Risk Interactions of Coronavirus Infection across Age Groups after the Peak of COVID-19 Epidemic
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- Carpenter, Bob & Gelman, Andrew & Hoffman, Matthew D. & Lee, Daniel & Goodrich, Ben & Betancourt, Michael & Brubaker, Marcus & Guo, Jiqiang & Li, Peter & Riddell, Allen, 2017. "Stan: A Probabilistic Programming Language," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i01).
- Hilbe,Joseph M., 2014.
"Modeling Count Data,"
Cambridge Books,
Cambridge University Press, number 9781107028333.
- Hilbe,Joseph M., 2014. "Modeling Count Data," Cambridge Books, Cambridge University Press, number 9781107611252.
- Brandt, Patrick T. & Sandler, Todd, 2012. "A Bayesian Poisson Vector Autoregression Model," Political Analysis, Cambridge University Press, vol. 20(3), pages 292-315, July.
- Joël Mossong & Niel Hens & Mark Jit & Philippe Beutels & Kari Auranen & Rafael Mikolajczyk & Marco Massari & Stefania Salmaso & Gianpaolo Scalia Tomba & Jacco Wallinga & Janneke Heijne & Malgorzata Sa, 2008. "Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases," PLOS Medicine, Public Library of Science, vol. 5(3), pages 1-1, March.
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Cited by:
- Peter Congdon, 2022. "A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates," Journal of Geographical Systems, Springer, vol. 24(4), pages 583-610, October.
- Calvin Lukas Kienbacher & Joshua Ray Tanzer & Guixing Wei & Jason M. Rhodes & Dominik Roth & Kenneth Alan Williams, 2022. "Increases in Ambulance Call Volume Are an Early Warning Sign of Major COVID-19 Surges in Children," IJERPH, MDPI, vol. 19(23), pages 1-11, December.
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Keywords
COVID-19; elderly people; risk interaction; South Korea; virus infection; SARS-CoV-2;All these keywords.
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