Assessment of malaria risk in Southeast Asia: a systematic review

BACKGROUND

Several countries in Southeast Asia are nearing malaria elimination, yet eradication remains elusive. This is largely due to the challenge of focusing elimination efforts, an area where risk prediction can play an essential supporting role. Despite its importance, there is no standard numerical method to quantify the risk of malaria infection. Thus, there is a need for a consolidated view of existing definitions of risk and factors considered in assessing risk to analyse the merits of risk prediction models. This systematic review examines studies of the risk of malaria in Southeast Asia with regard to their suitability in addressing the challenges of malaria elimination in low transmission areas.

METHODS

A search of four electronic databases over 2010-2020 retrieved 1297 articles, of which 25 met the inclusion and exclusion criteria. In each study, examined factors included the definition of the risk and indicators of malaria transmission used, the environmental and climatic factors associated with the risk, the statistical models used, the spatial and temporal granularity, and how the relationship between environment, climate, and risk is quantified.

RESULTS

This review found variation in the definition of risk used, as well as the environmental and climatic factors in the reviewed articles. GLM was widely adopted as the analysis technique relating environmental and climatic factors to malaria risk. Most of the studies were carried out in either a cross-sectional design or case-control studies, and most utilized the odds ratio to report the relationship between exposure to risk and malaria prevalence.

CONCLUSIONS

Adopting a standardized definition of malaria risk would help in comparing and sharing results, as would a clear description of the definition and method of collection of the environmental and climatic variables used. Further issues that need to be more fully addressed include detection of asymptomatic cases and considerations of human mobility. Many of the findings of this study are applicable to other low-transmission settings and could serve as a guideline for further studies of malaria in other regions.

The effect of 3D stereopsis and hand-tool alignment on learning effectiveness and skill transfer of a VR-based simulator for dental training

Recent years have seen the proliferation of VR-based dental simulators using a wide variety of different VR configurations with varying degrees of realism. Important aspects distinguishing VR hardware configurations are 3D stereoscopic rendering and visual alignment of the user's hands with the virtual tools. New dental simulators are often evaluated without analysing the impact of these simulation aspects. In this paper, we seek to determine the impact of 3D stereoscopic rendering and of hand-tool alignment on the teaching effectiveness and skill assessment accuracy of a VR dental simulator. We developed a bimanual simulator using an HMD and two haptic devices that provides an immersive environment with both 3D stereoscopic rendering and hand-tool alignment. We then independently controlled for each of the two aspects of the simulation. We trained four groups of students in root canal access opening using the simulator and measured the virtual and real learning gains. We quantified the real learning gains by pre- and post-testing using realistic plastic teeth and the virtual learning gains by scoring the training outcomes inside the simulator. We developed a scoring metric to automatically score the training outcomes that strongly correlates with experts' scoring of those outcomes. We found that hand-tool alignment has a positive impact on virtual and real learning gains, and improves the accuracy of skill assessment. We found that stereoscopic 3D had a negative impact on virtual and real learning gains, however it improves the accuracy of skill assessment. This finding is counter-intuitive, and we found eye-tooth distance to be a confounding variable of stereoscopic 3D, as it was significantly lower for the monoscopic 3D condition and negatively correlates with real learning gain. The results of our study provide valuable information for the future design of dental simulators, as well as simulators for other high-precision psycho-motor tasks.

Added-value of mosquito vector breeding sites from street view images in the risk mapping of dengue incidence in Thailand

Dengue is an emerging vector-borne viral disease across the world. The primary dengue mosquito vectors breed in containers with sufficient water and nutrition. Outdoor containers can be detected from geotagged images using state-of-the-art deep learning methods. In this study, we utilize such container information from street view images in developing a risk mapping model and determine the added value of including container information in predicting dengue risk. We developed seasonal-spatial models in which the target variable dengue incidence was explained using weather and container variable predictors. Linear mixed models with fixed and random effects are employed in our models to account for different characteristics of containers and weather variables. Using data from three provinces of Thailand between 2015 and 2018, the models are developed at the sub-district level resolution to facilitate the development of effective targeted intervention strategies. The performance of the models is evaluated with two baseline models: a classic linear model and a linear mixed model without container information. The performance evaluated with the correlation coefficients, R-squared, and AIC shows the proposed model with the container information outperforms both baseline models in all three provinces. Through sensitivity analysis, we investigate the containers that have a high impact on dengue risk. Our findings indicate that outdoor containers identified from street view images can be a useful data source in building effective dengue risk models and that the resulting models have potential in helping to target container elimination interventions.

Effects of COVID-19 government travel restrictions on mobility in a rural border area of Northern Thailand: A mobile phone tracking study

BACKGROUND

Thailand is among the top five countries with effective COVID-19 transmission control. This study examines how news of presence of COVID-19 in Thailand, as well as varying levels of government restriction on movement, affected human mobility in a rural Thai population along the border with Myanmar.

METHODS

This study makes use of mobility data collected using a smartphone app. Between November 2019 and June 2020, four major events concerning information dissemination or government intervention give rise to five time intervals of analysis. Radius of gyration is used to analyze movement in each interval, and movement during government-imposed curfew. Human mobility network visualization is used to identify changes in travel patterns between main geographic locations of activity. Cross-border mobility analysis highlights potential for intervillage and intercountry disease transmission.

RESULTS

Inter-village and cross-border movement was common in the pre-COVID-19 period. Radius of gyration and cross-border trips decreased following news of the first imported cases. During the government lockdown period, radius of gyration was reduced by more than 90% and cross-border movement was mostly limited to short-distance trips. Human mobility was nearly back to normal after relaxation of the lockdown.

CONCLUSIONS

This study provides insight into the impact of the government lockdown policy on an area with extremely low socio-economic status, poor healthcare resources, and highly active cross-border movement. The lockdown had a great impact on reducing individual mobility, including cross-border movement. The quick return to normal mobility after relaxation of the lockdown implies that close monitoring of disease should be continued to prevent a second wave.

Formative feedback generation in a VR-based dental surgical skill training simulator

Fine motor skill is indispensable for a dentist. As in many other medical fields of study, the traditional surgical master-apprentice model is widely adopted in dental education. Recently, virtual reality (VR) simulators have been employed as supplementary components to the traditional skill-training curriculum, and numerous dental VR systems have been developed academically and commercially. However, the full promise of such systems has yet to be realized due to the lack of sufficient support for formative feedback. Without such a mechanism, evaluation still demands dedicated time of experts in scarce supply. To fill the gap of formative assessment using VR simulators in skill training in dentistry, we present a framework to objectively assess the surgical skill and generate formative feedback automatically. VR simulators enable collecting detailed data on relevant metrics throughout a procedure. Our approach to formative feedback is to correlate procedure metrics with the procedure outcome to identify the portions of a procedure that need to be improved. Specifically, for the errors in the outcome, the responsible portions of the procedure are identified by using the location of the error. Tutoring formative feedback is provided using the video modality. The effectiveness of the feedback system is evaluated with dental students using randomized controlled trials. The findings show the feedback mechanisms to be effective and to have the potential to be used as valuable supplemental training resources.

Large scale detailed mapping of dengue vector breeding sites using street view images

Targeted environmental and ecosystem management remain crucial in control of dengue. However, providing detailed environmental information on a large scale to effectively target dengue control efforts remains a challenge. An important piece of such information is the extent of the presence of potential dengue vector breeding sites, which consist primarily of open containers such as ceramic jars, buckets, old tires, and flowerpots. In this paper we present the design and implementation of a pipeline to detect outdoor open containers which constitute potential dengue vector breeding sites from geotagged images and to create highly detailed container density maps at unprecedented scale. We implement the approach using Google Street View images which have the advantage of broad coverage and of often being two to three years old which allows correlation analyses of container counts against historical data from manual surveys. Containers comprising eight of the most common breeding sites are detected in the images using convolutional neural network transfer learning. Over a test set of images the object recognition algorithm has an accuracy of 0.91 in terms of F-score. Container density counts are generated and displayed on a decision support dashboard. Analyses of the approach are carried out over three provinces in Thailand. The container counts obtained agree well with container counts from available manual surveys. Multi-variate linear regression relating densities of the eight container types to larval survey data shows good prediction of larval index values with an R-squared of 0.674. To delineate conditions under which the container density counts are indicative of larval counts, a number of factors affecting correlation with larval survey data are analyzed. We conclude that creation of container density maps from geotagged images is a promising approach to providing detailed risk maps at large scale.

Complexity-Based Spatial Hierarchical Clustering for Malaria Prediction

Targeted intervention and resource allocation are essential in effective control of infectious diseases, particularly those like malaria that tend to occur in remote areas. Disease prediction models can help support targeted intervention, particularly if they have fine spatial resolution. But, choosing an appropriate resolution is a difficult problem since choice of spatial scale can have a significant impact on accuracy of predictive models. In this paper, we introduce a new approach to spatial clustering for disease prediction we call complexity-based spatial hierarchical clustering. The technique seeks to find spatially compact clusters that have time series that can be well characterized by models of low complexity. We evaluate our approach with 2 years of malaria case data from Tak Province in northern Thailand. We show that the technique's use of reduction in Akaike information criterion (AIC) and Bayesian information criterion (BIC) as clustering criteria leads to rapid improvement in predictability and significantly better predictability than clustering based only on minimizing spatial intra-cluster distance for the entire range of cluster sizes over a variety of predictive models and prediction horizons.

Automated outcome scoring in a virtual reality simulator for endodontic surgery

BACKGROUND AND OBJECTIVE

We address the problem of automated outcome assessment in a virtual reality (VR) simulator for endodontic surgery. Outcome assessment is an essential component of any system that provides formative feedback, which requires assessing the outcome, relating it to the procedure, and communicating in a language natural to dental students. This study takes a first step toward automated generation of such comprehensive feedback.

METHODS

Virtual reference templates are computed based on tooth anatomy and the outcome is assessed with a 3D score cube volume which consists of voxel-level non-linear weighted scores based on the templates. The detailed scores are transformed into standard scoring language used by dental schools. The system was evaluated on fifteen outcome samples that contained optimal results and those with errors including perforation of the walls, floor, and both, as well as various combinations of major and minor over and under drilling errors. Five endodontists who had professional training and varying levels of experiences in root canal treatment participated as raters in the experiment.

RESULTS

Results from evaluation of our system with expert endodontists show a high degree of agreement with expert scores (information based measure of disagreement 0.04-0.21). At the same time they show some disagreement among human expert scores, reflecting the subjective nature of human outcome scoring. The discriminatory power of the AOS scores analyzed with three grade tiers (A, B, C) using the area under the receiver operating characteristic curve (AUC). The AUC values are generally highest for the {AB: C} cutoff which is cutoff at the boundary between clinically acceptable (B) and clinically unacceptable (C) grades.

CONCLUSIONS

The objective consistency of computed scores and high degree of agreement with experts make the proposed system a promising addition to existing VR simulators. The translation of detailed level scores into terminology commonly used in dental surgery supports natural communication with students and instructors. With the reference virtual templates created automatically, the approach is robust and is applicable in scoring the outcome of any dental surgery procedure involving the act of drilling.

[A cross-sectional survey of receiving no methadone maintenance treatment in HIV infected injecting drug users in Dehong Dai and Jingpo autonomous prefecture, Yunnan province]

Objective: To understand the current status of receiving no methadone maintenance treatment (MMT) and influencing factors in HIV infected injecting drug users (IDUs) in Dehong Dai and Jingpo autonomous prefectures, Yunnan province. Methods: Data of survival of IDUs with AIDS in Dehong were collected from " Chinese National Comprehensive HIV/AIDS and Care Information System" in December, 2014. Results: There were 987 IDUs who should receive MMT, the majority of them were males (94.6%, 934/987), aged 35-44 years (53.0%, 523/987) and farmers (77.2%, 762/987). Among the 987 IDUs, 60.2% (592/987) received no MMT. Multivariate logistic regression analysis showed that being female (OR=2.66, 95%CI: 1.21-5.87), in Jingpo ethnic group (OR=3.05, 95% CI: 1.97-4.71) were the major risk factors for receiving no MMT; not being farmers (OR=0.46, 95%CI: 0.31-0.70), in Dai ethnic group (OR=0.53, 95%CI: 0.36-0.79), diagnosed HIV infection history ≥10 years (OR=0.60, 95%CI: 0.45-0.81) were the major protective factors for receiving no MMT. The reasons for receiving no MMT included long distance journey (289, 48.8%), fear of exposure (124, 20.9%), poor daily medication compliance (59, 10.0%), fear of side effects (47, 7.9%), others (73, 12.3%). Conclusions: The proportion of receiving no MMT in IDUs with AIDS in Dehong was high. Being female and farmer, in Jingpo ethnic group, low educational level, short diagnosed HIV infection history were influencing factors for receiving no MMT. The effective intervention measures should be taken to further improve MMT coverage according to the different characteristics of the patients.

Effects of zinc on interleukins and antioxidant enzyme values in psoriasis-induced mice

The effects of zinc chloride (ZnCl2), disodium zinc ethylenediamine tetraacetate (Zn-EDTA), and zinc gluconate (Zn-GLU) on the antioxidant enzyme activities and levels of interleukins (ILs) in psoriasis-induced mice were studied. One hundred twenty female mice were randomly divided into six groups with 20 mice in each group: the control, positive control (PC), methotrexate (MTX), ZnCl2, Zn-EDTA, and Zn-GLU groups. All animals except the control group were given diethylstilbestrol for three consecutive days. After successfully inducing psoriasis, the control and PC groups were given normal saline (i.g.) daily while the remaining groups were given MTX, ZnCl2, Zn-EDTA, and Zn-GLU, respectively. The results revealed that the zinc supplementation could significantly (p < 0.05) inhibit mitosis in the mouse vaginal epithelium as methotrexate did and the inhibiting efficacy had nothing to do with the zinc forms. After ZnCl2, Zn-EDTA, and Zn-GLU supplementation, the levels of liver superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) activities increased and the concentration of malondialdehyde (MDA) decreased significantly (p < 0.05) compared to the PC group. The levels of SOD, CAT activity, and MDA level between each zinc supplementation group and MTX group were insignificant (p > 0.05). The zinc treatments also caused a significant (p < 0.05) decrease in the raised IL-2 level of animal serum. The results obtained in the present work indicate the potential for zinc as a complementary pharmaceutical intervention for the treatment of topical psoriasis.