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Students in geographic information systems and science (GIS) require significant experience outside of spatial analysis, cartography, and other traditional geographic topics. Computer science knowledge, skills, and practices exist as essential components of GIS practice, but coursework in this area is not universally offered in geography or GIS degrees. To support those interested in developing such courses, this paper describes the design and implementation of a server-focused course in WebGIS at Texas A&M University. We provide an in-depth discussion of the equipment and resources required to build and operate an on-premise CyberGIS server infrastructure suitable for supporting such classes, providing comparisons with an equivalent solution built on Amazon Web Services (AWS). We consider the comparative costs of these systems, including benefits and drawbacks of each. In comparing these deployment options, we outline the technical expertise, monetary investments, operational expenses, and organizational strategies necessary to run server-based CyberGIS courses. Finally, we reflect on assignments and feedback from students and consider their experiences in a course of this nature. This article provides a resource for GIS instructors, academic departments, or other academic units to consider during infrastructure investment, curriculum redesign, the addition of courses in degree plans, or for the development of CyberGIS components.

Sufficient and reliable health care access is necessary for people to be able to maintain good health. Hence, investigating the uncertainty embedded in the temporal changes of inputs would be beneficial for understanding their impact on spatial accessibility. However, previous studies are limited to implementing only the uncertainty of mobility, while health care resource availability is a significant concern during the coronavirus disease (COVID‐19) pandemic. Our study examined the stochastic distribution of spatial accessibility under the uncertainties underlying the availability of intensive care unit (ICU) beds and ease of mobility in the Greater Houston area of Texas. Based on the randomized supply and mobility from their historical changes, we employed Monte Carlo simulation to measure ICU bed accessibility with an enhanced two‐step floating catchment area (E2SFCA) method. We then conducted hierarchical clustering to classify regions of adequate (sufficient and reliable) accessibility and inadequate (insufficient and unreliable) accessibility. Lastly, we investigated the relationship between the accessibility measures and the case fatality ratio of COVID‐19. As result, locations of sufficient access also had reliable accessibility; downtown and outer counties, respectively, had adequate and inadequate accessibility. We also raised the possibility that inadequate health care accessibility may cause higher COVID‐19 fatality ratios. [ABSTRACT FROM AUTHOR]

The implementation of temporal dynamic variables improves the accuracy of spatial accessibility measurements. However, in previous studies, the temporal dynamics were partially incorporated, and a few snapshots were subjectively selected to demonstrate temporal changes of spatial accessibility, which may not represent the entire variation. In this study, we proposed a conceptual framework to leverage spatial accessibility temporal fluctuation, facilitating decision-making. Not only was the full implementation of time-dependent inputs, but the framework also employed the Gaussian two-step floating catchment area (G2SFCA) method and measured hourly spatial accessibility over 24 hours. Then, a temporal clustering with K-means and hierarchical clustering methods was performed, detecting a few distinctive temporal changes. Lastly, the significance of dynamic accessibility measurement and temporal clustering was validated using Pearson's correlations. We took electric vehicle (EV) charging stations in Seoul, South Korea, as a case study. The results presented that neglecting temporal dynamics could fail to predict accessibility during the daytime. Additionally, temporal clustering summarized the 24-hour changes of accessibility into five temporal phases and showed the need for additional resources for insufficient accessibility locations in the afternoon. Consequently, our framework elicited the temporal changes of accessibility measures and identified a specific space and time for supplementary infrastructure. [ABSTRACT FROM AUTHOR]

Abstract Background The process of geocoding produces output coordinates of varying degrees of quality. Previous studies have revealed that simply excluding records with low-quality geocodes from analysis can introduce significant bias, but depending on the number and severity of the inaccuracies, their inclusion may also lead to bias. Little quantitative research has been presented on the cost and/or effectiveness of correcting geocodes through manual interactive processes, so the most cost effective methods for improving geocoded data are unclear. The present work investigates the time and effort required to correct geocodes contained in five health-related datasets that represent examples of data commonly used in Health GIS. Results Geocode correction was attempted on five health-related datasets containing a total of 22,317 records. The complete processing of these data took 11.4 weeks (427 hours), averaging 69 seconds of processing time per record. Overall, the geocodes associated with 12,280 (55%) of records were successfully improved, taking 95 seconds of processing time per corrected record on average across all five datasets. Geocode correction improved the overall match rate (the number of successful matches out of the total attempted) from 79.3 to 95%. The spatial shift between the location of original successfully matched geocodes and their corrected improved counterparts averaged 9.9 km per corrected record. After geocode correction the number of city and USPS ZIP code accuracy geocodes were reduced from 10,959 and 1,031 to 6,284 and 200, respectively, while the number of building centroid accuracy geocodes increased from 0 to 2,261. Conclusion The results indicate that manual geocode correction using a web-based interactive approach is a feasible and cost effective method for improving the quality of geocoded data. The level of effort required varies depending on the type of data geocoded. These results can be used to choose between data improvement options (e.g., manual intervention, pseudocoding/geo-imputation, field GPS readings).

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Cervical cancer is widely preventable through screening, but little is known about the duration of protection offered by a negative screen in North America. A case–control study was conducted with records from population‐based registries in New Mexico. Cases were women diagnosed with cervical cancer in 2006–2016, obtained from the Tumor Registry. Five controls per case from the New Mexico HPV Pap Registry were matched to cases by sex, age and place of residence. Dates and results of all cervical screening and diagnostic tests since 2006 were identified from the pap registry. We estimated the odds ratio of nonlocalized (Stage II+) and localized (Stage I) cervical cancer associated with attending screening in the 3 years prior to case‐diagnosis compared to women not screened in 5 years. Of 876 cases, 527 were aged 25–64 years with ≥3 years of potential screening data. Only 38% of cases and 61% of controls attended screening in a 3‐year period. Women screened in the 3 years prior to diagnosis had 83% lower risk of nonlocalized cancer (odds ratio [OR] = 0.17, 95% CI: 0.12–0.24) and 48% lower odds of localized cancer (OR = 0.52, 95% CI: 0.38–0.72), compared to women not screened in the 5 years prior to diagnosis. Women remained at low risk of nonlocalized cancer for 3.5–5 years after a negative screen compared to women with no negative screens in the 5 years prior to diagnosis. Routine cervical screening is effective at preventing localized and nonlocalized cervical cancers; 3 yearly screening prevents 83% of nonlocalized cancers, with no additional benefit of more frequent screening. Increasing screening coverage remains essential to further reduce cervical cancer incidence. What's new? Screening is an effective means of preventing cervical cancer in women. However, while a negative screening result affords protection against cervical cancer, little is known about how long this protection lasts or when a woman should be screened again. Here, the authors estimate the impact of cervical screening at a state‐wide level, linking a U.S. population‐based screening registry with a SEER cancer registry. The results show that screening once every three years prevents 83 percent of stage 2+ cervical cancers, with no additional benefit from more frequent screening. The findings may help improve adherence to U.S. screening guidelines. [ABSTRACT FROM AUTHOR]