Transmission potential of influenza A/H7N9, February to May 2013, China

Effect of avian influenza scare on transmission of zoonotic avian influenza: A case study of influenza A (H7N9)

Avian influenza scare is a human psychological factor that asserts both positive and negative effects on the transmission of zoonotic avian influenza. In order to study the dichotomous effect of avian influenza scare on disease transmission, taking H7N9 avian influenza as a typical case, a two-patch epidemic model is proposed. The global dynamics and the threshold criteria are established by LaSalle invariant principle and the theory of asymptotic autonomous system. To mitigate the negative effects and curb illegal poultry trade, a game-theoretic model is adopted to explore the optimal policy of culling subsidies to reasonably compensate stakeholders for their economic losses resulting from the scare. The optimal policy of culling subsidy is found to heavily depend on the penalty of illegal poultry trade, the stakeholders' income, the intensity of control measures, and the prevalence level of the disease. The negative effect of avian influenza scare on disease transmission is considerably more significant than the positive effect. In order to avoid a widespread outbreak of zoonotic avian influenza across the region, a comprehensive national global control strategy is essential and effective, even in the presence of the negative effect of the avian influenza scare.

Policies to prevent zoonotic spillover: a systematic scoping review of evaluative evidence

BACKGROUND

Emerging infectious diseases of zoonotic origin present a critical threat to global population health. As accelerating globalisation makes epidemics and pandemics more difficult to contain, there is a need for effective preventive interventions that reduce the risk of zoonotic spillover events. Public policies can play a key role in preventing spillover events. The aim of this review is to identify and describe evaluations of public policies that target the determinants of zoonotic spillover. Our approach is informed by a One Health perspective, acknowledging the inter-connectedness of human, animal and environmental health.

METHODS

In this systematic scoping review, we searched Medline, SCOPUS, Web of Science and Global Health in May 2021 using search terms combining animal health and the animal-human interface, public policy, prevention and zoonoses. We screened titles and abstracts, extracted data and reported our process in line with PRISMA-ScR guidelines. We also searched relevant organisations' websites for evaluations published in the grey literature. All evaluations of public policies aiming to prevent zoonotic spillover events were eligible for inclusion. We summarised key data from each study, mapping policies along the spillover pathway.

RESULTS

Our review found 95 publications evaluating 111 policies. We identified 27 unique policy options including habitat protection; trade regulations; border control and quarantine procedures; farm and market biosecurity measures; public information campaigns; and vaccination programmes, as well as multi-component programmes. These were implemented by many sectors, highlighting the cross-sectoral nature of zoonotic spillover prevention. Reports emphasised the importance of surveillance data in both guiding prevention efforts and enabling policy evaluation, as well as the importance of industry and private sector actors in implementing many of these policies. Thoughtful engagement with stakeholders ranging from subsistence hunters and farmers to industrial animal agriculture operations is key for policy success in this area.

CONCLUSION

This review outlines the state of the evaluative evidence around policies to prevent zoonotic spillover in order to guide policy decision-making and focus research efforts. Since we found that most of the existing policy evaluations target 'downstream' determinants, additional research could focus on evaluating policies targeting 'upstream' determinants of zoonotic spillover, such as land use change, and policies impacting infection intensity and pathogen shedding in animal populations, such as those targeting animal welfare.

Regional Distribution of Non-human H7N9 Avian Influenza Virus Detections in China and Construction of a Predictive Model

Introduction

H7N9 avian influenza has broken out in Chinese poultry 10 times since 2013 and impacted the industry severely. Although the epidemic is currently under control, there is still a latent threat.

Material and Methods

Epidemiological surveillance data for non-human H7N9 avian influenza from April 2013 to April 2020 were used to analyse the regional distribution and spatial correlations of positivity rates in different months and years and before and after comprehensive immunisation. In addition, positivity rate monitoring data were disaggregated into a low-frequency and a high-frequency trend sequence by wavelet packet decomposition (WPD). The particle swarm optimisation algorithm was adopted to optimise the least squares support-vector machine (LS-SVM) model parameters to predict the low-frequency trend sequence, and the autoregressive integrated moving average (ARIMA) model was used to predict the high-frequency one. Ultimately, an LS-SVM-ARIMA combined model based on WPD was constructed.

Results

The virus positivity rate was the highest in late spring and early summer, and overall it fell significantly after comprehensive immunisation. Except for the year 2015 and the single month of December from 2013 to 2020, there was no significant spatiotemporal clustering in cumulative non-human H7N9 avian influenza virus detections. Compared with the ARIMA and LS-SVM models, the LS-SVM-ARIMA combined model based on WPD had the highest prediction accuracy. The mean absolute and root mean square errors were 2.4% and 2.0%, respectively.

Conclusion

Low error measures prove the validity of this new prediction method and the combined model could be used for inference of future H7N9 avian influenza virus cases. Live poultry markets should be closed in late spring and early summer, and comprehensive H7N9 immunisation continued.

A simple mathematical tool to forecast COVID-19 cumulative case numbers

Objective

Mathematical models are known to help determine potential intervention strategies by providing an approximate idea of the transmission dynamics of infectious diseases. To develop proper responses, not only are more accurate disease spread models needed, but also those that are easy to use.

Materials and methods

As of July 1, 2020, we selected the 20 countries with the highest numbers of COVID-19 cases in the world. Using the Verhulst–Pearl logistic function formula, we calculated estimates for the total number of cases for each country. We compared these estimates to the actual figures given by the WHO on the same dates. Finally, the formula was tested for longer-term reliability at t = 18 and t = 40 weeks.

Results

The Verhulst–Pearl logistic function formula estimated the actual numbers precisely, with only a 0.5% discrepancy on average for the first month. For all countries in the study and the world at large, the estimates for the 40th week were usually overestimated, although the estimates for some countries were still relatively close to the actual numbers in the forecasting long term. The estimated number for the world in general was about 8 times that actually observed for the long term.

Conclusions

The Verhulst–Pearl equation has the advantage of being very straightforward and applicable in clinical use for predicting the demand on hospitals in the short term of 4–6 weeks, which is usually enough time to reschedule elective procedures and free beds for new waves of the pandemic patients.

Beyond clinical trials: Evolutionary and epidemiological considerations for development of a universal influenza vaccine

The prospect of universal influenza vaccines is generating much interest and research at the intersection of immunology, epidemiology, and viral evolution. While the current focus is on developing a vaccine that elicits a broadly cross-reactive immune response in clinical trials, there are important downstream questions about global deployment of a universal influenza vaccine that should be explored to minimize unintended consequences and maximize benefits. Here, we review and synthesize the questions most relevant to predicting the population benefits of universal influenza vaccines and discuss how existing information could be mined to begin to address these questions. We review three research topics where computational modeling could bring valuable evidence: immune imprinting, viral evolution, and transmission. We address the positive and negative consequences of imprinting, in which early childhood exposure to influenza shapes and limits immune responses to future infections via memory of conserved influenza antigens. However, the mechanisms at play, their effectiveness, breadth of protection, and the ability to "reprogram" already imprinted individuals, remains heavily debated. We describe instances of rapid influenza evolution that illustrate the plasticity of the influenza virus in the face of drug pressure and discuss how novel vaccines could introduce new selective pressures on the evolution of the virus. We examine the possible unintended consequences of broadly protective (but infection-permissive) vaccines on the dynamics of epidemic and pandemic influenza, compared to conventional vaccines that have been shown to provide herd immunity benefits. In conclusion, computational modeling offers a valuable tool to anticipate the benefits of ambitious universal influenza vaccine programs, while balancing the risks from endemic influenza strains and unpredictable pandemic viruses. Moving forward, it will be important to mine the vast amount of data generated in clinical studies of universal influenza vaccines to ensure that the benefits and consequences of these vaccine programs have been carefully modeled and explored.

Comparison of methods to Estimate Basic Reproduction Number (R 0) of influenza, Using Canada 2009 and 2017-18 A (H1N1) Data

Background

The basic reproduction number (R ₀) has a key role in epidemics and can be utilized for preventing epidemics. In this study, different methods are used for estimating R ₀'s and their vaccination coverage to find the formula with the best performance.

Materials and Methods

We estimated R ₀ for cumulative cases count data from April 18 to July 6, 2009 and 35-2017 to 34-2018 weeks in Canada: maximum likelihood (ML), exponential growth rate (EG), time-dependent reproduction numbers (TD), attack rate (AR), gamma-distributed generation time (GT), and the final size of the epidemic. Gamma distribution with mean and standard deviation 3.6 ± 1.4 is used as GT.

Results

The AR method obtained a R _{0 (}95% confidence interval [CI]) value of 1.116 (1.1163, 1.1165) and an EG (95%CI) value of 1.46 (1.41, 1.52). The R ₀ (95%CI) estimate was 1.42 (1.27, 1.57) for the obtained ML, 1.71 (1.12, 2.03) for the obtained TD, 1.49 (1.0, 1.97) for the gamma-distributed GT, and 1.00 (0.91, 1.09) for the final size of the epidemic. The minimum and maximum vaccination coverage were related to AR and TD methods, respectively, where the TD method has minimum mean squared error (MSE). Finally, the R ₀ (95%CI) for 2018 data was 1.52 (1.11, 1.94) by TD method, and vaccination coverage was estimated as 34.2%.

Conclusion

For the purposes of our study, the estimation of TD was the most useful tool for computing the R ₀, because it has the minimum MSE. The estimation R ₀ > 1 indicating that the epidemic has occurred. Thus, it is required to vaccinate at least 41.5% to prevent and control the next epidemic.

Virus-induced pathogenesis, vaccine development, and diagnosis of novel H7N9 avian influenza A virus in humans: a systemic literature review

H7N9 avian influenza virus (AIV) caused human infections in 2013 in China. Phylogenetic analyses indicate that H7N9 AIV is a novel reassortant strain with pandemic potential. We conducted a systemic review regarding virus-induced pathogenesis, vaccine development, and diagnosis of H7N9 AIV infection in humans. We followed PRISMA guidelines and searched PubMed, Web of Science, and Google Scholar to identify relevant articles published between January 2013 and December 2018. Pathogenesis data indicated that H7N9 AIV belongs to low pathogenic avian influenza, which is mostly asymptomatic in avian species; however, H7N9 induces high mortality in humans. Sporadic human infections have recently been reported, caused by highly pathogenic avian influenza viruses detected in poultry. H7N9 AIVs resistant to adamantine and oseltamivir cause severe human infection by rapidly inducing progressive acute community-acquired pneumonia, multiorgan dysfunction, and cytokine dysregulation; however, mechanisms via which the virus induces severe syndromes remain unclear. An H7N9 AIV vaccine is lacking; designs under evaluation include synthesized peptide, baculovirus-insect system, and virus-like particle vaccines. Molecular diagnosis of H7N9 AIVs is suggested over conventional assays, for biosafety reasons. Several advanced or modified diagnostic assays are under investigation and development. We summarized virus-induced pathogenesis, vaccine development, and current diagnostic assays in H7N9 AIVs.

Live Poultry Trading Drives China's H7N9 Viral Evolution and Geographical Network Propagation

The on-going reassortment, human-adapted mutations, and spillover events of novel A(H7N9) avian influenza viruses pose a significant challenge to public health in China and globally. However, our understanding of the factors that disseminate the viruses and drive their geographic distributions is limited. We applied phylogenic analysis to examine the inter-subtype interactions between H7N9 viruses and the closest H9N2 lineages in China during 2010-2014. We reconstructed and compared the inter-provincial live poultry trading and viral propagation network via phylogeographic approach and network similarity technique. The substitution rates of the isolated viruses in live poultry markets and the characteristics of localized viral evolution were also evaluated. We discovered that viral propagation was geographically-structured and followed the live poultry trading network in China, with distinct north-to-east paths of spread and circular transmission between eastern and southern regions. The epicenter of H7N9 has moved from the Shanghai-Zhejiang region to Guangdong Province was also identified. Besides, higher substitution rate was observed among isolates sampled from live poultry markets, especially for those H7N9 viruses. Live poultry trading in China may have driven the network-structured expansion of the novel H7N9 viruses. From this perspective, long-distance geographic expansion of H7N9 were dominated by live poultry movements, while at local scales, diffusion was facilitated by live poultry markets with highly-evolved viruses.

Real-time modelling of a pandemic influenza outbreak

BACKGROUND

Real-time modelling is an essential component of the public health response to an outbreak of pandemic influenza in the UK. A model for epidemic reconstruction based on realistic epidemic surveillance data has been developed, but this model needs enhancing to provide spatially disaggregated epidemic estimates while ensuring that real-time implementation is feasible.

OBJECTIVES

To advance state-of-the-art real-time pandemic modelling by (1) developing an existing epidemic model to capture spatial variation in transmission, (2) devising efficient computational algorithms for the provision of timely statistical analysis and (3) incorporating the above into freely available software.

METHODS

Markov chain Monte Carlo (MCMC) sampling was used to derive Bayesian statistical inference using 2009 pandemic data from two candidate modelling approaches: (1) a parallel-region (PR) approach, splitting the pandemic into non-interacting epidemics occurring in spatially disjoint regions; and (2) a meta-region (MR) approach, treating the country as a single meta-population with long-range contact rates informed by census data on commuting. Model discrimination is performed through posterior mean deviance statistics alongside more practical considerations. In a real-time context, the use of sequential Monte Carlo (SMC) algorithms to carry out real-time analyses is investigated as an alternative to MCMC using simulated data designed to sternly test both algorithms. SMC-derived analyses are compared with 'gold-standard' MCMC-derived inferences in terms of estimation quality and computational burden.

RESULTS

The PR approach provides a better and more timely fit to the epidemic data. Estimates of pandemic quantities of interest are consistent across approaches and, in the PR approach, across regions (e.g. R₀ is consistently estimated to be 1.76-1.80, dropping by 43-50% during an over-summer school holiday). A SMC approach was developed, which required some tailoring to tackle a sudden 'shock' in the data resulting from a pandemic intervention. This semi-automated SMC algorithm outperforms MCMC, in terms of both precision of estimates and their timely provision. Software implementing all findings has been developed and installed within Public Health England (PHE), with key staff trained in its use.

LIMITATIONS

The PR model lacks the predictive power to forecast the spread of infection in the early stages of a pandemic, whereas the MR model may be limited by its dependence on commuting data to describe transmission routes. As demand for resources increases in a severe pandemic, data from general practices and on hospitalisations may become unreliable or biased. The SMC algorithm developed is semi-automated; therefore, some statistical literacy is required to achieve optimal performance.

CONCLUSIONS

Following the objectives, this study found that timely, spatially disaggregate, real-time pandemic inference is feasible, and a system that assumes data as per pandemic preparedness plans has been developed for rapid implementation.

FUTURE WORK RECOMMENDATIONS

Modelling studies investigating the impact of pandemic interventions (e.g. vaccination and school closure); the utility of alternative data sources (e.g. internet searches) to augment traditional surveillance; and the correct handling of test sensitivity and specificity in serological data, propagating this uncertainty into the real-time modelling.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN40334843.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology programme and will be published in full in Health Technology Assessment; Vol. 21, No. 58. See the NIHR Journals Library website for further project information. Daniela De Angelis was supported by the UK Medical Research Council (Unit Programme Number U105260566) and by PHE. She received funding under the NIHR grant for 10% of her time. The rest of her salary was provided by the MRC and PHE jointly.

The temporal distribution of new H7N9 avian influenza infections based on laboratory-confirmed cases in Mainland China, 2013-2017

In this study, estimates of the growth rate of new infections, based on the growth rate of new laboratory-confirmed cases, were used to provide a statistical basis for in-depth research into the epidemiological patterns of H7N9 epidemics. The incubation period, interval from onset to laboratory confirmation, and confirmation time for all laboratory-confirmed cases of H7N9 avian influenza in Mainland China, occurring between January 2013 and June 2017, were used as the statistical data. Stochastic processes theory and maximum likelihood were used to calculate the growth rate of new infections. Time-series analysis was then performed to assess correlations between the time series of new infections and new laboratory-confirmed cases. The rate of new infections showed significant seasonal fluctuation. Laboratory confirmation was delayed by a period of time longer than that of the infection (average delay, 13 days; standard deviation, 6.8 days). At the lags of −7.5 and −15 days, respectively, the time-series of new infections and new confirmed cases were significantly correlated; the cross correlation coefficients (CCFs) were 0.61 and 0.16, respectively. The temporal distribution characteristics of new infections and new laboratory-confirmed cases were similar and strongly correlated.

AVIAN INFLUENZA A H7N9 VIRUS HAS BEEN ESTABLISHED IN CHINA

In March 2013, a novel avian-origin influenza A H7N9 virus was identified among human patients in China and a total of 124 human cases with 24 related deaths were confirmed by May 2013. From November 2013 to July 2017, H7N9 broke out four more times in China. A deterministic model is proposed to study the transmission dynamics of the avian influenza A H7N9 virus between wild and domestic birds and from birds to humans, and is applied to simulate the open data on numbers of the infected human cases and related deaths reported from March to May 2013 and from November 2013 to June 2014 by the Chinese Center for Disease Control and Prevention. The basic reproduction number [Formula: see text] is estimated and sensitivity analysis of [Formula: see text] in terms of model parameters is performed. Taking into account the fact that it broke out again from November 2014 to June 2015, from November 2015 to July 2016, and from October 2016 to July 2017, we believe that H7N9 virus has been well established in birds and will likely cause regular outbreaks in humans again in the future. Control measures for the future spread of H7N9 include (i) reducing the transmission opportunities between wild birds and domestic birds, (ii) closing or monitoring the retail live-poultry markets in the infected areas, and (iii) culling the infected domestic birds in the epidemic regions.

Clusters of Human Infections With Avian Influenza A(H7N9) Virus in China, March 2013 to June 2015

Multiple clusters of human infections with novel avian influenza A(H7N9) virus have occurred since the virus was first identified in spring 2013. However, in many situations it is unclear whether these clusters result from person-to-person transmission or exposure to a common infectious source. We analyzed the possibility of person-to-person transmission in each cluster and developed a framework to assess the likelihood that person-to-person transmission had occurred. We described 21 clusters with 22 infected contact cases that were identified by the Chinese Center for Disease Control and Prevention from March 2013 through June 2015. Based on detailed epidemiological information and the timing of the contact case patients' exposures to infected persons and to poultry during their potential incubation period, we graded the likelihood of person-to-person transmission as probable, possible, or unlikely. We found that person-to-person transmission probably occurred 12 times and possibly occurred 4 times; it was unlikely in 6 clusters. Probable nosocomial transmission is likely to have occurred in 2 clusters. Limited person-to-person transmission is likely to have occurred on multiple occasions since the H7N9 virus was first identified. However, these transmission events represented a small fraction of all identified cases of H7N9 human infection, and sustained person-to-person transmission was not documented.

Are Poultry or Wild Birds the Main Reservoirs for Avian Influenza in Bangladesh?

Avian influenza viruses (AIV) are of great socioeconomic and health concern, notably in Southeast Asia where highly pathogenic strains, such as highly pathogenic avian influenza (HPAI) H5N1 and other H5 and H7 AIVs, continue to occur. Wild bird migrants are often implicated in the maintenance and spread of AIV. However, little systematic surveillance of wild birds has been conducted in Southeast Asia to evaluate whether the prevalence of AIV in wild birds is higher than in other parts of the world where HPAI outbreaks occur less frequently. Across Bangladesh, we randomly sampled a total of 3585 wild and domestic birds to assess the prevalence of AIV and antibodies against AIV and compared these with prevalence levels found in other endemic and non-endemic countries. Our study showed that both resident and migratory wild birds in Bangladesh do not have a particularly elevated AIV prevalence and AIV sero-prevalence compared to wild birds from regions in the world where H5N1 is not endemic and fewer AIV outbreaks in poultry occur. Like elsewhere, notably wild birds of the orders Anseriformes were identified as the main wild bird reservoir, although we found exceptionally high sero-prevalence in one representative of the order Passeriformes, the house crow (Corvus splendens), importantly living on offal from live bird markets. This finding, together with high sero- and viral prevalence levels of AIV in domestic birds, suggests that wild birds are not at the base of the perpetuation of AIV problems in the local poultry sector, but may easily become victim to AIV spill back from poultry into some species of wild birds, potentially assisting in further spread of the virus.

Epidemiological Risk Factors for Animal Influenza A Viruses Overcoming Species Barriers

Drivers and risk factors for Influenza A virus transmission across species barriers are poorly understood, despite the ever present threat to human and animal health potentially on a pandemic scale. Here we review the published evidence for epidemiological risk factors associated with influenza viruses transmitting between animal species and from animals to humans. A total of 39 papers were found with evidence of epidemiological risk factors for influenza virus transmission from animals to humans; 18 of which had some statistical measure associated with the transmission of a virus. Circumstantial or observational evidence of risk factors for transmission between animal species was found in 21 papers, including proximity to infected animals, ingestion of infected material and potential association with a species known to carry influenza virus. Only three publications were found which presented a statistical measure of an epidemiological risk factor for the transmission of influenza between animal species. This review has identified a significant gap in knowledge regarding epidemiological risk factors for the transmission of influenza viruses between animal species.

Inference and forecast of H7N9 influenza in China, 2013 to 2015

The recent emergence of A(H7N9) avian influenza poses a significant challenge to public health in China and around the world; however, understanding of the transmission dynamics and progression of influenza A(H7N9) infection in domestic poultry, as well as spillover transmission to humans, remains limited. Here, we develop a mathematical model–Bayesian inference system which combines a simple epidemic model and data assimilation method, and use it in conjunction with data on observed human influenza A(H7N9) cases from 19 February 2013 to 19 September 2015 to estimate key epidemiological parameters and to forecast infection in both poultry and humans. Our findings indicate a high outbreak attack rate of 33% among poultry but a low rate of chicken-to-human spillover transmission. In addition, we generated accurate forecasts of the peak timing and magnitude of human influenza A(H7N9) cases. This work demonstrates that transmission dynamics within an avian reservoir can be estimated and that real-time forecast of spillover avian influenza in humans is possible.

Interventions in live poultry markets for the control of avian influenza: a systematic review

Background

Live poultry markets (LPMs) pose a threat to public health by promoting the amplification and dissemination of avian influenza viruses (AIVs) and by providing the ideal setting for zoonotic influenza transmission.

Objective

This review assessed the impact of different interventions implemented in LPMs to control the emergence of zoonotic influenza.

Methods

Publications were identified through a systematic literature search in the PubMed, MEDLINE and Web of Science databases. Eligible studies assessed the impact of different interventions, such as temporary market closure or a ban on holding poultry overnight, in reducing i) AIV-detection rates in birds and the market environment or ii) influenza incidence in humans. Unpublished literature, reviews, editorials, cross-sectional studies, theoretical models and publications in languages other than English were excluded. Relevant findings were extracted and critically evaluated. For the comparative analysis of findings across studies, standardized outcome measures were computed as i) the relative risk reduction (RRR) of AIV-detection in LPMs and ii) incidence rate ratios (IRRs) of H7N9-incidence in humans.

Results

A total of 16 publications were identified and reviewed. Collectively, the data suggest that AIV-circulation can be significantly reduced in the LPM-environment and among market-birds through (i) temporary LPM closure, (ii) periodic rest days (iii) market depopulation overnight and (iv) improved hygiene and disinfection. Overall, the findings indicate that the length of stay of poultry in the market is a critical control point to interrupt the AIV-replication cycle within LPMs. In addition, temporary LPM closure was associated with a significant reduction of the incidence of zoonotic influenza. The interpretation of these findings is limited by variations in the implementation of interventions. In addition, some of the included studies were of ecologic nature or lacked an inferential framework, which might have lead to cosiderable confounding and bias.

Conclusions

The evidence collected in this review endorses permanent LPM-closure as a long-term objective to reduce the zoonotic risk of avian influenza, although its economic and socio-political implications favour less drastic interventions, e.g. weekly rest days, for implementation in the short-term.

•Avian influenza viruses (AIVs) can infect humans. Bird-to-human transmission is particularly intense in live poultry markets. •Periodic rest days, overnight depopulation or sale bans of certain species significantly reduce AIV-circulation in the markets. •Market closure would lastingly reduce the risk of animal and human infection.

Differences in the Epidemiology of Childhood Infections with Avian Influenza A H7N9 and H5N1 Viruses

The difference between childhood infections with avian influenza viruses A(H5N1) and A(H7N9) remains an unresolved but critically important question. We compared the epidemiological characteristics of 244 H5N1 and 41 H7N9 childhood cases (<15 years old), as well as the childhood cluster cases of the two viruses. Our findings revealed a higher proportion of H5N1 than H7N9 childhood infections (31.1% vs. 6.4%, p = 0.000). However, the two groups did not differ significantly in age (median age: 5.0 vs. 5.5 y, p = 0.0651). The proportion of clustered cases was significantly greater among children infected with H5N1 than among children infected with H7N9 [46.7% (71/152) vs. 23.6% (13/55), p = 0.005], and most of the childhood cases were identified as secondary cases [46.4% (45/97) vs. 33.3% (10/30), p = 0.000]. Mild status accounted for 79.49% and 22.66%, severe status for 17.95% and 2.34%, and fatal cases for 2.56% and 75.00% of the H7N9 and H5N1 childhood infection cases (all p<0.05), respectively. The fatality rates for the total, index and secondary childhood cluster cases were 52.86% (37/70), 88.5% (23/26) and 33.33% (15/45), respectively, in the H5N1 group, whereas no fatal H7N9 childhood cluster cases were identified. In conclusion, lower severity and greater transmission were found in the H7N9 childhood cases than in the H5N1 childhood cases.

Seasonality of Influenza A(H7N9) Virus in China-Fitting Simple Epidemic Models to Human Cases

Background

Three epidemic waves of influenza A(H7N9) (hereafter ‘H7N9’) human cases have occurred between March 2013 and July 2015 in China. However, the underlying transmission mechanism remains unclear. Our main objective is to use mathematical models to study how seasonality, secular changes and environmental transmission play a role in the spread of H7N9 in China.

Methods

Data on human cases and chicken cases of H7N9 infection were downloaded from the EMPRES-i Global Animal Disease Information System. We modelled on chicken-to-chicken transmission, assuming a constant ratio of 10⁻⁶ human case per chicken case, and compared the model fit with the observed human cases. We developed three different modified Susceptible-Exposed-Infectious-Recovered-Susceptible models: (i) a non-periodic transmission rate model with an environmental class, (ii) a non-periodic transmission rate model without an environmental class, and (iii) a periodic transmission rate model with an environmental class. We then estimated the key epidemiological parameters and compared the model fit using Akaike Information Criterion and Bayesian Information Criterion.

Results

Our results showed that a non-periodic transmission rate model with an environmental class provided the best model fit to the observed human cases in China during the study period. The estimated parameter values were within biologically plausible ranges.

Conclusions

This study highlighted the importance of considering secular changes and environmental transmission in the modelling of human H7N9 cases. Secular changes were most likely due to control measures such as Live Poultry Markets closures that were implemented during the initial phase of the outbreaks in China. Our results suggested that environmental transmission via viral shedding of infected chickens had contributed to the spread of H7N9 human cases in China.

Impact of Influenza on Outpatient Visits, Hospitalizations, and Deaths by Using a Time Series Poisson Generalized Additive Model

BACKGROUND

The disease burden associated with influenza in developing tropical and subtropical countries is poorly understood owing to the lack of a comprehensive disease surveillance system and information-exchange mechanisms. The impact of influenza on outpatient visits, hospital admissions, and deaths has not been fully demonstrated to date in south China.

METHODS

A time series Poisson generalized additive model was used to quantitatively assess influenza-like illness (ILI) and influenza disease burden by using influenza surveillance data in Zhuhai City from 2007 to 2009, combined with the outpatient, inpatient, and respiratory disease mortality data of the same period.

RESULTS

The influenza activity in Zhuhai City demonstrated a typical subtropical seasonal pattern; however, each influenza virus subtype showed a specific transmission variation. The weekly ILI case number and virus isolation rate had a very close positive correlation (r = 0.774, P < 0.0001). The impact of ILI and influenza on weekly outpatient visits was statistically significant (P < 0.05). We determined that 10.7% of outpatient visits were associated with ILI and 1.88% were associated with influenza. ILI also had a significant influence on the hospitalization rates (P < 0.05), but mainly in populations <25 years of age. No statistically significant effect of influenza on hospital admissions was found (P > 0.05). The impact of ILI on chronic obstructive pulmonary disease (COPD) was most significant (P < 0.05), with 33.1% of COPD-related deaths being attributable to ILI. The impact of influenza on the mortality rate requires further evaluation.

CONCLUSIONS

ILI is a feasible indicator of influenza activity. Both ILI and influenza have a large impact on outpatient visits. Although ILI affects the number of hospital admissions and deaths, we found no consistent influence of influenza, which requires further assessment.

Emergence and development of H7N9 influenza viruses in China

The occurrence of human infections with avian H7N9 viruses since 2013 demonstrates the continuing pandemic threat posed by the current influenza ecosystem in China. Influenza surveillance and phylogenetic analyses showed that these viruses were generated by multiple interspecies transmissions and reassortments among the viruses resident in domestic ducks and the H9N2 viruses enzootic in chickens. A large population of domestic ducks hosting diverse influenza viruses provided the precondition for these events to occur, while acquiring internal genes from enzootic H9N2 influenza viruses in chickens promoted the spread of these viruses. Human infections effectively act as sentinels, reflecting the intensity of the activity of these viruses in poultry.

Transmission Potential of Influenza A(H7N9) Virus, China, 2013-2014

To determine transmission potential of influenza A(H7N9) virus, we used symptom onset data to compare 2 waves of infection in China during 2013–2014. We found evidence of increased transmission potential in the second wave and showed that live bird market closure was significantly less effective in Guangdong than in other regions.

Interpreting the transmissibility of the avian influenza A(H7N9) infection from 2013 to 2015 in Zhejiang Province, China

Three epidemic waves of human influenza A(H7N9) were documented in several different provinces in China between 2013 and 2015. With limited understanding of the potential for human-to-human transmission, it was difficult to implement control measures efficiently or to inform the public adequately about the application of interventions. In this study, the human-to-human transmission rate for the epidemics that occurred between 2013 and 2015 in Zhejiang Province, China, was analysed. The reproduction number (R), a key indicator of transmission intensity, was estimated by fitting the number of infections from poultry to humans and from humans to humans into a mathematical model. The posterior mean R for human-to-human transmission was estimated to be 0·27, with a 95% credible interval of 0·14–0·44 for the first wave, whereas the posterior mean Rs decreased to 0·15 in the second and third waves. Overall, these estimates indicate that a human H7N9 pandemic is unlikely to occur in Zhejiang. The reductions in the viral transmissibility and the number of poultry-transmitted infections after the first epidemic may be attributable to the various intervention measures taken, including changes in the extent of closures of live poultry markets.

Health literacy in Beijing: an assessment of adults' knowledge and skills regarding communicable diseases

BACKGROUND

There have been a number of studies conducted to date looking at the issue of health literacy, but none have been conducted in Beijing, China. The aim of this study was to evaluate the communicable diseases health literacy (CDHL) levels of Beijing residents towards three key areas: knowledge, adoption of preventative measures/behaviours, and health skills.

METHODS

A structured survey was undertaken with Beijing residents aged ≥18 years. A multistage stratified sampling approach was used to identify and recruit residents. Participants were excluded if they were foreigners, residents of Hong Kong, Macau or Taiwan, or were unable to communicate in Mandarin.

RESULTS

The questionnaire was completed by 11052 participants, with a moderate accuracy rate (average: 61.3 %) and a good discrimination level (average: 0.428). Cronbach's alpha was 0.748. The items were grouped into three subscales representing knowledge, adoption of preventative measures and behaviours, and health skills. Correlations of the subscales and the Total Score is significant (P < 0.01), and all the three subscales correlate strongly with the Total Score The mean CDHL score of Beijing inhabitants was 15.28. The percentage of those who were identified as having adequate CDHL was 41 %.

CONCLUSIONS

The total CDHL level of residents in Beijing was relatively low, particularly in those residing in the suburbs, those above 60 years of age, manual workers, and the illiterates. Gender, age-group, level of education, occupation, self-reported health status and region were all shown to be significantly predictive of CDHL. It is important that more resources are dedicated to improving the CDHL in Beijing, given the risk of emerging and re-emerging infectious diseases in the region.

The pandemic potential of avian influenza A(H7N9) virus: a review

In March 2013 the first cases of human avian influenza A(H7N9) were reported to the World Health Organization. Since that time, over 650 cases have been reported. Infections are associated with considerable morbidity and mortality, particularly within certain demographic groups. This rapid increase in cases over a brief time period is alarming and has raised concerns about the pandemic potential of the H7N9 virus. Three major factors influence the pandemic potential of an influenza virus: (1) its ability to cause human disease, (2) the immunity of the population to the virus, and (3) the transmission potential of the virus. This paper reviews what is currently known about each of these factors with respect to avian influenza A(H7N9). Currently, sustained human-to-human transmission of H7N9 has not been reported; however, population immunity to the virus is considered very low, and the virus has significant ability to cause human disease. Several statistical and geographical modelling studies have estimated and predicted the spread of the H7N9 virus in humans and avian species, and some have identified potential risk factors associated with disease transmission. Additionally, assessment tools have been developed to evaluate the pandemic potential of H7N9 and other influenza viruses. These tools could also hypothetically be used to monitor changes in the pandemic potential of a particular virus over time.

Characterizing the transmission potential of zoonotic infections from minor outbreaks

The transmission potential of a novel infection depends on both the inherent transmissibility of a pathogen, and the level of susceptibility in the host population. However, distinguishing between these pathogen- and population-specific properties typically requires detailed serological studies, which are rarely available in the early stages of an outbreak. Using a simple transmission model that incorporates age-stratified social mixing patterns, we present a novel method for characterizing the transmission potential of subcritical infections, which have effective reproduction number R<1, from readily available data on the size of outbreaks. We show that the model can identify the extent to which outbreaks are driven by inherent pathogen transmissibility and pre-existing population immunity, and can generate unbiased estimates of the effective reproduction number. Applying the method to real-life infections, we obtained accurate estimates for the degree of age-specific immunity against monkeypox, influenza A(H5N1) and A(H7N9), and refined existing estimates of the reproduction number. Our results also suggest minimal pre-existing immunity to MERS-CoV in humans. The approach we describe can therefore provide crucial information about novel infections before serological surveys and other detailed analyses are available. The methods would also be applicable to data stratified by factors such as profession or location, which would make it possible to measure the transmission potential of emerging infections in a wide range of settings.

The transmission potential of a new infection depends on both the transmissibility of the pathogen and the level of immunity in the host population. However, it can be difficult to measure these properties if there are limited experimental studies of population immunity. By incorporating social contact patterns into a mathematical model of disease transmission, we show that it is possible to estimate both pathogen transmissibility and pre-existing immunity from available data on the size of outbreaks. When an infection does not transmit efficiently between humans, estimates often have to be made using case data from a limited number of small outbreaks. We find that, even with limited data, our technique can accurately evaluate the transmission potential of ‘stuttering’ chains of infection. We use the method to characterise transmission of four real infections: monkeypox, influenza A(H5N1) and A(H7N9) and MERS-CoV.

The impact of prior information on estimates of disease transmissibility using Bayesian tools

The basic reproductive number (R₀) and the distribution of the serial interval (SI) are often used to quantify transmission during an infectious disease outbreak. In this paper, we present estimates of R₀ and SI from the 2003 SARS outbreak in Hong Kong and Singapore, and the 2009 pandemic influenza A(H1N1) outbreak in South Africa using methods that expand upon an existing Bayesian framework. This expanded framework allows for the incorporation of additional information, such as contact tracing or household data, through prior distributions. The results for the R₀ and the SI from the influenza outbreak in South Africa were similar regardless of the prior information (R^0 = 1.36–1.46, μ^ = 2.0–2.7, μ^ = mean of the SI). The estimates of R₀ and μ for the SARS outbreak ranged from 2.0–4.4 and 7.4–11.3, respectively, and were shown to vary depending on the use of contact tracing data. The impact of the contact tracing data was likely due to the small number of SARS cases relative to the size of the contact tracing sample.

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

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.

An overview of the characteristics of the novel avian influenza A H7N9 virus in humans

The novel avian influenza A H7N9 virus which caused the first human infection in Shanghai, China; was reported on the 31st of March 2013 before spreading rapidly to other Chinese provinces and municipal cities. This is the first time the low pathogenic avian influenza A virus has caused human infections and deaths; with cases of severe respiratory disease with pneumonia being reported. There were 440 confirmed cases with 122 fatalities by 16 May 2014; with a fatality risk of ∼28%. The median age of patients was 61 years with a male-to-female ratio of 2.4:1. The main source of infection was identified as exposure to poultry and there is so far no definitive evidence of sustained person-to-person transmission. The neuraminidase inhibitors, namely oseltamivir, zanamivir, and peramivir; have shown good efficacy in the management of the novel H7N9 virus. Treatment is recommended for all hospitalized patients, and for confirmed and probable outpatient cases; and should ideally be initiated within 48 h of the onset of illness for the best outcome. Phylogenetic analysis found that the novel H7N9 virus is avian in origin and evolved from multiple reassortments of at least four origins. Indeed the novel H7N9 virus acquired human adaptation via mutations in its eight RNA gene segments. Enhanced surveillance and effective global control are essential to prevent pandemic outbreaks of the novel H7N9 virus.

Weather variability and influenza A (H7N9) transmission in Shanghai, China: a Bayesian spatial analysis

BACKGROUND

A novel avian influenza A (H7N9) virus was first found in humans in Shanghai, and infected over 433 patients in China. To date, very little is known about the spatiotemporal variability or environmental drivers of the risk of H7N9 infection. This study explored the spatial and temporal variation of H7N9 infection and assessed the effects of temperature and rainfall on H7N9 incidence.

METHODS

A Bayesian spatial conditional autoregressive (CAR) model was used to assess the spatiotemporal distribution of the risk of H7N9 infection in Shanghai, by district and fortnight for the period 19th February-14th April 2013. Data on daily laboratory-confirmed H7N9 cases, and weather variability including temperature (°C) and rainfall (mm) were obtained from the Chinese Information System for Diseases Control and Prevention and Chinese Meteorological Data Sharing Service System, respectively, and aggregated by fortnight.

RESULTS

High spatial variations in the H7N9 risk were mainly observed in the east and centre of Shanghai municipality. H7N9 incidence rate was significantly associated with fortnightly mean temperature (Relative Risk (RR): 1.54; 95% credible interval (CI): 1.22-1.94) and fortnightly mean rainfall (RR: 2.86; 95% CI: 1.47-5.56).

CONCLUSION

There was a substantial variation in the spatiotemporal distribution of H7N9 infection across different districts in Shanghai. Optimal temperature and rainfall may be one of the driving forces for H7N9.

Quantification of bird-to-bird and bird-to-human infections during 2013 novel H7N9 avian influenza outbreak in China

From February to May, 2013, 132 human avian influenza H7N9 cases were identified in China resulting in 37 deaths. We developed a novel, simple and effective compartmental modeling framework for transmissions among (wild and domestic) birds as well as from birds to human, to infer important epidemiological quantifiers, such as basic reproduction number for bird epidemic, bird-to-human infection rate and turning points of the epidemics, for the epidemic via human H7N9 case onset data and to acquire useful information regarding the bird-to-human transmission dynamics. Estimated basic reproduction number for infections among birds is 4.10 and the mean daily number of human infections per infected bird is 3.16*10-5 [3.08*10-5, 3.23*10-5]. The turning point of 2013 H7N9 epidemic is pinpointed at April 16 for bird infections and at April 9 for bird-to-human transmissions. Our result reveals very low level of bird-to-human infections, thus indicating minimal risk of widespread bird-to-human infections of H7N9 virus during the outbreak. Moreover, the turning point of the human epidemic, pinpointed at shortly after the implementation of full-scale control and intervention measures initiated in early April, further highlights the impact of timely actions on ending the outbreak. This is the first study where both the bird and human components of an avian influenza epidemic can be quantified using only the human case data.

Evaluation of outbreak detection performance using multi-stream syndromic surveillance for influenza-like illness in rural Hubei Province, China: a temporal simulation model based on healthcare-seeking behaviors

BACKGROUND

Syndromic surveillance promotes the early detection of diseases outbreaks. Although syndromic surveillance has increased in developing countries, performance on outbreak detection, particularly in cases of multi-stream surveillance, has scarcely been evaluated in rural areas.

OBJECTIVE

This study introduces a temporal simulation model based on healthcare-seeking behaviors to evaluate the performance of multi-stream syndromic surveillance for influenza-like illness.

METHODS

Data were obtained in six towns of rural Hubei Province, China, from April 2012 to June 2013. A Susceptible-Exposed-Infectious-Recovered model generated 27 scenarios of simulated influenza A (H1N1) outbreaks, which were converted into corresponding simulated syndromic datasets through the healthcare-behaviors model. We then superimposed converted syndromic datasets onto the baselines obtained to create the testing datasets. Outbreak performance of single-stream surveillance of clinic visit, frequency of over the counter drug purchases, school absenteeism, and multi-stream surveillance of their combinations were evaluated using receiver operating characteristic curves and activity monitoring operation curves.

RESULTS

In the six towns examined, clinic visit surveillance and school absenteeism surveillance exhibited superior performances of outbreak detection than over the counter drug purchase frequency surveillance; the performance of multi-stream surveillance was preferable to signal-stream surveillance, particularly at low specificity (Sp <90%).

CONCLUSIONS

The temporal simulation model based on healthcare-seeking behaviors offers an accessible method for evaluating the performance of multi-stream surveillance.

Emerging viral respiratory tract infections--environmental risk factors and transmission

The past decade has seen the emergence of several novel viruses that cause respiratory tract infections in human beings, including Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia, an H7N9 influenza A virus in eastern China, a swine-like influenza H3N2 variant virus in the USA, and a human adenovirus 14p1 also in the USA. MERS-CoV and H7N9 viruses are still a major worldwide public health concern. The pathogenesis and mode of transmission of MERS-CoV and H7N9 influenza A virus are poorly understood, making it more difficult to implement intervention and preventive measures. A united and coordinated global response is needed to tackle emerging viruses that can cause fatal respiratory tract infections and to fill major gaps in the understanding of the epidemiology and transmission dynamics of these viruses.

H7N9: preparing for the unexpected in influenza

In the years prior to 2013, avian influenza A H7 viruses were a cause of significant poultry mortality; however, human illness was generally mild. In March 2013, a novel influenza A(H7N9) virus emerged in China as an unexpected cause of severe human illness with 36% mortality. Chinese and other public health officials responded quickly, characterizing the virus and identifying more than 400 cases through use of new technologies and surveillance tools made possible by past preparedness and response efforts. Genetic sequencing, glycan-array receptor-binding assays, and ferret studies reveal the H7N9 virus to have increased binding to mammalian respiratory cells and to have mutations associated with higher virus replication rates and illness severity. New risk-assessment tools indicate H7N9 has the potential for further mammalian adaptation with possible human-to-human transmission. Vigilant virologic and epidemiologic surveillance is needed to monitor H7N9 and detect other unexpected novel influenza viruses that may emerge.

Synthesizing data and models for the spread of MERS-CoV, 2013: key role of index cases and hospital transmission

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Transmission models for the MERS-CoV outbreak during April–October 2013.

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MERS-CoV transmission models with index and secondary cases.

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MERS-CoV transmission models with community and hospital compartments.

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Calibration of MERS-CoV transmission models using MCMC methods.

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Data indicate a strong support for R  < 1 in the first stage of the outbreak in 2013.

The outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) has caused 209 deaths and 699 laboratory-confirmed cases in the Arabian Peninsula as of June 11, 2014. Preparedness efforts are hampered by considerable uncertainty about the nature and intensity of human-to-human transmission, with previous reproduction number estimates ranging from 0.4 to 1.5. Here we synthesize epidemiological data and transmission models for the MERS-CoV outbreak during April–October 2013 to resolve uncertainties in epidemic risk, while considering the impact of observation bias. We match the progression of MERS-CoV cases in 2013 to a dynamic transmission model that incorporates community and hospital compartments, and distinguishes transmission by zoonotic (index) cases and secondary cases. When observation bias is assumed to account for the fact that all reported zoonotic cases are severe, but only ∼57% of secondary cases are symptomatic, the average reproduction number of MERS-CoV is estimated to be 0.45 (95% CI:0.29–0.61). Alternatively, if these epidemiological observations are taken at face value, index cases are estimated to transmit substantially more effectively than secondary cases, (R_i = 0.84 (0.58-1.20) vs R_s = 0.36 (0.24–0.51)). In both scenarios the relative contribution of hospital-based transmission is over four times higher than that of community transmission, indicating that disease control should be focused on hospitalized patients.

Adjusting previously published estimates for observation bias confirms a strong support for the average R < 1 in the first stage of the outbreak in 2013 and thus, transmissibility of secondary cases of MERS-CoV remained well below the epidemic threshold. More information on the observation process is needed to clarify whether MERS-CoV is intrinsically weakly transmissible between people or whether existing control measures have contributed meaningfully to reducing the transmissibility of secondary cases. Our results could help evaluate the progression of MERS-CoV in recent months in response to changes in disease surveillance, control interventions, or viral adaptation.

Pandemic potential of avian influenza A (H7N9) viruses

Avian influenza viruses rarely infect humans, but the recently emerged avian H7N9 influenza viruses have caused sporadic infections in humans in China, resulting in 440 confirmed cases with 122 fatalities as of 16 May 2014. In addition, epidemiologic surveys suggest that there have been asymptomatic or mild human infections with H7N9 viruses. These viruses replicate efficiently in mammals, show limited transmissibility in ferrets and guinea pigs, and possess mammalian-adapting amino acid changes that likely contribute to their ability to infect mammals. In this review, we summarize the characteristic features of the novel H7N9 viruses and assess their pandemic potential.

Distinguishing Between Reservoir Exposure and Human-to-Human Transmission for Emerging Pathogens Using Case Onset Data

Pathogens such as MERS-CoV, influenza A/H5N1 and influenza A/H7N9 are currently generating sporadic clusters of spillover human cases from animal reservoirs. The lack of a clear human epidemic suggests that the basic reproductive number R0 is below or very close to one for all three infections. However, robust cluster-based estimates for low R0 values are still desirable so as to help prioritise scarce resources between different emerging infections and to detect significant changes between clusters and over time. We developed an inferential transmission model capable of distinguishing the signal of human-to-human transmission from the background noise of direct spillover transmission (e.g. from markets or farms). By simulation, we showed that our approach could obtain unbiased estimates of R0, even when the temporal trend in spillover exposure was not fully known, so long as the serial interval of the infection and the timing of a sudden drop in spillover exposure were known (e.g. day of market closure). Applying our method to data from the three largest outbreaks of influenza A/H7N9 outbreak in China in 2013, we found evidence that human-to-human transmission accounted for 13% (95% credible interval 1%–32%) of cases overall. We estimated R0 for the three clusters to be: 0.19 in Shanghai (0.01-0.49), 0.29 in Jiangsu (0.03-0.73); and 0.03 in Zhejiang (0.00-0.22). If a reliable temporal trend for the spillover hazard could be estimated, for example by implementing widespread routine sampling in sentinel markets, it should be possible to estimate sub-critical values of R0 even more accurately. Should a similar strain emerge with R0>1, these methods could give a real-time indication that sustained transmission is occurring with well-characterised uncertainty.