Cargando…
Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates
BACKGROUND: The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case co...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169703/ https://www.ncbi.nlm.nih.gov/pubmed/35500140 http://dx.doi.org/10.2196/37377 |
_version_ | 1784721255995277312 |
---|---|
author | Lundberg, Alexander L Lorenzo-Redondo, Ramon Hultquist, Judd F Hawkins, Claudia A Ozer, Egon A Welch, Sarah B Prasad, P V Vara Achenbach, Chad J White, Janine I Oehmke, James F Murphy, Robert L Havey, Robert J Post, Lori A |
author_facet | Lundberg, Alexander L Lorenzo-Redondo, Ramon Hultquist, Judd F Hawkins, Claudia A Ozer, Egon A Welch, Sarah B Prasad, P V Vara Achenbach, Chad J White, Janine I Oehmke, James F Murphy, Robert L Havey, Robert J Post, Lori A |
author_sort | Lundberg, Alexander L |
collection | PubMed |
description | BACKGROUND: The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case counts, so it was unclear how the arrival of Omicron would impact the trajectory of the pandemic in countries already experiencing high levels of community transmission of Delta. OBJECTIVE: The objective of this study is to quantify and explain the impact of Omicron on pandemic trajectories and how they differ between countries that were or were not in a Delta outbreak at the time Omicron occurred. METHODS: We used SARS-CoV-2 surveillance and genetic sequence data to classify countries into 2 groups: those that were in a Delta outbreak (defined by at least 10 novel daily transmissions per 100,000 population) when Omicron was first sequenced in the country and those that were not. We used trend analysis, survival curves, and dynamic panel regression models to compare outbreaks in the 2 groups over the period from November 1, 2021, to February 11, 2022. We summarized the outbreaks in terms of their peak rate of SARS-CoV-2 infections and the duration of time the outbreaks took to reach the peak rate. RESULTS: Countries that were already in an outbreak with predominantly Delta lineages when Omicron arrived took longer to reach their peak rate and saw greater than a twofold increase (2.04) in the average apex of the Omicron outbreak compared to countries that were not yet in an outbreak. CONCLUSIONS: These results suggest that high community transmission of Delta at the time of the first detection of Omicron was not protective, but rather preluded larger outbreaks in those countries. Outbreak status may reflect a generally susceptible population, due to overlapping factors, including climate, policy, and individual behavior. In the absence of strong mitigation measures, arrival of a new, more transmissible variant in these countries is therefore more likely to lead to larger outbreaks. Alternately, countries with enhanced surveillance programs and incentives may be more likely to both exist in an outbreak status and detect more cases during an outbreak, resulting in a spurious relationship. Either way, these data argue against herd immunity mitigating future outbreaks with variants that have undergone significant antigenic shifts. |
format | Online Article Text |
id | pubmed-9169703 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-91697032022-06-07 Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates Lundberg, Alexander L Lorenzo-Redondo, Ramon Hultquist, Judd F Hawkins, Claudia A Ozer, Egon A Welch, Sarah B Prasad, P V Vara Achenbach, Chad J White, Janine I Oehmke, James F Murphy, Robert L Havey, Robert J Post, Lori A JMIR Public Health Surveill Original Paper BACKGROUND: The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case counts, so it was unclear how the arrival of Omicron would impact the trajectory of the pandemic in countries already experiencing high levels of community transmission of Delta. OBJECTIVE: The objective of this study is to quantify and explain the impact of Omicron on pandemic trajectories and how they differ between countries that were or were not in a Delta outbreak at the time Omicron occurred. METHODS: We used SARS-CoV-2 surveillance and genetic sequence data to classify countries into 2 groups: those that were in a Delta outbreak (defined by at least 10 novel daily transmissions per 100,000 population) when Omicron was first sequenced in the country and those that were not. We used trend analysis, survival curves, and dynamic panel regression models to compare outbreaks in the 2 groups over the period from November 1, 2021, to February 11, 2022. We summarized the outbreaks in terms of their peak rate of SARS-CoV-2 infections and the duration of time the outbreaks took to reach the peak rate. RESULTS: Countries that were already in an outbreak with predominantly Delta lineages when Omicron arrived took longer to reach their peak rate and saw greater than a twofold increase (2.04) in the average apex of the Omicron outbreak compared to countries that were not yet in an outbreak. CONCLUSIONS: These results suggest that high community transmission of Delta at the time of the first detection of Omicron was not protective, but rather preluded larger outbreaks in those countries. Outbreak status may reflect a generally susceptible population, due to overlapping factors, including climate, policy, and individual behavior. In the absence of strong mitigation measures, arrival of a new, more transmissible variant in these countries is therefore more likely to lead to larger outbreaks. Alternately, countries with enhanced surveillance programs and incentives may be more likely to both exist in an outbreak status and detect more cases during an outbreak, resulting in a spurious relationship. Either way, these data argue against herd immunity mitigating future outbreaks with variants that have undergone significant antigenic shifts. JMIR Publications 2022-06-03 /pmc/articles/PMC9169703/ /pubmed/35500140 http://dx.doi.org/10.2196/37377 Text en ©Alexander L Lundberg, Ramon Lorenzo-Redondo, Judd F Hultquist, Claudia A Hawkins, Egon A Ozer, Sarah B Welch, P V Vara Prasad, Chad J Achenbach, Janine I White, James F Oehmke, Robert L Murphy, Robert J Havey, Lori A Post. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 03.06.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Lundberg, Alexander L Lorenzo-Redondo, Ramon Hultquist, Judd F Hawkins, Claudia A Ozer, Egon A Welch, Sarah B Prasad, P V Vara Achenbach, Chad J White, Janine I Oehmke, James F Murphy, Robert L Havey, Robert J Post, Lori A Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates |
title | Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates |
title_full | Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates |
title_fullStr | Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates |
title_full_unstemmed | Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates |
title_short | Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates |
title_sort | overlapping delta and omicron outbreaks during the covid-19 pandemic: dynamic panel data estimates |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169703/ https://www.ncbi.nlm.nih.gov/pubmed/35500140 http://dx.doi.org/10.2196/37377 |
work_keys_str_mv | AT lundbergalexanderl overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT lorenzoredondoramon overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT hultquistjuddf overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT hawkinsclaudiaa overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT ozeregona overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT welchsarahb overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT prasadpvvara overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT achenbachchadj overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT whitejaninei overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT oehmkejamesf overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT murphyrobertl overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT haveyrobertj overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates AT postloria overlappingdeltaandomicronoutbreaksduringthecovid19pandemicdynamicpaneldataestimates |