Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design
<p dir="ltr">The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection (PE<sub>s</sub>) by novel SARS-CoV-2 variants. Mathematical modeling was used to demonstrate a the...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
| Published: |
2023
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513512832761856 |
|---|---|
| author | Houssein H Ayoub (17704359) |
| author2 | Milan Tomy (17704362) Hiam Chemaitelly (439114) Heba N Altarawneh (17704365) Peter Coyle (787159) Patrick Tang (239534) Mohammad R Hasan (14634173) Zaina Al Kanaani (5018198) Einas Al Kuwari (12024471) Adeel A Butt (17704368) Andrew Jeremijenko (11506565) Anvar Hassan Kaleeckal (11847034) Ali Nizar Latif (11570540) Riyazuddin Mohammad Shaik (11847037) Gheyath K Nasrallah (17704371) Fatiha M Benslimane (17704374) Hebah A Al Khatib (17704377) Hadi M Yassine (17704380) Mohamed G Al Kuwari (17704383) Hamad Eid Al Romaihi (12024477) Hanan F Abdul-Rahim (17704386) Mohamed H Al-Thani (17704389) Abdullatif Al Khal (12024468) Roberto Bertollini (9538620) Laith J Abu-Raddad (11868161) |
| author2_role | author author author author author author author author author author author author author author author author author author author author author author author author |
| author_facet | Houssein H Ayoub (17704359) Milan Tomy (17704362) Hiam Chemaitelly (439114) Heba N Altarawneh (17704365) Peter Coyle (787159) Patrick Tang (239534) Mohammad R Hasan (14634173) Zaina Al Kanaani (5018198) Einas Al Kuwari (12024471) Adeel A Butt (17704368) Andrew Jeremijenko (11506565) Anvar Hassan Kaleeckal (11847034) Ali Nizar Latif (11570540) Riyazuddin Mohammad Shaik (11847037) Gheyath K Nasrallah (17704371) Fatiha M Benslimane (17704374) Hebah A Al Khatib (17704377) Hadi M Yassine (17704380) Mohamed G Al Kuwari (17704383) Hamad Eid Al Romaihi (12024477) Hanan F Abdul-Rahim (17704386) Mohamed H Al-Thani (17704389) Abdullatif Al Khal (12024468) Roberto Bertollini (9538620) Laith J Abu-Raddad (11868161) |
| author_role | author |
| dc.creator.none.fl_str_mv | Houssein H Ayoub (17704359) Milan Tomy (17704362) Hiam Chemaitelly (439114) Heba N Altarawneh (17704365) Peter Coyle (787159) Patrick Tang (239534) Mohammad R Hasan (14634173) Zaina Al Kanaani (5018198) Einas Al Kuwari (12024471) Adeel A Butt (17704368) Andrew Jeremijenko (11506565) Anvar Hassan Kaleeckal (11847034) Ali Nizar Latif (11570540) Riyazuddin Mohammad Shaik (11847037) Gheyath K Nasrallah (17704371) Fatiha M Benslimane (17704374) Hebah A Al Khatib (17704377) Hadi M Yassine (17704380) Mohamed G Al Kuwari (17704383) Hamad Eid Al Romaihi (12024477) Hanan F Abdul-Rahim (17704386) Mohamed H Al-Thani (17704389) Abdullatif Al Khal (12024468) Roberto Bertollini (9538620) Laith J Abu-Raddad (11868161) |
| dc.date.none.fl_str_mv | 2023-12-07T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1093/aje/kwad239 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Estimating_protection_afforded_by_prior_infection_in_preventing_reinfection_Applying_the_test-negative_study_design/24906717 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Clinical sciences Health sciences Epidemiology Public health reinfection test-negative design effectiveness mathematical model SARS-CoV-2 COVID-19 |
| dc.title.none.fl_str_mv | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection (PE<sub>s</sub>) by novel SARS-CoV-2 variants. Mathematical modeling was used to demonstrate a theoretical foundation for applicability of the test-negative, case-control study design to derive PE<sub>s</sub>. Apart from the very early phase of an epidemic, the difference between the test-negative estimate for PE<sub>s</sub> and true value of PE<sub>s</sub> was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of PE<sub>s</sub> and its waning. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated PE<sub>s</sub>, but the underestimate was considerable only when >50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated PE<sub>s</sub>. The test-negative design was applied to national-level testing data in Qatar to estimate PE<sub>s</sub> for SARS-CoV-2. PE<sub>s</sub> against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI: 93.6-98.6) and 85.5% (95% CI: 82.4-88.1), respectively. These estimates were validated using a cohort study design. The test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.</p><h2>Other Information</h2><p dir="ltr">Published in: American Journal of Epidemiology<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/10.1093/aje/kwad239" target="_blank">https://dx.doi.org/10.1093/aje/kwad239</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_a8dacb2725a9792af54076df2ef86499 |
| identifier_str_mv | 10.1093/aje/kwad239 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24906717 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study designHoussein H Ayoub (17704359)Milan Tomy (17704362)Hiam Chemaitelly (439114)Heba N Altarawneh (17704365)Peter Coyle (787159)Patrick Tang (239534)Mohammad R Hasan (14634173)Zaina Al Kanaani (5018198)Einas Al Kuwari (12024471)Adeel A Butt (17704368)Andrew Jeremijenko (11506565)Anvar Hassan Kaleeckal (11847034)Ali Nizar Latif (11570540)Riyazuddin Mohammad Shaik (11847037)Gheyath K Nasrallah (17704371)Fatiha M Benslimane (17704374)Hebah A Al Khatib (17704377)Hadi M Yassine (17704380)Mohamed G Al Kuwari (17704383)Hamad Eid Al Romaihi (12024477)Hanan F Abdul-Rahim (17704386)Mohamed H Al-Thani (17704389)Abdullatif Al Khal (12024468)Roberto Bertollini (9538620)Laith J Abu-Raddad (11868161)Biomedical and clinical sciencesClinical sciencesHealth sciencesEpidemiologyPublic healthreinfectiontest-negative designeffectivenessmathematical modelSARS-CoV-2COVID-19<p dir="ltr">The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection (PE<sub>s</sub>) by novel SARS-CoV-2 variants. Mathematical modeling was used to demonstrate a theoretical foundation for applicability of the test-negative, case-control study design to derive PE<sub>s</sub>. Apart from the very early phase of an epidemic, the difference between the test-negative estimate for PE<sub>s</sub> and true value of PE<sub>s</sub> was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of PE<sub>s</sub> and its waning. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated PE<sub>s</sub>, but the underestimate was considerable only when >50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated PE<sub>s</sub>. The test-negative design was applied to national-level testing data in Qatar to estimate PE<sub>s</sub> for SARS-CoV-2. PE<sub>s</sub> against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI: 93.6-98.6) and 85.5% (95% CI: 82.4-88.1), respectively. These estimates were validated using a cohort study design. The test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.</p><h2>Other Information</h2><p dir="ltr">Published in: American Journal of Epidemiology<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/10.1093/aje/kwad239" target="_blank">https://dx.doi.org/10.1093/aje/kwad239</a></p>2023-12-07T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1093/aje/kwad239https://figshare.com/articles/journal_contribution/Estimating_protection_afforded_by_prior_infection_in_preventing_reinfection_Applying_the_test-negative_study_design/24906717CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/249067172023-12-07T03:00:00Z |
| spellingShingle | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design Houssein H Ayoub (17704359) Biomedical and clinical sciences Clinical sciences Health sciences Epidemiology Public health reinfection test-negative design effectiveness mathematical model SARS-CoV-2 COVID-19 |
| status_str | publishedVersion |
| title | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design |
| title_full | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design |
| title_fullStr | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design |
| title_full_unstemmed | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design |
| title_short | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design |
| title_sort | Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design |
| topic | Biomedical and clinical sciences Clinical sciences Health sciences Epidemiology Public health reinfection test-negative design effectiveness mathematical model SARS-CoV-2 COVID-19 |