Grupos de contactos, superpropagación y percolación en la pandemia de COVID-19

Melanie Maldonado

doi:10.52428/20758944.v17i50.22

Autores/as

Melanie Maldonado Servicios de Ciencia & Tecnologia (SC&T)

DOI:

https://doi.org/10.52428/20758944.v17i50.22

Palabras clave:

Clústeres, COVID-19, Dispersión, Percolación, Superpropagación

Resumen

En el contexto de la pandemia de COVID-19, este artículo ha sido escrito con fines de vulgarización científica para no especialistas. El objetivo es explicar el rol de los grupos de interacción en ciertos fenómenos que caracterizan a la dinámica de propagación del virus, como el de la superpropagación y la percolación. Se presentan algunas nociones necesarias para describir la dinámica de una epidemia, como el número de reproducción y la de redes de contactos que, a lo largo de este documento, por simplicidad también se denomina cluster, proveniente del inglés.

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Citas

Akira, E., Abbott, S., Kuscharski, A. J., y Funk, S. (2020). Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China, Wellcome Open Research, 5(67). https://doi.org/10.12688/wellcomeopenres.15842.3

Althouse, B. M., Wenger, E. A., Miller, J. C., Scarpino, S. V., Allard, A., Hébert-Dufresne, L., y Hu, H. (2020). Stochasticity and heterogeneity in the transmission dynamics of SARS-CoV-2. pre-print- arXiv:2005.13689. Retrieved November 28, 2020, from https://covid.idmod.org/data/Stochasticity_heterogeneity_transmission_dynamics_SARS-CoV-2.pdf

Asadi, S., Wexler, A. S., y Kappa, C. D. (2019). Aerosol emission and superemission during human speech increase with voice loudness. Scientific Reports, 9, 2348. https://doi.org/10.1038/s41598-019-38808-z

BBC News (2020). Coronavirus: France's first known case 'was in December'. BBC News. Retrieved November 28, 2020, from https://www.bbc.com/news/world-europe-52526554

Blumberg, S., y Lloyd-Smith, J. O. (2013). Inference of R(0) and transmission heterogeneity from the size distribution of stuttering chains. PLOS Computational Biology, 9(5), e1002993. https://dx.doi.org/10.1371%2Fjournal.pcbi.1002993

Bonasera, A., y Zhang, S. (2020). Chaos, Percolations and the Coronavirus Spread. Frontiers in Physics, 8, 171. https://doi.org/10.3389/fphy.2020.00171

CDC, Centers for Disease Control and Prevention, Coronavirus, Appendix A - Glossary of Key Terms: Close Contact. Retrieved February 05, 2021 https://www.cdc.gov/coronavirus/2019-ncov/php/contact-tracing/contact-tracing-plan/appendix.html

Crawley, M. J. (2012). The R Book. Wiley. ISBN 978-1-118-44896-0.

Davis, S., Trapman, P., Lairs, H., Begon, M., y Heesterbeek, J.A.P. (2008). The abundance threshold for plague as a critical percolation phenomenon. Nature, 454, 634–637. https://doi.org/10.1038/nature07053

Drosten, C. (2020). Ein Plan für den Herbst. Die Zeit. Retrieved November 28, 2020, from https://www.zeit.de/2020/33/corona-zweite-welle-eindaemmung-massnahmen-christian-drosten

DWH, Technical Solutions Simulation Services (2020). COVID-19: The Search for Superspreaders. DWH, Technical Solutions Simulation Services. Retrieved November 28, 2020, from https://www.dwh.at/en/blog/covid-19-die-suche-nach-den-superspreadern/

Frasser, C., Cummings, D. A., Klinkenberg, D., Burke, S. S., y Ferguson, N. M. (2011). Influenza transmission in households during the 1918 pandemic. American journal of epidemiology, 174(5), 505-514. https://doi.org/10.1093/aje/kwr122

Hamner, L., Dubbel, P., y Cappron, I. (2020). High SARS-CoV-2 Attack Rate Following Exposure at a Choir Practice — Skagit County, Washington, March 2020. Morbidity and Mortality Weekly Report (MMWR), 69, 606–610. http://dx.doi.org/10.15585/mmwr.mm6919e6

Hilbe, J. M. (2011). Negative Binomial Regression (Second ed.). Cambridge, UK: Cambridge University Press. ISBN 978-0-521-19815-8.

Kersten, H. (2006). "What is percolation?" Notices of the AMS, AMS. Retrieved November 28, 2020, from http://www.ams.org/notices/200605/what-is-kesten.pdf

Kupferschmidt, K. (2020). Why do some COVID-19 patients infect many others, whereas most don’t spread the virus at all? Science Mag. Retrieved November 28, 2020, from https://www.sciencemag.org/news/2020/05/why-do-some-covid-19-patients-infect-many-others-whereas-most-don-t-spread-virus-all

Leclerc, Q. J., Fuller, N. M., y Knight, L. E. (2020). What settings have been linked to SARS-CoV-2 transmission clusters? Wellcome Open Research, 5, 83. https://doi.org/10.12688/wellcomeopenres.15889.2

Lloyd-Smith, J., Schreiber, S., Kopp, P., y Getz, W. M. (2005). Superspreading and the effect of individual variation on disease emergence. Nature, 438, 355-359. https://doi.org/10.1038/nature04153

Lloyd-Smith, J. O. (2007). Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases. PLoS ONE, 2(2), e180. https://doi.org/10.1371/journal.pone.0000180

Mello, Y. F., Squillante, L., Gomez, G., Seridonio, A. C., y Souza, M. (2020). Epidemics, the Ising-model and percolation theory: a comprehensive review focussed on Covid-19. arXiv e-prints. Retrieved November 28, 2020, from https://arxiv.org/abs/2003.11860

Ministry of Health Labour and Welfare (2020). Japan’s COVID-19 Response. Information on Coronavirus disease 2019 (COVID-19). Retrieved November 28, 2020, from https://www.mhlw.go.jp/content/10900000/000635891.pdf

NDR-Info, Drosten, C., y Hennig, K. (2020a). Die rote Murmel kontrollieren. Coronavirus-Update, Folge 44. Retrieved November 28, 2020, from https://www.ndr.de/nachrichten/info/coronaskript202.pdf

NDR-Info, Drosten, C., y Hennig, K. (2020b). Eine Empfehlung für den Herbst. Coronavirus Update, Folge 54. Retrieved November 28, 2020, from https://www.ndr.de/nachrichten/info/coronaskript222.pdf

Nishiura, H., Oshitani, H., Kobayashi, T., Saito, T., Sunagawa, T., Matsui, T., Wakita, T., MHLW COVID-19 Response Team, y Suzuki, M. (2020). Closed environments facilitate secondary transmission of coronavirus disease 2019 (COVID-19). Medrxiv.org Preprints-Database. https://doi.org/10.1101/2020.02.28.20029272

Oliveira, G. (2020). Early epidemic spread, percolation and Covid-19. Journal of Mathematical Biology, 81, 1143–1168. https://doi.org/10.1007/s00285-020-01539-1

Quian, H., Miao, T., Liu, L., Zheng, X., Luo, D., y Li, Y. (2020). Indoor transmission of SARS‐CoV‐2. Indoor Air, 00, 1-7. https://doi.org/10.1101/2020.04.04.20053058

Riou, J., y Althaus, C. L. (2020). Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020. Eurosurveillance, Europe's journal on infectious disease surveillance, epidemiology, prevention and control, 25(4), pii=2000058. https://doi.org/10.2807/1560-7917.ES.2020.25.4.2000058

Schneider, M. F. (2020). Wir können Corona noch stoppen. Die Zeit Online, Wissenschaft. https://www.zeit.de/wissen/gesundheit/2020-09/corona-ausbruch-stoppen-physik-neuinfektionen-perkolation-zweite-welle

Stauffer, D., y Ammon, A. (1994). Introduction To Percolation Theory: Revised Second Edition (Second Edition ed., Vol. ISBN 9780748402533.). Taylor & Francis.

Tang, S., Mao, Y., Jones, R. M., Tan, Q., Ji, J. S., Li, N., Shen, J., Lv, Y., Pan, L., Ding, P., Wang, X., MacIntyre, C. R., y Shi, X. (2020, November). Aerosol transmission of SARS-CoV-2? Evidence, prevention and control. Environment International, 144, 106039. https://doi.org/10.1016/j.envint.2020.106039

Thurner, S., Klimek, P., y Hanel, R. (2020). A network-based explanation of why most COVID-19 infection curves are linear. Proceedings of the National Academy of Sciences of the United States of America, 117(37), 22684-22689. https://doi.org/10.1073/pnas.2010398117