MALARIA IN CHILDREN IN ILORIN, NIGERIA

Objectives: To determine the prevalence of paediatric malaria admissions in an area of stablemalaria transmission and to ascertain the relative contributions of different forms of severemalaria to morbidity and mortality.Design: A descriptive restrospective study.Setting: Olanrewaju hospital, a general practice health facility in a malaria holoendemic cityin Nigeria.Subjects and rnethods: Case files of paediatric (age <15years) admissions between 1/1/98 and31/12/98 with a diagnosis of acute malaria were retrieved and relevant information includingdemographic data, clinical signs, laboratory records, treatments received and diagnosis ondischarge were extracted. Grouped age-associated prevalence rates were calculated;characteristics of different groups were compared using standard statistical methods.Results: Children with Falciparum malaria accounted for 95 (18%) of the 526 medicaladmissions. The proportion of children admitted with severe malaria was significantlyhigher among the under-fives compared to those over five years (p< 0.001; RR=S.36,95 %CI of 2.58 to 11.2). Thirty two (33.7%) children had severe malaria. Fifteen (15.8%) hadconvulsions without coma, 13 (13.68%) had malaria-associated anaemia and four (4.2%)were diagnosed as having had cerebral malaria. Seizures were significantly more frequentin the under-fives (p=0.001, RR=6.0; 95 % CI of 1.8 to 19.6). There was a significant negativecorrelation between age and severe anaemialblood transfusions (p=0.002). Cerebral malariacarried the greatest risk of fatality (CFR=25%; RR=7,95% CI of 1.5 to 91).Conclusion: High prevalence of paediatric malaria admissions in this study underscores themorbidity burden in Nigerian children, especially in under-fives in whom the severe formsare more common. A high incidence of anaemia requiring blood transfusions furtherincreases the risk of paediatric HIV infectionin Nigeria where organised control programmesare rudimentary

Exploring hyper-heuristic methodologies with genetic programming

Hyper-heuristics represent a novel search methodology that is motivated by the goal of automating the process of selecting or combining simpler heuristics in order to solve hard computational search problems. An extension of the original hyper-heuristic idea is to generate new heuristics which are not currently known. These approaches operate on a search space of heuristics rather than directly on a search space of solutions to the underlying problem which is the case with most meta-heuristics implementations. In the majority of hyper-heuristic studies so far, a framework is provided with a set of human designed heuristics, taken from the literature, and with good measures of performance in practice. A less well studied approach aims to generate new heuristics from a set of potential heuristic components. The purpose of this chapter is to discuss this class of hyper-heuristics, in which Genetic Programming is the most widely used methodology. A detailed discussion is presented including the steps needed to apply this technique, some representative case studies, a literature review of related work, and a discussion of relevant issues. Our aim is to convey the exciting potential of this innovative approach for automating the heuristic design process