Journal article
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19
Mehrdad A. Mizani,
Muhammad H Dashtban,
Laura Pasea,
Alvina G Lai,
Johan Hilge Thygesen,
Christopher Tomlinson,
Alex Handy,
Jil Billy Mamza,
Tamsin Morris,
Sara Khalid,
Francesco Zaccardi,
Mary Joan Macleod,
Fatemeh Torabi 
,
Dexter Canoy,
Ashley Akbari ,
Colin Berry,
Thomas Bolton,
John Nolan,
Kamlesh Khunti,
Spiros Denaxas,
Harry Hemingway,
Cathie Sudlow,
Amitava Banerjee,
CVD-COVID-UK Consortium
,
Dexter Canoy,
Ashley Akbari ,
Colin Berry,
Thomas Bolton,
John Nolan,
Kamlesh Khunti,
Spiros Denaxas,
Harry Hemingway,
Cathie Sudlow,
Amitava Banerjee,
CVD-COVID-UK Consortium
SSRN Electronic Journal
Swansea University Authors:
Fatemeh Torabi , Ashley Akbari
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.2139/ssrn.4066712
Abstract
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19
| Published in: | SSRN Electronic Journal |
|---|---|
| ISSN: | 1556-5068 |
| Published: |
Elsevier BV
|
| Online Access: |
Check full text
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa71656 |
| first_indexed |
2026-03-20T07:01:27Z |
|---|---|
| last_indexed |
2026-04-21T07:36:04Z |
| id |
cronfa71656 |
| recordtype |
SURis |
| fullrecord |
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| spelling |
2026-04-20T16:26:24.3150041 v2 71656 2026-03-19 Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 f569591e1bfb0e405b8091f99fec45d3 0000-0002-5853-4625 Fatemeh Torabi Fatemeh Torabi true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 2026-03-19 MEDS Journal Article SSRN Electronic Journal Elsevier BV 1556-5068 0 0 0 0001-01-01 10.2139/ssrn.4066712 Preprint article before certification by peer review. COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University 2026-04-20T16:26:24.3150041 2026-03-19T23:28:12.6215179 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Mehrdad A. Mizani 1 Muhammad H Dashtban 2 Laura Pasea 3 Alvina G Lai 4 Johan Hilge Thygesen 5 Christopher Tomlinson 6 Alex Handy 7 Jil Billy Mamza 8 Tamsin Morris 9 Sara Khalid 10 Francesco Zaccardi 11 Mary Joan Macleod 12 Fatemeh Torabi 0000-0002-5853-4625 13 Dexter Canoy 14 Ashley Akbari 0000-0003-0814-0801 15 Colin Berry 16 Thomas Bolton 17 John Nolan 18 Kamlesh Khunti 19 Spiros Denaxas 20 Harry Hemingway 21 Cathie Sudlow 22 Amitava Banerjee 23 CVD-COVID-UK Consortium 24 |
| title |
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 |
| spellingShingle |
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 Fatemeh Torabi Ashley Akbari |
| title_short |
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 |
| title_full |
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 |
| title_fullStr |
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 |
| title_full_unstemmed |
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 |
| title_sort |
Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19 |
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f569591e1bfb0e405b8091f99fec45d3 aa1b025ec0243f708bb5eb0a93d6fb52 |
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f569591e1bfb0e405b8091f99fec45d3_***_Fatemeh Torabi aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari |
| author |
Fatemeh Torabi Ashley Akbari |
| author2 |
Mehrdad A. Mizani Muhammad H Dashtban Laura Pasea Alvina G Lai Johan Hilge Thygesen Christopher Tomlinson Alex Handy Jil Billy Mamza Tamsin Morris Sara Khalid Francesco Zaccardi Mary Joan Macleod Fatemeh Torabi Dexter Canoy Ashley Akbari Colin Berry Thomas Bolton John Nolan Kamlesh Khunti Spiros Denaxas Harry Hemingway Cathie Sudlow Amitava Banerjee CVD-COVID-UK Consortium |
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Journal article |
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SSRN Electronic Journal |
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Swansea University |
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1556-5068 |
| doi_str_mv |
10.2139/ssrn.4066712 |
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Elsevier BV |
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Faculty of Medicine, Health and Life Sciences |
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facultyofmedicinehealthandlifesciences |
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Faculty of Medicine, Health and Life Sciences |
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Faculty of Medicine, Health and Life Sciences |
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Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science |
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0001-01-01T08:28:19Z |
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