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

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

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