Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation
<h3>Introduction</h3><p dir="ltr">Reinfections are increasingly becoming a feature in the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, accurately defining reinfection poses methodological challenges. Conventionally, rein...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , , , , , , , , , , , , , , , , , , |
| Published: |
2024
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513509316886528 |
|---|---|
| author | Hiam Chemaitelly (439114) |
| author2 | Houssein H. Ayoub (9262512) Patrick Tang (239534) Hadi M. Yassine (4675846) Asmaa A. Al Thani (10494576) Mohammad R. Hasan (13777597) Peter Coyle (787159) Zaina Al-Kanaani (4557205) Einas Al-Kuwari (13777606) Andrew Jeremijenko (11506565) Anvar Hassan Kaleeckal (11847034) Ali Nizar Latif (11570540) Riyazuddin Mohammad Shaik (11847037) Hanan F. Abdul-Rahim (13777600) Gheyath K. Nasrallah (9200525) Mohamed Ghaith Al-Kuwari (4264192) Adeel A. Butt (3697705) Hamad Eid Al-Romaihi (6837251) Mohamed H. Al-Thani (11847049) Abdullatif Al-Khal (11721410) Roberto Bertollini (9538620) Laith J. Abu-Raddad (9262524) |
| author2_role | author author author author author author author author author author author author author author author author author author author author author |
| author_facet | Hiam Chemaitelly (439114) Houssein H. Ayoub (9262512) Patrick Tang (239534) Hadi M. Yassine (4675846) Asmaa A. Al Thani (10494576) Mohammad R. Hasan (13777597) Peter Coyle (787159) Zaina Al-Kanaani (4557205) Einas Al-Kuwari (13777606) Andrew Jeremijenko (11506565) Anvar Hassan Kaleeckal (11847034) Ali Nizar Latif (11570540) Riyazuddin Mohammad Shaik (11847037) Hanan F. Abdul-Rahim (13777600) Gheyath K. Nasrallah (9200525) Mohamed Ghaith Al-Kuwari (4264192) Adeel A. Butt (3697705) Hamad Eid Al-Romaihi (6837251) Mohamed H. Al-Thani (11847049) Abdullatif Al-Khal (11721410) Roberto Bertollini (9538620) Laith J. Abu-Raddad (9262524) |
| author_role | author |
| dc.creator.none.fl_str_mv | Hiam Chemaitelly (439114) Houssein H. Ayoub (9262512) Patrick Tang (239534) Hadi M. Yassine (4675846) Asmaa A. Al Thani (10494576) Mohammad R. Hasan (13777597) Peter Coyle (787159) Zaina Al-Kanaani (4557205) Einas Al-Kuwari (13777606) Andrew Jeremijenko (11506565) Anvar Hassan Kaleeckal (11847034) Ali Nizar Latif (11570540) Riyazuddin Mohammad Shaik (11847037) Hanan F. Abdul-Rahim (13777600) Gheyath K. Nasrallah (9200525) Mohamed Ghaith Al-Kuwari (4264192) Adeel A. Butt (3697705) Hamad Eid Al-Romaihi (6837251) Mohamed H. Al-Thani (11847049) Abdullatif Al-Khal (11721410) Roberto Bertollini (9538620) Laith J. Abu-Raddad (9262524) |
| dc.date.none.fl_str_mv | 2024-03-11T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3389/fmed.2024.1363045 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Addressing_bias_in_the_definition_of_SARS-CoV-2_reinfection_implications_for_underestimation/26508280 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Health sciences Epidemiology Public health reinfection bias time window immunity COVID-19 epidemiology |
| dc.title.none.fl_str_mv | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <h3>Introduction</h3><p dir="ltr">Reinfections are increasingly becoming a feature in the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, accurately defining reinfection poses methodological challenges. Conventionally, reinfection is defined as a positive test occurring at least 90 days after a previous infection diagnosis. Yet, this extended time window may lead to an underestimation of reinfection occurrences. This study investigated the prospect of adopting an alternative, shorter time window for defining reinfection.</p><h3>Methods</h3><p dir="ltr">A longitudinal study was conducted to assess the incidence of reinfections in the total population of Qatar, from February 28, 2020 to November 20, 2023. The assessment considered a range of time windows for defining reinfection, spanning from 1 day to 180 days. Subgroup analyses comparing first versus repeat reinfections and a sensitivity analysis, focusing exclusively on individuals who underwent frequent testing, were performed.</p><h3>Results</h3><p dir="ltr">The relationship between the number of reinfections in the population and the duration of the time window used to define reinfection revealed two distinct dynamical domains. Within the initial 15 days post-infection diagnosis, almost all positive tests for SARS-CoV-2 were attributed to the original infection. However, surpassing the 30-day post-infection threshold, nearly all positive tests were attributed to reinfections. A 40-day time window emerged as a sufficiently conservative definition for reinfection. By setting the time window at 40 days, the estimated number of reinfections in the population increased from 84,565 to 88,384, compared to the 90-day time window. The maximum observed reinfections were 6 and 4 for the 40-day and 90-day time windows, respectively. The 40-day time window was appropriate for defining reinfection, irrespective of whether it was the first, second, third, or fourth occurrence. The sensitivity analysis, confined to high testers exclusively, replicated similar patterns and results.</p><h3>Discussion</h3><p dir="ltr">A 40-day time window is optimal for defining reinfection, providing an informed alternative to the conventional 90-day time window. Reinfections are prevalent, with some individuals experiencing multiple instances since the onset of the pandemic.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Medicine<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fmed.2024.1363045" target="_blank">https://dx.doi.org/10.3389/fmed.2024.1363045</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_7f4e99a74c2a55659ddabb0aee5b57ae |
| identifier_str_mv | 10.3389/fmed.2024.1363045 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26508280 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimationHiam Chemaitelly (439114)Houssein H. Ayoub (9262512)Patrick Tang (239534)Hadi M. Yassine (4675846)Asmaa A. Al Thani (10494576)Mohammad R. Hasan (13777597)Peter Coyle (787159)Zaina Al-Kanaani (4557205)Einas Al-Kuwari (13777606)Andrew Jeremijenko (11506565)Anvar Hassan Kaleeckal (11847034)Ali Nizar Latif (11570540)Riyazuddin Mohammad Shaik (11847037)Hanan F. Abdul-Rahim (13777600)Gheyath K. Nasrallah (9200525)Mohamed Ghaith Al-Kuwari (4264192)Adeel A. Butt (3697705)Hamad Eid Al-Romaihi (6837251)Mohamed H. Al-Thani (11847049)Abdullatif Al-Khal (11721410)Roberto Bertollini (9538620)Laith J. Abu-Raddad (9262524)Health sciencesEpidemiologyPublic healthreinfectionbiastime windowimmunityCOVID-19epidemiology<h3>Introduction</h3><p dir="ltr">Reinfections are increasingly becoming a feature in the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, accurately defining reinfection poses methodological challenges. Conventionally, reinfection is defined as a positive test occurring at least 90 days after a previous infection diagnosis. Yet, this extended time window may lead to an underestimation of reinfection occurrences. This study investigated the prospect of adopting an alternative, shorter time window for defining reinfection.</p><h3>Methods</h3><p dir="ltr">A longitudinal study was conducted to assess the incidence of reinfections in the total population of Qatar, from February 28, 2020 to November 20, 2023. The assessment considered a range of time windows for defining reinfection, spanning from 1 day to 180 days. Subgroup analyses comparing first versus repeat reinfections and a sensitivity analysis, focusing exclusively on individuals who underwent frequent testing, were performed.</p><h3>Results</h3><p dir="ltr">The relationship between the number of reinfections in the population and the duration of the time window used to define reinfection revealed two distinct dynamical domains. Within the initial 15 days post-infection diagnosis, almost all positive tests for SARS-CoV-2 were attributed to the original infection. However, surpassing the 30-day post-infection threshold, nearly all positive tests were attributed to reinfections. A 40-day time window emerged as a sufficiently conservative definition for reinfection. By setting the time window at 40 days, the estimated number of reinfections in the population increased from 84,565 to 88,384, compared to the 90-day time window. The maximum observed reinfections were 6 and 4 for the 40-day and 90-day time windows, respectively. The 40-day time window was appropriate for defining reinfection, irrespective of whether it was the first, second, third, or fourth occurrence. The sensitivity analysis, confined to high testers exclusively, replicated similar patterns and results.</p><h3>Discussion</h3><p dir="ltr">A 40-day time window is optimal for defining reinfection, providing an informed alternative to the conventional 90-day time window. Reinfections are prevalent, with some individuals experiencing multiple instances since the onset of the pandemic.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Medicine<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fmed.2024.1363045" target="_blank">https://dx.doi.org/10.3389/fmed.2024.1363045</a></p>2024-03-11T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3389/fmed.2024.1363045https://figshare.com/articles/journal_contribution/Addressing_bias_in_the_definition_of_SARS-CoV-2_reinfection_implications_for_underestimation/26508280CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/265082802024-03-11T09:00:00Z |
| spellingShingle | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation Hiam Chemaitelly (439114) Health sciences Epidemiology Public health reinfection bias time window immunity COVID-19 epidemiology |
| status_str | publishedVersion |
| title | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation |
| title_full | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation |
| title_fullStr | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation |
| title_full_unstemmed | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation |
| title_short | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation |
| title_sort | Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation |
| topic | Health sciences Epidemiology Public health reinfection bias time window immunity COVID-19 epidemiology |