The effect of HIV, behavioural change, and STD syndromic management on STD epidemiology in sub-Saharan Africa: simulations of Uganda

An assessment was made of how the HIV epidemic may have influenced sexually transmitted disease (STD) epidemiology in Uganda, and how HIV would affect the effectiveness of syndromic STD treatment programmes during different stages of the epidemic. The dynamic transmission model STDSIM was used to simulate the spread of HIV and four bacterial and one viral STD. Model parameters were quantified using demographic, behavioural, and epidemiological data from rural Rakai and ot

Effects of meteorological factors on epidemic malaria in Ethiopia: a statistical modelling approach based on theoretical reasoning.

This study was conducted to quantify the association between meteorological variables and incidence of Plasmodium falciparum in areas with unstable malaria transmission in Ethiopia. We used morbidity data pertaining to microscopically confirmed cases reported from 35 sites throughout Ethiopia over a period of approximately 6-7 years. A model was developed reflecting biological relationships between meteorological and morbidity variables. A model that included rainfall 2 and 3 months earlier, mean minimum temperature of the previous month and P. falciparum case incidence during the previous month was fitted to morbidity data from the various areas. The model produced similar percentages of over-estimation (19.7% of predictions exceeded twice the observed values) and under-estimation (18.6%, were less than half the observed values). Inclusion of maximum temperature did not improve the model. The model performed better in areas with relatively high or low incidence (>85% of the total variance explained) than those with moderate incidence (55-85% of the total variance explained). The study indicated that a dynamic immunity mechanism is needed in a prediction model. The potential usefulness and drawbacks of the modelling approach in studying the weather-malaria relationship are discussed, including a need for mechanisms that can adequately handle temporal variations in immunity to malaria

Risk factors for septic arthritis in patients with joint disease: A prospective study

Objective. To quantify potential risk factors for septic arthritis, in order to identify a basis for prevention. Methods. The occurrence of potential risk factors for septic arthritis in patients with joint diseases attending a rheumatic disease clinic was prospectively monitored at 3-m onth intervals over a period of 3 years. Potential risk factors investigated were type of joint disease, comorbidity, medication, joint prosthesis, infections, and invasive procedures. The frequencies of risk factors in patients with and those without septic arthritis were compared using multiple logistic regression analysis. Results. There were 37 patients with and 4,870 without septic arthritis. Risk factors for developing septic arthritis were age ≥80 years (odds ratio [OR] = 3.5, 95% confidence interval [95% CI] 1.4–8.6), diabetes mellitus (OR = 3.3, 95% CI 1.1–10.1), rheumatoid arthritis (OR = 4.0, 95% CI 1.9–8.3), hip and/or knee prosthesis (OR = 15, 95% CI 4.1–54.3), joint surgery (OR = 5.1, 95% CI 2.2–11.9), and skin infection (OR = 27.2, 95% CI 7.6–97.1) Conclusion. These findings indicate that preventive measures against septic arthritis in patients with joint diseases should mainly be directed at those with joint prostheses and/or skin infection

Kernel density classification and boosting: an L2 sub analysis

Kernel density estimation is a commonly used approach to classification. However, most of the theoretical results for kernel methods apply to estimation per se and not necessarily to classification. In this paper we show that when estimating the difference between two densities, the optimal smoothing parameters are increasing functions of the sample size of the complementary group, and we provide a small simluation study which examines the relative performance of kernel density methods when the final goal is classification. A relative newcomer to the classification portfolio is “boosting”, and this paper proposes an algorithm for boosting kernel density classifiers. We note that boosting is closely linked to a previously proposed method of bias reduction in kernel density estimation and indicate how it will enjoy similar properties for classification. We show that boosting kernel classifiers reduces the bias whilst only slightly increasing the variance, with an overall reduction in error. Numerical examples and simulations are used to illustrate the findings, and we also suggest further areas of research

The impact of pre-exposure prophylaxis (PrEP) on HIV epidemics in Africa and India: A simulation study

Background: Pre-exposure prophylaxis (PrEP) is a promising new HIV prevention method, especially for women. An urgent demand for implementation of PrEP is expected at the moment efficacy has been demonstrated in clinical trials. We explored the long-term impact of PrEP on HIV transmission in different HIV epidemics. Methodology/Principal Findings: We used a mathematical model that distinguishes the general population, sex workers and their clients. PrEP scenarios varying in effectiveness, coverage and target group were modeled in the epidemiological settings of Botswana, Nyanza Province in Kenya, and Southern India. We also studied the effect of condom addition or condom substitution during PrEP use. Main outcome was number of HIV infections averted over ten years of PrEP use. PrEP strategies with high effectiveness and high coverage can have a substantial impact in African settings. In Southern India, by contrast, the number of averted HIV infections in different PrEP scenarios would be much lower. The impact of PrEP may be strongly diminished or even reversed by behavioral disinhibition, especially in scenarios with low coverage and low effectiveness. However, additional condom use during low coverage and low effective PrEP doubled the amount of averted HIV infections. Conclusions/Significance: The public health impact of PrEP can be substantial. However, this impact may be diminished, or even reversed, by changes in risk behavior. Implementation of PrEP strategies should therefore come on top of current condom campaigns, not as a substitution