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Garcia-Calavaro C, Harrison LH, Pokutnaya D, Mair CF, Brooks MM, van Panhuis W. North to south gradient and local waves of influenza in Chile. Sci Rep 2022; 12:2409. [PMID: 35165325 PMCID: PMC8844068 DOI: 10.1038/s41598-022-06318-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 01/24/2022] [Indexed: 11/09/2022] Open
Abstract
Influenza seasonality is caused by complex interactions between environmental factors, viral mutations, population crowding, and human travel. To date, no studies have estimated the seasonality and latitudinal patterns of seasonal influenza in Chile. We obtained influenza-like illness (ILI) surveillance data from 29 Chilean public health networks to evaluate seasonality using wavelet analysis. We assessed the relationship between the start, peak, and latitude of the ILI epidemics using linear and piecewise regression. To estimate the presence of incoming and outgoing traveling waves (timing vs distance) between networks and to assess the association with population size, we used linear and logistic regression. We found a north to south gradient of influenza and traveling waves that were present in the central, densely populated region of Chile. Our findings suggest that larger populations in central Chile drive seasonal influenza epidemics.
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Affiliation(s)
- Christian Garcia-Calavaro
- Centro Programa de Salud Pública, Facultad de Ciencias Médicas, Universidad de Santiago, Avenida Libertador Bernardo O'Higgins no 3363, Estación Central, Santiago, Chile.
| | - Lee H Harrison
- Center for Genomic Epidemiology, University of Pittsburgh, Pittsburgh, USA
| | - Darya Pokutnaya
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Christina F Mair
- Department of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria M Brooks
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wilbert van Panhuis
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
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2
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Trentini F, Pariani E, Bella A, Diurno G, Crottogini L, Rizzo C, Merler S, Ajelli M. Characterizing the transmission patterns of seasonal influenza in Italy: lessons from the last decade. BMC Public Health 2022; 22:19. [PMID: 34991544 PMCID: PMC8734132 DOI: 10.1186/s12889-021-12426-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 12/14/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Despite thousands of influenza cases annually recorded by surveillance systems around the globe, estimating the transmission patterns of seasonal influenza is challenging. METHODS We develop an age-structured mathematical model to influenza transmission to analyze ten consecutive seasons (from 2010 to 2011 to 2019-2020) of influenza epidemiological and virological data reported to the Italian surveillance system. RESULTS We estimate that 18.4-29.3% of influenza infections are detected by the surveillance system. Influenza infection attack rate varied between 12.7 and 30.5% and is generally larger for seasons characterized by the circulation of A/H3N2 and/or B types/subtypes. Individuals aged 14 years or less are the most affected age-segment of the population, with A viruses especially affecting children aged 0-4 years. For all influenza types/subtypes, the mean effective reproduction number is estimated to be generally in the range 1.09-1.33 (9 out of 10 seasons) and never exceeding 1.41. The age-specific susceptibility to infection appears to be a type/subtype-specific feature. CONCLUSIONS The results presented in this study provide insights on type/subtype-specific transmission patterns of seasonal influenza that could be instrumental to fine-tune immunization strategies and non-pharmaceutical interventions aimed at limiting seasonal influenza spread and burden.
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Affiliation(s)
- Filippo Trentini
- Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy. .,Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy.
| | - Elena Pariani
- Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milan, Italy
| | - Antonino Bella
- Department of Infectious Diseases, Italian National Institute of Health (ISS), Rome, Italy
| | - Giulio Diurno
- General Directorate for Health Planning, Ministry of Health, Rome, Italy
| | - Lucia Crottogini
- Unità Organizzativa Prevenzione, Regione Lombardia, Milan, Italy
| | - Caterina Rizzo
- Clinical Pathways and Epidemiology Functional Area, Bambino Gesù Children's Hospital, IRCCS IT, Rome, Italy
| | - Stefano Merler
- Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy
| | - Marco Ajelli
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
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Bernardo CDO, González-Chica DA, Chilver M, Stocks N. Influenza-like illness in Australia: A comparison of general practice surveillance system with electronic medical records. Influenza Other Respir Viruses 2020; 14:605-609. [PMID: 32578932 PMCID: PMC7578326 DOI: 10.1111/irv.12774] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 05/29/2020] [Accepted: 06/02/2020] [Indexed: 12/01/2022] Open
Abstract
Surveillance systems are fundamental to detect infectious disease outbreaks and guide public health responses. We compared influenza-like illness (ILI) rates for 2015-2017 using data from the Australian Sentinel Practice Research Network (ASPREN) and electronic medical records from 550 general practices across Australia (MedicineInsight). There was a high correlation between both sources (r = .84-.95) and a consistent higher ILI rate in 2017. Both sources also showed higher ILI rates among women and patients aged 20-49 years. The use of routinely collected electronic medical records like those in MedicineInsight could be used to complement active influenza surveillance systems in Australia.
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Affiliation(s)
- Carla De Oliveira Bernardo
- Discipline of General Practice, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
| | - David Alejandro González-Chica
- Discipline of General Practice, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia.,Adelaide Rural Clinical School, The University of Adelaide, Adelaide, SA, Australia
| | - Monique Chilver
- Discipline of General Practice, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
| | - Nigel Stocks
- Discipline of General Practice, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia.,Australian Partnership for Preparedness Research on Infectious Disease Emergencies (APPRISE) Centre of Research Excellence, NHMRC, Adelaide, SA, Australia
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4
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Hosseini S, Karami M, Farhadian M, Mohammadi Y. Seasonal Activity of Influenza in Iran: Application of Influenza-like Illness Data from Sentinel Sites of Healthcare Centers during 2010 to 2015. J Epidemiol Glob Health 2019; 8:29-33. [PMID: 30859784 PMCID: PMC7325813 DOI: 10.2991/j.jegh.2018.08.100] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 06/21/2018] [Indexed: 11/26/2022] Open
Abstract
This study aimed to predict seasonal influenza activity and detection of influenza outbreaks. Data of all registered cases (n = 53,526) of influenza-like illnesses (ILIs) from sentinel sites of healthcare centers in Iran were obtained from the FluNet web-based tool, World Health Organization (WHO), from 2010 to 2015. The status of the ILI activity was obtained from the FluNet and considered as the gold standard of the seasonal activity of influenza during the study period. The cumulative sum (CUSUM) as an outbreak detection method was used to predict the seasonal activity of influenza. Also, time series similarity between the ILI trend and CUSUM was assessed using the cross-correlogram. Of 7684 (14%) positive cases of influenza, about 71% were type A virus and 28% were type B virus. The majority of the outbreaks occurred in winter and autumn. Results of the cross-correlogram showed that there was a considerable similarity between time series graphs of the ILI cases and CUSUM values. However, the CUSUM algorithm did not have a good performance in the timely detection of influenza activity. Despite a considerable similarity between time series of the ILI cases and CUSUM algorithm in weekly lag, the seasonal activity of influenza in Iran could not be predicted by the CUSUM algorithm.
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Affiliation(s)
- Seyedhadi Hosseini
- Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Manoochehr Karami
- Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.,Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Maryam Farhadian
- Modeling of Non-communicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Younes Mohammadi
- Social Determinants of Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
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Gilbertson DT, Rothman KJ, Chertow GM, Bradbury BD, Brookhart MA, Liu J, Winkelmayer WC, Stürmer T, Monda KL, Herzog CA, Ashfaq A, Collins AJ, Wetmore JB. Excess Deaths Attributable to Influenza-Like Illness in the ESRD Population. J Am Soc Nephrol 2019; 30:346-353. [PMID: 30679380 DOI: 10.1681/asn.2018060581] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 12/04/2018] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Morbidity and mortality vary seasonally. Timing and severity of influenza seasons contribute to those patterns, especially among vulnerable populations such as patients with ESRD. However, the extent to which influenza-like illness (ILI), a syndrome comprising a range of potentially serious respiratory tract infections, contributes to mortality in patients with ESRD has not been quantified. METHODS We used data from the Centers for Disease Control and Prevention (CDC) Outpatient Influenza-like Illness Surveillance Network and Centers for Medicare and Medicaid Services ESRD death data from 2000 to 2013. After addressing the increasing trend in deaths due to the growing prevalent ESRD population, we calculated quarterly relative mortality compared with average third-quarter (summer) death counts. We used linear regression models to assess the relationship between ILI data and mortality, separately for quarters 4 and 1 for each influenza season, and model parameter estimates to predict seasonal mortality counts and calculate excess ILI-associated deaths. RESULTS An estimated 1% absolute increase in quarterly ILI was associated with a 1.5% increase in relative mortality for quarter 4 and a 2.0% increase for quarter 1. The average number of annual deaths potentially attributable to ILI was substantial, about 1100 deaths per year. CONCLUSIONS We found an association between community ILI activity and seasonal variation in all-cause mortality in patients with ESRD, with ILI likely contributing to >1000 deaths annually. Surveillance efforts, such as timely reporting to the CDC of ILI activity within dialysis units during influenza season, may help focus attention on high-risk periods for this vulnerable population.
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Affiliation(s)
- David T Gilbertson
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota; .,Department of Medicine, University of Minnesota, Minneapolis, Minnesota
| | - Kenneth J Rothman
- Research Triangle Institute Health Solutions, Research Triangle Park, North Carolina.,Departments of Epidemiology and.,Medicine, Boston University Medical Center, Boston, Massachusetts
| | - Glenn M Chertow
- Department of Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Brian D Bradbury
- Center for Observational Research, Amgen, Inc., Thousand Oak, California
| | - M Alan Brookhart
- Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Jiannong Liu
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota
| | | | - Til Stürmer
- Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Keri L Monda
- Center for Observational Research, Amgen, Inc., Thousand Oak, California
| | - Charles A Herzog
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota.,Department of Medicine, University of Minnesota, Minneapolis, Minnesota
| | - Akhtar Ashfaq
- Renal Division, Opko Pharmaceuticals, Miami, Florida
| | - Allan J Collins
- Department of Medicine, University of Minnesota, Minneapolis, Minnesota.,NxStage Medical, Inc., Lawrence, Massachusetts; and
| | - James B Wetmore
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota.,Department of Medicine, University of Minnesota, Minneapolis, Minnesota.,Division of Nephrology, Hennepin Healthcare, Minneapolis, Minnesota
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Hendriks W, Boshuizen H, Dekkers A, Knol M, Donker GA, van der Ende A, Korthals Altes H. Temporal cross-correlation between influenza-like illnesses and invasive pneumococcal disease in The Netherlands. Influenza Other Respir Viruses 2017; 11:130-137. [PMID: 27943624 PMCID: PMC5304567 DOI: 10.1111/irv.12442] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/02/2016] [Indexed: 11/28/2022] Open
Abstract
Background While the burden of community‐acquired pneumonia and invasive pneumococcal disease (IPD) is still considerable, there is little insight in the factors contributing to disease. Previous research on the lagged relationship between respiratory viruses and pneumococcal disease incidence is inconclusive, and studies correcting for temporal autocorrelation are lacking. Objectives To investigate the temporal relation between influenza‐like illnesses (ILI) and IPD, correcting for temporal autocorrelation. Methods Weekly counts of ILI were obtained from the Sentinel Practices of NIVEL Primary Care Database. IPD data were collected from the Dutch laboratory‐based surveillance system for bacterial meningitis from 2004 to 2014. We analysed the correlation between time series, pre‐whitening the dependent time series with the best‐fit seasonal autoregressive integrated moving average (SARIMA) model to the independent time series. We performed cross‐correlations between ILI and IPD incidences, and the (pre‐whitened) residuals, in the overall population and in the elderly. Results We found significant cross‐correlations between ILI and IPD incidences peaking at lags ‐3 overall and at 1 week in the 65+ population. However, after pre‐whitening, no cross‐correlations were apparent in either population group. Conclusion Our study suggests that ILI occurrence does not seem to be the major driver of IPD incidence in The Netherlands.
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Affiliation(s)
- Wilke Hendriks
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Hendriek Boshuizen
- Department for Statistics, Informatics and Modeling, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Arnold Dekkers
- Department for Statistics, Informatics and Modeling, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Mirjam Knol
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Ge A Donker
- NIVEL Primary Care Database, Sentinel Practices, Utrecht, The Netherlands
| | - Arie van der Ende
- Department of Medical Microbiology, Academic Medical Center, Center for Infection and Immunity Amsterdam, Amsterdam, The Netherlands.,Netherlands Reference Laboratory for Bacterial Meningitis, Amsterdam, The Netherlands
| | - Hester Korthals Altes
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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