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Chen Z, Tsui JLH, Gutierrez B, Busch Moreno S, du Plessis L, Deng X, Cai J, Bajaj S, Suchard MA, Pybus OG, Lemey P, Kraemer MUG, Yu H. COVID-19 pandemic interventions reshaped the global dispersal of seasonal influenza viruses. Science 2024; 386:eadq3003. [PMID: 39509510 DOI: 10.1126/science.adq3003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 09/11/2024] [Indexed: 11/15/2024]
Abstract
The global dynamics of seasonal influenza viruses inform the design of surveillance, intervention, and vaccination strategies. The COVID-19 pandemic provided a singular opportunity to evaluate how influenza circulation worldwide was perturbed by human behavioral changes. We combine molecular, epidemiological, and international travel data and find that the pandemic's onset led to a shift in the intensity and structure of international influenza lineage movement. During the pandemic, South Asia played an important role as a phylogenetic trunk location of influenza A viruses, whereas West Asia maintained the circulation of influenza B/Victoria. We explore drivers of influenza lineage dynamics across the pandemic period and reasons for the possible extinction of the B/Yamagata lineage. After a period of 3 years, the intensity of among-region influenza lineage movements returned to pre-pandemic levels, with the exception of B/Yamagata, after the recovery of global air traffic, highlighting the robustness of global lineage dispersal patterns to substantial perturbation.
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Affiliation(s)
- Zhiyuan Chen
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | | | - Bernardo Gutierrez
- Department of Biology, University of Oxford, Oxford, UK
- Colegio de Ciencias Biologicas y Ambientales, Universidad San Francisco de Quito (USFQ), Quito, Ecuador
| | | | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Xiaowei Deng
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
- Department of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jun Cai
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Sumali Bajaj
- Department of Biology, University of Oxford, Oxford, UK
| | - Marc A Suchard
- Departments of Biostatistics, Biomathematics, and Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College, London, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Moritz U G Kraemer
- Department of Biology, University of Oxford, Oxford, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Hongjie Yu
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
- Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China
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Khaleel HA, Alhilfi RA, Rawaf S, Tabche C. Identify future epidemic threshold and intensity for influenza-like illness in Iraq by using the moving epidemic method. IJID REGIONS 2024; 10:126-131. [PMID: 38260712 PMCID: PMC10801321 DOI: 10.1016/j.ijregi.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 12/16/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024]
Abstract
Objectives Influenza-like illness (ILI) entered the Iraq surveillance system in 2021. The alert threshold was determined using the cumulative sum 2 method, which did not provide other characteristics. This study uses the moving epidemic method (MEM) to describe duration and estimate alert thresholds for ILI in Iraq for 2023-2024. Methods MEM default package was used to estimate influenza 2023-2024 epidemic thresholds. Analysis was repeated using optimum parameter of epidemic timing for fixed criteria method, which is 3.3. Arithmetic means and 95% confidence interval upper limit were used to estimate threshold. Geometric mean and 40%, 90%, and 97.3% confidence interval upper limits were used to estimate intensity levels. Aggregated Centers for Disease Control and Prevention surveillance data were used to detect epidemic thresholds, length, sensitivity, and predictive values. Results ILI activity starts at week 30 and lasts 7 weeks. Optimized epidemic threshold is 4513 cases, lower than default (4540 cases). Optimized medium-intensity level was higher than default, and high and very high-intensity levels were lower. Conclusions MEM is essential to determine an influenza epidemic's threshold and intensity levels. Despite requiring 3-5 years of data, using it on data for 2.5 years has resulted in an epidemic threshold slightly higher than the threshold calculated using the cumulative sum 2 method.
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Affiliation(s)
| | | | - Salman Rawaf
- WHO Collaborating Centre, Department of Primary Care and Public Health, Imperial College London, UK
| | - Celine Tabche
- WHO Collaborating Centre, Department of Primary Care and Public Health, Imperial College London, UK
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