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While agent-based models (ABMs) provide an effective means for investigating complex interactions between heterogeneous agents and their environment, they may hinder an improved understanding of phenomena being modeled due to inherent challenges associated with uncertainty in model parameters. This study uses uncertainty analysis and global sensitivity analysis (UA-GSA) to examine the effects of such uncertainty on model outputs. The statistics used in UA-GSA, however, are likely to be affected by the modifiable areal unit problem (MAUP). Therefore, to examine the scale varying-effects of model inputs, UA-GSA needs to be performed at multiple spatiotemporal scales. Unfortunately, performing comprehensive UA-GSA comes with considerable computational cost. In this paper, our cyberGIS-enabled spatiotemporally explicit UA-GSA approach helps to not only resolve the computational burden, but also to measure dynamic associations between model inputs and outputs. A set of computational and modeling experiments shows that input factors have scale-dependent impacts on modeling output variability. In other words, most of the input factors have relatively large impacts in a certain region, but may not influence outcomes in other regions. Furthermore, our spatiotemporally explicit UA-GSA approach sheds light on the effects of input factors on modeling outcomes that are particularly spatially and temporally clustered, such as the occurrence of communicable disease transmission.

Topographic effects on Cs-137 concentrations in a forested area were quantitatively examined using 58 soil core samples collected in a village in Fukushima, Japan, which was directly impacted by the radioactive plume emitted during the 2011 Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. In this study, five topographic parameters and two soil properties were evaluated as controls on the soil Cs-137 concentration using generalized additive models (GAMs), a flexible statistical method for evaluating the functional dependencies of multiple parameters. GAMs employing soil dry bulk density, mass water content, and elevation explained 54 % of the observed concentrations of Cs-137 within this landscape, whereas GAMs employing elevation, slope, and upslope distance explained 47 % of the observed concentrations, which provide strong evidence of topographic effects on Cs-137 concentrations in soils. The model fit analysis confirmed that the topographic effects are strongest when multiple topographic parameters and soil properties are included. The ability of each topographic feature to predict Cs-137 concentrations was influenced by the resolution of the digital elevation models. The movement of Cs-137 into the subsurface in this area near Fukushima was faster in comparison to regions affected by the Chernobyl Nuclear Power Plant accident. These results suggest that the effects of topographic parameters should be considered carefully in the use of anthropogenic radionuclides as environmental tracers and in the assessment of current and future environmental risks due to nuclear power plant accidents.

Alors que divers organismes internationaux ont récemment proposé des plans pour la création de systèmes de surveillance de la résistance antimicrobienne (RAM), la plupart des PRMF ne disposent pas des infrastructures et des ressources pour le faire efficacement. La RAM est donc un problème majeur d’équité en matière de santé, mais aussi un exemple de la connexion dans notre monde unique: les populations les plus à risque disposent des mécanismes de surveillance et de confinement les plus médiocres; dans le même temps, la migration mondiale, les voyages et le commerce nous rendent tous vulnérables. Les mesures que nous utilisons actuellement ne capturent pas de manière significative l'impact potentiel de la RAM aux niveaux sanitaire, économique et sociétal plus large. La surveillance mondiale de la RAM devrait inclure une surveillance étroite de l'utilisation d'antibiotiques chez les animaux, ainsi que les concentrations de divers produits chimiques libérés dans l'environnement. En fin de compte, les efforts coordonnés de divers scientifiques et parties prenantes, dans diverses disciplines et dans le monde, sont essentiels pour relever les défis pressants de la RAM mondiale croissante.

Researchers have measured aerial gamma-rays using remote measurement devices to estimate the radionuclide concentrations in soils. However, an issue arises when measuring air dose rates in forested areas, where canopies exist between the remote sensing device and the ground. When researchers do the reverse conversion from soil contamination levels to the air dose rates, the conversion formula is derived by assuming a flat ground surface (Jacob et al., 1994; Saito and Jacob, 1998); however, topography in forested areas is often not flat. This study examines the relationships among the air dose rates under the canopies, topography, and the soil contamination levels on forested hillslopes in Fukushima, Japan. Gamma-ray air dose rates were measured using a hand-held scintillator during the summer of 2018 (two days), and in the winter of 2019 using KURAMA, a portable scintillator carried in a backpack (one day). This study employed numerical methods, including semivariogram and R's CAR (Companion to Applied Regression) package, to find aerial gamma-ray activities' spatial structure and the optimal combinations of topographic predictors. The survey routes and soil sampling points did not coincide completely. Thus, spatial and temporal reorganizations and re-definitions of the spatial boundary to incorporate the air (boundaryless mass), topography (three-dimensional structure), and soil samples (point measurements) were needed to overcome data analysis challenges. Some preliminary results show that the median air dose rate on a summer day with stronger winds (wind speed 7.1 m/s) was closer to the one on a winter day than to the median on the other summer day with calm air. Distance dependency (semivariogram range) on the windy summer day and the winter day was 30 to 60 m. Distance dependency on a summer day with calm air was much longer, > 500 m. The aerial gamma-ray levels were not in a linear relationship with the elevation. Meanwhile, the areas under evergreen trees showed higher air dose rates (3-8 %) than the areas under deciduous trees in absolute measurements. However, the differences were not statistically significant. The combination of slope degrees, hillslope aspects, and curvature or upslope distance best described the air dose rates, depending on the survey routes, although their predictabilities (R2) were low, 0.35 at the most. The air dose rates, which were estimated from soil samples' effective relaxation mass depths, did not correlate with the actual air dose measurements, but this result is under further investigation. This study's complete results will provide additional consideration points to the gamma-ray air dose vs. soil contamination assessment in the forested areas.

This research collected forest soil samples from Fukushima, Japan, where the 2011 Fukushima Daiichi Nuclear Power Plant (FDNPP) accident contaminated the land. The purpose of this study was to examine how the local topography influenced the radiocesium (Cs-137) accumulation patterns in soils over the years since the accident. As an analytical method, the general additive model (GAM) was used to determine at what percentages the topographic parameters explain Cs-137 contamination levels down to a depth of 30 cm. For comparison, topographic parameters were extracted from both 1 m and 10 m digital evaluation models (DEMs). The effects of topography were compared with the effects of the soil water content and dry soil bulk density. An additional Tukey’s honestly significant difference (HSD) test was conducted to determine the significance of the hillslope aspect and vegetation cover differences on concentration predictions. The results showed that, at this study site, topographic parameters extracted from the 10 m DEM better predicted Cs-137 levels. The models with a single topographic parameter did not explain Cs-137 levels higher than 30 %. However, combining the parameters improved the explanation percentages. The relative influences of topographic parameters and soil properties were similar throughout the soil depth, showing their subsurface co-functionalities for Cs-137 concentration levels. Tukey’s HSD test results showed the inter-effects of topography and vegetation cover differences. The results of this study indicate that the selection of topographic parameters, as well as the chosen methods of their extractions, have implications for physical models assessing radionuclide contamination levels.

Antimicrobials are perhaps the greatest public health gain ever of humankind. As 2000 approached, many claimed penicillin to be the greatest discovery of the millennium; commercially available only from the early 1940s, the drug had already saved an estimated 200 million lives. Currently, however, the emergence and spread of multidrug-resistant pathogens threatens to reverse these benefits, and experts believe we are in the dawn of a post-antibiotic era. The global projections are alarming: AR infections may cause ten million deaths/year and lead all causes of mortality by 2050. Similar to other pressing global issues, the burden of AR is inequitably distributed, with 90% of AR infections occurring in Asia and Africa. This chapter discusses various forces, natural and anthropogenic, that contribute to AR, and how successful containment demands coordinated efforts from environmental, behavioral, and medical scientists, to public health educators and leaders in agricultural and international policy.

Forests provide valuable water and nutrient resources to farming activities as well as places for various leisure activities. However, decontaminating forests in the aftermath of a massive radionuclide contamination event presents challenges because of the topography and the difficulty of collecting a large number of field samples. Achieving accurate remote measurements also can be hindered by the canopy cover. In Fukushima, Japan, where elevated radioactive fallout occurred following the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in March 2011, about 70 percent of the land is covered with forests. Soil samples collected in a forest in Iitate Village, Fukushima, beginning in 2016 through 2018 still contained an average 98200 Bq/kg of Cs-137 in the top 4 cm depth (std. dev. 114100 Bq/kg). Thus, decontamination and identification of Cs-137 distribution patterns in those forests is still a pressing issue. However, soil types in that region, 1000 mm annual precipitation with intense rain during typhoons, and microtopography have presented challenges to understanding how Cs-137 behaves in those forests. In this study, six topographic parameters were computed from 1-m and 10-m resolution DEMs and the relationships between those parameters and soil water content and bulk density were systematically analyzed for their effects on Cs-137 concentration levels. As the first analytical step, correlation indices and the generalized additive models (GAM) analysis were conducted on those parameters. The results show that not all topographic effects are apparent in the correlation analysis, yet the results can be improved when mixed with other parameters in GAM models. Overall the effect of topographic parameters on Cs-137 levels is DEM resolution-dependent while individual soil properties indicate a strong relationship. Also, it was found that depending on the analysis depth, correlation levels and significance of those parameters in GAM models fluctuate. As the second step, Cs-137 levels were extrapolated to a larger area in the study site to understand further the connections between topography and soil properties. The results, including the limitations and proposals for future forest decontamination, will be presented in the session. Understanding how Cs-137 moves and accumulates in forests, especially immediately after contamination, is critical to avoiding the negative impacts on the environment by decontamination measures and to protecting lowlands from harmful radioactivity levels. This study contributes to the radionuclide research field by presenting an example of data analysis processes using field sampled data.

Understanding bat habitat use and how bat activity changes in response to differing habitats across time and space is critical in developing and implementing effective bat conservation actions. To investigate the utility of geographic information systems (GIS) in studying bat habitat interactions, habitat delineations and bioacoustic sampling were conducted along two transects in Chautauqua County, NY (USA) from mid-May until the end of August 2013. Surveys were vehicular, and driven between 29 and 32 kmph in order to match bats' flying speed. They were conducted starting 30 min after sunset on nights where the temperature was greater than 13 °C. In total, twenty surveys were completed, and 1248 bat calls were identified to species. Mixed models regression analysis revealed significant interactions among all of the species of bat analyzed in the model. The model was supported with a secondary analysis comparing bat call density with land cover. This study supports the hypothesis that bats forage in different habitats at the species level and indicates the importance of forested areas to bats. Additionally, the methodology for this study has the potential to gather large data sets in a short period of time, while collecting data on several species of bat at once and has been shown to be useful in identifying important habitat features for bats using bioacoustics and geospatial analysis. Since the data has been collected following state guidelines, the dataset and its analysis establish a baseline for future data collection campaigns and in performing a similar analysis for other regions within the state of New York or areas worldwide.

Spatially explicit agent-based models (ABMs) have been widely utilized to simulate the dynamics of spatial processes that involve the interactions of individual agents. The assumptions embedded in the ABMs may be responsible for uncertainty in the model outcomes. To ensure the reliability of the outcomes in terms of their space-time patterns, model validation should be performed. In this paper, we propose the use of multiple scale spatio-temporal patterns for validating spatially explicit ABMs. We evaluated several specifications of vector-borne disease transmission models by comparing space-time patterns of model outcomes to observations at multiple scales via the sum of root mean square error (RMSE) measurement. The results indicate that specifications of the spatial configurations of residential area and immunity status of individual humans are of importance to reproduce observed patterns of dengue outbreaks at multiple space-time scales. Our approach to using multiple scale spatio-temporal patterns can help not only to understand the dynamic associations between model specifications and model outcomes, but also to validate spatially explicit ABMs.

Sedentary behavior and lack of physical activity are key modifiable behavioral risk factors for chronic health problems, such as obesity and diabetes. Little is known about how sedentary behavior and physical activity among adolescents spatially cluster. The objective was to detect spatial clustering of sedentary behavior and physical activity among Boston adolescents. Data were used from the 2008 Boston Youth Survey Geospatial Dataset, a sample of public high school students who responded to a sedentary behavior and physical activity questionnaire. Four binary variables were created: 1) TV watching (>2 hours/day), 2) video games (>2 hours/day), 3) total screen time (>2 hours/day); and 4) 20 minutes/day of physical activity (≥5 days/week). A spatial scan statistic was utilized to detect clustering of sedentary behavior and physical activity. One statistically significant cluster of TV watching emerged among Boston adolescents in the unadjusted model. Students inside the cluster were more than twice as likely to report > 2 hours/day of TV watching compared to respondents outside the cluster. No significant clusters of sedentary behavior and physical activity emerged. Findings suggest that TV watching is spatially clustered among Boston adolescents. Such findings may serve to inform public health policymakers by identifying specific locations in Boston that could provide opportunities for policy intervention. Future research should examine what is linked to the clusters, such as neighborhood environments and network effects.

Community-acquired multidrug resistant Enterobacteriaceae (MDR-Ent) infections continue to increase in the United States. In prior studies, we identified neighboring regions in Chicago, Illinois, where children have 5 to 6 times greater odds of MDR-Ent infections. To prevent community spread of MDR-Ent, we need to identify the MDR-Ent reservoirs. A pilot study of 4 Chicago waterways for MDR-Ent and associated antibiotic resistance genes (ARGs) was conducted. Three waterways (A1 to A3) are labeled safe for “incidental contact recreation” (e.g., kayaking), and A4 is a nonrecreational waterway that carries nondisinfected water. Surface water samples were collected and processed for standard bacterial culture and shotgun metagenomic sequencing. Generally, A3 and A4 (neighboring waterways which are not hydraulically connected) were strikingly similar in bacterial taxa, ARG profiles, and abundances of corresponding clades and genera within the Enterobacteriaceae. Additionally, total ARG abundances recovered from the full microbial community were strongly correlated between A3 and A4 (R(2) = 0.97). Escherichia coli numbers (per 100 ml water) were highest in A4 (783 most probable number [MPN]) and A3 (200 MPN) relative to A2 (84 MPN) and A1 (32 MPN). We found concerning ARGs in Enterobacteriaceae such as MCR-1 (colistin), Qnr and OqxA/B (quinolones), CTX-M, OXA and ACT/MIR (beta-lactams), and AAC (aminoglycosides). We found significant correlations in microbial community composition between nearby waterways that are not hydraulically connected, suggesting cross-seeding and the potential for mobility of ARGs. Enterobacteriaceae and ARG profiles support the hypothesized concerns that recreational waterways are a potential source of community-acquired MDR-Ent.

The effects of water, sanitation, and hygiene (WASH) interventions have been well acknowledged to reduce the risk from diarrheal disease-causing pathogens. In spite of the recognized importance of WASH interventions on the reduction of diarrheal disease, there are still gaps in the understanding of the time-varying effects of interventions. To bridge this research gap, we developed agent-based models (ABMs) of diarrheal disease transmission in a community context. In the model, infections occur via two pathways: (i) between household members within the household environment and (ii) from the community environment outside the household. To measure the effectiveness of WASH interventions, we performed global sensitivity analysis (GSA) at the macro and micro temporal scales, varying the level of intervention coverage in the community. We simulated three intervention strategies, implemented separately in the experiments. The clean drinking water intervention, sanitation intervention, and hand washing intervention had similar success rates in the long-term. The handwashing intervention had the largest immediate effect. This highlights that proper short- and long-term intervention strategies need to be considered for disease control and the effective management of limited resources.Les effets des interventions sur l'eau, les sanitaires et l'hygiène (WASH) ont été bien reconnus pour réduire le risque d'agents pathogènes causant des maladies diarrhéiques. En dépit de l'importance reconnue des interventions WASH sur la réduction des maladies diarrhéiques, il reste des lacunes dans la compréhension des variations en fonction du temps des effets des interventions. Pour combler cette lacune en matière de recherche, nous avons développé des modèles à base d'agents (MBA) de la transmission des maladies diarrhéiques dans un contexte communautaire. Dans le modèle, les infections se produisent via deux voies: (1) entre les membres du ménage dans l'environnement du ménage et (2) depuis l'environnement de la communauté en dehors du ménage. Pour mesurer l'efficacité des interventions WASH, nous avons effectué une analyse de sensibilité globale (ASG) aux échelles macro et micro-temporelles, en faisant varier le niveau de couverture des interventions dans la communauté. Nous avons simulé trois stratégies d'intervention, mises en œuvre séparément dans les expériences. Les interventions sur l'eau potable, sur les sanitaires et sur le lavage des mains ont eu des taux de réussite similaires à long terme. L'intervention sur le lavage des mains a eu l'effet immédiat le plus important. Cela montre qu'il faut envisager des stratégies d'intervention appropriées à court et à long terme pour lutter contre la maladie et pour la gestion efficace des ressources limitées.

BackgroundThe purpose of this cross-sectional study was to determine the percentage of the US population with 60 min ground or air access to accredited or state-designated endovascular-capable stroke centers (ECCs) and non-endovascular capable stroke centers (NECCs) and the percentage of NECCs with an ECC within a 30 min drive.MethodsStroke centers were identified and classified broadly as ECCs or NECCs. Geographic mapping of stroke centers was performed. The population was divided into census blocks, and their centroids were calculated. Fastest air and ground travel times from centroid to nearest ECC and NECC were estimated.ResultsOverall, 49.6% of US residents had 60 min ground access to ECCs. Approximately 37.7% (113 million) lack 60 min ground or air access to ECCs. Approximately 84.4% have 60 min access to NECCs. Ground-only access was available to 77.9%. Approximately 738 NECCs (45.4%) had an ECC within a 30 min drive.ConclusionNearly one-third of the US population lacks 60 min access to endovascular stroke care, but this is highly variable. Transport models and planning of additional centers should be tailored to each state depending on location and proximity of existing facilities.

Background: Understanding geographic variation in youth drug use is important for both identifying etiologic factors and planning prevention interventions. However, little research has examined spatial clustering of drug use among youths by using rigorous statistical methods. Objectives: The purpose of this study was to examine spatial clustering of youth use of tobacco, alcohol, and marijuana. Methods: Responses on tobacco, alcohol, and marijuana use from 1,292 high school students ages 13–19 who provided complete residential addresses were drawn from the 2008 Boston Youth Survey Geospatial Dataset. Response options on past month use included “none,” “1–2,” “3–9,” and “10 or more.” The response rate for each substance was approximately 94%. Spatial clustering of youth drug use was assessed using the spatial Bernoulli model in the SatScan™ software package. Results: Approximately 12%, 36%, and 18% of youth reported any past-month use of tobacco, alcohol, and/or marijuana, respectively. Two cluster...

Densely populated countries in Asia, such as Bangladesh, are considered to be major contributors to the increased occurrence of global antimicrobial resistance (AMR). Several factors make low-and middle-income countries vulnerable to increased emergence and spread of AMR in the environment including limited regulations on antimicrobial drug use, high volume of antimicrobials used in human medicine and agricultural production, and poor wastewater management. Previous monitoring campaigns to investigate the presence of antibiotics in the aquatic environment have employed targeted analysis in which selected antibiotics are measured using liquid chromatography with tandem mass spectrometry (LC/MS/MS). However, this approach can miss several important contaminants that can contribute to the selective pressure that promotes maintenance and dissemination of antibiotic resistance genes (ARGs) in the environment. Nontarget analysis by suspect screening and reanalysis of stored digital data of previously ran samples can provide information on analytes that were formerly uncharacterized and may be chemicals of emerging concern (CECs). In this study, surface waters in both urban and rural sites in Bangladesh were collected and analyzed for the presence of antibiotic residues and other pharmaceuticals. Utilizing targeted analysis, the antibiotics with the highest concentrations detected were ciprofloxacin (1407 ng/L) and clarithromycin (909 ng/L). In addition, using high-resolution LC/MS/MS in the first ever application of retrospective analysis in samples from Bangladesh, additional antibiotics clindamycin, lincomycin, linezolid, metronidazole, moxifloxacin, nalidixic acid, and sulfapyridine were detected. Prevalence of amoxicillin transformation products in surface waters was also confirmed. In addition, medicinal and agricultural antifungal compounds were frequently found in Bangladeshi surface waters. This later finding – the near ubiquity of antifungal agents in environmental samples – is of particular concern, as it may be contributing to the alarming rise of multi-drug resistant fungal (e.g. Candida auris) disease recently seen in humans throughout the world.

International audience; Dengue is of public health importance in tropical and sub-tropical regions. Dengue virus (DENV) transmission dynamics was studied in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance of 93 hospitalized subjects with confirmed dengue (initiates) and associated cluster individuals (associates) with entomologic sampling. A total of 438 associates were enrolled from 208 houses with household members with a history of fever, located within a 200-m radius of an initiate case. Of 409 associates, 86 (21%) had laboratory-confirmed DENV infection. A total of 63 (1.8%) of the 3,565 mosquitoes collected were dengue polymerase chain reaction positive (PCR+). There was a significant relationship between spatial proximity to the initiate case and likelihood of detecting DENV from associate cases and Aedes mosquitoes. The viral detection rate from human hosts and mosquito vectors in this study was higher than previously observed by the study team in the same geographic area using different methodologies. We propose that the sampling strategy used in this study could support surveillance of DENV transmission and vector interactions.

This study examined the spatio-temporal relationship between on-premises alcohol outlet locations and crime events in Buffalo, New York. Specifically, this research examined whether crime became clustered around on-premises alcohol outlet locations after those locations were licensed. Data from licensed alcohol outlets and violent crime events that occurred between 2005 and 2011 were analyzed using global and local bivariate space-time k-function analyses. The global bivariate space-time K-function analyses indicated that there was dispersion between bars and crime over space and time. Personal crimes showed both dispersion and clustering. Local analyses revealed clustering between alcohol outlets and crimes at discrete space-time intervals. Spatio-temporal analysis of the association between bars and crime gives an indication of the direction of the relationship between them. If this dynamic is better understood, it could be better regulated.

The objective was to detect geospatial clustering of sugar-sweetened beverage (SSB) intake in Boston adolescents (age = 16.3 ± 1.3 years [range: 13-19]; female = 56.1%; White = 10.4%, Black = 42.6%, Hispanics = 32.4%, and others = 14.6%) using spatial scan statistics. We used data on self-reported SSB intake from the 2008 Boston Youth Survey Geospatial Dataset (n = 1292). Two binary variables were created: consumption of SSB (never versus any) on (1) soda and (2) other sugary drinks (e.g., lemonade). A Bernoulli spatial scan statistic was used to identify geospatial clusters of soda and other sugary drinks in unadjusted models and models adjusted for age, gender, and race/ethnicity. There was no statistically significant clustering of soda consumption in the unadjusted model. In contrast, a cluster of non-soda SSB consumption emerged in the middle of Boston (relative risk = 1.20, p = .005), indicating that adolescents within the cluster had a 20% higher probability of reporting non-soda SSB intake than outside the cluster. The cluster was no longer significant in the adjusted model, suggesting spatial variation in non-soda SSB drink intake correlates with the geographic distribution of students by race/ethnicity, age, and gender.

As geospatial researchers' access to high-performance computing clusters continues to increase alongside the availability of high-resolution spatial data, it is imperative that techniques are devised to exploit these clusters' ability to quickly process and analyze large amounts of information. This research concentrates on the parallel computation of A Multidirectional Optimal Ecotope-Based Algorithm AMOEBA. AMOEBA is used to derive spatial weight matrices for spatial autoregressive models and as a method for identifying irregularly shaped spatial clusters. While improvements have been made to the original ‘exhaustive’ algorithm, the resulting ‘constructive’ algorithm can still take a significant amount of time to complete with large datasets. This article outlines a parallel implementation of AMOEBA the P-AMOEBA written in Java utilizing the message passing library MPJ Express. In order to account for differing types of spatial grid data, two decomposition methods are developed and tested. The benefits of using the new parallel algorithm are demonstrated on an example dataset. Results show that different decompositions of spatial data affect the computational load balance across multiple processors and that the parallel version of AMOEBA achieves substantially faster runtimes than those reported in related publications.

Objective To determine the temporal intervals at which spatial clustering of dengue hospitalisations occurs. Methods Space-time analysis of 262 people hospitalised and serologically confirmed with dengue virus infections in Kamphaeng Phet, Thailand was performed. The cases were observed between 1 January 2009 and 6 May 2011. Spatial coordinates of each patient’s home were captured using the Global Positioning System. A novel method based on the Knox test was used to determine the temporal intervals between cases at which spatial clustering occurred. These intervals are indicative of the length of time between successive illnesses in the chain of dengue virus transmission. Results The strongest spatial clustering occurred at the 15–17-day interval. There was also significant spatial clustering over short intervals (2–5 days). The highest excess risk was observed within 200 m of a previous hospitalised case and significantly elevated risk persisted within this distance for 32–34 days. Conclusions Fifteen to seventeen days are the most likely serial interval between successive dengue illnesses. This novel method relies only on passively detected, hospitalised case data with household locations and provides a useful tool for understanding region-specific and outbreak-specific dengue virus transmission dynamics. Objectif: Determiner les intervalles temporels au cours desquels survient le regroupement spatial des hospitalisations pour dengue. Methodes: L’’analyse spatio-temporelle de 262 personnes hospitalisees et confirmees par la serologie pour des infections au virus de la dengue a Kamphaeng Phet, en Thailande a ete realisee. Les cas ont ete observes entre le 1er janvier 2009 et le 6 mai 2011. Les coordonnees spatiales du domicile de chaque patient ont ete capturees a l’aide du Systeme de Positionnement Global. Une nouvelle methode basee sur le test de Knox a ete utilisee pour determiner les intervalles temporels entre les cas au cours desquels le regroupement spatial a eu lieu. Ces intervalles sont des indicateurs de la duree de temps entre les maladies successives dans la chaine de transmission de virus de la dengue. Resultats: Le plus important regroupement spatial a eu lieu dans l’intervalle de 15 a 17 jours. Il y avait egalement un regroupement spatial significatif sur des intervalles courts (2 a 5 jours). Le risque en exces le plus eleve a ete observea endeans 200 m d’un cas precedent hospitalise et un risque significativement eleve a persiste dans cette zone durant 32 a 34 jours. Conclusions: L’intervalle de series de 15 a 17 jours est le plus probable entre les maladies successives de la dengue. Cette nouvelle methode repose uniquement sur les donnees de cas hospitalises, detectes passivement avec les emplacements des menages et constitue un outil utile pour comprendre la dynamique de la transmission du virus de la dengue specifique a la region et specifique a l’epidemie. Objetivo: Determinar los intervalos temporales en los que ocurren conglomerados espaciales de hospitalizacion por dengue. Metodos: Se realizo un analisis espacio temporal a 262 personas hospitalizadas y con confirmacion serologica de infeccion por el virus del dengue en Kamphaeng Phet, Tailandia. Los casos se observaron entre el 1 de Enero del 2009 y el 6 de Mayo del 2011. Las coordenadas espaciales del hogar de cada paciente fueron capturadas utilizando un Sistema de Posicionamiento Global. Se utilizo un nuevo metodo, basado en la prueba de Knox, para determinar los intervalos temporales entre los casos en los que habia conglomerados espaciales. Estos intervalos son indicativos del lapso de tiempo entre enfermedades sucesivas en la cadena de transmision del virus del dengue. Resultados: El mayor conglomerado espacial ocurrio en un intervalo de 15 a 17 dias. Tambien habia un conglomerado espacial significativo en intervalos cortos (2–5 dias). El mayor exceso de riesgo se observo dentro de un radio de 200 m de un caso previamente hospitalizado y un riesgo significativamente elevado persistia, dentro de esta distancia, durante 32–34 dias. Conclusiones: Los 15–17 dias son el intervalo mas probable entre dos casos sucesivos de dengue. Este nuevo metodo depende solamente de la disponibilidad de datos de casos hospitalizados, detectados de forma pasiva y con hogares localizables, y brinda una herramienta util para entender la dinamica de transmision del virus del dengue, region-especifica y especifica de brotes.

We investigated the validity of Walk Scores and Transit Scores from the Walk Score website using several objective geographic information systems (GIS) measures of neighborhood walkabiltiy and transit availability based on 400- and 800-m street network buffers. Address data come from the 2008 Boston Youth Survey Geospatial Dataset, a school-based sample of public high school students in Boston, MA with complete residential address information (n = 1,292). GIS data were used to create multiple objective measures of neighborhood walkability and transit availability. We also obtained Walk Scores and Transit Scores. We calculated Spearman correlations of Walk Scores and Transit Scores with the GIS neighborhood walkability/transit availability measures as well as Spearman correlations accounting for spatial autocorrelation. Several significant correlations were observed between Walk Score and 400-m buffer GIS measures of neighborhood walkability; all significant correlations were found for the 800-m buffer. All correlations between Transit Scores and GIS measures of neighborhood transit availability were also significant (all p < 0.0001). However, the magnitude of correlations varied by the GIS measure and neighborhood definition. Relative to the 400-m buffer, correlations for the 800-m buffer were higher. This study suggests that Walk Score is a good, convenient tool to measure certain aspects of neighborhood walkability and transit availability (such as density of retail destinations, density of recreational open space, intersection density, residential density and density of subway stops). However, Walk Score works best at larger spatial scales.

Neighborhood walkability can influence physical activity. We evaluated the validity of Walk Score(®) for assessing neighborhood walkability based on GIS (objective) indicators of neighborhood walkability with addresses from four US metropolitan areas with several street network buffer distances (i.e., 400-, 800-, and 1,600-meters). Address data come from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5-11 years and their families participating in YMCA-administered, after-school programs located in four geographically diverse metropolitan areas in the US (n = 733). GIS data were used to measure multiple objective indicators of neighborhood walkability. Walk Scores were also obtained for the participant's residential addresses. Spearman correlations between Walk Scores and the GIS neighborhood walkability indicators were calculated as well as Spearman correlations accounting for spatial autocorrelation. There were many significant moderate correlations between Walk Scores and the GIS neighborhood walkability indicators such as density of retail destinations and intersection density (p0.05). The magnitude varied by the GIS indicator of neighborhood walkability. Correlations generally became stronger with a larger spatial scale, and there were some geographic differences. Walk Score(®) is free and publicly available for public health researchers and practitioners. Results from our study suggest that Walk Score(®) is a valid measure of estimating certain aspects of neighborhood walkability, particularly at the 1600-meter buffer. As such, our study confirms and extends the generalizability of previous findings demonstrating that Walk Score is a valid measure of estimating neighborhood walkability in multiple geographic locations and at multiple spatial scales.

In this paper, we present an efficiency improvement for the algorithm called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, devised by Aldstadt and Getis (Geogr Anal 38(4):327–343, 2006). AMOEBA embeds a local spatial autocorrelation statistic in an iterative procedure in order to identify spatial clusters (ecotopes) of related spatial units. We provide an analysis of the computational complexity of the original AMOEBA and develop an alternative formulation that reduces computational time without losing optimality. Empirical evidence is provided using georeferenced socio-demographic data in Accra, Ghana.

We investigated how temporal and spatial effects confound the functional relationship between pupal and adult populations of Aedes aegypti and thus the value of pupal numbers as predictors of dengue transmission risk in Kamphaeng Phet, Thailand. We found considerable seasonal shifts in productivity of key containers. Tires contained much less pupae in the dry season than in the wet season. Earthenware jars and cement tanks for washing purposes were consistent producers over the entire study period. Houses in the two villages, with approximately twice as many houses per unit area, were significantly more likely to have adults and pupae. No significant annual, seasonal, or spatial effects on the strength of correlations between pupal and adult populations were found. Except for 2 (of 16) occasions, pupal, and adult populations were correlated strongly in time and space. Our results are consistent with application of the pupal survey technique for assessing dengue transmission risk.

Given that tools for dengue emergency control are limited, continuous evaluation of the effectiveness of insecticide applications in the field is of utmost importance. Such studies will provide a sound basis for defining spraying schemes for public health authorities in dengue-affected countries. In this article, we address the following research questions: How do different space spraying strategies affect Aedes aegypti (L.) (Diptera: Culicidae) populations in both space and time? More specifically, how well are these mosquitoes killed, and how quickly do their populations recover and from where? Field trials were carried out with ultralow volume sprayers in Kamphaeng Phet province, Thailand, with a pyrethrin mixture that was applied 1) indoors only, 2) indoors plus outdoors, 3) indoors with a doubled spraying time, and 4) indoors with doubled spraying time plus outdoors. We found that within 7 d, Ae. aegypti populations recovered to ≈50% of their original numbers. Spraying the outdoor area and doubling the time sprayed per room only had a significant impact on mosquito numbers 1 d after spraying. Two and 7 d after spraying, these effects were no longer detected. By investigating the spatial arrangement of Ae. aegypti numbers, we found that during the first 2 d after spraying immigration from untreated areas extended ≈15 m into the sprayed area, whereas after 7 d this effect extended up to 50 m. Results are discussed in relation to ongoing dengue control efforts in Thailand.

Cardiac remodeling and failure are regulated by a myriad of cardiac protein phosphorylations. In the present study, cardiac phosphoprotein patterns were examined in rodent and human hearts Left ventricular tissue samples were obtained from human systolic failing (n = 5) and control (n = 5) hearts and from two rat models of hypertensive heart failure, i.e., spontaneously hypertensive heart failure and Dahl salt-sensitive rats and corresponding controls. Phosphoproteins were separated by 2D-DIGE with Cydye staining, phosphoprotein patterns were analyzed using pixel intensity in rectified images. Specific phosphoproteins which were different in human versus rodent hearts were identified by MALDI-TOF/TOF Mass Spectrometry. Targeted pair-wise analyses showed differences (p

Background: Rodent models are commonly used to study hypertensive heart disease. Several recent studies have probed the level of correlation between specific signaling pathways and proteins in human and rodents. Current evidence is overwhelming that protein phosphorylations play a key role in cardiac remodeling. Methods: Left ventricular tissue samples were obtained from human systolic failing (n=5) and control (n=5) hearts and 3 rat models of hypertensive heart failure (aortic banding, Dahl salt-sensitive, and spontaneously hypertensive rats (SHR)) and corresponding controls. Total proteins were extracted and and phosphoenrichment performed. Phosphoproteins were separated by 2D-DIGE with Cydye staining. Gel images were registered and rectified for composite analysis and statistical comparisons using pixel intensity. Phosphoproteins were identified by MALDI-TOF/TOF Mass Spectrometry. Results: The patterns of overall protein abundance from normal and failing hearts were not statistically different. However, when the composite of human hearts were compared with composite patterns of phosphoproteins in normal and failing rodent hearts, there were profound differences in the phosphoprotein patterns in 26% of pixels in registered images (P < 0.05). Targeted pair wise analyses showed differences (P < 0.05) between human and rodent hearts for troponin T, myosin light chain, peroxiredoxin, and haptoglobin phosphorylations. Conclusions: Together, the present results indicate significant differences in cardiac phosphoproteins in human versus rodent heart and the importance of confirming findings from rodent studies in humans for translational studies of kinases, phosphatases, and phosphoproteins. This may specifically relate to studies of phosphorylation of myosin light chain and troponin.

The creation of a spatial weights matrix by a procedure called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, is dependent on the use of a local spatial autocorrelation statistic. The result is (1) a vector that identifies those spatial units that are related and unrelated to contiguous spatial units and (2) a matrix of weights whose values are a function of the relationship of the ith spatial unit with all other nearby spatial units for which there is a spatial association. In addition, the AMOEBA procedure aids in the demarcation of clusters, called ecotopes, of related spatial units. Experimentation reveals that AMOEBA is an effective tool for the identification of clusters. A comparison with a scan statistic procedure (SaTScan) gives evidence of the value of AMOEBA. Total fertility rates in enumeration districts in Amman, Jordan, are used to show a real-world example of the use of AMOEBA for the construction of a spatial weights matrix and for the identification of clusters. Again, comparisons reveal the effectiveness of the AMOEBA procedure.

Dengue is a mosquito-borne infectious disease that is endemic in tropical and subtropical countries. Many individual-level simulation models have been developed to test hypotheses about dengue virus transmission. Often these efforts assume that human host and mosquito vector populations are randomly or uniformly distributed in the environment. Although, the movement of mosquitoes is affected by spatial configuration of buildings and mosquito populations are highly clustered in key buildings, little research has focused on the influence of the local built environment in dengue transmission models. We developed an agent-based model of dengue transmission in a village setting to test the importance of using realistic environments in individual-level models of dengue transmission. The results from one-way ANOVA analysis of simulations indicated that the differences between scenarios in terms of infection rates as well as serotype-specific dominance are statistically significant. Specifically, the infection rates in scenarios of a realistic environment are more variable than those of a synthetic spatial configuration. With respect to dengue serotype-specific cases, we found that a single dengue serotype is more often dominant in realistic environments than in synthetic environments. An agent-based approach allows a fine-scaled analysis of simulated dengue incidence patterns. The results provide a better understanding of the influence of spatial heterogeneity on dengue transmission at a local scale.