Spatial-Temporal Disease Modeling is a computational framework that integrates geographic location and time-based dynamics to analyze and predict the spread of diseases across populations, distinguishing it from purely spatial or temporal approaches by simultaneously accounting for both space and time in disease trend analysis.
452
Publications
21.2K
Citations
1.7K
Authors
831
Institutions
Publications per year
2017–2026
230
Parents
Publications
452
1–5 of 452
Authors
1.7K
- GC
10
h-index
- MD
8
h-index
- LH
8
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- RW
7
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- TG
7
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1–5 of 1.7K
Institutions
831
University of Oxford
Oxford, United Kingdom
11 h-index
17 publications
1.8K citations
University of Cambridge
Cambridge, United Kingdom
11 h-index
20 publications
1.6K citations
Chinese Academy of Sciences
Beijing, China
10 h-index
21 publications
608 citations
San Diego State University
San Diego, United States
10 h-index
19 publications
1.1K citations
University of Southampton
Southampton, United Kingdom
9 h-index
22 publications
1.3K citations
Kenya Medical Research Institute
Nairobi, Kenya
9 h-index
27 publications
3.2K citations
Lancaster University
Lancaster, United Kingdom
9 h-index
12 publications
914 citations
Institute of Geographic Sciences and Natural Resources Research
Beijing, China
9 h-index
24 publications
645 citations
1–8 of 831
Venues
- PLoS ONE
20 publications · 547 citations
15
h-index
- Scientific Reports
14 publications · 521 citations
12
h-index
- Spatial and Spatio-temporal Epidemiology
14 publications · 533 citations
12
h-index
- Statistics in Medicine
12 publications · 1.8K citations
12
h-index
- International Journal of Environmental Research and Public Health
10 publications · 241 citations
10
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1–5