scholarly journals Transmission of and susceptibility to seasonal influenza in Switzerland from 2003–2015

2018 ◽  
Author(s):  
Jon Brugger ◽  
Christian L. Althaus
Keyword(s):  
Disease Transmission ◽  
Seasonal Influenza ◽  
Age Groups ◽  
Transmission Model ◽  
Mcmc Methods ◽  
Influenza Surveillance ◽  
Modeling Framework ◽  
Surveillance Network ◽  
Influenza Transmission ◽  
Control Of Epidemics

AbstractUnderstanding the seasonal patterns of influenza transmission is critical to help plan public health measures for the management and control of epidemics. Mathematical models of infectious disease transmission have been widely used to quantify the transmissibility of and susceptibility to past influenza seasons in many countries. The objective of this study was to obtain a detailed picture of the transmission dynamics of seasonal influenza in Switzerland from 2003-2015. To this end, we developed a compartmental influenza transmission model taking into account social mixing between different age groups and seasonal forcing. We applied a Bayesian approach using Markov chain Monte Carlo (MCMC) methods to fit the model to the reported incidence of influenza-like-illness (ILI) and virological data from Sentinella, the Swiss Sentinel Surveillance Network. The maximal basic reproduction number, R0, ranged from 1.46 to 1.81 (median). Median estimates of susceptibility to influenza ranged from 29% to 98% for different age groups, and typically decreased with age. We also found a decline in ascertainability of influenza cases with age. Our study illustrates how influenza surveillance data from Switzerland can be integrated into a Bayesian modeling framework in order to assess age-specific transmission of and susceptibility to influenza.

scholarly journals Effects of School Holidays on Seasonal Influenza in South Korea, 2014–2016

2020 ◽  
Vol 222 (5) ◽  
pp. 832-835 ◽  
Author(s):  
Sukhyun Ryu ◽  
Sheikh Taslim Ali ◽  
Benjamin J Cowling ◽  
Eric H Y Lau
Keyword(s):  
South Korea ◽  
Seasonal Influenza ◽  
School Closure ◽  
Surveillance Data ◽  
Influenza Surveillance ◽  
School Closures ◽  
School Aged Children ◽  
Severe Influenza ◽  
Influenza Transmission

Abstract School closures are considered as a potential nonpharmaceutical intervention to mitigate severe influenza epidemics and pandemics. In this study, we assessed the effects of scheduled school closure on influenza transmission using influenza surveillance data before, during, and after spring breaks in South Korea, 2014–2016. During the spring breaks, influenza transmission was reduced by 27%–39%, while the overall reduction in transmissibility was estimated to be 6%–23%, with greater effects observed among school-aged children.

scholarly journals Vaccinating Adolescents and Children Significantly Reduces COVID-19 Morbidity and Mortality across All Ages: A Popula-Tion-Based Modeling Study Using the UK as an Example

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1180
Author(s):  
Tinevimbo Shiri ◽  
Marc Evans ◽  
Carla A. Talarico ◽  
Angharad R. Morgan ◽  
Maaz Mussad ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Age Groups ◽  
Population Level ◽  
Vital Role ◽  
Morbidity And Mortality ◽  
Transmission Model ◽  
Base Case ◽  
Global Public Health ◽  
The Uk ◽  
The Impact

Debate persists around the risk–benefit balance of vaccinating adolescents and children against COVID-19. Central to this debate is quantifying the contribution of adolescents and children to the transmission of SARS-CoV-2, and the potential impact of vaccinating these age groups. In this study, we present a novel SEIR mathematical disease transmission model that quantifies the impact of different vaccination strategies on population-level SARS-CoV-2 infections and clinical outcomes. The model employs both age- and time-dependent social mixing patterns to capture the impact of changes in restrictions. The model was used to assess the impact of vaccinating adolescents and children on the natural history of the COVID-19 pandemic across all age groups, using the UK as an example. The base case model demonstrates significant increases in COVID-19 disease burden in the UK following a relaxation of restrictions, if vaccines are limited to those ≥18 years and vulnerable adolescents (≥12 years). Including adolescents and children in the vaccination program could reduce overall COVID-related mortality by 57%, and reduce cases of long COVID by 75%. This study demonstrates that vaccinating adolescents and children has the potential to play a vital role in reducing SARS-CoV-2 infections, and subsequent COVID-19 morbidity and mortality, across all ages. Our results have major global public health implications and provide valuable information to inform a potential pandemic exit strategy.

Cost-effectiveness of influenza control measures: a dynamic transmission model-based analysis

2013 ◽  
Vol 141 (12) ◽  
pp. 2581-2594 ◽  
Author(s):  
S.-C. CHEN ◽  
C.-M. LIAO
Keyword(s):  
Cost Effectiveness ◽  
Natural Ventilation ◽  
Seasonal Influenza ◽  
School Setting ◽  
Control Measures ◽  
Transmission Model ◽  
Model Based ◽  
Dynamic Transmission Model ◽  
Influenza Transmission ◽  
The Cost

SUMMARYWe investigated the cost-effectiveness of different influenza control strategies in a school setting in Taiwan. A susceptible-exposure-infected-recovery (SEIR) model was used to simulate influenza transmission and we used a basic reproduction number (R0)–asymptomatic proportion (θ) control scheme to develop a cost-effectiveness model. Based on our dynamic transmission model and economic evaluation, this study indicated that the optimal cost-effective strategy for all modelling scenarios was a combination of natural ventilation and respiratory masking. The estimated costs were US$10/year per person in winter for one kindergarten student. The cost for hand washing was estimated to be US$32/year per person, which was much lower than that of isolation (US$55/year per person) and vaccination (US$86/year per person) in containing seasonal influenza. Transmission model-based, cost-effectiveness analysis can be a useful tool for providing insight into the impacts of economic factors and health benefits on certain strategies for controlling seasonal influenza.

scholarly journals Increased urbanization reduced the effectiveness of school closures on seasonal influenza epidemics in China

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Hao Lei ◽  
Hangjin Jiang ◽  
Nan Zhang ◽  
Xiaoli Duan ◽  
Tao Chen ◽  
...  
Keyword(s):  
Seasonal Influenza ◽  
Southern China ◽  
Social Contact ◽  
School Closure ◽  
Surveillance Data ◽  
Reproductive Number ◽  
Influenza Surveillance ◽  
Sirs Model ◽  
Influenza Transmission ◽  
The Impact

Abstract Background School closure is a common mitigation strategy during severe influenza epidemics and pandemics. However, the effectiveness of this strategy remains controversial. In this study, we aimed to explore the effectiveness of school closure on seasonal influenza epidemics in provincial-level administrative divisions (PLADs) with varying urbanization rates in China. Methods This study analyzed influenza surveillance data between 2010 and 2019 provided by the Chinese National Influenza Center. Taking into consideration the climate, this study included a region with 3 adjacent PLADs in Northern China and another region with 4 adjacent PLADs in Southern China. The effect of school closure on influenza transmission was evaluated by the reduction of the effective reproductive number of seasonal influenza during school winter breaks compared with that before school winter breaks. An age-structured Susceptible-Infected-Recovered-Susceptible (SIRS) model was built to model influenza transmission in different levels of urbanization. Parameters were determined using the surveillance data via robust Bayesian method. Results Between 2010 and 2019, in the less urbanized provinces: Hebei, Zhejiang, Jiangsu and Anhui, during school winter breaks, the effective reproductive number of seasonal influenza epidemics reduced 14.6% [95% confidential interval (CI): 6.2–22.9%], 9.6% (95% CI: 2.5–16.6%), 7.3% (95% CI: 0.1–14.4%) and 8.2% (95% CI: 1.1–15.3%) respectively. However, in the highly urbanized cities: Beijing, Tianjin and Shanghai, it reduced only 5.2% (95% CI: -0.7–11.2%), 4.1% (95% CI: -0.9–9.1%) and 3.9% (95% CI: -1.6–9.4%) respectively. In China, urbanization is associated with decreased proportion of children and increased social contact. According to the SIRS model, both factors could reduce the impact of school closure on seasonal influenza epidemics, and the proportion of children in the population is thought to be the dominant influencing factor. Conclusions Effectiveness of school closure on the epidemics varies with the age structure in the population and social contact patterns. School closure should be recommended in the low urbanized regions in China in the influenza seasons. Graphical abstract

scholarly journals Utility of Nontraditional Data Sources for Early Detection of Influenza

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Shari Barlow ◽  
Jonathan Temte ◽  
Yenlik Zheteyeva ◽  
Ashley Fowlkes ◽  
Carrie Reed ◽  
...  
Keyword(s):  
Age Groups ◽  
School Closure ◽  
Influenza Viruses ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
School Absenteeism ◽  
School Closures ◽  
School Based ◽  
Influenza Transmission ◽  
Influenza Outbreaks

ObjectiveThis session will provide an overview of the current systemsfor influenza surveillance; review the role of schools in influenzatransmission; discuss relationships between school closures, schoolabsenteeism, and influenza transmission; and explore the usefulnessof school absenteeism and unplanned school closure monitoring forearly detection of influenza in schools and broader communities.IntroductionInfluenza surveillance is conducted through a complex networkof laboratory and epidemiologic systems essential for estimatingpopulation burden of disease, selecting influenza vaccine viruses,and detecting novel influenza viruses with pandemic potential (1).Influenza surveillance faces numerous challenges, such as constantlychanging influenza viruses, substantial variability in the number ofaffected people and the severity of disease, nonspecific symptoms,and need for laboratory testing to confirm diagnosis. Exploringadditional components that provide morbidity information mayenhance current influenza surveillance.School-aged children have the highest influenza incidence ratesamong all age groups. Due to the close interaction of children inschools and subsequent introduction of influenza into households,it is recognized that schools can serve as amplification points ofinfluenza transmission in communities. For this reason, pandemicpreparedness recommendations include possible pre-emptive schoolclosures, before transmission is widespread within a school system orbroader community, to slow influenza transmission until appropriatevaccines become available. During seasonal influenza epidemics,school closures are usually reactive, implemented in response tohigh absenteeism of students and staff after the disease is alreadywidespread in the community. Reactive closures are often too late toreduce influenza transmission and are ineffective.To enhance timely influenza detection, a variety of nontraditionaldata sources have been explored. School absenteeism was suggestedby several research groups to improve school-based influenzasurveillance. A study conducted in Japan demonstrated that influenza-associated absenteeism can predict influenza outbreaks with highsensitivity and specificity (2). Another study found the use of all-causes absenteeism to be too nonspecific for utility in influenzasurveillance (3). Creation of school-based early warning systemsfor pandemic influenza remains an interest, and further studies areneeded. The panel will discuss how school-based surveillance cancomplement existing influenza surveillance systems.

scholarly journals Spotlight influenza: Influenza surveillance before and after the introduction of point-of-care testing in Denmark, season 2014/15 to 2018/19

2021 ◽  
Vol 26 (37) ◽  
Author(s):  
Guido Benedetti ◽  
Tyra Grove Krause ◽  
Uffe Vest Schneider ◽  
Jan Gorm Lisby ◽  
Marianne Voldstedlund ◽  
...  
Keyword(s):  
Seasonal Influenza ◽  
Point Of Care ◽  
Relative Proportion ◽  
Age Groups ◽  
Population Based ◽  
Influenza Surveillance ◽  
Routine Surveillance ◽  
Before And After ◽  
Data Capturing ◽  
Analytical Time

Background In Denmark, influenza surveillance is ensured by data capturing from existing population-based registers. Since 2017, point-of-care (POC) testing has been implemented outside the regional clinical microbiology departments (CMD). Aim We aimed to assess influenza laboratory results in view of the introduction of POC testing. Methods We retrospectively observed routine surveillance data on national influenza tests before and after the introduction of POC testing as available in the Danish Microbiological Database. Also, we conducted a questionnaire study among Danish CMD about influenza diagnostics. Results Between the seasons 2014/15 and 2018/19, 199,744 influenza tests were performed in Denmark of which 44,161 were positive (22%). After the introduction of POC testing, the overall percentage of positive influenza tests per season did not decrease. The seasonal influenza test incidence was higher in all observed age groups. The number of operating testing platforms placed outside a CMD and with an instrument analytical time ≤ 3 h increased after 2017. Regionally, the number of tests registered as POC in the Danish Microbiological Database and the number of tests performed with an instrument analytical time ≤ 3 h or outside a CMD partially differed. Where comparable (71% of tests), the relative proportion of POC tests out of all tests increased from season 2017/18 to 2018/19. In both seasons, the percentage of positive POC tests resulted slightly lower than for non-POC tests. Conclusion POC testing integrated seamlessly into national influenza surveillance. We propose the use of POC results in the routine surveillance of seasonal influenza.

scholarly journals Seasonal influenza during the COVID-19 pandemic in Bangladesh

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255646
Author(s):  
Zubair Akhtar ◽  
Fahmida Chowdhury ◽  
Mahmudur Rahman ◽  
Probir Kumar Ghosh ◽  
Md. Kaousar Ahmmed ◽  
...  
Keyword(s):  
Seasonal Influenza ◽  
Web Applications ◽  
Influenza Season ◽  
Tertiary Care ◽  
Age Groups ◽  
Influenza Viruses ◽  
Control Measures ◽  
Mitigation Measures ◽  
Influenza Surveillance ◽  
Severe Acute Respiratory Infection

Introduction During the 2019 novel coronavirus infectious disease (COVID-19) pandemic in 2020, limited data from several countries suggested reduced seasonal influenza viruses’ circulation. This was due to community mitigation measures implemented to control the pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used sentinel surveillance data to identify changes in the 2020 influenza season compared with previous seasons in Bangladesh. Methods We used hospital-based influenza surveillance (HBIS) data of Bangladesh that are generated year-round and are population-representative severe acute respiratory infection (SARI) data for all age groups from seven public and two private tertiary care level hospitals data from 2016 to 2019. We applied the moving epidemic method (MEM) by using R language (v4.0.3), and MEM web applications (v2.14) on influenza-positive rates of SARI cases collected weekly to estimate an average seasonal influenza curve and establish epidemic thresholds. Results The 2016–2019 average season started on epi week 18 (95% CI: 15–25) and lasted 12.5 weeks (95% CI: 12–14 weeks) until week 30.5. The 2020 influenza season started on epi week 36 and ended at epi week 41, lasting for only five weeks. Therefore, influenza epidemic started 18 weeks later, was 7.5 weeks shorter, and was less intense than the average epidemic of the four previous years. The 2020 influenza season started on the same week when COVID-19 control measures were halted, and 13 weeks after the measures were relaxed. Conclusion Our findings suggest that seasonal influenza circulation in Bangladesh was delayed and less intense in 2020 than in previous years. Community mitigation measures may have contributed to this reduction of seasonal influenza transmission. These findings contribute to a limited but growing body of evidence that influenza seasons were altered globally in 2020.

scholarly journals Performance of influenza case definitions for influenza community surveillance: based on the French influenza surveillance network GROG, 2009-2014

2017 ◽  
Vol 22 (14) ◽  
Author(s):  
Jean-Sebastien Casalegno ◽  
Daniel Eibach ◽  
Martine Valette ◽  
Vincent Enouf ◽  
Isabelle Daviaud ◽  
...  
Keyword(s):  
Influenza Infection ◽  
Age Groups ◽  
Case Definition ◽  
World Health ◽  
Influenza Surveillance ◽  
Case Definitions ◽  
Surveillance Network ◽  
Increased Risk ◽  
Influenza Case ◽  
Health Organization

International case definitions recommended by the Centers for Disease Control and Prevention (CDC), the European Centre for Disease Prevention and Control (ECDC), and the World Health Organization (WHO) are commonly used for influenza surveillance. We evaluated clinical factors associated with the laboratory-confirmed diagnosis of influenza and the performance of these influenza case definitions by using a complete dataset of 14,994 patients with acute respiratory infection (ARI) from whom a specimen was collected between August 2009 and April 2014 by the Groupes Régionaux d’Observation de la Grippe (GROG), a French national influenza surveillance network. Cough and fever ≥ 39 °C most accurately predicted an influenza infection in all age groups. Several other symptoms were associated with an increased risk of influenza (headache, weakness, myalgia, coryza) or decreased risk (adenopathy, pharyngitis, shortness of breath, otitis/otalgia, bronchitis/ bronchiolitis), but not throughout all age groups. The WHO case definition for influenza-like illness (ILI) had the highest specificity with 21.4%, while the ECDC ILI case definition had the highest sensitivity with 96.1%. The diagnosis among children younger than 5 years remains challenging. The study compared the performance of clinical influenza definitions based on outpatient surveillance and will contribute to improving the comparability of data shared at international level.

scholarly journals Model-based reconstruction of an epidemic using multiple datasets: understanding influenza A/H1N1 pandemic dynamics in Israel

2016 ◽  
Vol 13 (116) ◽  
pp. 20160099 ◽  
Author(s):  
R. Yaari ◽  
G. Katriel ◽  
L. Stone ◽  
E. Mendelson ◽  
M. Mandelboim ◽  
...  
Keyword(s):  
School Children ◽  
Disease Transmission ◽  
Influenza A ◽  
Influenza Pandemic ◽  
Age Groups ◽  
Absolute Humidity ◽  
Transmission Model ◽  
Reproductive Number ◽  
Infection Pattern ◽  
Influenza A H1n1

Intensified surveillance during the 2009 A/H1N1 influenza pandemic in Israel resulted in large virological and serological datasets, presenting a unique opportunity for investigating the pandemic dynamics. We employ a conditional likelihood approach for fitting a disease transmission model to virological and serological data, conditional on clinical data. The model is used to reconstruct the temporal pattern of the pandemic in Israel in five age-groups and evaluate the factors that shaped it. We estimate the reproductive number at the beginning of the pandemic to be R = 1.4. We find that the combined effect of varying absolute humidity conditions and school vacations (SVs) is responsible for the infection pattern, characterized by three epidemic waves. Overall attack rate is estimated at 32% (28–35%) with a large variation among the age-groups: the highest attack rates within school children and the lowest within the elderly. This pattern of infection is explained by a combination of the age-group contact structure and increasing immunity with age. We assess that SVs increased the overall attack rates by prolonging the pandemic into the winter. Vaccinating school children would have been the optimal strategy for minimizing infection rates in all age-groups.

scholarly journals Optimal Vaccine Distribution Strategy for Different Age Groups of Population: A Differential Evolution Algorithm Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Xiao-Min Hu ◽  
Jun Zhang ◽  
Haihong Chen
Keyword(s):  
Differential Evolution ◽  
Disease Transmission ◽  
Vaccine Coverage ◽  
Age Groups ◽  
Differential Evolution Algorithm ◽  
Transmission Model ◽  
Distribution Strategy ◽  
De Algorithm ◽  
Vaccine Distribution ◽  
Disease Transmission Model

Vaccination is one of the effective ways for protecting susceptible individuals from infectious diseases. Different age groups of population have different vulnerability to the disease and different contact frequencies. In order to achieve the maximum effects, the distribution of vaccine doses to the groups of individuals needs to be optimized. In this paper, a differential evolution (DE) algorithm is proposed to address the problem. The performance of the proposed algorithm has been tested by a classical infectious disease transmission model and a series of simulations have been made. The results show that the proposed algorithm can always obtain the best vaccine distribution strategy which can minimize the number of infectious individuals during the epidemic outbreak. Furthermore, the effects of vaccination on different days and the vaccine coverage percentages have also been discussed.

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