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Carpooling is an effective means of reducing traffic. A carpool team shares a vehicle for their commute, which reduces the number of vehicles on the road during rush hour periods. Carpooling is officially sanctioned by most governments, and is supported by the construction of high-occupancy vehicle lanes. A number of carpooling services have been designed in order to match commuters into carpool teams, but it known that the determination of optimal carpool teams is a combinatorially complex problem, and therefore technological solutions are difficult to achieve. In this paper, a model for carpool matching services is proposed, and both optimal and heuristic approaches are tested to find solutions for that model. The results show that different solution approaches are preferred over different ranges of problem instances. Most importantly, it is demonstrated that a new formulation and associated solution procedures can permit the determination of optimal carpool teams and routes. An instantiation of the model is presented (using the street network of Guangzhou city, China) to demonstrate how carpool teams can be determined.

Disparities in geographic access to medication for opioid use disorder (OUD) are well documented. Further, historical implications of systemic racism and of the longstanding War on Drugs in the United States have driven both social and spatial inequities in access to treatment. This work builds on a previously published spatial access methodology that uses a gravity-based variant of the enhanced two-step floating catchment area model, to determine how OUD pharmacotherapy accessibility varies nationally at the census tract level. Medication for OUD (MOUD) accessibility scores are then analyzed by rurality and racial/ethnic segregation. The Getis-Ord Gi* statistic was used to identify clusters of high or low accessibility to MOUD, while the interaction index was used as a measure of segregation to assess the racial/ethnic population distribution. The results of the clustering statistic, and the associated significance values were then compared to rurality and interaction using the Chi-Square test to determine if hot or cold areas of access are independent of rurality and racial/ethnic spatial distributions. Lastly, the percentage of buprenorphine providers at capacity by census tract was calculated using the binary 'at-capacity' data attribute associated with each SAMHSA buprenorphine provider record. The results demonstrate distinct spatial variability of MOUD resources based on urbanicity and racial makeup that have significant implications for intervention or policy reform that seeks to encourage equal access to both treatment modalities. MOUD access varies by racial segregation and rurality Black segregated and integrated Black-White urban communities have greater accessibility to both MOUD types White urban communities have significantly lower levels of spatial access to MOUD Low urban MOUD induction and adherence rates of minority populations are likely not strongly driven by spatial access, rather structural, political, physical, and social components are more influential to intervention uptake. 97% of buprenorphine providers were at their patient capacity limit prior to the end of the federal DATA waiver process in June 2023.

Understanding the determinants that influence obesity among children and adolescents is critical to the prevention of obesity and obesity-related diseases later in life. The findings presented here broaden the understanding of obesity-related challenges by adding analyses that compare nutritional indicators among boys and girls between the ages of 11 and 16 years, by exploring the more recent literature to examine if past trends have continued or not, and by synthesizing the recent findings concerning the causes and determinants of such trends in obesity. Both data from 2005 and the more recent literature review have shown that the consumption of high calorie foods and snacks, greater screen time, body image, and depressive factors play a significant role regarding obesity during adolescence in Thailand. There continues to be a trend of increasing obesity among adolescents in Thailand, and this may be more of a concern in boys. Interviews with health professionals and parents from the 2005 study suggested that girls were more aware of their physical appearance, and there was more societal acceptance to be obese as a boy in Thailand compared to girls. These findings can inform nutritional education practices and policies.

Transnational cocaine trafficking, or ‘narco-trafficking’, networks often move large shipments of harmful and illegal drugs by sea through the use of unregulated boats in remote maritime spaces. This study presents a framework for identifying narco-trafficking drop-off zones by detecting and analyzing Unreported and Unregulated Boats (UUBs) potentially linked to narco-trafficking in Costa Rica’s Guanacaste and Puntarenas regions, utilizing a combination of high-resolution satellite imagery, machine learning, and spatial analysis. By training a YoloV5 convolutional neural network model, we detected boat wakes in PlanetScope satellite images, which were then cross-referenced with legal vessel traffic data (Automatic Identification System and Vessel Monitoring System) to isolate UUBs. A spatial autocorrelation analysis revealed a positive association between UUB locations and narco-trafficking activity indicators, such as drug-related media reports, court arrest records, and cocaine seizure data. High-high clusters of UUBs and trafficking indicators suggested that particular coastal districts may serve as primary landing zones for illicit shipments, a finding consistent with secondary data on cocaine trafficking in the region. By integrating geospatial intelligence with contextual data sources, this study advances methodology for identifying narco-trafficking drop-off zones and contributes a spatially explicit perspective to the broader understanding of cocaine and other illicit supply chains. Despite the limitations of cloud cover and restricted nighttime visibility, this framework offers a proof-of-concept approach for identifying UUB concentrations and cocaine drop-off shipment zones. Future work should consider expanding temporal coverage and multiple imagery to further enhance the identification of narco-trafficking zones.

BACKGROUND: Dengue is an acute arboviral disease responsible for most of the illness and death in tropical and subtropical regions. Over the last 25 years there has been increase epidemic activity of the disease in the Caribbean, with the co-circulation of multiple serotypes. An understanding of the space and time dynamics of dengue could provide health agencies with important clues for reducing its impact. METHODS: Dengue Haemorrhagic Fever (DHF) cases observed for the period 1998–2004 were georeferenced using Geographic Information System software. Spatial clustering was calculated for individual years and for the entire study period using the Nearest Neighbor Index. Space and time interaction between DHF cases was determined using the Knox Test while the Nearest Neighbor Hierarchical method was used to extract DHF hot spots. All space and time distances calculated were validated using the Pearson r significance test. RESULTS: Results shows that (1) a decrease in mean distance between DHF cases correlates with activity leading up to an outbreak, (2) a decrease in temporal distance between DHF cases leads to increased geographic spread of the disease, with an outbreak occurrence about every 2 years, and (3) a general pattern in the movement of dengue incidents from more rural to urban settings leading up to an outbreak with hotspot areas associated with transportation hubs in Trinidad. CONCLUSION: Considering only the spatial dimension of the disease, results suggest that DHF cases become more concentrated leading up to an outbreak. However, with the additional consideration of time, results suggest that when an outbreak occurs incidents occur more rapidly in time leading to a parallel increase in the rate of distribution of the disease across space. The results of this study can be used by public health officers to help visualize and understand the spatial and temporal patterns of dengue, and to prepare warnings for the public. Dengue space-time patterns and hotspot detection will provide useful information to support public health officers in their efforts to control and predict dengue spread over critical hotspots allowing better allocation of resources.

This paper presents a new method for determining efficient spatial distributions of police patrol areas. This method employs a traditional maximal covering formulation and an innovative backup covering formulation to provide alternative optimal solutions to police decision makers, and to address the lack of objective quantitative methods for police area design in the literature or in practice. This research demonstrates that operations research methods can be used in police decision making, presents a new backup coverage model that is appropriate for patrol area design, and encourages the integration of geographic information systems and optimal solution procedures. The models and methods are tested with the police geography of Dallas, TX. The optimal solutions are compared with the existing police geography, showing substantial improvement in number of incidents covered as well as total distance traveled.

Pedestrian infrastructure is an essential part of the urban fabric. Typically, it is carefully planned and maintained by governments and local experts, who recognize the benefits to health, wellbeing, and even economics associated with a walkable environment. Pedestrian walkway characteristics, including running slope, cross slope, curb cuts, cross walks, sidewalk widths, and signalization are a part of the comprehensive design elements used by most municipalities. However, barriers or obstacles, including temporary obstructions, construction detours, and surface irregularities make this infrastructure difficult for individuals with a mobility impairment or vision impairment to use. Crowdsourcing can assist these individuals by providing information about transient and permanent navigation obstacles, through an accessibility mapping system. Accessibility mapping systems, several examples of which are discussed in this paper, provide routing functions to make navigation easier for individuals with a mobility impairment or vision impairment. A geocrowdsourced accessibility system can also identify deficiencies in a pedestrian network dynamically, and can provision routing and obstacle avoidance functions in real-time, with data about transient events provided by the public. This paper is based upon previous geocrowdsourced data quality studies, and presents a modeling methodology to identify high-value routing corridors in a dynamic geocrowdsourced accessibility system. The corridor measurement can help civic employees from city public works and transportation departments prioritize maintenance of a pedestrian infrastructure, including the rectification of obstacles identified through crowdsourcing. In this paper, we augment geocrowdsourcing data quality metrics with input from subject matter experts trained in orientation and mobility services, and discuss the accessibility elements that could directly influence the usability of the pedestrian infrastructure. We also present a cost optimization model to measure the value of a pedestrian network segment. Lastly, this paper analyzes how the value of a network segment in a geocrowdsourced accessibility system changes with network conditions and how this relates to prioritization of maintenance tasks through optimization criteria.

Tower-mounted camera-based wildfire detection systems provide an effective means of early forest fire detection. Historically, tower sites have been identified by foresters and locals with intimate knowledge of the terrain and without the aid of computational optimisation tools. When moving into vast new territories and without the aid of local knowledge, this process becomes cumbersome and daunting. In such instances, the optimisation of final site layouts may be streamlined if a suitable strategy is employed to limit the candidate sites to landforms which offer superior system visibility. A framework for the exploitation of landforms for these purposes is proposed. The landform classifications at 165 existing tower sites from wildfire detection systems in South Africa, Canada and the USA are analysed using the geomorphon technique, and it is noted that towers are located at or near certain landform types. A metaheuristic and integer linear programming approach is then employed to search for optimal tower sites in a large area currently monitored by the ForestWatch wildfire detection system, and these sites are then classified according to landforms. The results support the observations made for the existing towers in terms of noteworthy landforms, and the optimisation process is repeated by limiting the candidate sites to selected landforms. This leads to solutions with improved system coverage, achieved within reduced computation times. The presented framework may be replicated for use in similar applications, such as site-selection for military equipment, cellular transmitters, and weather radar.

The purpose of the study was to examine geographic relationships of nutritional status (BMI), including underweight, overweight and obesity, among Kenyan mothers and children. Spatial relationships were examined concerning BMI of the mothers and BMI-for-age percentiles of their children. These included spatial statistical measures of the clustering of segments of the population, in addition to inspection of co-location of significant clusters. Rural and urban areas of Kenya, including the cities of Nairobi and Mombasa, and the Kisumu region. Mother-child pairs from Demographic and Health Survey data including 1541 observations in 2003 and 1592 observations in 2009. These mother-child pairs were organized into 399 locational clusters. There is extremely strong evidence that high BMI values exhibit strong spatial clustering. There were co-locations of overweight mothers and overweight children only in the Nairobi region, while both underweight mothers and children tended to cluster in rural areas. In Mombasa clusters of overweight mothers were associated with normal-weight children, while in the Kisumu region clusters of overweight children were associated with normal-weight mothers. These findings show there is geographic variability as well as some defined patterns concerning the distribution of malnutrition among mothers and children in Kenya, and suggest the need for further geographic analyses concerning the potential factors which influence nutritional status in this population. In addition, the methods used in this research may be easily applied to other Demographic and Health Survey data in order to begin to understand the geographic determinants of health in low-income countries.

The purposes of this study were to evaluate the psychometric properties of English and Spanish instruments that measure the nutrition behavior and practices of children and their parents. Orem’s self-care deficit nursing theory was used in this methodological study. A convenience sample of 333 children and 262 mothers participated from two schools in Washington, D.C. and two schools in Santiago, Chile. Principal component analysis indicated three component per instrument corresponding to Orem’s Theory of operations demonstrating construct validity of the instrument. The study findings showed evidence for validity and reliability of the English and Spanish versions and indicated that the instruments appropriately represented Orem’s operations. The results have implications for the development of health behavior measurement instruments that are valid, reliable, designed for children, culturally appropriate, and efficient. Measuring the nutrition behavior of children and parents is critical for determining the effectiveness of nutrition intervention programs. Furthermore, instruments are needed so that researchers can compare corresponding child and parent behaviors or compare behaviors across cultures.