Performance Assessment of Malaria Conventional and Molecular Diagnostics Processes by a Computational Statistical Approach

Dagnogo Oléfongo^{1, 2}, Dago Dougba Noel^3, , Eboulé Ago Eliane Rebecca³, Koffi N'Guessan Bénédicte Sonia^{3, 4} and Djaman Allico Joseph^{1, 2}

¹Biosciences Training and Research Unit (UFR), Biology and Health Laboratory, Felix Houphouët-Boigny University, BP V 34 Abidjan 01, Ivory Coast

²Pasteur Institute of Côte d’Ivoire, Department of Parasitology-Mycology. 01 BP 490 Abidjan 01, Côte d’Ivoire

³Training and Research Unit (UFR) of Biological Sciences, Pedagogical and Research Unit (UPR) of Genetics, Peleforo Gon Coulibaly University, Korhogo, Côte d’Ivoire

⁴Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biology and Genetics, University of Verona, Italy

Cite this paper:
Dagnogo Oléfongo, Dago Dougba Noel, Eboulé Ago Eliane Rebecca, Koffi N'Guessan Bénédicte Sonia and Djaman Allico Joseph. Performance Assessment of Malaria Conventional and Molecular Diagnostics Processes by a Computational Statistical Approach. American Journal of Microbiological Research. 2023; 11(4):106-118. doi: 10.12691/ajmr-11-4-3

Abstract

Background: Malaria is the most widespread infectious disease in the world, especially in developing countries. The World Health Organization (WHO) recommends that malaria should be diagnosed biologically before antimalarial treatment starting. Several tests are available for its diagnosis, albeit with varying degrees of sensitivity and specificity. The limitations of the thick drop technique and the advent of molecular diagnostic techniques, which have revolutionized therapeutic approaches in several biomedical fields, led us to evaluate the performance of conventional and molecular malaria diagnostic tests at three experimental sites in Côte d'Ivoire. Methodology: We collected blood, saliva and urine samples in Anonkoua-kouté, Port-Bouët, and Ayamé from 93 patients with microscopically confirmed uncomplicated P. falciparum malaria. These patients, aged over 2 years, gave their informed consent before blood, saliva and urine samples were taken. P. falciparum genomic DNA extracted from these samples was amplified by nested PCR using primers specific to certain P. falciparum genes (Pfk13 propeller, pfdhfr and pfcrt genes). Computational statistical analyses requiring various functions and/or scripts of the R software (v 4.1.0) were performed on the data relating to the parasite density of malaria patients subjected to conventional (thick drop and blood smear) and molecular diagnostic procedures. Results: Significant variability in parasite density was observed at all three sites (p<0.05), with a higher parasite density at the Port-Bouët site. The conventional malaria diagnostic system performed moderately well at all three sites and for all patients (AUC=61.4%-62.9%). This performance tended to improve markedly when malaria patients were discriminated by age in young and adult patients (AUC=77.3%-78%), suggesting the susceptibility of the classical malaria diagnostic method to this anthropomorphic parameter. ROC analysis supported a very high performance of the molecular diagnosis of malaria for the biomarkers pfcrt and pfdhfr in the three biological fluids (AUC=100%) in contrast to the molecular biomarker pk13 propeller (AUC=50%). Considering biological fluids, ROC analysis suggested very high performance of malaria molecular diagnostic process for blood sample (AUC=100%) in contrast to saliva (AUC=79.8%) and urine (76.4%) which exhibited moderate performance. Conclusion: Considering as whole, malaria molecular diagnosis, although depending on molecular biomarkers typology as well as biological fluid, performs better than conventional diagnosis, which performances result strongly linked to patient’s age.

Keywords:
malaria classical diagnosis molecular diagnosis molecular markers roc analysis Côte d’Ivoire.

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