| dc.description.abstract | Malaria remains one of the most devastating infectious diseases in the world with an estimated 207 million cases of infection and over 500,000 deaths annually. Malaria eradication programs have seen a 42% decrease in incidence and 66% decrease in mortality in Africa but complete control and eradication requires proper diagnostic methods for detection, species identification and
quantification of the parasite. Microscopy is the gold standard for diagnosis but false positives, false negatives, errors in species identification, and errors in enumeration of parasites make it unreliable in detection of submicroscopic parasites. The introduction of quantitative real-time PCR (qPCR) has improved submicroscopic malaria diagnosis especially in clinical trials and drug efficacy studies. Most qPCR methods target different genes in the parasite genome with most detecting 18S-rRNA, although there are many other non-18S-rRNA-qPCR methods being developed. The data reported here came from a cross sectional study that collected 127 blood samples from five locations in Kenya. Malaria microscopy was performed by independent microscopists who identified the infecting species as well as the parasite density. The 18S-rRNAqPCR and non-18S-rRNA-qPCR assays were performed at the Walter Reed Basic Science Laboratory in Kisumu and identified the infecting species as well as the parasite density. The sensitivity, specificity, predictive values, likelihood ratios and method odds ratios were estimated
using Fishers exact test. McNemar-χ tests were used to investigate the accuracy between the three methods, Cohen Kappa value was used to quantify the method agreement and Bland Altman test was used to assess the limits of agreement. Correlation between microscopy and qPCR parasite densities was determined by the Spearman’s rank test. Statistical significance was calculated at P<0.05. The sensitivity and specificity of 18S-rRNA-qPCR in the detecting P. falciparum was 91.3% and 75.0% respectively, 67.6% and 88.1% in the detection of P. malariae, and 55.8% and 91.4% in the detection of P. ovale. The sensitivity and specificity of non 18S-rRNA-qPCR was 99.1% and 66.7% in the detection of P. falciparum, 77.9% and 88.1% in the detection of P. malariae, and 79.4% and 90.3% in the detection of P. ovale. All the positive and negative predictive values were above 70% except the negative predictive value for 18S-rRNA-qPCR (47.4%). There was a significant concordance between 18S-rRNA-qPCR and non-18S-rRNAqPCR and microscopy in the detection of P. falciparum and P.malariae (P<0.05). There was a moderately strong agreement (kappa>0.5) between microscopy and both18S-rRNA-qPCR and non-18S-rRNA-qPCR in the detection of all three Plasmodium species. There was a positive correlation between microscopy parasite density and the parasite densities estimated by the 18SrRNA-qPCR and Non-18S-rRNA-qPCR(P<0.001). More studies need to be conducted before the adoption of the 18S-rRNA-qPCR or Non-18S-rRNA-qPCR as alternatives to microscopy in the detection, speciation and quantification of both microscopic and submicroscopic malaria parasites. | en_US |