Minimal Transmission in an Influenza A (H3N2) Human Challenge-Transmission Model with Exposure Events in a Controlled Environment

2019 ◽  
Author(s):  
Jonathan S. Nguyen-Van-Tam ◽  
Ben Killingley ◽  
Joanne Enstone ◽  
Michael Hewitt ◽  
Jovan Pantelic ◽  
...  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Juping Zhang ◽  
Wenjun Jing ◽  
Wenyi Zhang ◽  
Zhen Jin

In order to analyze the spread of avian influenza A (H7N9), we construct an avian influenza transmission model from poultry (including poultry farm, backyard poultry farm, live-poultry wholesale market, and wet market) to human according to poultry transport network. We obtain the threshold value for the prevalence of avian influenza A (H7N9) and also give the existence and number of the boundary equilibria and endemic equilibria in different conditions. We can see that poultry transport network plays an important role in controlling avian influenza A (H7N9). Finally, numerical simulations are presented to illustrate the effects of poultry in different places on avian influenza. In order to reduce human infections in China, our results suggest that closing the retail live-poultry market or preventing the poultry of backyard poultry farm into the live-poultry market is feasible in a suitable condition.


2019 ◽  
Author(s):  
Jonathan S. Nguyen-Van-Tam ◽  
Ben Killingley ◽  
Joanne Enstone ◽  
Michael Hewitt ◽  
Jovan Pantelic ◽  
...  

AbstractUncertainty about the importance of influenza transmission by airborne droplet nuclei generates controversy for infection control. Human challenge-transmission studies have been supported as the most promising approach to fill this knowledge gap. Healthy, seronegative volunteer ‘Donors’ (n=52) were randomly selected for intranasal challenge with influenza A/Wisconsin/67/2005 (H3N2). ‘Recipients’ randomized to Intervention (IR, n=40) or Control (CR, n=35) groups were exposed to Donors for four days. IRs wore face shields and hand sanitized frequently to limit large droplet and contact transmission. One transmitted infection was confirmed by serology in a CR, yielding a secondary attack rate of 2.9% among CR, 0% in IR (p=0.47 for group difference), and 1.3% overall, significantly less than 16% (p<0.001) expected based on a proof-of-concept study secondary attack rate and considering that there were twice as many Donors and days of exposure. The main difference between these studies was mechanical building ventilation in the follow-on study, suggesting a possible role for aerosols.Author summaryUnderstanding the relative importance of influenza modes of transmission informs strategic use of preventive measures to reduce influenza risk in high-risk settings such as hospitals and is important for pandemic preparedness. Given the increasing evidence from epidemiological modelling, exhaled viral aerosol, and aerobiological survival studies supporting a role for airborne transmission and the potential benefit of respirators (and other precautions designed to prevent inhalation of aerosols) versus surgical masks (mainly effective for reducing exposure to large droplets) to protect healthcare workers, more studies are needed to evaluate the extent of risk posed airborne versus contact and large droplet spray transmission modes. New human challenge-transmission studies should be carefully designed to overcome limitations encountered in the current study. The low secondary attack rate reported herein also suggests that the current challenge-transmission model may no longer be a more promising approach to resolving questions about transmission modes than community-based studies employing environmental monitoring and newer, state-of-the-art deep sequencing-based molecular epidemiological methods.


2016 ◽  
Vol 145 (4) ◽  
pp. 723-727 ◽  
Author(s):  
R. WARDELL ◽  
K. PREM ◽  
B. J. COWLING ◽  
A. R. COOK

SUMMARYComputer models can be useful in planning interventions against novel strains of influenza. However such models sometimes make unsubstantiated assumptions about the relative infectivity of asymptomatic and symptomatic cases, or conversely assume there is no impact at all. Using household-level data from known-index studies of virologically confirmed influenza A infection, the relationship between an individual's infectiousness and their symptoms was quantified using a discrete-generation transmission model and Bayesian Markov chain Monte Carlo methods. It was found that the presence of particular respiratory symptoms in an index case does not influence transmission probabilities, with the exception of child-to-child transmission where the donor has phlegm or a phlegmy cough.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Juping Zhang ◽  
Yun Li ◽  
Zhen Jin ◽  
Huaiping Zhu

H7N9 virus in the environment plays a role in the dynamics of avian influenza A (H7N9). A nationwide poultry vaccination with H7N9 vaccine program was implemented in China in October of 2017. To analyze the effect of vaccination and environmental virus on the development of avian influenza A (H7N9), we establish an avian influenza A (H7N9) transmission model with vaccination and seasonality among human, birds, and poultry. The basic reproduction number for the prevalence of avian influenza is obtained. The global stability of the disease-free equilibrium and the existence of positive periodic solution are proved by the comparison theorem and the asymptotic autonomous system theorem. Finally, we use numerical simulations to demonstrate the theoretical results. Simulation results indicate that the risk of H7N9 infection is higher in colder environment. Vaccinating poultry can significantly reduce human infection.


2020 ◽  
Vol 16 (7) ◽  
pp. e1008704 ◽  
Author(s):  
Jonathan S. Nguyen-Van-Tam ◽  
Ben Killingley ◽  
Joanne Enstone ◽  
Michael Hewitt ◽  
Jovan Pantelic ◽  
...  

10.36469/9801 ◽  
2017 ◽  
Vol 5 (1) ◽  
pp. 89-108 ◽  
Author(s):  
Laetitia Gerlier ◽  
Judith Hackett ◽  
Richard Lawson ◽  
Sofia Dos Santos Mendes ◽  
Catherine Weil-Olivier ◽  
...  

Objectives: To estimate the public health impact of annual vaccination of children with a quadrivalent live-attenuated influenza vaccine (QLAIV) across Europe. Methods: A deterministic, age-structured, dynamic model was used to simulate influenza transmission across 14 European countries, comparing current vaccination coverage using a quadrivalent inactivated vaccine (QIV) to a scenario whereby vaccination coverage was extended to 50% of 2–17 year-old children, using QLAIV. Differential equations described demographic changes, exposure to infectious individuals, recovery and immunity dynamics. For each country, the basic reproduction number (R0) was calibrated to published influenza incidence statistics. Assumed vaccine efficacy for children was 80% (QLAIV) and 59% (QIV). Symptomatic cases cumulated over 10 years were calculated per 100 000 person-years. One-way sensitivity analyses were conducted on QLAIV efficacy in 7–17 year-olds (59% instead of 80%), durations of natural (±3 years; base case: 6, 12 years for influenza A, B respectively) and QLAIV vaccine-induced immunity (100% immunity loss after 1 season; base case: 30%), and R0 (+/-10% around all-year average value). Results: Across countries, annual QLAIV vaccination additionally prevents 1366–3604 symptomatic cases per 100 000 population (average 2495 /100 000, ie, a reduction of 47.6% of the cases which occur in the reference scenario with QIV vaccination only). Among children (2–17 years), QLAIV prevents 551–1555 cases per 100 000 population (average 990 /100 000, ie, 67.2% of current cases). Among adults, QLAIV indirectly prevents 726-2047 cases per 100 000 population (average 1466 /100 000, ie, 40.0% of current cases). The most impactful drivers of total protection were duration of natural immunity against influenza A, R0 and QLAIV immunity duration and efficacy. In all evaluated scenarios, there was a large direct and even larger indirect protection compared with the reference scenario. Conclusions: The model highlights direct and indirect protection benefits when vaccinating healthy children with QLAIV in Europe, across a range of demographic structures, contact patterns and vaccination coverage rates.


2019 ◽  
Vol 71 (5) ◽  
pp. 1195-1203 ◽  
Author(s):  
Tim K Tsang ◽  
Kyu Han Lee ◽  
Betsy Foxman ◽  
Angel Balmaseda ◽  
Lionel Gresh ◽  
...  

Abstract Background Previous studies suggest that the nose/throat microbiome may play an important role in shaping host immunity and modifying the risk of respiratory infection. Our aim is to quantify the association between the nose/throat microbiome and susceptibility to influenza virus infection. Methods In this household transmission study, index cases with confirmed influenza virus infection and their household contacts were followed for 9–12 days to identify secondary influenza infections. Respiratory swabs were collected at enrollment to identify and quantify bacterial species via high-performance sequencing. Data were analyzed by an individual hazard-based transmission model that was adjusted for age, vaccination, and household size. Results We recruited 115 index cases with influenza A(H3N2) or B infection and 436 household contacts. We estimated that a 10-fold increase in the abundance in Streptococcus spp. and Prevotella salivae was associated with 48% (95% credible interval [CrI], 9–69%) and 25% (95% CrI, 0.5–42%) lower susceptibility to influenza A(H3N2) infection, respectively. In contrast, for influenza B infection, a 10-fold increase in the abundance in Streptococcus vestibularis and Prevotella spp. was associated with 63% (95% CrI, 17–83%) lower and 83% (95% CrI, 15–210%) higher susceptibility, respectively. Conclusions Susceptibility to influenza infection is associated with the nose/throat microbiome at the time of exposure. The effects of oligotypes on susceptibility differ between influenza A(H3N2) and B viruses. Our results suggest that microbiome may be a useful predictor of susceptibility, with the implication that microbiome could be modulated to reduce influenza infection risk, should these associations be causal.


2017 ◽  
Author(s):  
Xiangjun Du ◽  
Aaron A. King ◽  
Robert J. Woods ◽  
Mercedes Pascual

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.


2013 ◽  
Vol 280 (1770) ◽  
pp. 20131174 ◽  
Author(s):  
Daihai He ◽  
Jonathan Dushoff ◽  
Raluca Eftimie ◽  
David J. D. Earn

Understanding spatial patterns of influenza transmission is important for designing control measures. We investigate spatial patterns of laboratory-confirmed influenza A across Canada from October 1999 to August 2012. A statistical analysis (generalized linear model) of the seasonal epidemics in this time period establishes a clear spatio-temporal pattern, with influenza emerging earlier in western provinces. Early emergence is also correlated with low temperature and low absolute humidity in the autumn. For the richer data from the 2009 pandemic, a mechanistic mathematical analysis, based on a transmission model, shows that both school terms and weather had important effects on pandemic influenza transmission.


2020 ◽  
Author(s):  
Guanghu Zhu ◽  
Min Kang ◽  
Xueli Wei ◽  
Tian Tang ◽  
Tao Liu ◽  
...  

AbstractBackgroundDifferent interventions targeting live poultry markets (LPMs) have been applied in China for controlling the avian influenza A (H7N9), including LPM closure and “1110” policy (i.e., daily cleaning, weekly disinfection, monthly rest day, zero poultry stock overnight). However, the effects of these interventions have not been comprehensively assessed.MethodsBased on the available data (including reported cases, domestic poultry volume, and climate) collected in Guangdong Province between October 2013 and June 2017, we developed a new compartmental model that enabled us to infer H7N9 transmission dynamics. The proposed model incorporated the intrinsic interplay among humans and poultry as well as the effects of absolute humidity and LPM intervention, in which different intervention strategies were parameterized and estimated by Markov chain Monte Carlo (MCMC) method.ResultsThere were 258 confirmed human H7N9 cases in Guangdong Province during the study period. If without interventions, the number would reach 646 (95%CI, 575-718) cases. The temporal, seasonal and permanent closures of LPMs can substantially reduce transmission risk, which might respectively reduce human infections by 67.2% (95%CI, 64.3%-70.1%), 75.6% (95%CI, 73.8%-77.5%), 86.6% (95%CI, 85.7-87.6%) in total four epidemic seasons, and 81.9% CI(95%, 78.7%-85.2%), 91.5% (95%CI, 89.9%-93.1%), 99.0% (95%CI, 98.7%-99.3%) in the last two epidemic seasons. Moreover, implementing the “1110” policy from 2014 to 2017 would reduce the cases by 34.1% (95%CI, 20.1%-48.0%), suggesting its limited role in preventing H7N9 transmission.ConclusionsOur study quantified the effects of different interventions and execution time toward LPMs for controlling H7N9 transmission. The results highlighted the importance of closing LPMs during epidemic period, and supported permanent closure as a long-term plan.Author summaryFive waves of human influenza A (H7N9) epidemics affected China during 2013 and 2017. Its continuous emergence poses a big threat to public health. Given the key role of live poultry markets (LPMs) in H7N9 transmission, different interventions in LPMs (including the “1110’’ policy and LPM closure) were widely employed to prevent human infection with H7N9. Providing scientific evidence of their long-term effects is very important for the disease control, which can help to maximize control benefits and to minimize economic loss. To achieve this, we established a new transmission model and parameterized the intervention strategies. By using the proposed model to investigate the recent H7N9 outbreak in Guangdong Province, we quantified the effects of temporal, seasonal and permanent PLM closures, and the “1110’’ policy, as well as different intervention timing on the emergence of human H7N9 infections. The results can offer useful information for local authorities to take proper management in LPMs, and help in preparing optimal control strategies.


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