Hot spot or not: a comparison of spatial statistical methods to predict prospective malaria infections.

BACKGROUND: Within affected communities, Plasmodium falciparum infections may be skewed in distribution such that single or small clusters of households consistently harbour a disproportionate number of infected individuals throughout the year. Identifying these hotspots of malaria transmission would permit targeting of interventions and a more rapid reduction in malaria burden across the whole community. This study set out to compare different statistical methods of hotspot detection (SaTScan, kernel smoothing, weighted local prevalence) using different indicators (PCR positivity, AMA-1 and MSP-1 antibodies) for prediction of infection the following year. METHODS: Two full surveys of four villages in Mwanza, Tanzania were completed over consecutive years, 2010-2011. In both surveys, infection was assessed using nested polymerase chain reaction (nPCR). In addition in 2010, serologic markers (AMA-1 and MSP-119 antibodies) of exposure were assessed. Baseline clustering of infection and serological markers were assessed using three geospatial methods: spatial scan statistics, kernel analysis and weighted local prevalence analysis. Methods were compared in their ability to predict infection in the second year of the study using random effects logistic regression models, and comparisons of the area under the receiver operating curve (AUC) for each model. Sensitivity analysis was conducted to explore the effect of varying radius size for the kernel and weighted local prevalence methods and maximum population size for the spatial scan statistic. RESULTS: Guided by AUC values, the kernel method and spatial scan statistics appeared to be more predictive of infection in the following year. Hotspots of PCR-detected infection and seropositivity to AMA-1 were predictive of subsequent infection. For the kernel method, a 1 km window was optimal. Similarly, allowing hotspots to contain up to 50% of the population was a better predictor of infection in the second year using spatial scan statistics than smaller maximum population sizes. CONCLUSIONS: Clusters of AMA-1 seroprevalence or parasite prevalence that are predictive of infection a year later can be identified using geospatial models. Kernel smoothing using a 1 km window and spatial scan statistics both provided accurate prediction of future infection.

Inactivation of Plasmodium falciparum in whole blood by riboflavin plus irradiation.

BACKGROUND: Malaria parasites are frequently transmitted by unscreened blood transfusions in Africa. Pathogen reduction methods in whole blood would thus greatly improve blood safety. We aimed to determine the efficacy of riboflavin plus irradiation for treatment of whole blood infected with Plasmodium falciparum. STUDY DESIGN AND METHODS: Blood was inoculated with 10(4) or 10(5) parasites/mL and riboflavin treated with or without ultraviolet (UV) irradiation (40-160 J/mL red blood cells [mL(RBCs)]). Parasite genome integrity was assessed by quantitative amplification inhibition assays, and P. falciparum viability was monitored in vitro. RESULTS: Riboflavin alone did not affect parasite genome integrity or parasite viability. Application of UV after riboflavin treatment disrupted parasite genome integrity, reducing polymerase-dependent amplification by up to 2 logs (99%). At 80 J/mL(RBCs), riboflavin plus irradiation prevented recovery of viable parasites in vitro for 2 weeks, whereas untreated controls typically recovered to approximately 2% parasitemia after 4 days of in vitro culture. Exposure of blood to 160 J/mL(RBCs) was not associated with significant hemolysis. CONCLUSIONS: Riboflavin plus irradiation treatment of whole blood damages parasite genomes and drastically reduces P. falciparum viability in vitro. In the absence of suitable malaria screening assays, parasite inactivation should be investigated for prevention of transfusion-transmitted malaria in highly endemic areas.

Epidemiology of subpatent Plasmodium falciparum infection: implications for detection of hotspots with imperfect diagnostics.

BACKGROUND: At the local level, malaria transmission clusters in hotspots, which may be a group of households that experience higher than average exposure to infectious mosquitoes. Active case detection often relying on rapid diagnostic tests for mass screen and treat campaigns has been proposed as a method to detect and treat individuals in hotspots. Data from a cross-sectional survey conducted in north-western Tanzania were used to examine the spatial distribution of Plasmodium falciparum and the relationship between household exposure and parasite density. METHODS: Dried blood spots were collected from consenting individuals from four villages during a survey conducted in 2010. These were analysed by PCR for the presence of P. falciparum, with the parasite density of positive samples being estimated by quantitative PCR. Household exposure was estimated using the distance-weighted PCR prevalence of infection. Parasite density simulations were used to estimate the proportion of infections that would be treated using a screen and treat approach with rapid diagnostic tests (RDT) compared to targeted mass drug administration (tMDA) and Mass Drug Administration (MDA). RESULTS: Polymerase chain reaction PCR analysis revealed that of the 3,057 blood samples analysed, 1,078 were positive. Mean distance-weighted PCR prevalence per household was 34.5%. Parasite density was negatively associated with transmission intensity with the odds of an infection being subpatent increasing with household exposure (OR 1.09 per 1% increase in exposure). Parasite density was also related to age, being highest in children five to ten years old and lowest in those > 40 years. Simulations of different tMDA strategies showed that treating all individuals in households where RDT prevalence was above 20% increased the number of infections that would have been treated from 43 to 55%. However, even with this strategy, 45% of infections remained untreated. CONCLUSION: The negative relationship between household exposure and parasite density suggests that DNA-based detection of parasites is needed to provide adequate sensitivity in hotspots. Targeting MDA only to households with RDT-positive individuals may allow a larger fraction of infections to be treated. These results suggest that community-wide MDA, instead of screen and treat strategies, may be needed to successfully treat the asymptomatic, subpatent parasite reservoir and reduce transmission in similar settings.