Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates.
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| Title: | Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates. |
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| Authors: | Inward RPD; Department of Biology, University of Oxford, United Kingdom. Electronic address: rhys.inward@zoo.ox.ac.uk., Jackson F; Department of Biology, University of Oxford, United Kingdom; Department of Computer Science, University of Oxford, United Kingdom., Dasgupta A; Department of Biology, University of Oxford, United Kingdom; Department of Computer Science, University of Oxford, United Kingdom., Lee G; Department of Biology, University of Oxford, United Kingdom; Department of Computer Science, University of Oxford, United Kingdom., Battle AL; Department of Biology, University of Oxford, United Kingdom., Parag KV; MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom; NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, United Kingdom., Kraemer MUG; Department of Biology, University of Oxford, United Kingdom; Reuben College, University of Oxford, United Kingdom. Electronic address: moritz.kraemer@zoo.ox.ac.uk. |
| Corporate Authors: | Global.health consortium |
| Source: | Epidemics [Epidemics] 2022 Dec; Vol. 41, pp. 100627. Date of Electronic Publication: 2022 Sep 05. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101484711 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-0067 (Electronic) Linking ISSN: 18780067 NLM ISO Abbreviation: Epidemics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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