Comparative analysis of four malaria diagnostic tools and implications for malaria treatment in southwestern Nigeria

One of the problems encountered in malaria control and elimination is inaccurate diagnosis, resulting from the degree of sensitivity of the different malaria diagnostic tools. Even though microscopy remains the gold standard for malaria diagnosis, more sensitive and robust diagnostic tools such as polymerase chain reactions (PCR) are used in research settings to monitor interventions and track sub-microscopic infections due to some of the drawbacks of microscopy. Since diagnosis is a critical determinant for rational malaria treatment, it is imperative that accurate diagnosis must be assured for an effective treatment plan. Therefore, this study compared two routinely used point of care malaria diagnostic tools with two molecular tools and discussed their implication for malaria treatment.

In this study, 436 individuals with suspected malaria were sampled and systematically tested using four methods, namely rapid diagnostic test (henceforth referred to as malaria RDT- mRDT), microscopy, nested PCR (nPCR), and quantitative PCR (qPCR). Test sensitivities and specificities were compared, and their level of concordance was determined.

With nPCR as the gold standard, a false positivity rate of 42.2%, 8.9%, and 57.8% was obtained for mRDT, microscopy, and qPCR. Similarly, false negativity rates of 12.5%, 62.5%, and 0.8% were obtained for each of the methods mentioned above, respectively. Of all the tools assessed, qPCR gave the highest sensitivity (99.2%) and moderate specificity (42.2%), followed by the mRDT kit used (87.5%).

With the detection of a high false positivity rate based on mRDT and a substantial proportion of sub-microscopic carriers in this study area by nested/quantitative PCR, we recommend that these molecular tools should be in specialized laboratories within the region to (i) track and treat sub-microscopic carriers to prevent their contribution to malaria transmission; (ii) provide reliable epidemiological data using high throughput testing tools for evaluating malaria interventions.