Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020.
Mexico has experienced one of the highest COVID-19 mortality rates in the world. A delayed implementation of social distancing interventions in late March 2020 and a phased reopening of the country in June 2020 has facilitated sustained disease transmission in the region. In this study we systematic...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0254826 |
| _version_ | 1811233674116464640 |
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| author | Amna Tariq Juan M Banda Pavel Skums Sushma Dahal Carlos Castillo-Garsow Baltazar Espinoza Noel G Brizuela Roberto A Saenz Alexander Kirpich Ruiyan Luo Anuj Srivastava Humberto Gutierrez Nestor Garcia Chan Ana I Bento Maria-Eugenia Jimenez-Corona Gerardo Chowell |
| author_facet | Amna Tariq Juan M Banda Pavel Skums Sushma Dahal Carlos Castillo-Garsow Baltazar Espinoza Noel G Brizuela Roberto A Saenz Alexander Kirpich Ruiyan Luo Anuj Srivastava Humberto Gutierrez Nestor Garcia Chan Ana I Bento Maria-Eugenia Jimenez-Corona Gerardo Chowell |
| author_sort | Amna Tariq |
| collection | DOAJ |
| description | Mexico has experienced one of the highest COVID-19 mortality rates in the world. A delayed implementation of social distancing interventions in late March 2020 and a phased reopening of the country in June 2020 has facilitated sustained disease transmission in the region. In this study we systematically generate and compare 30-day ahead forecasts using previously validated growth models based on mortality trends from the Institute for Health Metrics and Evaluation for Mexico and Mexico City in near real-time. Moreover, we estimate reproduction numbers for SARS-CoV-2 based on the methods that rely on genomic data as well as case incidence data. Subsequently, functional data analysis techniques are utilized to analyze the shapes of COVID-19 growth rate curves at the state level to characterize the spatiotemporal transmission patterns of SARS-CoV-2. The early estimates of the reproduction number for Mexico were estimated between Rt ~1.1-1.3 from the genomic and case incidence data. Moreover, the mean estimate of Rt has fluctuated around ~1.0 from late July till end of September 2020. The spatial analysis characterizes the state-level dynamics of COVID-19 into four groups with distinct epidemic trajectories based on epidemic growth rates. Our results show that the sequential mortality forecasts from the GLM and Richards model predict a downward trend in the number of deaths for all thirteen forecast periods for Mexico and Mexico City. However, the sub-epidemic and IHME models perform better predicting a more realistic stable trajectory of COVID-19 mortality trends for the last three forecast periods (09/21-10/21, 09/28-10/27, 09/28-10/27) for Mexico and Mexico City. Our findings indicate that phenomenological models are useful tools for short-term epidemic forecasting albeit forecasts need to be interpreted with caution given the dynamic implementation and lifting of social distancing measures. |
| first_indexed | 2024-04-12T11:24:33Z |
| format | Article |
| id | doaj.art-aee29630ec6349d1911a0374b5ceb2ab |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-12T11:24:33Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-aee29630ec6349d1911a0374b5ceb2ab2022-12-22T03:35:16ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01167e025482610.1371/journal.pone.0254826Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020.Amna TariqJuan M BandaPavel SkumsSushma DahalCarlos Castillo-GarsowBaltazar EspinozaNoel G BrizuelaRoberto A SaenzAlexander KirpichRuiyan LuoAnuj SrivastavaHumberto GutierrezNestor Garcia ChanAna I BentoMaria-Eugenia Jimenez-CoronaGerardo ChowellMexico has experienced one of the highest COVID-19 mortality rates in the world. A delayed implementation of social distancing interventions in late March 2020 and a phased reopening of the country in June 2020 has facilitated sustained disease transmission in the region. In this study we systematically generate and compare 30-day ahead forecasts using previously validated growth models based on mortality trends from the Institute for Health Metrics and Evaluation for Mexico and Mexico City in near real-time. Moreover, we estimate reproduction numbers for SARS-CoV-2 based on the methods that rely on genomic data as well as case incidence data. Subsequently, functional data analysis techniques are utilized to analyze the shapes of COVID-19 growth rate curves at the state level to characterize the spatiotemporal transmission patterns of SARS-CoV-2. The early estimates of the reproduction number for Mexico were estimated between Rt ~1.1-1.3 from the genomic and case incidence data. Moreover, the mean estimate of Rt has fluctuated around ~1.0 from late July till end of September 2020. The spatial analysis characterizes the state-level dynamics of COVID-19 into four groups with distinct epidemic trajectories based on epidemic growth rates. Our results show that the sequential mortality forecasts from the GLM and Richards model predict a downward trend in the number of deaths for all thirteen forecast periods for Mexico and Mexico City. However, the sub-epidemic and IHME models perform better predicting a more realistic stable trajectory of COVID-19 mortality trends for the last three forecast periods (09/21-10/21, 09/28-10/27, 09/28-10/27) for Mexico and Mexico City. Our findings indicate that phenomenological models are useful tools for short-term epidemic forecasting albeit forecasts need to be interpreted with caution given the dynamic implementation and lifting of social distancing measures.https://doi.org/10.1371/journal.pone.0254826 |
| spellingShingle | Amna Tariq Juan M Banda Pavel Skums Sushma Dahal Carlos Castillo-Garsow Baltazar Espinoza Noel G Brizuela Roberto A Saenz Alexander Kirpich Ruiyan Luo Anuj Srivastava Humberto Gutierrez Nestor Garcia Chan Ana I Bento Maria-Eugenia Jimenez-Corona Gerardo Chowell Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020. PLoS ONE |
| title | Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020. |
| title_full | Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020. |
| title_fullStr | Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020. |
| title_full_unstemmed | Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020. |
| title_short | Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020. |
| title_sort | transmission dynamics and forecasts of the covid 19 pandemic in mexico march december 2020 |
| url | https://doi.org/10.1371/journal.pone.0254826 |
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