University of Zimbabwe

About: University of Zimbabwe is a education organization based out in Harare, Harare, Zimbabwe. It is known for research contribution in the topics: Population & Acquired immunodeficiency syndrome (AIDS). The organization has 4378 authors who have published 6800 publications receiving 160720 citations. The organization is also known as: UZ & University College of Rhodesia and Nyasaland.

Poisoning in Zimbabwe: a survey of eight major referral hospitals.

Abstract: A retrospective study of the pattern of poisoning cases admitted to eight major urban referral hospitals in Zimbabwe over a 2-year period (1998-1999 inclusive) was conducted to describe the pattern of poisoning at these centres. There were a total of 2764 hospital admissions due to poisoning, involving a total of 2846 toxic agents. Accidental poisoning (AP) and deliberate self-poisoning (DSP) accounted for 48.9% (1352 cases) and 41.3% (1142 cases), respectively. With AP, the highest number of cases (45.9%) occurred in children below the age of 5 years, with half of these due to chemicals, mainly paraffin. In the DSP group, however, more than 60% of all cases occurred in the 16-25-year age group. In addition, twice as many females as males were admitted for DSP compared with an overall male/female ratio of 1 : 1.2. Pesticides (31.4%) and pharmaceuticals (30.4%) were the most common groups of toxic agents responsible for the hospital admissions. Unknown toxins, natural toxins and pesticides showed the highest mortality rates (15.4%, 8.3% and 6.7%, respectively). Compared with the last major survey of poisoning in Zimbabwe, the pattern of poisoning at referral hospitals has changed over the last decade, with an increase in pesticide and pharmaceutical cases and a marked fall in cases of traditional medicine poisoning. Educational and legislative interventions may be required to address these changes. There is the need also to investigate further the high mortality rates associated with traditional medicine poisoning.

Prediction of base flows from basin characteristics : a case study from Zimbabwe

Abstract: Base flows make up the flows of most rivers in Zimbabwe during the dry season. Prediction of base flows from basin characteristics is necessary for water resources planning of ungauged basins. Linear regression and artificial neural networks were used to predict the base flow index (BFI) from basin characteristics for 52 basins in Zimbabwe. Base flow index was positively related to mean annual precipitation (r = 0.71), basin slope (r = 0.76), and drainage density (r = 0.29), and negatively related to mean annual evapotranspiration (r = –0.74), and proportion of a basin with grasslands and wooded grasslands (r = –0.53). Differences in lithology did not significantly affect BFI. Linear regression and artificial neural networks were both suitable for predicting BFI values. The predicted BFI was used in turn to derive flow duration curves of the 52 basins and with R 2 being 0.89–0.99.