Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19
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Abstract
BACKGROUND: Mathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. The study investigated the epidemic's time-course, forecasted health care needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions. METHODS: An age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population. RESULTS: declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak. CONCLUSIONS: Use of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the health care system.
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Cases and controls were exact-matched by sex, 10-year-age group, nationality, and calendar week of PCR test to control for established differences in risk of exposure to SARS-CoV-2 infection in Qatar.
“Cases (persons infected with BA.1, BA.2, or any-Omicron-subvariant) and controls (uninfected persons) were exact-matched by sex, 10-year-age group, nationality, and calendar week of polymerase chain reaction (PCR) test to control for established differences in the risk of exposure to SARS-CoV-2 infection in Qatar15–19.”
From Duration of mRNA vaccine protection against SARS-CoV-2 Omicron BA.1 and BA.2 subvariants in Qatar (2022) · cites this paper as [16]
Matching was implemented to control for established differences in the risk of exposure to SARS-CoV-2 infection in Qatar.
“Matching was implemented to control for established differences in the risk of exposure to SARS-CoV-2 infection in Qatar15–19.”
From Duration of mRNA vaccine protection against SARS-CoV-2 Omicron BA.1 and BA.2 subvariants in Qatar (2022) · cites this paper as [16]
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“Qatar had a significant first wave of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that peaked in late May 2020 [1,2].”
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Self-citationBiological Properties of SARS-CoV-2 Variants: Epidemiological Impact and Clinical Consequences
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Self-citationAll-cause and COVID-19 mortality in Qatar during the COVID-19 pandemic
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Self-citationProtection of natural infection against reinfection with SARS-CoV-2 JN.1 variant
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Self-citationHistory of primary-series and booster vaccination and protection against Omicron reinfection
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Self-citationAddressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation
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Self-citationCOVID-19 primary series and booster vaccination and potential for immune imprintingPreprint
Chemaitelly, H. S., Ayoub, H. H., Tang, P., Coyle, P. V., Yassine, H. M., Thani, A. A. A., Al-Khatib, H. A., Hasan, M. R., Kanaani, Z. A., Al‐Kuwari, E., et al. (2022) · medRxiv · doi:10.1101/2022.10.31.22281756 · Cited by 14 · see citing works
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Self-citationSARS-CoV-2 vaccine effectiveness in immunosuppressed kidney transplant recipients
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Desk Review on COVID-19 Pandemic in Sub-Sahara Africa: The Challenges and Proffered Solutions
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Self-citationAnalyzing inherent biases in SARS-CoV-2 PCR and serological epidemiologic metrics
Makhoul, M., Abu-Hijleh, F. M., Seedat, S., Mumtaz, G. R., Chemaitelly, H. S., Ayoub, H. H., & Abu-Raddad, L. J. (2022) · BMC Infectious Diseases · doi:10.1186/s12879-022-07425-z · Cited by 7 · see citing works
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Self-citationGlobal Estimates of COVID‐19 Morbidity and Mortality: A Cohort Study and Mathematical Model Analysis
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Self-citationModeling the population-level impact of treatment on COVID-19 disease and SARS-CoV-2 transmission
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Protection against reinfection with SARS-CoV-2 omicron BA.2.75 * sublineagePreprint
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Self-citationImmune histories and natural infection protection during the omicron era
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Self-citationSeroprevalence of SARS-CoV-2 Infection Among Working Women and Impact of Workplace Restrictions
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Self-citationEffect of BNT162b2 antigen dosage on protection against SARS-CoV-2 omicron infectionPreprint
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Assessing the Impact of the Healthy Vaccinee Effect on COVID-19 Vaccine Effectiveness EstimatesPreprint
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Self-citationHealthy vaccinee effect did not bias COVID-19 vaccine effectiveness estimates
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Self-citation
- Authors
- Ayoub, H. H., Chemaitelly, H., Seedat, S., Makhoul, M., Al Kanaani, Z., Al Khal, A., Al Kuwari, E., Butt, A. A., Coyle, P., Jeremijenko, A., Kaleeckal, A. H., Latif, A. N., Shaik, R. M., Rahim, H. A., Yassine, H. M., Al Kuwari, M. G., Al Romaihi, H. E., Al-Thani, M. H., Bertollini, R., & Abu Raddad, L. J.
- Affiliations
- Qatar University (QA)
- Cornell University (US)
- Hamad Medical Corporation, Doha, Qatar
- Hamad Medical Corporation (QA)
- College of Health Sciences, QU Health, Qatar University, Doha, Qatar
- Primary Health Care Corporation, Doha, Qatar
- Ministry of Public Health, Doha, Qatar
- Ministry of Public Health (QA)
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- Corresponding author
- Ayoub, Houssein H
- ORCID
- Venue
- Journal of Global Health
- Published
- 2021-01-16
- Volume
- 11
- Pages
- 05005-05005
- ISSN
- 2047-2978 (ISSN-L)
- 2047-2986
- PMC
- PMC7897910
- OpenAlex
- W3135605231
- Cited by
- 81
- References
- 44
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 6 · 2023: 11 · 2022: 30 · 2021: 17 · 2020: 1 · 2015: 1
- FWCI
- 6.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Global Health (publishedVersion, cc-by)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Qatar University QSpace (Qatar University) (submittedVersion)
- Funders
- Hamad Medical Corporation
- Weill Cornell Medical College
- Weill Cornell Medicine - Qatar
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Keywords
- SARS-CoV-2, COVID-19 epidemic, epidemic forecasting, transmission dynamics, social distancing, easing of restrictions, health care needs, second wave, epidemic peak, Qatar
- MeSH terms
- COVID-19, Forecasting, Hospitalization, Humans, Intensive Care Units, Models, Theoretical, Qatar, Incidence, Prevalence, Epidemics
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