Predicting Malaria Infection using Haematological Indices: A Case Study at Bremang SDA Hospital in the Suame Municipality of the Ashanti Region, Ghana

Abstract

Background: Malaria continues to wreak havoc in Africa, which accounted for about 96% of global cases in 2020. Malaria deaths increased by 12% compared with 2019, to an estimated 627000; an estimated 47000 (68%) of the additional 69000 deaths were due to service disruptions during the COVID-19 pandemic. Full blood count (FBC) and malaria microscopy are among the commonest tests run in most laboratories in Ghana. This study looked at the possibility of predicting malaria infection using results from a full blood count. Methodology: This retrospective hospital-based observational study involved 400 samples. Data on age, sex, FBC and blood film for malaria parasites were obtained as secondary data from the laboratory unit of Bremang SDA Hospital in the Suame Municipality of the Ashanti Region of Ghana. Fischer’s exact test was used to evaluate the association of demographic characteristics with malaria status. Multivariate logistic regression was used to determine significant predictor variables for malaria positive status with p-value<0.05. Results: There was no association between malaria-positive status and either age or sex. All positive samples (n=41) were P. falciparum. The crude odds ratios revealed that all platelet parameters, absolute counts of lymphocytes, monocytes and eosinophils as well as per centages of neutrophils, lymphocytes and eosinophils were associated with malaria-positive status (p-value<0.05). In the overall model, only mean platelet volume was found to be statistically significant with AOR=164.44 (p-value<0.001). The model had a sensitivity of 56.10%, specificity of 98.33%, and positive predictive and negative predictive values of 79.31% and 95.15% respectively. Conclusion: The findings demonstrate that malaria infection alters haematological parameters and that these can be used to predict malaria infection in the study population. Prescribers in the study area are therefore encouraged to consider platelet parameters especially mean platelet volume as predictors of malaria infection.