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Background: Accurate identification of Plasmodium infections in community surveys is essential to successful malaria control. Microscopy and rapid diagnostic tests (RDTs) are the main techniques used to diagnose malaria in field-based surveys. While microscopy is still considered the gold standard, RDTs are growing in popularity as they allow for rapid and inexpensive diagnosis. Using data from a prevalence survey conducted in north-western Angola in 2010, the authors aimed to compare the performance of microscopy and RDTs in identifying Plasmodium falciparum infections, using polymerase chain reaction (PCR) as the gold standard., Methods: Results from 3,307 subjects (1,225 preschool-aged children (zero to five year olds), 1,134 school-aged children (six to 15 year olds) and 948 mothers/caregivers (>15 years of age)), tested for P. falciparum infections, were utilized. The sensitivity, specificity, positive, and negative predictive values (PPV and NPV) of microscopy and Paracheck-Pf® were compared using the McNemar's test and the weighted generalized score Chi-squared test for paired data., Results: The prevalence of P. falciparum infections determined by PCR and microscopy was 15.9% and by Paracheck- Pf® was 16.3%. Compared to microscopy, Paracheck-Pf® had significantly higher sensitivity (72.8% versus 60%), specificity (94.3% versus 92.5%), PPV (70.7% versus 60%) and NPV (94.8% versus 92.5%). Both tests had significantly lower sensitivity in mothers (36.8% for microscopy and 43.7% for Paracheck-Pf®) than in their children (68.4% in zero to five years-old and 60.6% in six to 15 years-old for microscopy and 80.4% in zero to five year-olds and 76.5% in six to 15 year-olds for Paracheck-Pf®)., Conclusion: Both microscopy and RDTs performed suboptimally when compared to PCR. False negativity could be associated with the low parasite density profile of the samples. False positivity may be related to the well-described limitations of those techniques such as level of expertise of microscopists or persistent antigenicity from previous infections in the case of RDTs. Nevertheless, RDTs had enhanced performance comparatively to microscopy in detecting malaria infections, favouring their use in community cross-sectional malaria surveys, where expert performance of microscopy is hard to accomplish.

Background: Identifying and targeting hyper-endemic communities within meso-endemic areas constitutes an important challenge in malaria control in endemic countries such like Angola. Recent national and global predictive maps of malaria allow the identification and quantification of the population at risk of malaria infection in Angola, but their small-scale accuracy is surrounded by large uncertainties. To observe the need to develop higher resolution malaria endemicity maps a predictive risk map of malaria infection for the municipality of Dande (a malaria endemic area in Northern Angola) was developed and compared to existing national and global maps, the role of individual, household and environmental risk factors for malaria endemicity was quantified and the spatial variation in the number of children at-risk of malaria was estimated., Methods: Bayesian geostatistical models were developed to predict small-scale spatial variation using data collected during a parasitological survey conducted from May to August 2010. Maps of the posterior distributions of predicted prevalence were constructed in a geographical information system., Results: Malaria infection was significantly associated with maternal malaria awareness, households with canvas roofing, distance to health care centre and distance to rivers. The predictive map showed remarkable spatial heterogeneity in malaria risk across the Dande municipality in contrast to previous national and global spatial risk models; large high-risk areas of malaria infection (prevalence >50%) were found in the northern and most eastern areas of the municipality, in line with the observed prevalence., Conclusions: There is remarkable spatial heterogeneity of malaria burden which previous national and global spatial modelling studies failed to identify suggesting that the identification of malaria hot-spots within seemingly mesoendemic areas may require the generation of high resolution malaria maps. Individual, household and hydrological factors play an important role in the small-scale geographical variation of malaria risk in northern Angola. The results presented in this study can be used by provincial malaria control programme managers to help target the delivery of malaria control resources to priority areas in the Dande municipality.