A clinical algorithm for the diagnosis of malaria: results of an evaluation in an area of low endemicity

Open Access
Publisher Website
Google Scholar
Abstract
We conducted a study of 1945 children and 2885 adults who presented with fever to a hospital outpatients clinic in an urban area of India order to develop and evaluate a clinical algorithm for the diagnosis of malaria. Only 139 (7%) children and 349 (12%) adults had microscopically confirmed malaria. None of the symptoms or signs elicited from the respondents were good predictors of clinical malaria. Simple scores were derived through combining clinical features which were associated with slide positivity or were judged by clinicians to be important. The best‐performing algorithms were a score of 4 clinical features in children (sensitivity 60.0% and specificity 61.2%) and a score of 5 in adults (sensitivity 54.6% and specificity 57.5%). The clinical features differed and algorithm performances were poorer than in previous studies in highly endemic areas. The conclusion is that malaria diagnosis in areas of low endemicity requires microscopy to be accurate.