Symptomatic malaria diagnosis overestimate malaria prevalence, but underestimate anaemia burdens in children: results of a follow up study in Kenya
- Equal contributors
1 Kabianga University College, P.O. Box 2030-20200, Kericho, Kenya
2 Department of Medical Physiology, School of Medicine, Moi University, P.O. Box 4606, Eldoret, Kenya
3 Disease Prevention and Control, Ministry of Public Health, Kenya, P.O. BOX 45335, 00100 (GPO) Nairobi, Kenya
4 School Natural Resources and Environmental Studies, Karatina University, P.O. Box 1957-10101, Karatina, Kenya
5 Department of Aquatic Ecology and Ecotoxicology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Science Park 904, Amsterdam 1098 XH, The Netherlands
6 Department of Environmental Biology and Health, School of Environmental Studies, University of Eldoret, P.O. Box 1125, Eldoret, Kenya
7 Institute of Tropical Medicine and Infectious Diseases (ITROMID), Jomo Kenyatta University of Agriculture and Technology (JKUAT), P.O. Box 62000-00200, Nairobi, Kenya
8 Tropical Pesticides Research Institute, Division of Livestock and Human Diseases Vector Control, Mosquito Section, Ngaramtoni, Off Nairobi road, P.O. Box 3024, Arusha, Tanzania
BMC Public Health 2014, 14:332 doi:10.1186/1471-2458-14-332Published: 9 April 2014
The commonly accepted gold standard diagnostic method for detecting malaria is a microscopic reading of Giemsa-stained blood films. However, symptomatic diagnosis remains the basis of therapeutic care for the majority of febrile patients in malaria endemic areas. This study aims to compare the discrepancy in malaria and anaemia burdens between symptomatic diagnosed patients with those diagnosed through the laboratory.
Data were collected from Western Kenya during a follow-up study of 887 children with suspected cases of malaria visiting the health facilities. In the laboratory, blood samples were analysed for malaria parasite and haemoglobin levels. Differences in malaria prevalence between symptomatic diagnosis and laboratory diagnosis were analysed by Chi-square test. Bayesian probabilities were used for the approximation of the malaria and anaemia burdens. Regression analysis was applied to: (1) determine the relationships between haemoglobin levels, and malaria parasite density and (2) relate the prevalence of anaemia and the prevalence of malaria.
The prevalence of malaria and anaemia ranged from 10% to 34%, being highest during the rainy seasons. The predominant malaria parasite was P. falciparum (92.3%), which occurred in higher density in children aged 2‒5 years. Fever, high temperature, sweating, shivering, vomiting and severe headache symptoms were associated with malaria during presumptive diagnosis. After conducting laboratory diagnosis, lower malaria prevalence was reported among the presumptively diagnosed patients. Surprisingly, there were no attempts to detect anaemia in the same cohort. There was a significant negative correlation between Hb levels and parasite density. We also found a positive correlation between the prevalence of anaemia and the prevalence of malaria after laboratory diagnosis indicating possible co-occurrence of malaria and anaemia.
Symptomatic diagnosis of malaria overestimates malaria prevalence, but underestimates the anaemia burden in children. Good clinical practice dictates that a laboratory should confirm the presence of parasites for all suspected cases of malaria.