scholarly journals Explaining the geographical origins of seasonal influenza A (H3N2)

2016 ◽  
Vol 283 (1838) ◽  
pp. 20161312 ◽  
Author(s):  
Frank Wen ◽  
Trevor Bedford ◽  
Sarah Cobey
Keyword(s):  
Influenza A ◽  
Seasonal Influenza ◽  
Evolutionary Dynamics ◽  
Spatial Dynamics ◽  
Basic Reproductive Number ◽  
Viral Population ◽  
Reproductive Number ◽  
Antigenic Evolution ◽  
Migratory Patterns ◽  
Seasonal Population

Most antigenically novel and evolutionarily successful strains of seasonal influenza A (H3N2) originate in East, South and Southeast Asia. To understand this pattern, we simulated the ecological and evolutionary dynamics of influenza in a host metapopulation representing the temperate north, tropics and temperate south. Although seasonality and air traffic are frequently used to explain global migratory patterns of influenza, we find that other factors may have a comparable or greater impact. Notably, a region's basic reproductive number ( R 0 ) strongly affects the antigenic evolution of its viral population and the probability that its strains will spread and fix globally: a 17–28% higher R 0 in one region can explain the observed patterns. Seasonality, in contrast, increases the probability that a tropical (less seasonal) population will export evolutionarily successful strains but alone does not predict that these strains will be antigenically advanced. The relative sizes of different host populations, their birth and death rates, and the region in which H3N2 first appears affect influenza's phylogeography in different but relatively minor ways. These results suggest general principles that dictate the spatial dynamics of antigenically evolving pathogens and offer predictions for how changes in human ecology might affect influenza evolution.

scholarly journals Comparison of Clinical Features and Outcomes of Medically Attended COVID-19 and Influenza Patients in a Defined Population in the 2020 Respiratory Virus Season

2021 ◽  
Vol 9 ◽  
Author(s):  
Long Liu ◽  
Feng Zeng ◽  
Jingjing Rao ◽  
Shengren Yuan ◽  
Manshan Ji ◽  
...  
Keyword(s):  
Influenza A Virus ◽  
Clinical Features ◽  
Influenza A ◽  
Seasonal Influenza ◽  
Respiratory Virus ◽  
Distress Syndrome ◽  
Evolutionary Rate ◽  
Clinical Manifestations ◽  
Basic Reproductive Number ◽  
Reproductive Number

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), which is causing the coronavirus disease-2019 (COVID-19) pandemic, poses a global health threat. However, it is easy to confuse COVID-19 with seasonal influenza in preliminary clinical diagnosis. In this study, the differences between influenza and COVID-19 in epidemiological features, clinical manifestations, comorbidities and pathogen biology were comprehensively compared and analyzed. SARS-CoV-2 causes a higher proportion of pneumonia (90.67 vs. 17.07%) and acute respiratory distress syndrome (12.00 vs. 0%) than influenza A virus. The proportion of leukopenia for influenza patients was 31.71% compared with 12.00% for COVID-19 patients (P = 0.0096). The creatinine and creatine kinase were significantly elevated when there were COVID-19 patients. The basic reproductive number (R0) for SARS-CoV-2 is 2.38 compared with 1.28 for seasonal influenza A virus. The mutation rate of SARS-CoV-2 ranges from 1.12 × 10−3 to 6.25 × 10−3, while seasonal influenza virus has a lower evolutionary rate (0.60-2.00 × 10−6). Overall, this study compared the clinical features and outcomes of medically attended COVID-19 and influenza patients. In addition, the S477N and N439K mutations on spike may affect the affinity with receptor ACE2. This study will contribute to COVID-19 control and epidemic surveillance in the future.

scholarly journals Estimation of the Basic Reproduction Number of Novel Influenza A (H1N1) pdm09 in Elementary Schools Using the SIR Model

2017 ◽  
Vol 11 (1) ◽  
pp. 64-72 ◽  
Author(s):  
Daisuke Furushima ◽  
Shoko Kawano ◽  
Yuko Ohno ◽  
Masayuki Kakehashi
Keyword(s):  
Elementary Schools ◽  
Infection Rate ◽  
School Size ◽  
Influenza A ◽  
Missing Values ◽  
Sir Model ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Influenza A H1n1 ◽  
Novel Influenza A

Background: The novel influenza A (H1N1) pdm09 (A/H1N1pdm) pandemic of 2009-2010 had a great impact on society. Objective: We analyzed data from the absentee survey, conducted in elementary schools of Oita City, to evaluate the A/H1N1pdm pandemic and to estimate the basic reproductive number (R0 ) of this novel strain. Method: We summarized the overall absentee data and calculated the cumulative infection rate. Then, we classified the data into 3 groups according to school size: small (<300 students), medium (300–600 students), and large (>600 students). Last, we estimated the R0 value by using the Susceptible-Infected-Recovered (SIR) mathematical model. Results: Data from 60 schools and 27,403 students were analyzed. The overall cumulative infection rate was 44.4%. There were no significant differences among the grades, but the cumulative infection rate increased as the school size increased, being 37.7%, 44.4%, and 46.6% in the small, medium, and large school groups, respectively. The optimal R0 value was 1.33, comparable with that previously reported. The data from the absentee survey were reliable, with no missing values. Hence, the R0 derived from the SIR model closely reflected the observed R0 . The findings support previous reports that school children are most susceptible to A/H1N1pdm virus infection and suggest that the scale of an outbreak is associated with the size of the school. Conclusion: Our results provide further information about the A/H1N1pdm pandemic. We propose that an absentee survey should be implemented in the early stages of an epidemic, to prevent a pandemic.

scholarly journals Different Transmission Dynamics of Coronavirus Disease 2019 (COVID-19) and Influenza Suggest the Relative Efficiency of Isolation/Quarantine and Social Distancing Against COVID-19 in China

2020 ◽  
Author(s):  
Hao Lei ◽  
Xifeng Wu ◽  
Xiao Wang ◽  
Modi Xu ◽  
Yu Xie ◽  
...  
Keyword(s):  
Relative Efficiency ◽  
Seasonal Influenza ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Social Distancing ◽  
Relative Age ◽  
Age Dependent ◽  
The Mean ◽  
Age Structured ◽  
Nonpharmaceutical Interventions

Abstract Background Nonpharmaceutical interventions (NPIs) against coronavirus disease 2019 (COVID-19) are vital to reducing transmission risks. However, the relative efficiency of social distancing against COVID-19 remains controversial, since social distancing and isolation/quarantine were implemented almost at the same time in China. Methods In this study, surveillance data of COVID-19 and seasonal influenza in 2018–2020 were used to quantify the relative efficiency of NPIs against COVID-19 in China, since isolation/quarantine was not used for the influenza epidemics. Given that the relative age-dependent susceptibility to influenza and COVID-19 may vary, an age-structured susceptible/infected/recovered model was built to explore the efficiency of social distancing against COVID-19 under different population susceptibility scenarios. Results The mean effective reproductive number, Rt, of COVID-19 before NPIs was 2.12 (95% confidence interval [CI], 2.02–2.21). By 11 March 2020, the overall reduction in Rt of COVID-19 was 66.1% (95% CI, 60.1–71.2%). In the epidemiological year 2019–20, influenza transmissibility was reduced by 34.6% (95% CI, 31.3–38.2%) compared with transmissibility in epidemiological year 2018–19. Under the observed contact pattern changes in China, social distancing had similar efficiency against COVID-19 in 3 different scenarios. By assuming the same efficiency of social distancing against seasonal influenza and COVID-19 transmission, isolation/quarantine and social distancing could lead to 48.1% (95% CI, 35.4–58.1%) and 34.6% (95% CI, 31.3–38.2%) reductions of the transmissibility of COVID-19, respectively. Conclusions Though isolation/quarantine is more effective than social distancing, given that the typical basic reproductive number of COVID-19 is 2–3, isolation/quarantine alone could not contain the COVID-19 pandemic effectively in China.

Evolution-informed forecasting of seasonal influenza A (H3N2)

2017 ◽  
Author(s):  
Xiangjun Du ◽  
Aaron A. King ◽  
Robert J. Woods ◽  
Mercedes Pascual
Keyword(s):  
Influenza A ◽  
Seasonal Influenza ◽  
The United States ◽  
Evolutionary Change ◽  
Amino Acid Sequences ◽  
Epidemiological Surveillance ◽  
Transmission Model ◽  
Genetic Sequences ◽  
Antigenic Evolution ◽  
H3n2 Influenza

ABSTRACTInter-pandemic or seasonal influenza exacts an enormous annual burden both in terms of human health and economic impact. Incidence prediction ahead of season remains a challenge largely because of the virus’ antigenic evolution. We propose here a forecasting approach that incorporates evolutionary change into a mechanistic epidemiological model. The proposed models are simple enough that their parameters can be estimated from retrospective surveillance data. These models link amino-acid sequences of hemagglutinin epitopes with a transmission model for seasonal H3N2 influenza, also informed by H1N1 levels. With a monthly time series of H3N2 incidence in the United States over 10 years, we demonstrate the feasibility of prediction ahead of season and an accurate real-time forecast for the 2016/2017 influenza season.SUMMARYSkillful forecasting of seasonal (H3N2) influenza incidence ahead of the season is shown to be possible by means of a transmission model that explicitly tracks evolutionary change in the virus, integrating information from both epidemiological surveillance and readily available genetic sequences.

scholarly journals Antigenic waves of virus–immune coevolution

2021 ◽  
Vol 118 (27) ◽  
pp. e2103398118
Author(s):  
Jacopo Marchi ◽  
Michael Lässig ◽  
Aleksandra M. Walczak ◽  
Thierry Mora
Keyword(s):  
Mathematical Theory ◽  
Seasonal Influenza ◽  
Evolutionary Dynamics ◽  
Cross Reactivity ◽  
Host Population ◽  
Viral Population ◽  
Immune Systems ◽  
Persistence Time ◽  
Immune Pressure ◽  
Finite Dimensional

The evolution of many microbes and pathogens, including circulating viruses such as seasonal influenza, is driven by immune pressure from the host population. In turn, the immune systems of infected populations get updated, chasing viruses even farther away. Quantitatively understanding how these dynamics result in observed patterns of rapid pathogen and immune adaptation is instrumental to epidemiological and evolutionary forecasting. Here we present a mathematical theory of coevolution between immune systems and viruses in a finite-dimensional antigenic space, which describes the cross-reactivity of viral strains and immune systems primed by previous infections. We show the emergence of an antigenic wave that is pushed forward and canalized by cross-reactivity. We obtain analytical results for shape, speed, and angular diffusion of the wave. In particular, we show that viral–immune coevolution generates an emergent timescale, the persistence time of the wave’s direction in antigenic space, which can be much longer than the coalescence time of the viral population. We compare these dynamics to the observed antigenic turnover of influenza strains, and we discuss how the dimensionality of antigenic space impacts the predictability of the evolutionary dynamics. Our results provide a concrete and tractable framework to describe pathogen–host coevolution.

scholarly journals Modelling the role of immunity in reversion of viral antigenic sites

2015 ◽  
Author(s):  
Carmen H. S. Chan ◽  
Lloyd P. Sanders ◽  
Mark M. Tanaka
Keyword(s):  
Influenza A ◽  
Evolutionary Dynamics ◽  
Immune Escape ◽  
Low Cost ◽  
Synonymous Substitution ◽  
Host Immunity ◽  
Viral Population ◽  
Viral Pathogens ◽  
Site Model ◽  
Antigenic Sites

Antigenic sites in viral pathogens exhibit distinctive evolutionary dynamics due to their role in evading recognition by host immunity. Antigenic selection is known to drive higher rates of non-synonymous substitution; less well understood is why differences are observed between viruses in their propensity to mutate to a novel or previously encountered amino acid. Here, we present a model to explain patterns of antigenic reversion and forward substitution in terms of the epidemiological and molecular processes of the viral population. We develop an analytical three-strain model and extend the analysis to a multi-site model to predict characteristics of observed sequence samples. Our model provides insight into how the balance between selection to escape immunity and to maintain viability is affected by the rate of mutational input. We also show that while low probabilities of reversion may be due to either a low cost of immune escape or slowly decaying host immunity, these two scenarios can be differentiated by the frequency patterns at antigenic sites. Comparison between frequency patterns of human influenza A (H3N2) and human RSV-A suggests that the increased rates of antigenic reversion in RSV-A is due to faster decaying immunity and not higher costs of escape.

scholarly journals Selection on non-antigenic gene segments of seasonal influenza A virus and its impact on adaptive evolution

2017 ◽  
Author(s):  
Jayna Raghwani ◽  
Robin Thompson ◽  
Katia Koelle
Keyword(s):  
Adaptive Evolution ◽  
Genetic Background ◽  
Influenza A ◽  
Seasonal Influenza ◽  
Evolutionary Dynamics ◽  
Gene Segment ◽  
Influenza Viruses ◽  
Neutral Evolution ◽  
H3n2 Virus ◽  
Genome Wide

ABSTRACTMost studies on seasonal influenza A/H3N2 virus adaptation have focused on the main antigenic gene, haemagglutinin. However, there is increasing evidence that the genome-wide genetic background of novel antigenic variants can influence these variants’ emergence probabilities and impact their patterns of dominance in the population. This suggests that non-antigenic genes may be important in shaping the viral evolutionary dynamics. To better understand the role of selection on non-antigenic genes in the adaptive evolution of seasonal influenza viruses, we here develop a simple population genetic model that considers a virus with one antigenic and one non-antigenic gene segment. By simulating this model under different regimes of selection and reassortment, we find that the empirical patterns of lineage turnover for the antigenic and non-antigenic gene segments are best captured when there is both limited viral coinfection and selection operating on both gene segments. In contrast, under a scenario of only neutral evolution in the non-antigenic gene segment, we see persistence of multiple lineages for long periods of time in that segment, which is not compatible with the observed molecular evolutionary patterns. Further, we find that reassortment, occurring in coinfected individuals, can increase the speed of viral adaptive evolution by primarily reducing selective interference and genetic linkage effects mediated by the non-antigenic gene segment. Together, these findings suggest that, for influenza, with 6 internal or non-antigenic gene segments, the evolutionary dynamics of novel antigenic variants are likely to be influenced by the genome-wide genetic background as a result of linked selection among both beneficial and deleterious mutations.

scholarly journals Household transmissibility of avian influenza A (H7N9) virus, China, February to May 2013 and October 2013 to March 2014

2015 ◽  
Vol 20 (10) ◽  
Author(s):  
Y Yang ◽  
Y Zhang ◽  
L Fang ◽  
M E Halloran ◽  
M Ma ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Influenza A ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Age Difference ◽  
H7n9 Virus ◽  
Relative Transmission ◽  
History Of ◽  
A Minor ◽  
Index Cases

To study human-to-human transmissibility of the avian influenza A (H7N9) virus in China, household contact information was collected for 125 index cases during the spring wave (February to May 2013), and for 187 index cases during the winter wave (October 2013 to March 2014). Using a statistical model, we found evidence for human-to-human transmission, but such transmission is not sustainable. Under plausible assumptions about the natural history of disease and the relative transmission frequencies in settings other than household, we estimate the household secondary attack rate (SAR) among humans to be 1.4% (95% CI: 0.8 to 2.3), and the basic reproductive number R0 to be 0.08 (95% CI: 0.05 to 0.13). The estimates range from 1.3% to 2.2% for SAR and from 0.07 to 0.12 for R0 with reasonable changes in the assumptions. There was no significant change in the human-to-human transmissibility of the virus between the two waves, although a minor increase was observed in the winter wave. No sex or age difference in the risk of infection from a human source was found. Human-to-human transmissibility of H7N9 continues to be limited, but it needs to be closely monitored for potential increase via genetic reassortment or mutation.

scholarly journals Mathematical Analysis of Epidemiological Model of Influenza a (H1N1) Virus Transmission Dynamics in Perspective of Bangladesh

2018 ◽  
Vol 37 ◽  
pp. 39-50 ◽  
Author(s):  
Rafiqul Islam ◽  
Md Haider Ali Biswas ◽  
ARM Jalal Uddin Jamali
Keyword(s):  
Influenza A ◽  
H1n1 Virus ◽  
Herd Immunity ◽  
Virus Transmission ◽  
Transmission Dynamics ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Numerical Result ◽  
Influenza A H1n1 ◽  
Novel Influenza A

This study deals with transmission dynamics of novel influenza A (H1N1) virus to understand the evolution of its epidemic in Bangladesh. For this purpose an SEIR model has been employed to study the dynamics of A (H1N1) virus relating to data of Bangladesh. To find threshold conditions, the equilibria and stability of the equilibria of the model have been determined and also analyzed. Basic Reproductive Number (R0) is determined relating to data of Bangladesh by which Herd Immunity Threshold has been estimated. Our numerical result suggests that vaccinating 12.69% population of Bangladesh can control spread of the pandemic novel A (H1N1) virus when outbreak occurs.GANIT J. Bangladesh Math. Soc.Vol. 37 (2017) 39-50

scholarly journals Antigenic waves of virus-immune co-evolution

2021 ◽  
Author(s):  
Jacopo Marchi ◽  
Michael Lässig ◽  
Aleksandra M. Walczak ◽  
Thierry Mora
Keyword(s):  
Mathematical Theory ◽  
Seasonal Influenza ◽  
Evolutionary Dynamics ◽  
Cross Reactivity ◽  
Host Population ◽  
Viral Population ◽  
Immune Systems ◽  
Persistence Time ◽  
Immune Pressure ◽  
Finite Dimensional

The evolution of many microbes and pathogens, including circulating viruses such as seasonal influenza, is driven by immune pressure from the host population. In turn, the immune systems of infected populations get updated, chasing viruses even further away. Quantitatively understanding how these dynamics result in observed patterns of rapid pathogen and immune adaptation is instrumental to epidemiological and evolutionary forecasting. Here we present a mathematical theory of co-evolution between immune systems and viruses in a finite-dimensional antigenic space, which describes the cross-reactivity of viral strains and immune systems primed by previous infections. We show the emergence of an antigenic wave that is pushed forward and canalized by cross-reactivity. We obtain analytical results for shape, speed, and angular diffusion of the wave. In particular, we show that viral-immune co-evolution generates a new emergent timescale, the persistence time of the wave’s direction in antigenic space, which can be much longer than the coalescence time of the viral population. We compare these dynamics to the observed antigenic turnover of influenza strains, and we discuss how the dimensionality of antigenic space impacts on the predictability of the evolutionary dynamics. Our results provide a rigorous and tractable framework to describe pathogen-host co-evolution.

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