A Multi-Activity Fusion Approach for Gender Recognition based on Human Activity.

Due to its advantages in numerous industries, including healthcare, sports, rehabilitation, and wearable electronics, gender recognition has garnered a lot of attention in the last ten years. The gender recognition method described in this study uses a wearable sensor device with inertial measurement units to record a variety of activities. The system consists of five sensors that are mounted to the upper and lower bodies while performing seven standing, walking, and climbing exercises that are meant to replicate daily activity. To create a model for gender recognition, we carried out an extensive study based on supervised machine learning. This study identifies a collection of sensor locations and behaviours to better precisely classify gender. Gender classification based on single activity was performed using Random Forest Classifier (RFC) and Support Vector Machines (SVM). Maximum accuracy of 92.06% was gained using Random Forest Classifier for the sensor located at the ankle when walking. Multi-activity based gender classification outperformed former by achieving an accuracy of 94.13% using RFC. This was for the activity combination of Romberg test eyes open, Single leg stance eyes open and Staircase up and down.

Modified Recurrence Quantification Analysis for Objective Assessment of Cerebellar Ataxia.

Cerebellar Ataxia (CA) is a neurological condition that affects coordination, balance and speech. Assessing its severity is important for developing effective treatment and rehabilitation plans. Traditional assessment methods involve a clinician instructing a person with ataxia to perform tests and assigning a severity score based on their performance. However, this approach is subjective as it relies on the clinician's experience, and can vary between clinicians. To address this subjectivity, some researchers have developed automated assessment methods using signal processing and data-driven approaches, such as supervised machine learning. These methods still rely on subjective ground truth and can perform poorly in real-world scenarios. This research proposed an alternative approach that uses signal processing to modify recurrence plots and compare the severity of ataxia in a person with CA to a control cohort. The highest correlation score obtained was 0.782 on the back sensor with the feet-apart and eyes-open test. The contributions of the research include modifying the recurrence plot as a measurement tool for assessing CA severity, proposing a new approach to assess severity by comparing kinematic data between people with CA and a control reference group, and identifying the best subtest and sensor position for practical use in CA assessments.

Blockchained Federated Learning for Privacy and Security Preservation: Practical Example of Diagnosing Cerebellar Ataxia.

Cerebellar ataxia (CA) refers to the incoordination of movements of the eyes, speech, trunk, and limbs caused by cerebellar dysfunction. Conventional machine learning (ML) utilizes centralised databases to train a model of diagnosing CA. Despite the high accuracy, these approaches raise privacy concern as participants' data revealed in the data centre. Federated learning is an effective distributed solution to exchange only the ML model weight rather than the raw data. However, FL is also vulnerable to network attacks from malicious devices. In this study, we depict the concept of blockchained FL with individual's validators. We simulate the proposed approach with real-world dataset collected from kinematic sensors of CA individuals with four geographically separated clinics. Experimental results show the blockchained FL maintains competitive accuracy of 89.30%, while preserving both privacy and security.

Understanding the epidemiology, clinical characteristics, knowledge and barriers to treatment and prevention of malaria among returning international laborers in northern Vietnam: a mixed-methods study.

BACKGROUND: With the decline in local malaria transmission in Vietnam as a result of the National Malaria Control Program (NMCP) elimination activities, a greater focus on the importation and potential reintroduction of transmission are essential to support malaria elimination objectives. METHODS: We conducted a multi-method assessment of the demographics, epidemiology, and clinical characteristics of imported malaria among international laborers returning from African or Southeast Asian countries to Vietnam. Firstly, we conducted a retrospective review of hospital records of patients from January 2014 to December 2016. Secondly, we conducted a mixed-methods prospective study for malaria patients admitted to the study sites from January 2017 to May 2018 using a structured survey with blood sample collection for PCR analysis and in-depth interviews. Data triangulation of the qualitative and quantitative data was used during analysis. RESULTS: International laborers were young (median age 33.0 years IQR 28.0-39.5 years), predominantly male (92%) adults returning mostly from the African continent (84%) who stayed abroad for prolonged periods (median time 13.5 months; IQR 6.0-331.5 months) and were involved in occupations that exposed them to a higher risk of malaria infection. Epidemiological trends were also similar amongst study strands and included the importation of Plasmodium falciparum primarily from African countries and P. vivax from Southeast Asian countries. Of 11 P. malariae and P. ovale infections across two study strands, 10 were imported from the African continent. Participants in the qualitative arm demonstrated limited knowledge about malaria prior to travelling abroad, but reported knowledge transformation through personal or co-worker's experience while abroad. Interestingly, those who had a greater understanding of the severity of malaria presented to the hospital for treatment sooner than those who did not; median of 3 days (IQR 2.0-7.0 days) versus 5 days (IQR 4.0-9.5 days) respectively. CONCLUSION: To address the challenges to malaria elimination raised by a growing Vietnamese international labor force, consideration should be given to appropriately targeted interventions and malaria prevention strategies that cover key stages of migration including pre-departure education and awareness, in-country prevention and prophylaxis, and malaria screening upon return.

Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor.

Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been used to objectively diagnose and quantify the severity of CA. Although these approaches achieved high accuracy, large scale deployment will require large clinics and raises privacy concerns. In this study, we propose an image transformation-based approach to leverage the advantages of state-of-the-art deep learning with federated learning in diagnosing CA. We use motion capture sensors during the performance of a standard neurological balance test obtained from four geographically separated clinics. The recurrence plot, melspectrogram, and poincaré plot are three transformation techniques explored. Experimental results indicate that the recurrence plot yields the highest validation accuracy (86.69%) with MobileNetV2 model in diagnosing CA. The proposed scheme provides a practical solution with high diagnosis accuracy, removing the need for feature engineering and preserving data privacy for a large-scale deployment.

Diagnosis Cerebellar Ataxia using Deep Learning with Time Series Transformed Image.

Cerebellar ataxia (CA) is defined by disrupted coordination of movement suffering from disease of the cerebellum. It reflects fragmented movements of the eyes, vocal, upper limbs, balance, gait, and lower limbs. This study aims to use a motion sensor to form a simple yet effective CA quantitative assessment framework. We suggest a pendant device to use a single kinematic sensor attached to the wearer's chest to investigate the balance capability. Via a standard neurological test (Romberg's standing), the device may reveal an early symptom of Cerebellar Ataxia tailoring toward rehabilitation or therapeutic program. We adopt a transformed-image based approach to leverage the advantage of state-of-the-art deep learning models into diagnosis CA. Three transform techniques are employed including recurrence plot, melspectrogram, and Poincaré plot. Experiment results show that melspectrogram transform technique performs best in implementation with MobileNetV2 to diagnose CA with an average validation accuracy of 89.99%.

Risk factors for malaria in high incidence areas of Viet Nam: a case-control study.

BACKGROUND: A key step to advancing the goal of malaria elimination in Viet Nam by 2030 is focusing limited resources for treatment and prevention to groups most at risk for malaria transmission. METHODS: To better understand risk factors for malaria transmission in central Viet Nam, a survey of 1000 malaria positive cases and 1000 malaria negative controls was conducted. Cases and controls were matched for age and gender and self-presented at commune health stations (CHS) in Binh Phuoc, Dak Nong and Dak Lak Provinces. Diagnoses were confirmed with microscopy, rapid diagnostic test and PCR. Participants were interviewed about 50 potential risk factors for malaria, which included information about occupation, forest visitation, travel, healthcare-seeking behaviour and prior use of anti-malaria interventions. Participants were enrolled by trained government health workers and the samples were analysed in Vietnamese government laboratories. Data were analysed by univariable, block-wise and multivariable logistic regression. RESULTS: Among cases, 61.8% had Plasmodium falciparum, 35.2% Plasmodium vivax and 3% mixed species infections. Median (IQR) age was 27 (21-36) years and 91.2% were male. Twenty-five risk factors were associated with being a case and eleven with being a control. Multivariable analysis found that malaria cases correlated with forest workers, recent forest visitation, longer duration of illness, having a recorded fever, number of malaria infections in the past year, having had prior malaria treatment and having previously visited a clinic. CONCLUSIONS: This study demonstrates the benefits of increased statistical power from matched controls in malaria surveillance studies, which allows identification of additional independent risk factors. It also illustrates an example of research partnership between academia and government to collect high quality data relevant to planning malaria elimination activities. Modifiable risk factors and implications of the findings for malaria elimination strategy are presented.

Results from a malaria indicator survey highlight the importance of routine data capture in high-risk forest and farm transmission sites in Vietnam to tailor location-specific malaria elimination interventions.

In-line with the World Health Organization's (WHO) Global Technical Strategy for Malaria (2016-2030), Vietnam is striving to eliminate malaria by 2030. Targeting appropriate interventions in high-risk populations such as forest and forest-fringe communities is a critical component of malaria elimination efforts in Vietnam. In 2016, a household-level malaria indicator survey was conducted in Phu Yen Province, Vietnam with the aim of assessing the knowledge, behaviors and associated risks of malaria infection among priority mobile and migrant populations (MMPs) working and sleeping in forests and on farms. A total of 4211 people were included in the survey, comprised of 1074 heads of households and 3137 associated household members. Of the 1074 head-of-household respondents, 472 slept in a forest, 92 slept on a farm, 132 slept in both forests and farms, and 378 slept at their villages within the last 12 months. Age, literacy, and occupation were significantly different among those who slept in a forest versus on a farm. Of 301 respondents who answered questions about malaria risk factors at sleeping sites, 35% were somewhat aware of malaria prevention practices, but only 4% could recall at least four malaria prevention messages. Among the same group of 301 respondents, only 29% used nets and only 11% used treated nets. Ownership and use of nets among forest-goers was significantly lower than those who slept on a farm or in their village. Huts without walls were significantly prominent forest sleeping site locations (POR = 10.3; 95% CI 4.67-22.7). All respondents who slept in a forest requested standby malaria drugs and one-third of them self-treated without blood testing. Results from this study highlight the importance of capturing relevant location-specific data among priority populations such as remote forest and farm going mobile and migrant populations in Vietnam. Data regarding behavioral practices, knowledge, preventative measures, and intervention coverage at remote-area transmission sites must be routinely captured to effectively monitor progress and refine targeted intervention strategies accordingly.

Mosquito Net Ownership, Utilization, and Preferences among Mobile and Migrant Populations Sleeping in Forests and Farms in Central Vietnam: A Cross-Sectional Study.

Strengthening vector control measures among mobile and migrant populations (MMPs) is crucial to malaria elimination, particularly in areas with multidrug-resistant malaria. Although a global priority, providing access and ensuring high coverage of available tools such as long-lasting insecticidal nets (LLINs) among these vulnerable groups remains a significant challenge. We assessed mosquito net ownership, utilization, and preference among individuals who slept in a forest and/or on a farm against those residing only in village "home" settings in a priority malaria elimination area of Vietnam. Proportions of respondents owning bed nets were similar among forest, farm, and home sleeping sites, ranging between 96% and 98%. The proportion of respondents owning hammock nets was higher for the forest group (92%), whereas ownership of hammocks in general was significantly lower for the home group (55%). Most respondents (97%) preferred to bring hammock nets to their remote sleeping site, whereas a smaller proportion (25%) also considered bed nets as an option. Respondent preferences included thick hammock nets with zippers (53%), hammocks with a flip cover (17%), and thin hammock nets with zippers (15%), with none choosing polyethylene (hard) LLINs. Although there is high coverage and access to nets for this high-priority MMP group, there was a noted gap between coverage and net use, potentially undermining the effectiveness of net-related interventions that could impact malaria prevention and elimination efforts in Vietnam. The design and material of nets are important factors for user preferences that appear to drive net use.

Balance Deficits due to Cerebellar Ataxia: A Machine Learning and Cloud-Based Approach.

Cerebellar ataxia (CA) refers to the disordered movement that occurs when the cerebellum is injured or affected by disease. It manifests as uncoordinated movement of the limbs, speech, and balance. This study is aimed at the formation of a simple, objective framework for the quantitative assessment of CA based on motion data. We adopted the Recurrence Quantification Analysis concept in identifying features of significance for the diagnosis. Eighty-six subjects were observed undertaking three standard neurological tests (Romberg's, Heel-shin and Truncal ataxia) to capture 213 time series inertial measurements each. The feature selection was based on engaging six different common techniques to distinguish feature subset for diagnosis and severity assessment separately. The Gaussian Naive Bayes classifier performed best in diagnosing CA with an average double cross-validation accuracy, sensitivity, and specificity of 88.24%, 85.89%, and 92.31%, respectively. Regarding severity assessment, the voting regression model exhibited a significant correlation (0.72 Pearson) with the clinical scores in the case of the Romberg's test. The Heel-shin and Truncal tests were considered for diagnosis and assessment of severity concerning subjects who were unable to stand. The underlying approach proposes a reliable, comprehensive framework for the assessment of postural stability due to cerebellar dysfunction using a single inertial measurement unit.

A Comparative Severity Assessment of Impaired Balance due to Cerebellar Ataxia using Regression Models.

Cerebellar ataxia (CA) refers to the impaired balance and coordination resulting from injury or degeneration of the cerebellum. Testing balance is one of the simplest means of assessing CA. This study compares instrumented assessment and clinical assessment scales of the balance test called Romberg's test. Inertial Measurement Unit (IMU) data were collected from a sensor attached to their chest of 53 subjects while they performed the test. The corresponding clinical scores were also tabulated. Using this data, 99 features were extracted to quantify acceleration, tremor and displacement of body sway. These features were filtered to identify the subset that better characterize the distinctive behavior of CA subjects. Elastic Net Regression model resulted a greater agreement (0.70 Pearson coefficient) with the clinical SARA scores. The overall results indicated that data from a single IMU sensor is sufficient to accurately assess balance in CA. The significance of this study is that evaluation of balance using Recurrence Quantification Analysis produces a comprehensive framework for the assessment of CA.

Recurrence Quantification Analysis for Human Activity Recognition.

Human Activity Recognition (HAR) is a central unit to understand and predict human behavior. HAR has been used to estimate the levels of a sedentary, monitor lifestyle habits, track the levels of people's health, or build a recommendation system. Many researchers have utilized the inertial measurement unit as an input tool to explore the HAR land. The recurrence plot (RP) technique recently has its applications diverse in various areas. From the recurrence plot, a machine-auto or hand-crafted approach can be used to extract feature vectors. While the machine-auto based approach has been reported in the literature, the latter hand-crafted based method has not. For that reason, this paper evaluated and demonstrated the feasibility of utilizing Recurrence Quantification Analysis (RQA), which was a typical hand-crafted method from RP, to classify human activities. A Linear Discriminant Analysis classifier yielded a 95.08% accuracy, which belonged in the top accuracy reported in the literature. Compare to the machine-auto or end-to-end approach, RQA is a far less complicated and more lean system that should be further analyzed in a HAR application.

Targeting high risk forest goers for malaria elimination: a novel approach for investigating forest malaria to inform program intervention in Vietnam.

BACKGROUND: Individuals that work and sleep in remote forest and farm locations in the Greater Mekong Subregion continue to remain at high risk of both acquiring and transmitting malaria. These difficult-to-access population groups largely fall outside the reach of traditional village-centered interventions, presenting operational challenges for malaria programs. In Vietnam, over 60% of malaria cases are thought to be individuals who sleep in forests or on farms. New malaria elimination strategies are needed in countries where mobile and migrant workers frequently sleep outside of their homes. The aim of this study was to apply targeted surveillance-response based investigative approaches to gather location-specific data on confirmed malaria cases, with an objective to identify associated malaria prevention, treatment and risk behaviors of individuals sleeping in remote forest and farms sites in Vietnam. METHODS: A cross-sectional study using novel targeted reactive investigative approaches at remote area sleeping sites was conducted in three mountainous communes in Phu Yen province in 2016. Index cases were defined as individuals routinely sleeping in forests or farms who had tested positive for malaria. Index cases and non-infected neighbors from forest and farm huts within 500 m of the established sleeping locations of index cases were interviewed at their remote-area sleeping sites. RESULTS: A total of 307 participants, 110 index cases and 197 neighbors, were enrolled. Among 93 participants who slept in the forest, index cases were more likely to make > 5 trips to the forest per year (prevalence odds ratio (POR) 7.41, 95% confidence interval (CI) 2.66-20.63), sleep in huts without walls (POR 44.00, 95% CI 13.05-148.33), sleep without mosquito nets (POR 2.95, 95% CI 1.26-6.92), and work after dark (POR 5.48, 95% CI 1.84-16.35). Of the 204 farm-based respondents, a significantly higher proportion of index cases were involved in non-farming activities (logging) (POR 2.74, 95% CI 1.27-5.91). CONCLUSION: Investigative approaches employed in this study allowed for the effective recruitment and characterization of high-priority individuals frequently sleeping in remote forest and farm locations, providing relevant population and site-specific data that decision makers can use to design and implement targeted interventions to support malaria elimination.

Spatial and Temporal Patterns of Malaria in Phu Yen Province, Vietnam, from 2005 to 2016.

Malaria in Vietnam has become focal to a few provinces, including Phu Yen. This study aimed to assess correlations between intervention (population proportion protected by insecticide-treated nets and indoor residual spraying) and climatic variables with malaria incidence in Phu Yen Province. The Vietnam National Institute of Malariology, Parasitology, and Entomology provided incidence data for Plasmodium falciparum and Plasmodium vivax for 104 communes of Phu Yen Province from January 2005 to December 2016. A multivariable, zero-inflated Poisson regression model was developed with a conditional autoregressive prior structure to identify the underlying spatial structure of the data and quantify associations with covariates. There were a total of 2,778 P. falciparum and 1,770 P. vivax cases during the study period. Plasmodium falciparum and P. vivax incidence increased by 5.4% (95% credible interval [CrI] 5.1%, 5.7%) and 3.2% (95% CrI 2.9%, 3.5%) for a 10-mm increase in precipitation without lag, respectively. Plasmodium falciparum and P. vivax incidence decreased by 7.7% (95% CrI 5.6%, 9.7%) and 10.5% (95% CrI 8.3%, 12.6%) for a 1°C increase in minimum temperature without lag, respectively. There was a > 95% probability of a higher than provincial average trend of P. falciparum and P. vivax in Song Cau and Song Hoa districts. There was a > 95% probability of a lower than provincial average trend in Tuy Dong Xuan and Hoa districts for both species. Targeted distribution of resources, including intensified interventions, in this part of the province will be required for local malaria elimination.

Risk factor assessment for clinical malaria among forest-goers in a pre-elimination setting in Phu Yen Province, Vietnam.

BACKGROUND: The transition from malaria control to elimination requires understanding and targeting interventions among high-risk populations. In Vietnam, forest-goers are often difficult to test, treat and follow-up for malaria because they are highly mobile. If undiagnosed, forest-goers can maintain parasite reservoirs and contribute to ongoing malaria transmission. METHODS: A case-control study was conducted to identify malaria risk factors associated with forest-goers in three communes in Phu Yen Province, Vietnam. Cases (n = 81) were residents from the study area diagnosed with malaria and known to frequent forest areas. Controls (n = 94) were randomly selected forest-going residents from within the study area with no identified malaria infection. Participants were interviewed face-to-face using a standard questionnaire to identify malaria risk factors. Logistic regression was used to calculate odds ratios (ORs) and 95% CI for risk factors after adjusting for socio-demographic characteristics. RESULTS: Among the cases, malaria infection varied by species: 66.7% were positive for Plasmodium falciparum, 29.6% for Plasmodium vivax, and 3.7% were diagnosed as mixed infection. Cases were less likely than controls to use treated nets (aOR = 0.31; 95% CI 0.12-0.80), work after dark (aOR = 2.93; 95% CI 1.35, 6.34), bath in a stream after dark (aOR = 2.44; 95% CI 1.02-5.88), and collect water after dark (aOR = 1.99; 95% CI 1.02-3.90). CONCLUSIONS: As Vietnam moves toward malaria elimination, these findings can inform behaviour change communication and malaria prevention strategies, incorporating the risk of after-dark and water-related activities, in this priority and difficult-to-access population group.

Addressing operational challenges of combatting malaria in a remote forest area of Vietnam using spatial decision support system approaches.

This study examines the development of a spatial decision support system (SDSS) to address operational challenges for combatting malaria in a priority remote forest area of Vietnam including locating active malaria transmission, guiding targeted response, and identifying mobile and high-risk populations. A customized SDSS was developed for three communes in Phu Yen Province, Vietnam. Geographical reconnaissance (GR) was conducted to map and enumerate all households in the study site. During 2015 and 2016, detected malaria cases were reported to the SDSS and georeferenced to household residence. Individual case data were analysed in the SDSS to guide targeted response. Case investigation data, including suspected forest and remote area transmission locations, were also integrated into the SDSS. Surveys and in-depth interviews were conducted to assess utility and user acceptability. In 2015 and 2016, 4,667 households and a population of 17,563 were captured during GR. During the study period, 128 malaria cases were reported and automatically mapped in the SDSS. Targeted response interventions were conducted in 12 villages, testing 1,872 individuals. Intervention and remote-area sleeping site data were mapped and analysed using the SDSS. During follow-up interviews in 2017 the SDSS was found to be highly acceptable to malaria surveillance personnel. Results suggest that an SDSS can provide an effective tool in Vietnam to support the implementation of specialized surveillance, and calls for further research, application and roll-out in the Greater Mekong Subregion.

Wire-like Pt on mesoporous Ti0.7W0.3O2 Nanomaterial with Compelling Electro-Activity for Effective Alcohol Electro-Oxidation.

Finding out robust active and sustainable catalyst towards alcohol electro-oxidation reaction is major challenges for large-scale commercialization of direct alcohol fuel cells. Herein, a robust Pt nanowires (NWs)/Ti0.7W0.3O2 electrocatalyst, as the coherency of using non-carbon catalyst support and controlling the morphology and structure of the Pt nanocatalyst, was fabricated via an effortless chemical reduction reaction approach at room temperature without using surfactant/stabilizers or template to assemble an anodic electrocatalyst towards methanol electro-oxidation reaction (MOR) and ethanol electro-oxidation reaction (EOR). These observational results demonstrated that the Pt NWs/Ti0.7W0.3O2 electrocatalyst is an intriguing anodic electrocatalyst, which can alter the state-of-the-art Pt NPs/C catalyst. Compared with the conventional Pt NPs/C electrocatalyst, the Pt NWs/Ti0.7W0.3O2 electrocatalyst exhibited the lower onset potential (~0.1 V for MOR and ~0.2 for EOR), higher mass activity (~355.29 mA/mgPt for MOR and ~325.01 mA/mgPt for EOR) and much greater durability. The outperformance of the Pt NWs/Ti0.7W0.3O2 electrocatalyst is ascribable to the merits of the anisotropic one-dimensional Pt nanostructure and the mesoporous Ti0.7W0.3O2 support along with the synergistic effects between the Ti0.7W0.3O2 support and the Pt nanocatalyst. Furthermore, this approach may provide a promising catalytic platform for fuel cell technology and a variety of applications.

Survey of peer review programs among pediatric radiologists: report from the SPR Quality and Safety Committee.

During the last 15 years, peer review has been widely incorporated into radiology quality improvement programs. However, current implementations are variable and carry concerns, including subjectivity of numerical scores and a sense of merely satisfying regulatory requirements. The Society for Pediatric Radiology (SPR) Quality and Safety Committee sought to evaluate the state of peer review programs in pediatric radiology practices, including implementation methods, perceived functions, strengths and weaknesses, and opportunities for improvement. We distributed an online 16-question survey to SPR members. Questions pertained to the type of peer review system, the use of numerical scores and comments, how feedback on discordances is given and received, and the use of peer learning conferences. We collected 219 responses (15% of survey invitations), 80% of which were from children's hospitals. Fifty percent of respondents said they use a picture archiving and communication system (PACS)-integrated peer review system. Comment-enhanced feedback for interpretive discordances was either very important or somewhat important to performance improvement in 86% of responses, compared to 48% with a similar perception of numerical scores. Sixty-eight percent of respondents said they either rarely or never check their numerical scores, and 82% either strongly or somewhat agreed that comments are more effective feedback than numerical scores. Ninety-three percent either strongly or somewhat agreed that peer learning conferences would be beneficial to their practice. Forty-eight percent thought that their current peer review system should be modified. Survey results demonstrate that peer review systems in pediatric radiology practices are implemented variably, and nearly half of respondents believe their systems should be modified. Most respondents prefer feedback in the form of comments and peer learning conferences, which are thought to be more beneficial for performance improvement than numerical scores.

Analysis of clinical malaria disease patterns and trends in Vietnam 2009-2015.

BACKGROUND: Viet Nam has made tremendous progress towards reducing mortality and morbidity associated with malaria in recent years. Despite the success in malaria control, there has been a recent increase in cases in some provinces. In order to understand the changing malaria dynamics in Viet Nam and measure progress towards elimination, the aim of this study was to describe and quantify spatial and temporal trends of malaria by species at district level across the country. METHODS: Malaria case reports at the Viet Nam National Institute of Malariology, Parasitology, and Entomology were reviewed for the period of January 2009 to December 2015. The population of each district was obtained from the Population and Housing Census-2009. A multivariate (insecticide-treated mosquito nets [ITN], indoor residual spraying [IRS], maximum temperature), zero-inflated, Poisson regression model was developed with spatial and spatiotemporal random effects modelled using a conditional autoregressive prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. Covariates included in the models were coverage of intervention (ITN and IRS) and maximum temperature. RESULTS: There was a total of 57,713 Plasmodium falciparum and 32,386 Plasmodium vivax cases during the study period. The ratio of P. falciparum to P. vivax decreased from 4.3 (81.0% P. falciparum; 11,121 cases) in 2009 to 0.8 (45.0% P. falciparum; 3325 cases) in 2015. Coverage of ITN was associated with decreased P. falciparum incidence, with a 1.1% (95% credible interval [CrI] 0.009%, 1.2%) decrease in incidence for 1% increase in the ITN coverage, but this was not the case for P. vivax, nor was it the case for IRS coverage. Maximum temperature was associated with increased incidence of both species, with a 4% (95% CrI 3.5%, 4.3%) and 1.6% (95% CrI 0.9%, 2.0%) increase in P. falciparum and P. vivax incidence for a temperature increase of 1 °C, respectively. Temporal trends of P. falciparum and P. vivax incidence were significantly higher than the national average in Central and Central-Southern districts. CONCLUSION: Interventions (ITN distribution) and environmental factors (increased temperature) were associated with incidence of P. falciparum and P. vivax during the study period. The factors reviewed were not exhaustive, however the data suggest distribution of resources can be targeted to areas and times of increased malaria transmission. Additionally, changing distribution of the two predominant malaria species in Viet Nam will require different programmatic approaches for control and elimination.

Pediatric brain MRI, Part 2: Advanced techniques.

Pediatric neuroimaging is a complex and specialized field that uses magnetic resonance (MR) imaging as the workhorse for diagnosis. MR protocols should be tailored to the specific indication and reviewed by the supervising radiologist in real time. Targeted advanced imaging sequences can be added to provide information regarding tissue microstructure, perfusion, metabolism and function. In part 2 of this review, we highlight the utility of advanced imaging techniques for superior evaluation of pediatric neurologic disease. We focus on the following techniques, with clinical examples: phase-contrast imaging, perfusion-weighted imaging, vessel wall imaging, diffusion tensor imaging, task-based functional MRI and MR spectroscopy.