Reflections on pandemic (H1N1) 2009 and the international response

Development of an Enhanced High-Yield Influenza Vaccine Backbone in Embryonated Chicken Eggs

Vaccination is an efficient approach to preventing influenza virus infections. Recently, we developed influenza A and B virus vaccine backbones that increased the yield of several vaccine viruses in Madin-Darby canine kidney (MDCK) and African green monkey kidney (Vero) cells. These vaccine backbones also increased viral replication in embryonated chicken eggs, which are the most frequently used platform for influenza vaccine manufacturing. In this study, to further increase the viral titers in embryonated chicken eggs, we introduced random mutations into the 'internal genes' (i.e., all influenza viral genes except those encoding the hemagglutinin and neuraminidase proteins) of the influenza A virus high-yield virus backbone we developed previously. The randomly mutated viruses were sequentially passaged in embryonated chicken eggs to select variants with increased replicative ability. We identified a candidate that conferred higher influenza virus growth than the high-yield parental virus backbone. Although the observed increases in virus growth may be considered small, they are highly relevant for vaccine manufacturers.

Optimal timing of non-pharmaceutical interventions during an epidemic

In response to the recent outbreak of the SARS-CoV-2 virus governments have aimed to reduce the virus's spread through, inter alia, non-pharmaceutical intervention. We address the question when such measures should be implemented and, once implemented, when to remove them. These issues are viewed through a real-options lens and we develop an SIRD-like continuous-time Markov chain model to analyze a sequence of options: the option to intervene and introduce measures and, after intervention has started, the option to remove these. Measures can be imposed multiple times. We implement our model using estimates from empirical studies and, under fairly general assumptions, our main conclusions are that: (1) measures should be put in place not long after the first infections occur; (2) if the epidemic is discovered when there are many infected individuals already, then it is optimal never to introduce measures; (3) once the decision to introduce measures has been taken, these should stay in place until the number of susceptible or infected members of the population is close to zero; (4) it is never optimal to introduce a tier system to phase-in measures but it is optimal to use a tier system to phase-out measures; (5) a more infectious variant may reduce the duration of measures being in place; (6) the risk of infections being brought in by travelers should be curbed even when no other measures are in place. These results are robust to several variations of our base-case model.

The gendered dimensions of the anti-mask and anti-lockdown movement on social media

This paper examines the anti-mask and anti-lockdown online movement in connection to the COVID-19 pandemic. To combat the spread of the coronavirus, health officials around the world urged and/or mandated citizens to wear facemasks and adopt physical distancing measures. These health policies and guidelines have become highly politicized in some parts of the world, often discussed in association with freedom of choice and independence. We downloaded references to the anti-mask and anti-lockdown social media posts using 24 search terms. From a total of 4209 social media posts, the researchers manually filtered the explicit visual and textual content that is related to discussions of different genders. We used multimodal discourse analysis (MDM) which analyzes diverse modes of communicative texts and images and focuses on appeals to emotions and reasoning. Using the MDM approach, we analysed posts taken from Facebook and Instagram from active anti-mask and anti-lockdown users, and we identified three main discourses around the gendered discussion of the anti-mask movement including hypermasculine, sexist and pejorative portrayals of "Karen", and appropriating freedom and feminism discourses. A better understanding of how social media users evoke gendered discourses to spread anti-mask and anti-lockdown messages can help researchers identify differing reactions toward pandemic measures.

Characteristics of the 100 largest modern zoonotic disease outbreaks

Zoonotic disease outbreaks are an important threat to human health and numerous drivers have been recognized as contributing to their increasing frequency. Identifying and quantifying relationships between drivers of zoonotic disease outbreaks and outbreak severity is critical to developing targeted zoonotic disease surveillance and outbreak prevention strategies. However, quantitative studies of outbreak drivers on a global scale are lacking. Attributes of countries such as press freedom, surveillance capabilities and latitude also bias global outbreak data. To illustrate these issues, we review the characteristics of the 100 largest outbreaks in a global dataset (n = 4463 bacterial and viral zoonotic outbreaks), and compare them with 200 randomly chosen background controls. Large outbreaks tended to have more drivers than background outbreaks and were related to large-scale environmental and demographic factors such as changes in vector abundance, human population density, unusual weather conditions and water contamination. Pathogens of large outbreaks were more likely to be viral and vector-borne than background outbreaks. Overall, our case study shows that the characteristics of large zoonotic outbreaks with thousands to millions of cases differ consistently from those of more typical outbreaks. We also discuss the limitations of our work, hoping to pave the way for more comprehensive future studies. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Bad law or implementation flaws? Lessons from the implementation of the new law on epidemics during the response to the first wave of COVID-19 in Switzerland

After the 2009-2010 H1N1 pandemic, Switzerland overhauled its 1970 law on epidemics. The reform aimed at improving early detection, surveillance, and preparedness for future outbreaks of infectious diseases. Notably, the law introduced stronger coordination between Federal and Cantonal authorities, better management tools and international cooperation. The new law entered into force in 2016 after a long legislative process. During the process, the law survived a referendum fuelled by concerns about vaccine safety and pharmaceutical industry interference. The law was first applied during the COVID-19 pandemic in early 2020. The epicentre of the outbreak in Europe was in Lombardy, a large Italian region adjacent to Switzerland and with strong economic ties with its southern region of Ticino. The first months of pandemic response highlighted two major weaknesses. Firstly, the mechanisms introduced by the new law did not ease the tension between Cantonal autonomy and central coordination of the pandemic response. Central and Cantonal authorities will need to put in place new rules and arrangements to avoid dangerous delayed responses to foreseeable problems related to the spread of infectious diseases. Secondly, relevant stakeholders excluded from the policymaking process (trade unions, firms, large industries) should be involved to allow the introduction of harsh restrictions when needed, both internally and in relation to cross-border workers.

The impact of crisis and disasters risk management in COVID-19 times: Insights and lessons learned from Saudi Arabia

Background

All countries all over the world strive to fight the outbreak of COVID-19 pandemic and their governments are facing unprecedented strains and challenges. Since COVID-19 has engendered socioeconomic recession and the deterioration of health systems, Insights and lessons from some countries can illustrate various approaches designing their people-centric health and socioeconomic policies. The kingdom of Saudi Arabia has implemented various measures and strategies to mitigate the spread of pandemic and to save the lives of people. Therefore, we investigate the role of the Saudi disaster risk reduction system (DRRS) to fight the virus outbreak and provide a safe environment for the well-being of its inhabitants.

Methodology

We use a qualitative case study methodology to document and analyze the crisis and disasters risk management framework within the hazard management process. The case study methodology is suitable in investigating a phenomenon in its real-life settings and contexts. Thus, we outline lessons learned from Saudi disaster risk management experience in combating COVID-19 pandemic.

Results

During COVID-19 disaster, we found that the Saudi disaster risk reduction system (DRRS) is structured into three main levels: strategic, operational and tactical. The strategic level represents the strategic planning division and runs audit and monitoring of overall decentralized units of crisis management at operational and tactical levels. The findings show that there are three policy implications: keep vigilance at the public national level, remaining flexible in a national management structure and good governance at local administration level.

Conclusion

The application of disaster risk reduction framework in COVID-19 times requires the use of multi-level strategies to protect vulnerable peoples during the four stages of mitigation (readiness), preparedness, response (implementation) and recovery (post-COVID).

Investigating Public Discourses Around Gender and COVID-19: a Social Media Analysis of Twitter Data

We collected over 50 million tweets referencing COVID-19 to understand the public’s gendered discourses and concerns during the pandemic. We filtered the tweets based on English language and among three gender categories: men, women, and sexual and gender minorities. We used a mixed-method approach that included topic modelling, sentiment analysis, and text mining extraction procedures including words’ mapping, proximity plots, top hashtags and mentions, and most retweeted posts. Our findings show stark differences among the different genders. In relation to women, we found a salient discussion on the risks of domestic violence due to the lockdown especially towards women and girls, while emphasizing financial challenges. The public discourses around SGM mostly revolved around blood donation concerns, which is a reminder of the discrimination against some of these communities during the early days of the HIV/AIDS epidemic. Finally, the discourses around men were focused on the high death rates and the sentiment analysis results showed more negative tweets than among the other genders. The study concludes that Twitter influencers can drive major online discussions which can be useful in addressing communication needs during pandemics.

Flashback and lessons learnt from history of pandemics before COVID-19

With an increasing frequency of infectious disease outbreaks, the COVID-19 pandemic causing mortality around the world and the threat of similar future events looming large, mankind is faced with the herculean task of counteracting such threats with the best possible strategies and public health decisions. It is key that such decisions should be guided by previous examples of similar health emergencies. Here we review some of the significant infectious disease outbreaks, including epidemics and pandemics occurring worldwide in the past including their impact at population and global levels, unique challenges presented by each and the measures taken by authorities worldwide as well as the crucial lessons each epidemic or pandemic provided. This review highlights that throughout history measures such as contact tracing, quarantine and isolation have been incredibly effective in limiting an outbreak in its severity, thus ensuring accurate information flow to the public is as essential as limiting the spread of misinformation. With global populations rising, surveillance for emerging and re-emerging pathogens will play an immense role in preventing future epidemics or pandemics. And finally that even though for novel strains or pathogens, although vaccines are thought to be an irreplaceable defense, but their development and distribution in time to curb an epidemic has seldom been witnessed and remains an important challenge for the future. Hence, we conclude that looking at these past examples not only highlights the important knowledge gained for the strategies to devise, but also the mistakes that can be avoided in the way forward.

Social connections with COVID-19-affected areas increase compliance with mobility restrictions

We study the role of social connections in compliance of U.S. households with mobility restrictions imposed in response to the coronavirus disease 2019 (COVID-19) pandemic, using aggregated and anonymized Facebook data on social connections and mobile phone data for measuring social distancing at the county level. Relative to the average restriction efficacy, a county with one-SD more social connections with China and Italy-the first countries with major COVID-19 outbreaks-has a nearly 50% higher compliance with mobility restrictions. By contrast, social connections of counties with less-educated populations, a higher Trump vote share, and a higher fraction of climate change deniers show decreased compliance with mobility restrictions. Our analysis suggests that social connections are conduits of information about the pandemic and an economically important factor affecting compliance with, and impact of, mobility restrictions.

Nonpharmaceutical Interventions for Pandemic Influenza: Communication, Training, and Guidance Needs of Public Health Officials

OBJECTIVES

The aim of this study was to identify the needs of state, tribal, local, and territorial (STLT) public health officials in communicating, implementing, and monitoring nonpharmaceutical interventions (NPIs) during an influenza pandemic.

METHODS

A Web-based survey collected data from a nonrandom sample of STLT health departments.

RESULTS

A total of 267 of 346 public health officials responded (77.2% response rate). STLTs identified the general public, families, childcare programs, K-12 schools, and workplaces as their priority audiences for NPI communication. Training needs included NPI decision-making strategies, triggers for implementing NPIs, and communicating NPI recommendations to families and communities, as well as a more practical orientation and real-world examples of how to incorporate NPI guidance into preparedness and response activities. Information is needed on health messaging for various populations and settings and on the legal authority for implementing specific NPIs.

CONCLUSIONS

Future NPI recommendations by CDC should continue to be based on feedback solicited from STLT health departments. To fill identified gaps, CDC used these findings to create NPI guidance and materials to assist in prepandemic planning and preparedness for STLTs and various community settings.

Brief History of Pandemics (Pandemics Throughout History)

Intermittent outbreaks of infectious diseases have had profound and lasting effects on societies throughout history. Those events have powerfully shaped the economic, political, and social aspects of human civilization, with their effects often lasting for centuries. Epidemic outbreaks have defined some of the basic tenets of modern medicine, pushing the scientific community to develop principles of epidemiology, prevention, immunization, and antimicrobial treatments. This chapter outlines some of the most notable outbreaks that took place in human history and are relevant for a better understanding of the rest of the material. Starting with religious texts, which heavily reference plagues, this chapter establishes the fundamentals for our understanding of the scope, social, medical, and psychological impact that some pandemics effected on civilization, including the Black Death (a plague outbreak from the fourteenth century), the Spanish Flu of 1918, and the more recent outbreaks in the twenty-first century, including SARS, Ebola, and Zika.

Public preferences for interventions to prevent emerging infectious disease threats: a discrete choice experiment

OBJECTIVE

When faced with an emergent epidemic with high mortality and morbidity potential, policy makers must decide what public health interventions to deploy at different stages of the outbreak. However, almost nothing is known about how the public view these interventions or how they trade off risks (of disease) with inconvenience (of interventions). In this paper, we aim to understand public perceptions on pandemic interventions, as well as to identify if there are any distinct respondent preference classes.

DESIGN

A discrete choice experiment.

SETTING

This study was fielded in Singapore between November 2012 and February 2013.

PARTICIPANTS

A random sample of 500 Singapore residents aged 21 and over, including 271 women and 229 men, was analysed.

OUTCOME MEASURES

Demographic information was collected from each participant. Participants were also shown a series of pairs of alternatives, each combining interventions and morbidity, mortality and cost outcomes and declared a preference for one combination. A random utility model was developed to determine the individual's preference for interventions and a hierarchical cluster analysis was performed to identify distinct respondent preference classes.

RESULTS

On average, participants preferred more intense interventions, and preferred scenarios with fewer deaths and lower tax. The number of infections did not significantly influence respondents' responses. We identified two broad classes of respondents: those who were mortality averse and those who were expenditure averse. Education was found to be a predictor of group membership.

CONCLUSION

Overall, there was considerable support for government interventions to prevent or mitigate outbreaks of emerging infectious diseases, including those that greatly restricted individual liberties, as long as the restrictions showed a reasonable chance of reducing the adverse health effects of the outbreak.

Relative incidence and individual-level severity of seasonal influenza A H3N2 compared with 2009 pandemic H1N1

Background

Two subtypes of influenza A currently circulate in humans: seasonal H3N2 (sH3N2, emerged in 1968) and pandemic H1N1 (pH1N1, emerged in 2009). While the epidemiological characteristics of the initial wave of pH1N1 have been studied in detail, less is known about its infection dynamics during subsequent waves or its severity relative to sH3N2. Even prior to 2009, few data was available to estimate the risk of severe outcomes following infection with one circulating influenza strain relative to another.

Methods

We analyzed antibodies in quadruples of sera from individuals in Hong Kong collected between July 2009 and December 2011, a period that included three distinct influenza virus epidemics. We estimated infection incidence using these assay data and then estimated rates of severe outcomes per infection using population-wide clinical data.

Results

Cumulative incidence of infection was high among children in the first epidemic of pH1N1. There was a change towards the older age group in the age distribution of infections for pH1N1 from the first to the second epidemic, with the age distribution of the second epidemic of pH1N1 more similar to that of sH3N2. We found no serological evidence that individuals were infected in both waves of pH1N1. The risks of excess mortality conditional on infection were higher for sH3N2 than for pH1N1, with age-standardized risk ratios of 2.6 [95% CI: 1.8, 3.7] for all causes and 1.5 [95% CI: 1.0, 2.1] for respiratory causes throughout the study period.

Conclusions

Overall increase in clinical incidence of pH1N1 and higher rates of severity in older adults in post pandemic waves were in line with an age-shift in infection towards the older age groups. The absence of repeated infection is good evidence that waning immunity did not cause the second wave. Despite circulating in humans since 1968, sH3N2 is substantially more severe per infection than the pH1N1 strain. Infection-based estimates of individual-level severity have a role in assessing emerging strains; updating seasonal vaccine components; and optimizing of vaccination programs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2432-7) contains supplementary material, which is available to authorized users.

Reducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context

BACKGROUND

Many nations maintain stockpiles of neuraminidase inhibitor (NAI) antiviral agents for use in influenza pandemics to reduce transmission and mitigate the course of clinical infection. Pandemic preparedness plans include the use of these stockpiles to deliver proportionate responses, informed by emerging evidence of clinical impact. Recent uncertainty about the effectiveness of NAIs has prompted these nations to reconsider the role of NAIs in pandemic response, with implications for pandemic planning and for NAI stockpile size.

METHODS

We combined a dynamic model of influenza epidemiology with a model of the clinical care pathways in the Australian health care system to identify effective NAI strategies for reducing morbidity and mortality in pandemic events, and the stockpile requirements for these strategies. The models were informed by a 2015 assessment of NAI effectiveness against susceptibility, pathogenicity, and transmission of influenza.

RESULTS

Liberal distribution of NAIs for early treatment in outpatient settings yielded the greatest benefits in all of the considered scenarios. Restriction of community-based treatment to risk groups was effective in those groups, but failed to prevent the large proportion of cases arising from lower risk individuals who comprise the majority of the population.

CONCLUSIONS

These targeted strategies are only effective if they can be deployed within the constraints of existing health care infrastructure. This finding highlights the critical importance of identifying optimal models of care delivery for effective emergency health care response.

Using Combined Diagnostic Test Results to Hindcast Trends of Infection from Cross-Sectional Data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to 'hindcast' (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time.

Evolution of 2009 H1N1 influenza viruses during the pandemic correlates with increased viral pathogenicity and transmissibility in the ferret model

There is increasing evidence that 2009 pandemic H1N1 influenza viruses have evolved after pandemic onset giving rise to severe epidemics in subsequent waves. However, it still remains unclear which viral determinants might have contributed to disease severity after pandemic initiation. Here, we show that distinct mutations in the 2009 pandemic H1N1 virus genome have occurred with increased frequency after pandemic declaration. Among those, a mutation in the viral hemagglutinin was identified that increases 2009 pandemic H1N1 virus binding to human-like α2,6-linked sialic acids. Moreover, these mutations conferred increased viral replication in the respiratory tract and elevated respiratory droplet transmission between ferrets. Thus, our data show that 2009 H1N1 influenza viruses have evolved after pandemic onset giving rise to novel virus variants that enhance viral replicative fitness and respiratory droplet transmission in a mammalian animal model. These findings might help to improve surveillance efforts to assess the pandemic risk by emerging influenza viruses.

Performance of rapid influenza diagnostic tests (QuickVue) for influenza A and B Infection in India

BACKGROUND

Rapid point-of-care (POC) tests provide an economical alternative for rapid diagnosis and treatment of influenza, especially in public health emergency situations.

OBJECTIVES

To test the performance of a rapid influenza diagnostic test, QuickVue (Quidel) as a POC test against a real-time polymerase chain reaction (RT-PCR) assay for detection of influenza A and B in a developing country setting.

STUDY DESIGN

In a prospective observational design, 600 patients with influenza-like illness (ILI) or with severe acute respiratory illness (SARI) who were referred to the Influenza Clinic of a tertiary care hospital in Srinagar, India from September 2012 to April 2013, were enrolled for diagnostic testing for influenza using QuickVue or RT-PCR. All influenza A-positive patients by RT-PCR were further subtyped using primers and probes for A/H1pdm09 and A/H3.

RESULTS

Of the 600 patients, 186 tested positive for influenza A or B by RT-PCR (90 A/H1N1pdm09, 7 A/H3 and 89 influenza B), whereas only 43 tested positive for influenza (influenza A=22 and influenza B=21) by QuickVue. Thus, the sensitivity of the QuickVue was only 23% (95% confidence interval, CI: 17.3-29.8) and specificity was 100% (95% CI: 99.1-100) with a positive predictive value (PPV) of 100% (95% CI 91.8-100) and a negative predictive value (NPV) of 74.3% (95% CI: 70.5-77.9) as compared to RT-PCR.

CONCLUSIONS

The high specificity of QuickVue suggest that this POC test can be a useful tool for patient management or triaging during a public health crisis but a low sensitivity suggests that a negative test result need to be further tested using RT-PCR.

Adaptive Mutations That Occurred during Circulation in Humans of H1N1 Influenza Virus in the 2009 Pandemic Enhance Virulence in Mice

During the 2009 H1N1 influenza pandemic, infection attack rates were particularly high among young individuals who suffered from pneumonia with occasional death. Moreover, previously reported determinants of mammalian adaptation and pathogenicity were not present in 2009 pandemic H1N1 influenza A viruses. Thus, it was proposed that unknown viral factors might have contributed to disease severity in humans. In this study, we performed a comparative analysis of two clinical 2009 pandemic H1N1 strains that belong to the very early and later phases of the pandemic. We identified mutations in the viral hemagglutinin (HA) and the nucleoprotein (NP) that occurred during pandemic progression and mediate increased virulence in mice. Lethal disease outcome correlated with elevated viral replication in the alveolar epithelium, increased proinflammatory cytokine and chemokine responses, pneumonia, and lymphopenia in mice. These findings show that viral mutations that have occurred during pandemic circulation among humans are associated with severe disease in mice.

IMPORTANCE

In this study, novel determinants of 2009 pandemic H1N1 influenza pathogenicity were identified in the viral hemagglutinin (HA) and the nucleoprotein (NP) genes. In contrast to highly pathogenic avian influenza viruses, increased virulence in mice did not correlate with enhanced polymerase activity but with reduced activity. Lethal 2009 pandemic H1N1 infection in mice correlated with lymphopenia and severe pneumonia. These studies suggest that molecular mechanisms that mediate 2009 pandemic H1N1 influenza pathogenicity are distinct from those that mediate avian influenza virus pathogenicity in mice.

Prior population immunity reduces the expected impact of CTL-inducing vaccines for pandemic influenza control

Vaccines that trigger an influenza-specific cytotoxic T cell (CTL) response may aid pandemic control by limiting the transmission of novel influenza A viruses (IAV). We consider interventions with hypothetical CTL-inducing vaccines in a range of epidemiologically plausible pandemic scenarios. We estimate the achievable reduction in the attack rate, and, by adopting a model linking epidemic progression to the emergence of IAV variants, the opportunity for antigenic drift. We demonstrate that CTL-inducing vaccines have limited utility for modifying population-level outcomes if influenza-specific T cells found widely in adults already suppress transmission and prove difficult to enhance. Administration of CTL-inducing vaccines that are efficacious in "influenza-experienced" and "influenza-naive" hosts can likely slow transmission sufficiently to mitigate a moderate IAV pandemic. However if neutralising cross-reactive antibody to an emerging IAV are common in influenza-experienced hosts, as for the swine-variant H3N2v, boosting CTL immunity may be ineffective at reducing population spread, indicating that CTL-inducing vaccines are best used against novel subtypes such as H7N9. Unless vaccines cannot readily suppress transmission from infected hosts with naive T cell pools, targeting influenza-naive hosts is preferable. Such strategies are of enhanced benefit if naive hosts are typically intensively mixing children and when a subset of experienced hosts have pre-existing neutralising cross-reactive antibody. We show that CTL-inducing vaccination campaigns may have greater power to suppress antigenic drift than previously suggested, and targeting adults may be the optimal strategy to achieve this when the vaccination campaign does not have the power to curtail the attack rate. Our results highlight the need to design interventions based on pre-existing cellular immunity and knowledge of the host determinants of vaccine efficacy, and provide a framework for assessing the performance requirements of high-impact CTL-inducing vaccines.

Emerging infectious diseases and pandemic potential: status quo and reducing risk of global spread

Emerging infectious diseases are an important public health threat and infections with pandemic potential are a major global risk. Although much has been learned from previous events the evidence for mitigating actions is not definitive and pandemic preparedness remains a political and scientific challenge. A need exists to develop trust and effective meaningful collaboration between countries to help with rapid detection of potential pandemic infections and initiate public health actions. This collaboration should be within the framework of the International Health Regulations. Collaboration between countries should be encouraged in a way that acknowledges the benefits that derive from sharing biological material and establishing equitable collaborative research partnerships. The focus of pandemic preparedness should include upstream prevention through better collaboration between human and animal health sciences to enhance capacity to identify potential pathogens before they become serious human threats, and to prevent their emergence where possible. The one-health approach provides a means to develop this and could potentially enhance alignment of global health and trade priorities.

Spatial epidemiology of networked metapopulation: an overview

An emerging disease is one infectious epidemic caused by a newly transmissible pathogen, which has either appeared for the first time or already existed in human populations, having the capacity to increase rapidly in incidence as well as geographic range. Adapting to human immune system, emerging diseases may trigger large-scale pandemic spreading, such as the transnational spreading of SARS, the global outbreak of A(H1N1), and the recent potential invasion of avian influenza A(H7N9). To study the dynamics mediating the transmission of emerging diseases, spatial epidemiology of networked metapopulation provides a valuable modeling framework, which takes spatially distributed factors into consideration. This review elaborates the latest progresses on the spatial metapopulation dynamics, discusses empirical and theoretical findings that verify the validity of networked metapopulations, and the sketches application in evaluating the effectiveness of disease intervention strategies as well.

Academics and competing interests in H1N1 influenza media reporting

BACKGROUND

Concerns have been raised over competing interests (CoI) among academics during the 2009 to 2010 A/H1N1 pandemic. Media reporting can influence public anxiety and demand for pharmaceutical products. We assessed CoI of academics providing media commentary during the early stages of the pandemic.

METHODS

We performed a retrospective content analysis of UK newspaper articles on A/H1N1 influenza, examining quoted sources. We noted when academics made a risk assessment of the pandemic and compared this with official estimations. We also looked for promotion or rejection of the use of neuraminidase inhibitors or H1N1-specific vaccine. We independently searched for CoI for each academic.

RESULTS

Academics were the second most frequently quoted source after Ministers of Health. Where both academics and official agencies estimated the risk of H1N1, one in two academics assessed the risk as higher than official predictions. For academics with CoI, the odds of a higher risk assessment were 5.8 times greater than those made by academics without CoI (Wald p value=0.009). One in two academics commenting on the use of neuraminidase inhibitors or vaccine had CoI. The odds of CoI in academics promoting the use of neuraminidase inhibitors were 8.4 times greater than for academics not commenting on their use (Fisher's exact p=0.005).

CONCLUSIONS

There is evidence of CoI among academics providing media commentary during the early H1N1 pandemic. Heightened risk assessments, combined with advocacy for pharmaceutical products to counter this risk, may lead to increased public anxiety and demand. Academics should declare, and journalists report, relevant CoI for media interviews.

Seroprevalence of antibody to influenza A(H1N1)pdm09 attributed to vaccination or infection, before and after the second (2010) pandemic wave in Australia

Objectives

Historical records of influenza pandemics demonstrate variability in incidence and severity between waves. The influenza A(H1N1)pdm09 pandemic was the first in which many countries implemented strain-specific vaccination to mitigate subsequent seasons. Serosurveys provide opportunity to examine the constraining influence of antibody on population disease experience.

Design

Changes in the proportion of adults seropositive to influenza A(H1N1)pdm09over the 2009/10 (summer) interepidemic period and 2010 (winter) influenza season were measured to determine whether there was a temporal relationship with vaccine distribution and influenza activity, respectively.

Setting

Australia.

Sample

Plasma samples were collected from healthy blood donors from seven cities at the end of the first wave (November 2009), and before (March/April 2010) and after (November 2010) the subsequent influenza season.

Main outcome measures

Haemagglutination inhibition (HI) assays were performed to assess reactivity of plasma against A(H1N1)pdm09, and the proportion seropositive (HI titre ≥ 40) compared over time, by age group and location.

Results

Between the 2009 and 2010 influenza seasons, the seropositive proportion rose from 22% to 43%, an increase observed across all ages and sites. Brisbane alone recorded a significant rise in seropositivity over the 2010 influenza season – from a baseline of 35% to 53%. The seropositive proportion elsewhere was ≥40% pre-season, and did not rise over winter.

Conclusions

A vaccine-associated increase in seropositive proportion preceding the influenza season correlated with low levels of disease activity in winter 2010. These observations support the role of immunisation in mitigating the ‘second wave’ of A(H1N1)pdm09, with timing critical to ensure sustained herd protection.

Chinese social media reaction to the MERS-CoV and avian influenza A(H7N9) outbreaks

Background

As internet and social media use have skyrocketed, epidemiologists have begun to use online data such as Google query data and Twitter trends to track the activity levels of influenza and other infectious diseases. In China, Weibo is an extremely popular microblogging site that is equivalent to Twitter. Capitalizing on the wealth of public opinion data contained in posts on Weibo, this study used Weibo as a measure of the Chinese people’s reactions to two different outbreaks: the 2012 Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreak, and the 2013 outbreak of human infection of avian influenza A(H7N9) in China.

Methods

Keyword searches were performed in Weibo data collected by The University of Hong Kong’s Weiboscope project. Baseline values were determined for each keyword and reaction values per million posts in the days after outbreak information was released to the public.

Results

The results show that the Chinese people reacted significantly to both outbreaks online, where their social media reaction was two orders of magnitude stronger to the H7N9 influenza outbreak that happened in China than the MERS-CoV outbreak that was far away from China.

Conclusions

These results demonstrate that social media could be a useful measure of public awareness and reaction to disease outbreak information released by health authorities.

Excess mortality impact of two epidemics of pandemic influenza A(H1N1pdm09) virus in Hong Kong

Hong Kong experienced two large epidemics of pandemic influenza A(H1N1pdm09). We used regression methods to estimate the excess mortality associated with each epidemic. The first epidemic of H1N1pdm09 peaked in September 2009 and was associated with 2·13 [95% confidence interval (CI): -8·08, 11·82] excess all-cause deaths per 100 000 population. The second epidemic of H1N1pdm09 in early 2011 was associated with 4·72 [95% CI: -0·70, 10·50] excess deaths per 100 000 population. More than half of the estimated excess all-cause deaths were attributable to respiratory causes in each epidemic. The reasons for substantial impact in the second wave remain to be clarified.

Immunosignatures can predict vaccine efficacy

The development of new vaccines would be greatly facilitated by having effective methods to predict vaccine performance. Such methods could also be helpful in monitoring individual vaccine responses to existing vaccines. We have developed "immunosignaturing" as a simple, comprehensive, chip-based method to display the antibody diversity in an individual on peptide arrays. Here we examined whether this technology could be used to develop correlates for predicting vaccine effectiveness. By using a mouse influenza infection, we show that the immunosignaturing of a natural infection can be used to discriminate a protective from nonprotective vaccine. Further, we demonstrate that an immunosignature can determine which mice receiving the same vaccine will survive. Finally, we show that the peptides comprising the correlate signatures of protection can be used to identify possible epitopes in the influenza virus proteome that are correlates of protection.

The pandemic H1N1 influenza experience

The pandemic H1N1 influenza that began in Mexico in the spring of 2009 spread rapidly to southern California within days and around the world within a few months. Because the genetic make-up of the new virus was novel, several months of lead-in time were required before a suitable vaccine for human use could be produced and distributed. The effort to confront the virus on the part of the World Health Organization which included almost every nation on earth and a vast array of scientists and public health officials was extensive and timely. However, it was the moderate severity of the virus itself that saved global public health from catastrophe. Because of the extensive publicity and research that occurred during the H1N1 pandemic, many lessons were learned that will be useful in confronting future influenza pandemics. A "One Health" approach to prevent, detect, and combat future pandemics is essential.

Determinants of 2009 A/H1N1 influenza vaccination among pregnant women in Hong Kong

During the 2009–2010 A/H1N1 influenza pandemic, pregnant women infected with the virus experienced excess morbidity and mortality when compared with other groups. Once a vaccine was available, pregnant women were a priority group for vaccination. Only a few studies have reported on the uptake of 2009 A/H1N1 influenza vaccine among pregnant women during the pandemic and none were from Asia. The purpose of this study was to examine factors associated with 2009 A/H1N1 influenza vaccine uptake among pregnant women in Hong Kong. Using a multi-center, cross-sectional design, we recruited 549 postpartum women from four post-natal wards in Hong Kong over a 4-month period during the second wave of the A/H1N1 influenza pandemic in the winter and spring of 2010. Only 6.2% (n = 34) of participants had received the 2009 A/H1N1 influenza vaccine and 4.9% (n = 27) had received the seasonal influenza vaccine. The most common reasons for not receiving the 2009 A/H1N1 vaccine were fear of causing harm to themselves or their fetus. A high knowledge level (OR = 19.06; 95% CI 5.55, 65.48), more positive attitudes (OR = 3.52; 95% CI 1.37, 9.07), and having a family member who had the 2009 A/H1N1 influenza vaccine (OR = 7.69; 95% CI 2.92, 20.19) were independently and positively associated with vaccination. Study results show an unacceptably low uptake of the pandemic A/H1N1 influenza vaccine among pregnant women in Hong Kong. Interventions to increase influenza vaccine knowledge and uptake among this group should be a priority for future pandemic planning and seasonal vaccination campaigns.

Drivers and consequences of influenza antiviral resistant-strain emergence in a capacity-constrained pandemic response

Antiviral agents remain a key component of most pandemic influenza preparedness plans, but there is considerable uncertainty regarding their optimal use. In particular, concerns exist regarding the likelihood of wide-scale distribution to select for drug-resistant variants. We used a model that considers the influence of logistical constraints on diagnosis and drug delivery to consider achievable 'reach' of alternative antiviral intervention strategies targeted at cases of varying severity, with or without pre-exposure prophylaxis of contacts. To identify key drivers of epidemic mitigation and resistance emergence, we used Latin hypercube sampling to explore plausible ranges of parameters describing characteristics of wild type and resistant viruses, along with intervention efficacy, target coverage and distribution capacity. Within our model framework, 'real world' constraints substantially reduced achievable drug coverage below stated targets as the epidemic progressed. In consequence, predictions of both intervention impact and selection for resistance were more modest than earlier work that did not consider such limitations. Definitive containment of transmission was unlikely but, where observed, achieved through early liberal post-exposure prophylaxis of known contacts of treated cases. Predictors of resistant strain dominance were high intrinsic fitness relative to the wild type virus, and early emergence in the course of the epidemic into a largely susceptible population, even when drug use was restricted to severe case treatment. Our work demonstrates the importance of consideration of 'real world' constraints in scenario analysis modeling, and highlights the utility of models to guide surveillance activities in preparedness and response.

Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm

BACKGROUND

Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches.

METHODS

We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability.

RESULTS

Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model.

CONCLUSIONS

Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models.

The epidemiological and public health research response to 2009 pandemic influenza A(H1N1): experiences from Hong Kong

In recent years, Hong Kong has invested in research infrastructure to appropriately respond to novel infectious disease epidemics. Research from Hong Kong made a strong contribution to the international response to the 2009 influenza A (H1N1) pandemic (pH1N1). Summarizing, describing, and reviewing Hong Kong’s response to the 2009 pandemic, this article aimed to identify key elements of a real‐time research response. A systematic search in PubMed and EMBASE for research into the infection dynamics and natural history, impact, or control of pH1N1 in Hong Kong. Eligible articles were analyzed according to their scope. Fifty‐five articles were included in the review. Transmissibility of pH1N1 was similar in Hong Kong to elsewhere, and only a small fraction of infections were associated with severe disease. School closures were effective in reducing pH1N1 transmission, oseltamivir was effective for treatment of severe cases while convalescent plasma therapy has the potential to mitigate future pandemics. There was a rapid and comprehensive research response to pH1N1 in Hong Kong, providing important information on the epidemiology of the novel virus with relevance internationally as well as locally. The scientific knowledge gained through these detailed studies of pH1N1 is now being used to revise and update pandemic plans. The experiences of the research response in Hong Kong could provide a template for the research response to future emerging and reemerging disease epidemics.

Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia

OBJECTIVE

To assess the likely benefit of the interventions under consideration for use in Mongolia during future influenza pandemics.

METHODS

A stochastic, compartmental patch model of susceptibility, exposure, infection and recovery was constructed to capture the key effects of several interventions--travel restrictions, school closure, generalized social distancing, quarantining of close contacts, treatment of cases with antivirals and prophylaxis of contacts--on the dynamics of influenza epidemics. The likely benefit and optimal timing and duration of each of these interventions were assessed using Latin-hypercube sampling techniques, averaging across many possible transmission and social mixing parameters.

FINDINGS

Timely interventions could substantially alter the time-course and reduce the severity of pandemic influenza in Mongolia. In a moderate pandemic scenario, early social distancing measures decreased the mean attack rate from around 10% to 7-8%. Similarly, in a severe pandemic scenario such measures cut the mean attack rate from approximately 23% to 21%. In both moderate and severe pandemic scenarios, a suite of non-pharmaceutical interventions proved as effective as the targeted use of antivirals. Targeted antiviral campaigns generally appeared more effective in severe pandemic scenarios than in moderate pandemic scenarios.

CONCLUSION

A mathematical model of pandemic influenza transmission in Mongolia indicated that, to be successful, interventions to prevent transmission must be triggered when the first cases are detected in border regions. If social distancing measures are introduced at this stage and implemented over several weeks, they may have a notable mitigating impact. In low-income regions such as Mongolia, social distancing may be more effective than the large-scale use of antivirals.

Novel influenza (H1N1) infection in pediatric renal transplant recipients: a single center experience

In 2009, novel influenza A H1N1 caused significant morbidity and mortality worldwide, particularly in children. Because they are immunocompromised, pediatric transplant recipients are presumed to be at high risk. This study assessed epidemiological characteristics, presenting symptoms, and clinical course among pediatric renal transplant recipients with confirmed H1N1 infection. A retrospective review was conducted in renal transplant recipients followed at The Hospital for Sick Children (Toronto) who contracted H1N1 infection between June and November, 2009. Epidemiological, clinical, and laboratory features at presentation, and clinical course were analyzed. Of 59 children, 14 (23.7%) developed H1N1 infection. Children with H1N1 infection had undergone kidney transplantation more recently than their uninfected counterparts. The most common symptoms included fever (92.9%), cough (85.7%), headache (42.9%), and vomiting (42.9%). Fifty percent of patients required hospitalization, of median duration 3.0 (1.0-5.0) days. No child required intensive care treatment. Half the H1N1-infected children had acute renal dysfunction, with serum creatinine elevated >10% above basal values (median increase 21.6 [14.3-46.2]%). In five of the seven children, serum creatinine returned to baseline within two wk. These findings indicate that H1N1 influenza infection in pediatric kidney transplant recipients followed at our center was surprisingly mild, and produced no lasting sequelae.

Organizational Collaborative Capacity in Fighting Pandemic Crises

Collaborative capacity serves for organizations as the capacity to collaborate with other network players. Organizational capacity matters as collaboration outcomes usually go beyond single-shot implementation efforts or a single-minded focus on either the vertical dimension of program or the horizontal component. This review article explores organizational collaborative capacities from the perspective of public management, in particular, network theory. By applying the 5 attributes of network theory—interdependence, membership, resources, information, and learning—to the explanation of collaborative capacity in fighting pandemic crises, I argue in some ways organizational collaborative capacity is very much like an organization in its own right. Studying collaborative capacity in the battle against pandemics facilitate our understanding of multisectoral collaboration in technical, political, and institutional dimensions, and greatly advances the richness of capacity vocabulary in pandemic response and preparedness.

Publication delay of randomized trials on 2009 influenza A (H1N1) vaccination

Background

Randomized evidence for vaccine immunogenicity and safety is urgently needed in the setting of pandemics with new emerging infectious agents. We carried out an observational survey to evaluate how many randomized controlled trials testing 2009 H1N1 vaccines were published among those registered, and what was the time lag from their start to publication and from their completion to publication.

Methods

PubMed, EMBASE and 9 clinical trial registries were searched for eligible randomized controlled trials. The units of the analysis were single randomized trials on any individual receiving influenza vaccines in any setting.

Results

73 eligible trials were identified that had been registered in 2009–2010. By June 30, 2011 only 21 (29%) of these trials had been published, representing 38% of the randomized sample size (19905 of 52765). Trials starting later were published less rapidly (hazard ratio 0.42 per month; 95% Confidence Interval: 0.27 to 0.64; p<0.001). Similarly, trials completed later were published less rapidly (hazard ratio 0.43 per month; 95% CI: 0.27 to 0.67; p<0.001). Randomized controlled trials were completed promptly (median, 5 months from start to completion), but only a minority were subsequently published.

Conclusions

Most registered randomized trials on vaccines for the H1N1 pandemic are not published in the peer-reviewed literature.

Age-dependent patterns of infection and severity explaining the low impact of 2009 influenza A (H1N1): evidence from serial serologic surveys in the Netherlands

Despite considerable research efforts in specific subpopulations, reliable estimates of the infection attack rates and severity of 2009 influenza A (H1N1) in the general population remain scarce. Such estimates are essential to the tailoring of future control strategies. Therefore, 2 serial population-based serologic surveys were conducted, before and after the 2009 influenza A (H1N1) epidemic, in the Netherlands. Random age-stratified samples were obtained using a 2-stage cluster design. Participants donated blood and completed a questionnaire. Data on sentinel general practitioner-attended influenza-like illness and nationwide hospitalization and mortality were used to assess the severity of infection. The estimated infection attack rates were low in the general population (7.6%, 95% confidence interval: 3.6, 11) but high in children aged 5-19 years (35%, 95% confidence interval: 25, 45). The estimated hospitalization and mortality rates per infection increased significantly with age (5-19 years: 0.042% and 0.00094%, respectively; 20-39 years: 0.12% and 0.0025%; 40-59 years: 0.68% and 0.032%; 60-75 years: >0.81% and >0.068%). The high infection attack rate in children and the very low attack rate in older adults, together with the low severity of illness per infection in children but substantial severity in older adults, produced an epidemic with a low overall impact.

The 2009 H1N1 pandemic response in remote First Nation communities of Subarctic Ontario: barriers and improvements from a health care services perspective

OBJECTIVES

To retrospectively examine the barriers faced and opportunities for improvement during the 2009 H1N1 pandemic response experienced by participants responsible for the delivery of health care services in 3 remote and isolated Subarctic First Nation communities of northern Ontario, Canada.

STUDY DESIGN

A qualitative community-based participatory approach.

METHODS

Semi-directed interviews were conducted with adult key informants (n=13) using purposive sampling of participants representing the 3 main sectors responsible for health care services (i.e., federal health centres, provincial hospitals and Band Councils). Data were manually transcribed and coded using deductive and inductive thematic analysis.

RESULTS

Primary barriers reported were issues with overcrowding in houses, insufficient human resources and inadequate community awareness. Main areas for improvement included increasing human resources (i.e., nurses and trained health care professionals), funding for supplies and general community awareness regarding disease processes and prevention.

CONCLUSIONS

Government bodies should consider focusing efforts to provide more support in terms of human resources, monies and education. In addition, various government organizations should collaborate to improve housing conditions and timely access to resources. These recommendations should be addressed in future pandemic plans, so that remote western James Bay First Nation communities of Subarctic Ontario and other similar communities can be better prepared for the next public health emergency.

Influenza virus vaccines: lessons from the 2009 H1N1 pandemic

Reflecting on the 2009 H1N1 pandemic, we summarize lessons regarding influenza vaccines that can be applied in the future. The two major challenges to vaccination during the 2009 H1N1 pandemic were timing and availability of vaccine. Vaccines were, however, well-tolerated and immunogenic, with inactivated vaccines containing 15μg of HA generally inducing antibody titers ≥1:40 in adults within 2 weeks of the administration of a single dose. Moreover, the use of oil-in-water adjuvants in Europe permitted dose- reduction, with vaccines containing as little as 3.75 or 7.5μg HA being immunogenic. Case-control studies demonstrated that monovalent 2009 H1N1 vaccines were effective in preventing infection with the 2009 H1N1 virus, but preliminary data suggests that it is important for individuals to be re-immunized annually.

Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administration capacity

Background

Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination proportional to the population at each point in time.

Methods

We present a SIR-like model that explicitly takes into account vaccine supply and the number of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the non-proportional model of vaccination and compare it to the proportional scheme typically found in the literature.

Results

The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity.

Conclusions

The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing nations with a wide variety of financial and medical resources. Finally, the model can be used by government and medical officials to create customized pandemic preparedness plans based on the supply and administration constraints of specific communities.

Improving the evidence base for decision making during a pandemic: the example of 2009 influenza A/H1N1

This article synthesizes and extends discussions held during an international meeting on "Surveillance for Decision Making: The Example of 2009 Pandemic Influenza A/H1N1," held at the Center for Communicable Disease Dynamics (CCDD), Harvard School of Public Health, on June 14 and 15, 2010. The meeting involved local, national, and global health authorities and academics representing 7 countries on 4 continents. We define the needs for surveillance in terms of the key decisions that must be made in response to a pandemic: how large a response to mount and which control measures to implement, for whom, and when. In doing so, we specify the quantitative evidence required to make informed decisions. We then describe the sources of surveillance and other population-based data that can presently--or in the future--form the basis for such evidence, and the interpretive tools needed to process raw surveillance data. We describe other inputs to decision making besides epidemiologic and surveillance data, and we conclude with key lessons of the 2009 pandemic for designing and planning surveillance in the future.