Using GIS for Disease Mapping and Clustering in Jeddah, Saudi Arabia

Murad, Abdulkader A.; Khashoggi, Bandar Fuad

doi:10.3390/ijgi9050328

Cited by 49 publications

(41 citation statements)

References 26 publications

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“…For example, mapping with GIS may further chart the regional spread of disease, possible risk factors, and effective diagnostic and preventive methods. Concerning the spatial analysis of these data, disease risks, outbreak levels over time and space, and infection hotspots may be calculated (Alamo et al 2020 ; Murad and Khashoggi 2020 ).…”

Section: Introductionmentioning

confidence: 99%

COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq

Yahya

Thannoun

2021

Appl Geomat

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The prediction of diseases caused by viral infections is a complex medical task where many real data that consists of different variables must be employed. As known, COVID-19 is the most dangerous disease worldwide; nowhere, an effective drug has been found yet. To limit its spread, it is essential to find a rational method that shows the spread of this virus by relying on many infected people’s data. A model consisting of three artificial neural networks’ (ANN) functions was developed to predict COVID-19 separation in Iraq based on real infection data supplied by the public health department at the Iraqi Ministry of Health. The performance efficiency of this model was evaluated, where its performance efficiency reached 81.6% when employed four statistical error criteria as mean absolute percentage error (MAPE), root mean square error (RMSE), coefficient of determination ( R 2 ), and Nash-Sutcliffe coefficient (NC). The severity of the virus’s spread across Iraq was assessed in a short term (in the next 6 months), where the results show that the spread severity will intensify in this short term by 17.1%, and the average death cases will increase by 8.3%. These results clarified by creating spatial distribution maps for virus spread are simulated by employing a Geographic Information System (GIS) environment to be used as a useful database for developing plans for combating viruses in Iraq.

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Section: Introductionmentioning

confidence: 99%

COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq

Yahya

Thannoun

2021

Appl Geomat

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“…Jeddah has witnessed a quantum leap in all areas of development, which has contributed to a massive increase in its population and urban growth over time. The total population of Jeddah is about 4.1 million people [53]. The rate of population growth in Jeddah is about 3.5% annually [45].…”

Section: Study Areamentioning

confidence: 99%

“…The GIS could provide a sense of directional orientation through a set of features drawn on the map; in contrast, calculation of the standard deviational ellipse helps make the trend more obvious. This tool can be helpful to several GIS applications, for instance, comparing the distributions of categories of health conditions, identifying ellipses for the spread of disease with passage of time, defining the directional distribution for a series of crimes, and detecting distributional trends of travel behavior [53]. However, the SDE was selected based on the healthcare center location (i.e., point features) in this study.…”

Section: Spatial Distribution Of the Moh Healthcare Centers And Analysismentioning

confidence: 99%

Use of 2SFCA Method to Identify and Analyze Spatial Access Disparities to Healthcare in Jeddah, Saudi Arabia

Khashoggi

Murad

2021

Applied Sciences

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The issue of reducing spatial disparities in access to healthcare is one of the most important healthcare planning issues that policy makers and planners investigate and consider as a key focus until present time. A healthcare system that meets the requirements of availability and affordability will be useless if the spatial accessibility to healthcare is not provided to all equally. Therefore, this study aims to identify and analyze spatial disparities in access to healthcare centers in Jeddah, Saudi Arabia. The two-step floating catchment area (2SFCA) method was used to measure spatial accessibility of healthcare centers based on the travel time threshold (i.e., 30-min drive time in this study). The GIS technology was used to execute the 2SFCA method. A geodatabase, which includes the population districts, locations of healthcare centers, and road network, was created. Some procedures were performed within the road network database to set the travel time that is considered as an essential step to compute the origin–destination (OD) cost matrix. The OD matrix was later used as the source for calculating provider-to-population ratios and the spatial accessibility scores for population districts. The results of the study revealed spatial disparities in access to healthcare centers in Jeddah city. The majority of the Jeddah population (i.e., 97.51%) have accessibility to healthcare centers, but with disparate levels. The central districts have a higher access score compared to the rest of the city’s districts. Most districts that do not have accessibility to healthcare centers are concentrated in the southeast of the city. The results can help local health planners improve spatial equity in access to healthcare centers through giving the less-served districts a priority when allocating future healthcare centers in Jeddah city.

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“…GIS refers to an information system that works toward processing geographical data; it is a computer system that captures, stores, integrates, manipulates, analyzes, and displays spatially referenced data. It is also used to standardize, store, analyze, and model data for novel output and display maps and reports (output) [20].…”

Section: Geographic Information Systems (Gis)mentioning

confidence: 99%

The Adoption of Geographic Information Systems in the Public Sector of Saudi Arabia: A Conceptual Model

Alzahrani

Abdullah

Mohamed

et al. 2021

Mathematical Problems in Engineering

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The development of fuzzy sets in geographic information systems (GIS) arose out of the need to handle uncertainty and the ability of soft computing technology to support fuzzy information processing. Fuzzy logic is an alternative logical foundation coming from artificial intelligence (AI) technology with several useful implications for spatial data handling. GIS has been found to have a crucial role in the performance of public sector organizations (PSO). However, the literature shows no universal model to support and shed light on GIS adoption, which lessens the chances for effective GIS adoption and usage. Therefore, a new model is needed for successful adoption and eventual enhanced organization’s performance. Thus, there is a need to investigate the factors that can bring about GIS adoption. Models for GIS adoption in literature are few and far between, and the few that exist are not applicable as they do not cover all the significant factors that can contribute to adoption success. Hence, this paper brought a GIS adoption model for PSOs to promote their performance. The model was developed through the extension of the Technology Acceptance Model (TAM) in addition to the DeLone and McLean’s Success Model. The study involved interviews with ten experts in ranking the extracted factors, and data was analyzed through thematic analysis. On the basis of the obtained analysis findings, the fundamental factors were found to be significant in their effects, and GIS adoption sufficiently related to the overall performance. Thus, the study contributes to the body of knowledge by filling the gap in the literature.

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Using GIS for Disease Mapping and Clustering in Jeddah, Saudi Arabia

Cited by 49 publications

References 26 publications

COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq

COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq

Use of 2SFCA Method to Identify and Analyze Spatial Access Disparities to Healthcare in Jeddah, Saudi Arabia

The Adoption of Geographic Information Systems in the Public Sector of Saudi Arabia: A Conceptual Model

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