Hot Spot or Not: A Comparison of Spatial Statistical Methods to Predict Prospective Malaria Infections.

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. 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. 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. 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

Modelling the Protective Efficacy of Alternative Delivery Schedules for Intermittent Preventive Treatment of Malaria in Infants and Children

BACKGROUND: Intermittent preventive treatment in infants (IPTi) with sulfadoxine-pyrimethamine (SP) is recommended by WHO where malaria incidence in infancy is high and SP resistance is low. The current delivery strategy is via routine Expanded Program on Immunisation contacts during infancy (EPI-IPTi). However, improvements to this approach may be possible where malaria transmission is seasonal, or where the malaria burden lies mainly outside infancy. METHODS AND FINDINGS: A mathematical model was developed to estimate the protective efficacy (PE) of IPT against clinical malaria in children aged 2-24 months, using entomological and epidemiological data from an EPI-IPTi trial in Navrongo, Ghana to parameterise the model. The protection achieved by seasonally-targeted IPT in infants (sIPTi), seasonal IPT in children (sIPTc), and by case-management with long-acting artemisinin combination therapies (LA-ACTs) was predicted for Navrongo and for sites with different transmission intensity and seasonality. In Navrongo, the predicted PE of sIPTi was 26% by 24 months of age, compared to 16% with EPI-IPTi. sIPTc given to all children under 2 years would provide PE of 52% by 24 months of age. Seasonally-targeted IPT retained its advantages in a range of transmission patterns. Under certain circumstances, LA-ACTs for case-management may provide similar protection to EPI-IPTi. However, EPI-IPTi or sIPT combined with LA-ACTs would be substantially more protective than either strategy used alone. CONCLUSION: Delivery of IPT to infants via the EPI is sub-optimal because individuals are not protected by IPT at the time of highest malaria risk, and because older children are not protected. Alternative delivery strategies to the EPI are needed where transmission varies seasonally or the malaria burden extends beyond infancy. Long-acting ACTs may also make important reductions in malaria incidence. However, delivery systems must be developed to ensure that both forms of chemoprevention reach the individuals who are most exposed to malaria

Hitting Hotspots: Spatial Targeting of Malaria for Control and Elimination

Teun Bousema and colleagues argue that targeting malaria “hotspots” is a highly efficient way to reduce malaria transmission at all levels of transmission intensity

Combined angiography and perfusion using radial imaging and arterial spin labeling

Purpose: To demonstrate the feasibility of a novel non-invasive MRI technique for the comprehensive evaluation of blood flow to the brain: combined angiography and perfusion using radial imaging and arterial spin labeling (CAPRIA). Methods: In the CAPRIA pulse sequence, blood labeled with a pseudocontinuous arterial spin labeling (PCASL) pulse train is continuously imaged as it flows through the arterial tree and into the brain tissue using a golden ratio radial readout. From a single raw data set, this flexible imaging approach allows the reconstruction of both high spatial/temporal resolution angiographic images with a high undersampling factor and low spatial/temporal resolution perfusion images with a low undersampling factor. The sparse and high SNR nature of angiographic images ensures that radial undersampling artifacts are relatively benign, even when using a simple regridding image reconstruction. Pulse sequence parameters were optimized through sampling efficiency calculations and the numerical evaluation of modified PCASL signal models. Comparison was made against conventional PCASL angiographic and perfusion acquisitions. Results: 2D CAPRIA data in healthy volunteers demonstrated the feasibility of this approach, with good vessel visualization in the angiographic images and clear tissue perfusion signal when reconstructed at 108 ms and 252 ms temporal resolution, respectively. Images were qualitatively similar to those from conventional acquisitions, but CAPRIA had significantly higher SNR-efficiency (48% improvement on average, p = 0.02). Conclusion: The CAPRIA technique shows potential for the efficient evaluation of both macrovascular blood flow and tissue perfusion within a single scan, with potential applications in a range of cerebrovascular diseases

Combined angiography and perfusion using radial imaging and arterial spin labeling

Purpose: To demonstrate the feasibility of a novel non-invasive MRI technique for the comprehensive evaluation of blood flow to the brain: combined angiography and perfusion using radial imaging and arterial spin labeling (CAPRIA). Methods: In the CAPRIA pulse sequence, blood labeled with a pseudocontinuous arterial spin labeling (PCASL) pulse train is continuously imaged as it flows through the arterial tree and into the brain tissue using a golden ratio radial readout. From a single raw data set, this flexible imaging approach allows the reconstruction of both high spatial/temporal resolution angiographic images with a high undersampling factor and low spatial/temporal resolution perfusion images with a low undersampling factor. The sparse and high SNR nature of angiographic images ensures that radial undersampling artifacts are relatively benign, even when using a simple regridding image reconstruction. Pulse sequence parameters were optimized through sampling efficiency calculations and the numerical evaluation of modified PCASL signal models. Comparison was made against conventional PCASL angiographic and perfusion acquisitions. Results: 2D CAPRIA data in healthy volunteers demonstrated the feasibility of this approach, with good vessel visualization in the angiographic images and clear tissue perfusion signal when reconstructed at 108 ms and 252 ms temporal resolution, respectively. Images were qualitatively similar to those from conventional acquisitions, but CAPRIA had significantly higher SNR-efficiency (48% improvement on average, p = 0.02). Conclusion: The CAPRIA technique shows potential for the efficient evaluation of both macrovascular blood flow and tissue perfusion within a single scan, with potential applications in a range of cerebrovascular diseases

Arterial spin labeling for cerebral perfusion and angiography

Arterial spin labeling (ASL) is an MRI technique that was first proposed a quarter of a century ago. It offers the prospect of non-invasive quantitative measurement of cerebral perfusion, making it potentially very useful for research and clinical studies, particularly where multiple longitudinal measurements are required. However, it has suffered from a number of challenges, including a relatively low signal-to-noise ratio, and a confusing number of sequence variants, thus hindering its clinical uptake. Recently, however, there has been a consensus adoption of an accepted acquisition and analysis framework for ASL, and thus a better penetration onto clinical MRI scanners. Here, we review the basic concepts in ASL, and describe the current state-of-the-art acquisition and analysis approaches, and the versatility of the method to perform both quantitative cerebral perfusion measurement, along with quantitative cerebral angiographic measurement

An optimized encoding scheme for planning vessel-encoded pseudocontinuous arterial spin labeling

Vessel-encoded pseudocontinuous arterial spin labeling allows the acquisition of vessel-selective angiograms and vascular territory perfusion maps. The technique generates a periodic variation in inversion efficiency across space that can be manipulated to encode specific combinations of vessels. Currently, the choice of these encodings is limited to scenarios with few vessels and may not optimize the signal-to-noise ratio (SNR). Here we present an automated, rapid method for calculating a minimal number of SNR optimal encodings for any number and arrangement of vessels.The proposed optimized encoding scheme (OES) is a Fourier-based method that finds SNR optimized encodings to best match the ideal encodings for a set of vessels. For nine or fewer vessels, the calculation takes less than 3 s.In simulations, the OES method produces encodings for a range of vessel geometries that, on average, have an SNR efficiency 37% greater than that for random encoding. When labeling vessels in the neck in healthy subjects, the OES encodings result in images with higher SNR than other encoding methods.The OES results in a minimal number of encodings with a higher SNR efficiency than other encoding methods, regardless of the number or geometry of the vessels. Magn Reson Med 74:1248-1256, 2015. © 2014 The Authors. Magnetic Resonance in Medicine Published by Wiley Periodicals, Inc. on behalf of International Society of Medicine in Resonance