PubMed · 10111081
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R Henson. 1991. Computer databases built for HR.. https://pubmed.ncbi.nlm.nih.gov/10111081/
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INTRODUCTION: Sustainable control of malaria in sub-Saharan Africa is jeopardized by dwindling public health resources resulting from competing health priorities that include an overwhelming acquired immunodeficiency syndrome (AIDS) epidemic. In Mpumalanga province, South Africa, rational planning has historically been hampered by a case surveillance system for malaria that only provided estimates of risk at the magisterial district level (a subdivision of a province). METHODS: To better map control programme activities to their geographical location, the malaria notification system was overhauled and a geographical information system implemented. The introduction of a simplified notification form used only for malaria and a carefully monitored notification system provided the good quality data necessary to support an effective geographical information system. RESULTS: The geographical information system displays data on malaria cases at a village or town level and has proved valuable in stratifying malaria risk within those magisterial districts at highest risk, Barberton and Nkomazi. The conspicuous west-to-east gradient, in which the risk rises sharply towards the Mozambican border (relative risk = 4.12, 95% confidence interval = 3.88-4.46 when the malaria risk within 5 km of the border was compared with the remaining areas in these two districts), allowed development of a targeted approach to control. DISCUSSION: The geographical information system for malaria was enormously valuable in enabling malaria risk at town and village level to be shown. Matching malaria control measures to specific strata of endemic malaria has provided the opportunity for more efficient malaria control in Mpumalanga province.
A computer-based method was developed for rapid and automatic identification of potential "frequent hitters". These compounds show up as hits in many different biological assays covering a wide range of targets. A scoring scheme was elaborated from substructure analysis, multivariate linear and nonlinear statistical methods applied to several sets of one and two-dimensional molecular descriptors. The final model is based on a three-layered neural network, yielding a predictive Matthews correlation coefficient of 0.81. This system was able to correctly classify 90% of the test set molecules in a 10-times cross-validation study. The method was applied to database filtering, yielding between 8% (compilation of trade drugs) and 35% (Available Chemicals Directory) potential frequent hitters. This filter will be a valuable tool for the prioritization of compounds from large databases, for compound purchase and biological testing, and for building new virtual libraries.
A sample of 1176 males from 10 Italian regions have been typed for DYS19, DYS389-I, DYS389-II, DYS390, DYS391, DYS392, DYS393, and DYS385. Individual haplotype data are available on line. A low degree of variation is present among regions. Use of this database is specifically recommended for forensic applications in Italy.