Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases
The COVID-19 outbreak has precipitated severe occurrences on a global scale. Hence, spatial analysis is crucial in determining the relationships and patterns of geospatial data. Moran’s I and Geary’s C are prominent methodologies used to measure the spatial autocorrelation of geographical data. Both...
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| Format: | Article |
| Language: | English |
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Page Press Publications
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/120172/ http://psasir.upm.edu.my/id/eprint/120172/1/120172.pdf |
| _version_ | 1848868130258944000 |
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| author | Isnan, Sarah Abdullah, Ahmad Fikri Shariff, Abdul Rashid Ishak, Iskandar Syed Ismail, Sharifah Norkhadijah Appanan, Maheshwara Rao |
| author_facet | Isnan, Sarah Abdullah, Ahmad Fikri Shariff, Abdul Rashid Ishak, Iskandar Syed Ismail, Sharifah Norkhadijah Appanan, Maheshwara Rao |
| author_sort | Isnan, Sarah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The COVID-19 outbreak has precipitated severe occurrences on a global scale. Hence, spatial analysis is crucial in determining the relationships and patterns of geospatial data. Moran’s I and Geary’s C are prominent methodologies used to measure the spatial autocorrelation of geographical data. Both measure the degree of similarity or dissimilarity between nearby locations based on attribute values in such a way that the selection of distance techniques and weight matrices significantly impact the spatial auto-correlation results. This paper aimed at carrying out the spatial epidemiological characteristics analysis of the pandemic comparing the results of Moran’s I and Geary’s C with different parameters to gain a comprehensive understanding of the spatial relation-ship of COVID-19 cases. We employed distance-based techniques, K-nearest neighbour, and Queen contiguity techniques to assess the sensitivity of the different parameter configurations for both Moran’s I and Geary’s C. The findings revealed that former provided more reliable and robust results compared to the latter, with consistent results of spatial autocorrelation (positive spatial autocorrelation). The distance weight of 0.05 using the Manhattan method of Moran’s I is the recommended distance weight, as it outperformed other weight matrices (Moran’s I = 0.0152, Z-value=110.8844 and p-value=0.001). |
| first_indexed | 2025-11-15T14:47:30Z |
| format | Article |
| id | upm-120172 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:47:30Z |
| publishDate | 2025 |
| publisher | Page Press Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1201722025-09-24T07:09:05Z http://psasir.upm.edu.my/id/eprint/120172/ Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases Isnan, Sarah Abdullah, Ahmad Fikri Shariff, Abdul Rashid Ishak, Iskandar Syed Ismail, Sharifah Norkhadijah Appanan, Maheshwara Rao The COVID-19 outbreak has precipitated severe occurrences on a global scale. Hence, spatial analysis is crucial in determining the relationships and patterns of geospatial data. Moran’s I and Geary’s C are prominent methodologies used to measure the spatial autocorrelation of geographical data. Both measure the degree of similarity or dissimilarity between nearby locations based on attribute values in such a way that the selection of distance techniques and weight matrices significantly impact the spatial auto-correlation results. This paper aimed at carrying out the spatial epidemiological characteristics analysis of the pandemic comparing the results of Moran’s I and Geary’s C with different parameters to gain a comprehensive understanding of the spatial relation-ship of COVID-19 cases. We employed distance-based techniques, K-nearest neighbour, and Queen contiguity techniques to assess the sensitivity of the different parameter configurations for both Moran’s I and Geary’s C. The findings revealed that former provided more reliable and robust results compared to the latter, with consistent results of spatial autocorrelation (positive spatial autocorrelation). The distance weight of 0.05 using the Manhattan method of Moran’s I is the recommended distance weight, as it outperformed other weight matrices (Moran’s I = 0.0152, Z-value=110.8844 and p-value=0.001). Page Press Publications 2025 Article PeerReviewed text en cc_by_nc_4 http://psasir.upm.edu.my/id/eprint/120172/1/120172.pdf Isnan, Sarah and Abdullah, Ahmad Fikri and Shariff, Abdul Rashid and Ishak, Iskandar and Syed Ismail, Sharifah Norkhadijah and Appanan, Maheshwara Rao (2025) Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases. Geospatial Health, 20 (1). art. no. 1277. pp. 1-9. ISSN 1827-1987; eISSN: 1970-7096 https://www.geospatialhealth.net/gh/article/view/1277 10.4081/gh.2025.1277 |
| spellingShingle | Isnan, Sarah Abdullah, Ahmad Fikri Shariff, Abdul Rashid Ishak, Iskandar Syed Ismail, Sharifah Norkhadijah Appanan, Maheshwara Rao Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases |
| title | Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases |
| title_full | Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases |
| title_fullStr | Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases |
| title_full_unstemmed | Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases |
| title_short | Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases |
| title_sort | moran’s i and geary’s c: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases |
| url | http://psasir.upm.edu.my/id/eprint/120172/ http://psasir.upm.edu.my/id/eprint/120172/ http://psasir.upm.edu.my/id/eprint/120172/ http://psasir.upm.edu.my/id/eprint/120172/1/120172.pdf |