Comparison of diagnostics for the detection of asymptomatic Plasmodium falciparum infections to inform control and elimination strategies

Over the past two decades, considerable progress has been made in reducing the global malaria burden. Between 2000 and 2013 alone, malaria-related mortality decreased by 47% worldwide and 54% in [...]
The global burden of malaria has been substantially reduced over the past two decades. Future efforts to reduce malaria further will require moving beyond the treatment of clinical infections to targeting malaria transmission more broadly in the community. As such, the accurate identification of asymptomatic human infections, which can sustain a large proportion of transmission, is becoming a vital component of control and elimination programmes. We determined the relationship across common diagnostics used to measure malaria prevalence--polymerase chain reaction (PCR), rapid diagnostic test and microscopy--for the detection of Plasmodium falciparum infections in endemic populations based on a pooled analysis of cross-sectional data. We included data from more than 170,000 individuals comparing the detection by rapid diagnostic test and microscopy, and 30,000 for detection by rapid diagnostic test and PCR. The analysis showed that, on average, rapid diagnostic tests detected 41% (95% confidence interval = 26-66%) of PCR-positive infections. Data for the comparison of rapid diagnostic test to PCR detection at high transmission intensity and in adults were sparse. Prevalence measured by rapid diagnostic test and microscopy was comparable, although rapid diagnostic test detected slightly more infections than microscopy. On average, microscopy captured 87% (95% confidence interval = 74-102%) of rapid diagnostic test-positive infections. The extent to which higher rapid diagnostic test detection reflects increased sensitivity, lack of specificity or both, is unclear. Once the contribution of asymptomatic individuals to the infectious reservoir is better defined, future analyses should ideally establish optimal detection limits of new diagnostics for use in control and elimination strategies. Nature 528, S86-S93 (3 December 2015), DOI: 10.1038/nature16039 This article has not been written or reviewed by Nature editors. Nature accepts no responsibility for the accuracy of the information provided.