Seasonality of endemic COVID-19
Successive waves of infection by SARS-CoV-2 have left little doubt that this virus will transition to an endemic disease. Foreknowledge of when to expect seasonal surges is crucial for healthcare and public health decision-making. However, the future seasonality of COVID-19 remains uncertain. Evaluating its seasonality is complicated due to the limited years of SARS-CoV-2 circulation, pandemic dynamics, and varied interventions. In this study, we project the expected endemic seasonality by employing a phylogenetic ancestral and descendant state approach that leverages long-term data on the incidence of circulating HCoV coronaviruses. Our projections indicate asynchronous surges of SARS-CoV-2 across different locations in the northern hemisphere, occurring between October and January in New York and between January and March in Yamagata, Japan. This knowledge of spatiotemporal surges leads to medical preparedness and enables the implementation of targeted public health interventions to mitigate COVID-19 transmission.IMPORTANCEThe seasonality of COVID-19 is important for effective healthcare and public health decision-making. Previous waves of SARS-CoV-2 infections have indicated that the virus will likely persist as an endemic pathogen with distinct surges. However, the timing and patterns of potentially seasonal surges remain uncertain, rendering effective public health policies uninformed and in danger of poorly anticipating opportunities for intervention, such as well-timed booster vaccination drives. Applying an evolutionary approach to long-term data on closely related circulating coronaviruses, our research provides projections of seasonal surges that should be expected at major temperate population centers. These projections enable local public health efforts that are tailored to expected surges at specific locales or regions. This knowledge is crucial for enhancing medical preparedness and facilitating the implementation of targeted public health interventions.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2023 |
|---|---|
| Enthalten in: |
mBio - (2023) vom: 08. Nov., Seite e0142623 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Townsend, Jeffrey P [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Revised 24.12.2023 published: Print-Electronic Citation Status Publisher |
|---|
| doi: |
10.1128/mbio.01426-23 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM36429731X |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM36429731X | ||
| 003 | DE-627 | ||
| 005 | 20231227140702.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1128/mbio.01426-23 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1237.xml |
| 035 | |a (DE-627)NLM36429731X | ||
| 035 | |a (NLM)37937979 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Townsend, Jeffrey P |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Seasonality of endemic COVID-19 |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 24.12.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status Publisher | ||
| 520 | |a Successive waves of infection by SARS-CoV-2 have left little doubt that this virus will transition to an endemic disease. Foreknowledge of when to expect seasonal surges is crucial for healthcare and public health decision-making. However, the future seasonality of COVID-19 remains uncertain. Evaluating its seasonality is complicated due to the limited years of SARS-CoV-2 circulation, pandemic dynamics, and varied interventions. In this study, we project the expected endemic seasonality by employing a phylogenetic ancestral and descendant state approach that leverages long-term data on the incidence of circulating HCoV coronaviruses. Our projections indicate asynchronous surges of SARS-CoV-2 across different locations in the northern hemisphere, occurring between October and January in New York and between January and March in Yamagata, Japan. This knowledge of spatiotemporal surges leads to medical preparedness and enables the implementation of targeted public health interventions to mitigate COVID-19 transmission.IMPORTANCEThe seasonality of COVID-19 is important for effective healthcare and public health decision-making. Previous waves of SARS-CoV-2 infections have indicated that the virus will likely persist as an endemic pathogen with distinct surges. However, the timing and patterns of potentially seasonal surges remain uncertain, rendering effective public health policies uninformed and in danger of poorly anticipating opportunities for intervention, such as well-timed booster vaccination drives. Applying an evolutionary approach to long-term data on closely related circulating coronaviruses, our research provides projections of seasonal surges that should be expected at major temperate population centers. These projections enable local public health efforts that are tailored to expected surges at specific locales or regions. This knowledge is crucial for enhancing medical preparedness and facilitating the implementation of targeted public health interventions | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a evolution | |
| 650 | 4 | |a seasonality | |
| 700 | 1 | |a Hassler, Hayley B |e verfasserin |4 aut | |
| 700 | 1 | |a Lamb, April D |e verfasserin |4 aut | |
| 700 | 1 | |a Sah, Pratha |e verfasserin |4 aut | |
| 700 | 1 | |a Alvarez Nishio, Aia |e verfasserin |4 aut | |
| 700 | 1 | |a Nguyen, Cameron |e verfasserin |4 aut | |
| 700 | 1 | |a Tew, Alexandra D |e verfasserin |4 aut | |
| 700 | 1 | |a Galvani, Alison P |e verfasserin |4 aut | |
| 700 | 1 | |a Dornburg, Alex |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t mBio |d 2010 |g (2023) vom: 08. Nov., Seite e0142623 |w (DE-627)NLM200128191 |x 2150-7511 |7 nnns |
| 773 | 1 | 8 | |g year:2023 |g day:08 |g month:11 |g pages:e0142623 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1128/mbio.01426-23 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |j 2023 |b 08 |c 11 |h e0142623 | ||