. iii) Non-linear mixed modeling (NLMM): 196 days [95% CrI 188–204]. iv) Survival analysis (SA): 192 days [95% CI 168–216]. Graphical analysis: 193 days. NLMM estimates of VT - based on a biologically more appropriate functional relationship than LMM – resulted in best fits to OD data, the smallest variance in estimates of VT , and best correspondence between BED and follow-up estimates of HIV incidence, for the same subjects over the same time period. SA and NLMM produced very similar estimates of VT but the coefficient of variation of the former was .3 times as high. The r/s method requires uniformly distributed seroconversion events but is useful if data are available only from a single follow-up. The graphical method produces the most variable results, involves unsound methodology and should not be used to provide estimates of VT . False-recent rates increased as a quadratic function of C: for incidence estimation C should thus be chosen as small as possible, consistent with an adequate resultant number of recent cases, and accurate estimation of VT . Inaccuracies in the estimation of VT should not now provide an impediment to incidence estimation.
- ItemSymptom screening rules to identify active pulmonary tuberculosis : findings from the Zambian South African Tuberculosis and HIV/ AIDS Reduction (ZAMSTAR) trial prevalence surveys(Public Library of Science, 2017-03-03) Claassens, M. M.; Van Schalkwyk, C.; Floyd, S.; Ayles, H.; Beyers, NuldaBackground: High tuberculosis (TB) burden countries should consider systematic screening among adults in the general population. We identified symptom screening rules to be used in addition to cough ≥2 weeks, in a context where X-ray screening is not feasible, aiming to increase the sensitivity of screening while achieving a specificity of ≥85%. Methods: We used 2010 Zambia South Africa Tuberculosis and HIV/AIDS Reduction (ZAMSTAR) survey data: a South African (SA) training dataset, a SA testing dataset for internal validation and a Zambian dataset for external validation. Regression analyses investigated relationships between symptoms or combinations of symptoms and active disease. Sensitivity and specificity were calculated for candidate rules. Results: Among all participants, the sensitivity of using only cough ≥2 weeks as a screening rule was less than 25% in both SA and Zambia. The addition of any three of six TB symptoms (cough <2 weeks, night sweats, weight loss, fever, chest pain, shortness of breath), or 2 or more of cough <2 weeks, night sweats, and weight loss, increased the sensitivity to ~38%, while reducing specificity from ~95% to ~85% in SA and ~97% to ~92% in Zambia. Among HIV-negative adults, findings were similar in SA, whereas in Zambia the increase in sensitivity was relatively small (15% to 22%). Conclusion: High TB burden countries should investigate cost-effective strategies for systematic screening: one such strategy could be to use our rule in addition to cough ≥2 weeks.