scholarly journals The Lyme and Tickborne Disease Dashboard: A map-based resource to promote public health awareness and research collaboration

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260122
Author(s):  
Frank C. Curriero ◽  
Cara Wychgram ◽  
Alison W. Rebman ◽  
Anne E. Corrigan ◽  
Anton Kvit ◽  
...  
Keyword(s):  
Public Health ◽  
Spatial Data ◽  
Scientific Collaboration ◽  
One Health ◽  
Research Collaboration ◽  
Data Driven ◽  
Data Sets ◽  
Future Directions ◽  
The Us ◽  
Spatial Data Sets

With the incidence of Lyme and other tickborne diseases on the rise in the US and globally, there is a critical need for data-driven tools that communicate the magnitude of this problem and help guide public health responses. We present the Johns Hopkins Lyme and Tickborne Disease Dashboard (https://www.hopkinslymetracker.org/), a new tool that harnesses the power of geography to raise awareness and fuel research and scientific collaboration. The dashboard is unique in applying a geographic lens to tickborne diseases, aiming not only to become a global tracker of tickborne diseases but also to contextualize their complicated geography with a comprehensive set of maps and spatial data sets representing a One Health approach. We share our experience designing and implementing the dashboard, describe the main features, and discuss current limitations and future directions.

scholarly journals An ABC-optimized fuzzy ELECTRE approach for assessing petroleum potential at the petroleum system level

2020 ◽  
Vol 12 (1) ◽  
pp. 580-597
Author(s):  
Mohamad Hamzeh ◽  
Farid Karimipour
Keyword(s):  
Spatial Data ◽  
Spatial Models ◽  
Model Performance ◽  
Essential Elements ◽  
Petroleum System ◽  
Petroleum Exploration ◽  
System Level ◽  
Data Sets ◽  
Petroleum Potential ◽  
Spatial Data Sets

AbstractAn inevitable aspect of modern petroleum exploration is the simultaneous consideration of large, complex, and disparate spatial data sets. In this context, the present article proposes the optimized fuzzy ELECTRE (OFE) approach based on combining the artificial bee colony (ABC) optimization algorithm, fuzzy logic, and an outranking method to assess petroleum potential at the petroleum system level in a spatial framework using experts’ knowledge and the information available in the discovered petroleum accumulations simultaneously. It uses the characteristics of the essential elements of a petroleum system as key criteria. To demonstrate the approach, a case study was conducted on the Red River petroleum system of the Williston Basin. Having completed the assorted preprocessing steps, eight spatial data sets associated with the criteria were integrated using the OFE to produce a map that makes it possible to delineate the areas with the highest petroleum potential and the lowest risk for further exploratory investigations. The success and prediction rate curves were used to measure the performance of the model. Both success and prediction accuracies lie in the range of 80–90%, indicating an excellent model performance. Considering the five-class petroleum potential, the proposed approach outperforms the spatial models used in the previous studies. In addition, comparing the results of the FE and OFE indicated that the optimization of the weights by the ABC algorithm has improved accuracy by approximately 15%, namely, a relatively higher success rate and lower risk in petroleum exploration.

scholarly journals Mining Co-Location Patterns with Rare Events from Spatial Data Sets

2006 ◽  
Vol 10 (3) ◽  
pp. 239-260 ◽  
Author(s):  
Yan Huang ◽  
Jian Pei ◽  
Hui Xiong
Keyword(s):  
Spatial Data ◽  
Rare Events ◽  
Data Sets ◽  
Location Patterns ◽  
Spatial Data Sets

scholarly journals Refinement Algoritm of Hypotheses Testing Research Based on Geochronological Tracking

2020 ◽  
Vol 6 (1) ◽  
pp. 86-93
Author(s):  
R. Ivakin ◽  
Y. Ivakin ◽  
S. Potapichev
Keyword(s):  
Spatial Data ◽  
Optimization Problem ◽  
Retrospective Studies ◽  
Subject Area ◽  
Statistical Testing ◽  
Time Interval ◽  
Data Sets ◽  
Hypotheses Testing ◽  
Practical Application ◽  
Spatial Data Sets

Geochronological tracking is an effective information technology for digital cartographic spatial data sets processing. It is widely known in retrospective patterns research about geographic relocation of figures, or any other units for a given time interval. Software component of geochronological tracking is becoming one the most popular GIS-integrated applications. The article presents the basic provisions for the algorithmization of the geochronological tracking procedure for statistical testing of retrospective studies hypotheses. We can observe the results of solving this optimization problem in a general form and in a number of the most typical variants. The obtained results of solving the optimization problem are interpreted in terms of the retrospective studies subject area. There are shown the ways of further practical application of the optimized algorithm in the tasks of modern logistics, data mining and formalized knowledge.

Understanding Accessibility

2016 ◽  
pp. 223-257
Author(s):  
Kivanc Ertugay ◽  
Sebnem H. Duzgun
Keyword(s):  
Spatial Data ◽  
Catchment Area ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Data Sets ◽  
Location Allocation ◽  
Modeling Process ◽  
Key Variables ◽  
Spatial Data Sets ◽  
Significant Support

Accessibility measures are generally concerned with equity and a better distribution of services in a territory and can be accepted as key variables for supporting supply/demand, location/allocation and service/catchment area related planning policies and strategies at national, regional, and local levels. Since accessibility measures need organization of huge and complex spatial data sets, accessibility modeling often lends itself to Geographical Information Systems (GIS) for analysis and presentation. Since numerous accessibility measures and modeling techniques ranging from simple to sophisticated can be found in the literature, this work aim to provide an overview of the theoretical framework and relevant background about GIS-based accessibility modeling process. The results could provide a significant support for the decision makers who are supposed to deal with transportation planning, accessibility modeling, location/allocation and service/catchment area related issues.

Understanding Accessibility

2018 ◽  
pp. 576-608
Author(s):  
Kivanc Ertugay ◽  
Sebnem H. Duzgun
Keyword(s):  
Spatial Data ◽  
Catchment Area ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Data Sets ◽  
Location Allocation ◽  
Modeling Process ◽  
Key Variables ◽  
Spatial Data Sets ◽  
Significant Support

Accessibility measures are generally concerned with equity and a better distribution of services in a territory and can be accepted as key variables for supporting supply/demand, location/allocation and service/catchment area related planning policies and strategies at national, regional, and local levels. Since accessibility measures need organization of huge and complex spatial data sets, accessibility modeling often lends itself to Geographical Information Systems (GIS) for analysis and presentation. Since numerous accessibility measures and modeling techniques ranging from simple to sophisticated can be found in the literature, this work aim to provide an overview of the theoretical framework and relevant background about GIS-based accessibility modeling process. The results could provide a significant support for the decision makers who are supposed to deal with transportation planning, accessibility modeling, location/allocation and service/catchment area related issues.

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