| Autor: |
NIRMALYA DAS, TANMAY PATRA, SUBHRANGSU DAS, SANTU GUCHHAIT |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Infectious diseases (London, England). 55(1) |
| ISSN: |
2374-4243 |
| Popis: |
Mapping of infectious diseases like COVID-19 is the foremost importance for diseases control and prevention. This study attempts to identify the spatio-temporal pattern and evolution trend of COVID-19 at the district level in India using spatial statistical models.Active cases of eleven time-stamps (30 March-2 December, 2020) with an approximately 20-day interval are considered. The study reveals applications of spatial statistical tools, i.e. optimised hotspot and outlier analysis (which follow Gi* and Moran I statistics) and emerging hotspot with the base of space time cube, are effective for the spatio-temporal evolution of disease clusters.The result shows the overall increasing trend of COVID-19 infection with a Mann-Kendall trend score of 2.95 (A total of eight types of patterns are identified, but the most concerning types are consecutive (7.24% of districts), intensifying (15.13% districts) and persistent (24.34% of districts) which will help health policy makers and the government to prioritize-based resource allocation and control measures. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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