Estimating SARS-CoV-2 infection incidence and detection rates: Demonstrating a novel surveillance method

Leveraging readily available testing data, the introduced method was validated in a real-world setting and has the potential for diverse applications to enhance infectious disease surveillance for both emerging and endemic infections.

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Publication Details

Journal
Public Health
Published
2025-10-29
DOI
https://doi.org/10.1016/j.puhe.2025.106016
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
0.00
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Estimating SARS-CoV-2 infection incidence and detection rates: Demonstrating a novel surveillance method

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Estimating SARS-CoV-2 infection incidence and detection rates: Demonstrating a novel surveillance method

Laith Jamal Abu-Raddad, Gheyath K. Nasrallah, Hadi Mohamad Yassine, Hiam S. Chemaitelly, Einas Al‐Kuwari, Abdullatif Al‐Khal, Roberto Bertollini, Mohammad R. Hasan, Anvar Hassan Kaleeckal, Adeel A. Butt, Ali Nizar Latif, Hanan F. Abdul Rahim, Houssein H. Ayoub, Hamad Eid Al‐Romaihi, Patrick Tang, Peter Coyle, Zaina Al-Kanaani, Mohamed H. Al-Thani, Asmaa A. Al Thani, Mohamed Ghaith Al-Kuwari
article en

Abstract

Leveraging readily available testing data, the introduced method was validated in a real-world setting and has the potential for diverse applications to enhance infectious disease surveillance for both emerging and endemic infections.

Public HealthVol. 249
Cornell University (US), Ministry of Public Health (QA), Primary Health Care (QA), Weill Cornell Medical College in Qatar (QA), Hamad Medical Corporation (QA), Qatar University (QA), McMaster University (CA)
Openalex Percentile: Top 63%
SARS-CoV-2 detection and testing
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