Pandemic potential of a strain of influenza A (H1N1): early findings

Networks and Models with Heterogeneous Population Structure in Epidemiology

Heterogeneous population structure can have a profound effect on infectious disease dynamics, and is particularly important when investigating “tactical” disease control questions. At times, the nature of the network involved in the transmission of the pathogen (bacteria, virus, macro-parasite, etc.) appears to be clear; however, the nature of the network involved is dependent on the scale (e.g. within-host, between-host, or between-population), the nature of the contact, which ranges from the highly specific (e.g. sexual acts or needle sharing at the person-to-person level) to almost completely non-specific (e.g. aerosol transmission, often over long distances as can occur with the highly infectious livestock pathogen foot-and-mouth disease virus—FMDv—at the farm-to-farm level, e.g. Schley et al. in J. R. Soc. Interface 6:455–462, 2008), and the timescale of interest (e.g. at the scale of the individual, the typical infectious period of the host). Theoretical approaches to examining the implications of particular network structures on disease transmission have provided critical insight; however, a greater challenge is the integration of network approaches with data on real population structures. In this chapter, some concepts in disease modelling will be introduced, the relevance of selected network phenomena discussed, and then results from real data and their relationship to network analyses summarised. These include examinations of the patterns of air traffic and its relation to the spread of SARS in 2003 (Colizza et al. in BMC Med., 2007; Hufnagel et al. in Proc. Natl. Acad. Sci. USA 101:15124–15129, 2004), the use of the extensively documented Great Britain livestock movements network (Green et al. in J. Theor. Biol. 239:289–297, 2008; Robinson et al. in J. R. Soc. Interface 4:669–674, 2007; Vernon and Keeling in Proc. R. Soc. Lond. B, Biol. Sci. 276:469–476, 2009) and the growing interest in combining contact structure data with phylogenetics to identify real contact patterns as they directly relate to diseases of interest (Cottam et al. in PLoS Pathogens 4:1000050, 2007; Hughes et al. in PLoS Pathogens 5:1000590, 2009).

Responding to pandemic (H1N1) 2009 influenza in Aboriginal communities in NSW through collaboration between NSW Health and the Aboriginal community-controlled health sector

As a vulnerable population, Aboriginal people in NSW were thought likely to be at more risk of serious illness from pandemic (H1N1) 2009 influenza than non-Aboriginal people. As such, the importance of consulting with Aboriginal people and communities was recognised early in the pandemic. This consultation was to enable key messages to be disseminated appropriately and to facilitate access to health care. Key stakeholders in the response were the NSW Department of Health, Area Health Services, the NSW Aboriginal Health and Medical Research Council, and Aboriginal Community Controlled Health Services. Regular teleconferences between the key stakeholders facilitated the flow of information and assisted with the identification of issues. A consultation process between Hunter New England Area Health Service and six Aboriginal communities helped inform the development of resources as well as the planning and delivery of pandemic-related services. Aboriginal people were four times more likely to be admitted to hospital with pandemic (H1N1) 2009 influenza than non-Aboriginal people.

Household transmission of 2009 pandemic influenza A (H1N1) virus in the United States

BACKGROUND

As of June 11, 2009, a total of 17,855 probable or confirmed cases of 2009 pandemic influenza A (H1N1) had been reported in the United States. Risk factors for transmission remain largely uncharacterized. We characterize the risk factors and describe the transmission of the virus within households.

METHODS

Probable and confirmed cases of infection with the 2009 H1N1 virus in the United States were reported to the Centers for Disease Control and Prevention with the use of a standardized case form. We investigated transmission of infection in 216 households--including 216 index patients and their 600 household contacts--in which the index patient was the first case patient and complete information on symptoms and age was available for all household members.

RESULTS

An acute respiratory illness developed in 78 of 600 household contacts (13%). In 156 households (72% of the 216 households), an acute respiratory illness developed in none of the household contacts; in 46 households (21%), illness developed in one contact; and in 14 households (6%), illness developed in more than one contact. The proportion of household contacts in whom acute respiratory illness developed decreased with the size of the household, from 28% in two-member households to 9% in six-member households. Household contacts 18 years of age or younger were twice as susceptible as those 19 to 50 years of age (relative susceptibility, 1.96; Bayesian 95% credible interval, 1.05 to 3.78; P=0.005), and household contacts older than 50 years of age were less susceptible than those who were 19 to 50 years of age (relative susceptibility, 0.17; 95% credible interval, 0.02 to 0.92; P=0.03). Infectivity did not vary with age. The mean time between the onset of symptoms in a case patient and the onset of symptoms in the household contacts infected by that patient was 2.6 days (95% credible interval, 2.2 to 3.5).

CONCLUSIONS

The transmissibility of the 2009 H1N1 influenza virus in households is lower than that seen in past pandemics. Most transmissions occur soon before or after the onset of symptoms in a case patient.

Outbreak of 2009 pandemic influenza A (H1N1) at a New York City school

BACKGROUND

In April 2009, an outbreak of novel swine-origin influenza A (2009 H1N1 influenza) occurred at a high school in Queens, New York. We describe the outbreak and characterize the clinical and epidemiologic aspects of this novel virus.

METHODS

The New York City Department of Health and Mental Hygiene characterized the outbreak through laboratory confirmation of the presence of the 2009 H1N1 virus in nasopharyngeal and oropharyngeal specimens and through information obtained from an online survey. Detailed information on exposure and the onset of symptoms was used to estimate the incubation period, generation time, and within-school reproductive number associated with 2009 H1N1 influenza, with the use of established techniques.

RESULTS

From April 24 through May 8, infection with the 2009 H1N1 virus was confirmed in 124 high-school students and employees. In responses to the online questionnaire, more than 800 students and employees (35% of student respondents and 10% of employee respondents) reported having an influenza-like illness during this period. No persons with confirmed 2009 H1N1 influenza or with influenza-like illness had severe symptoms. A linkage with travel to Mexico was identified. The estimated median incubation period for confirmed 2009 H1N1 influenza was 1.4 days (95% confidence interval [CI], 1.0 to 1.8), with symptoms developing in 95% of cases by 2.2 days (95% CI, 1.7 to 2.6). The estimated median generation time was 2.7 days (95% CI, 2.0 to 3.5). We estimate that the within-school reproductive number was 3.3.

CONCLUSIONS

The findings from this investigation suggest that 2009 H1N1 influenza in the high school was widespread but did not cause severe illness. The reasons for the rapid and extensive spread of influenza-like illnesses are unknown. The natural history and transmission of the 2009 H1N1 influenza virus appear to be similar to those of previously observed circulating pandemic and interpandemic influenza viruses.

Streptococcus pneumoniae coinfection is correlated with the severity of H1N1 pandemic influenza

Background

Initial reports in May 2009 of the novel influenza strain H1N1pdm estimated a case fatality rate (CFR) of 0.6%, similar to that of seasonal influenza. In July 2009, however, Argentina reported 3056 cases with 137 deaths, representing a CFR of 4.5%. Potential explanations for increased CFR included virus reassortment or genetic drift, or infection of a more vulnerable population. Virus genomic sequencing of 26 Argentinian samples representing both severe and mild disease indicated no evidence of reassortment, mutations associated with resistance to antiviral drugs, or genetic drift that might contribute to virulence. Furthermore, no evidence was found for increased frequency of risk factors for H1N1pdm disease.

Methods/Principal Findings

We examined nasopharyngeal swab samples (NPS) from 199 cases of H1N1pdm infection from Argentina with MassTag PCR, testing for 33 additional microbial agents. The study population consisted of 199 H1N1pdm-infected subjects sampled between 23 June and 4 July 2009. Thirty-nine had severe disease defined as death (n = 20) or hospitalization (n = 19); 160 had mild disease. At least one additional agent of potential pathogenic importance was identified in 152 samples (76%), including Streptococcus pneumoniae (n = 62); Haemophilus influenzae (n = 104); human respiratory syncytial virus A (n = 11) and B (n = 1); human rhinovirus A (n = 1) and B (n = 4); human coronaviruses 229E (n = 1) and OC43 (n = 2); Klebsiella pneumoniae (n = 2); Acinetobacter baumannii (n = 2); Serratia marcescens (n = 1); and Staphylococcus aureus (n = 35) and methicillin-resistant S. aureus (MRSA, n = 6). The presence of S. pneumoniae was strongly correlated with severe disease. S. pneumoniae was present in 56.4% of severe cases versus 25% of mild cases; more than one-third of H1N1pdm NPS with S. pneumoniae were from subjects with severe disease (22 of 62 S. pneumoniae-positive NPS, p = 0.0004). In subjects 6 to 55 years of age, the adjusted odds ratio (OR) of severe disease in the presence of S. pneumoniae was 125.5 (95% confidence interval [CI], 16.95, 928.72; p<0.0001).

Conclusions/Significance

The association of S. pneumoniae with morbidity and mortality is established in the current and previous influenza pandemics. However, this study is the first to demonstrate the prognostic significance of non-invasive antemortem diagnosis of S. pneumoniae infection and may provide insights into clinical management.

Optimizing infectious disease interventions during an emerging epidemic

The emergence and global impact of the novel influenza A(H1N1)v highlights the continuous threat to public health posed by a steady stream of new and unexpected infectious disease outbreaks in animals and humans. Once an emerging epidemic is detected, public health authorities will attempt to mitigate the epidemic by, among other measures, reducing further spread as much as possible. Scarce and/or costly control measures such as vaccines, anti-infective drugs, and social distancing must be allocated while epidemiological characteristics of the disease remain uncertain. Here we present first principles for allocating scarce resources with limited data. We show that under a broad class of assumptions, the simple rule of targeting intervention measures at the group with the highest risk of infection per individual will achieve the largest reduction in the transmission potential of a novel infection. For vaccination of susceptible persons, the appropriate risk measure is force of infection; for social distancing, the appropriate risk measure is incidence of infection. Unlike existing methods that rely on detailed knowledge of group-specific transmission rates, the method described here can be implemented using only data that are readily available during an epidemic, and allows ready adaptation as the epidemic progresses. The need to observe risk of infection helps to focus the ongoing planning and design of new infectious disease surveillance programs; from the presented first principles for allocating scarce resources, we can adjust the prioritization of groups for intervention when new observations on an emerging epidemic become available.

Calculating the potential for within-flight transmission of influenza A (H1N1)

BACKGROUND

Clearly air travel, by transporting infectious individuals from one geographic location to another, significantly affects the rate of spread of influenza A (H1N1). However, the possibility of within-flight transmission of H1N1 has not been evaluated; although it is known that smallpox, measles, tuberculosis, SARS and seasonal influenza can be transmitted during commercial flights. Here we present the first quantitative risk assessment to assess the potential for within-flight transmission of H1N1.

METHODS

We model airborne transmission of infectious viral particles of H1N1 within a Boeing 747 using methodology from the field of quantitative microbial risk assessment.

RESULTS

The risk of catching H1N1 will essentially be confined to passengers travelling in the same cabin as the source case. Not surprisingly, we find that the longer the flight the greater the number of infections that can be expected. We calculate that H1N1, even during long flights, poses a low to moderate within-flight transmission risk if the source case travels First Class. Specifically, 0-1 infections could occur during a 5 hour flight, 1-3 during an 11 hour flight and 2-5 during a 17 hour flight. However, within-flight transmission could be significant, particularly during long flights, if the source case travels in Economy Class. Specifically, two to five infections could occur during a 5 hour flight, 5-10 during an 11 hour flight and 7-17 during a 17 hour flight. If the aircraft is only partially loaded, under certain conditions more infections could occur in First Class than in Economy Class. During a 17 hour flight, a greater number of infections would occur in First Class than in Economy if the First Class Cabin is fully occupied, but Economy class is less than 30% full.

CONCLUSIONS

Our results provide insights into the potential utility of air travel restrictions on controlling influenza pandemics in the winter of 2009/2010. They show travel by one infectious individual, rather than causing a single outbreak of H1N1, could cause several simultaneous outbreaks. These results imply that, during a pandemic, quarantining passengers who travel in Economy on long-haul flights could potentially be an important control strategy. Notably, our results show that quarantining passengers who travel First Class would be unlikely to be an effective control strategy.

Breaking the waves: modelling the potential impact of public health measures to defer the epidemic peak of novel influenza A/H1N1

Background

On June 11, 2009, the World Health Organization declared phase 6 of the novel influenza A/H1N1 pandemic. Although by the end of September 2009, the novel virus had been reported from all continents, the impact in most countries of the northern hemisphere has been limited. The return of the virus in a second wave would encounter populations that are still nonimmune and not vaccinated yet. We modelled the effect of control strategies to reduce the spread with the goal to defer the epidemic wave in a country where it is detected in a very early stage.

Methodology/Principal Findings

We constructed a deterministic SEIR model using the age distribution and size of the population of Germany based on the observed number of imported cases and the early findings for the epidemiologic characteristics described by Fraser (Science, 2009). We propose a two-step control strategy with an initial effort to trace, quarantine, and selectively give prophylactic treatment to contacts of the first 100 to 500 cases. In the second step, the same measures are focused on the households of the next 5,000 to 10,000 cases. As a result, the peak of the epidemic could be delayed up to 7.6 weeks if up to 30% of cases are detected. However, the cumulative attack rates would not change. Necessary doses of antivirals would be less than the number of treatment courses for 0.1% of the population. In a sensitivity analysis, both case detection rate and the variation of R0 have major effects on the resulting delay.

Conclusions/Significance

Control strategies that reduce the spread of the disease during the early phase of a pandemic wave may lead to a substantial delay of the epidemic. Since prophylactic treatment is only offered to the contacts of the first 10,000 cases, the amount of antivirals needed is still very limited.

Clinical review: primary influenza viral pneumonia

Primary influenza pneumonia has a high mortality rate during pandemics, not only in immunocompromised individuals and patients with underlying comorbid conditions, but also in young healthy adults. Clinicians should maintain a high index of suspicion for this diagnosis in patients presenting with influenza-like symptoms that progress quickly (2 to 5 days) to respiratory distress and extensive pulmonary involvement. The sensitivity of rapid diagnostic techniques in identifying infections with the pandemic 2009 H1N1v influenza strain is currently suboptimal. The most reliable real-time reverse transcriptase-polymerase chain reaction molecular testing is available in limited clinical settings. Despite 6 months of pandemic circulation, most novel H1N1v pandemic strains remain susceptible to oseltamivir. Ensuring an appropriate oxygenation and ventilation strategy, as well as prompt initiation of antiviral therapy, is essential in management.

Epidemiological characteristics and low case fatality rate of pandemic (H1N1) 2009 in Japan

Pandemic (H1N1) 2009 has been causing large outbreaks in Japan. Yet, the case fatality rate (CFR) remains low and only 85 deaths have been confirmed as of December 17, 2009. Surveillance data was analyzed to define epidemiological characteristics of pandemic (H1N1) 2009 in Japan. It was shown that most of the reported influenza-like illness cases and hospitalizations have occurred in those aged 5-9 years and 10-14 years, in whom CFR is extremely low. However, CFRs are higher in small children (<5 years) and adults. The transmission to these age groups may possibly have been minimized through aggressive suspension of classes in schools.

Infection and death from influenza A H1N1 virus in Mexico: a retrospective analysis

BACKGROUND

In April, 2009, the first cases of influenza A H1N1 were registered in Mexico and associated with an unexpected number of deaths. We report the timing and spread of H1N1 in cases, and explore protective and risk factors for infection, severe disease, and death.

METHODS

We analysed information gathered by the influenza surveillance system from April 28 to July 31, 2009, for patients with influenza-like illness who attended clinics that were part of the Mexican Institute for Social Security network. We calculated odds ratios (ORs) to compare risks of testing positive for H1N1 in those with influenza-like illness at clinic visits, the risk of admission for laboratory-confirmed cases of H1N1, and of death for inpatients according to demographic characteristics, clinical symptoms, seasonal influenza vaccine status, and elapsed time from symptom onset to admission.

FINDINGS

By July 31, 63 479 cases of influenza-like illness were reported; 6945 (11%) cases of H1N1 were confirmed, 6407 (92%) were outpatients, 475 (7%) were admitted and survived, and 63 (<1%) died. Those aged 10-39 years were most affected (3922 [56%]). Mortality rates showed a J-shaped curve, with greatest risk in those aged 70 years and older (10.3%). Risk of infection was lowered in those who had been vaccinated for seasonal influenza (OR 0.65 [95% CI 0.55-0.77]). Delayed admission (1.19 [1.11-1.28] per day) and presence of chronic diseases (6.1 [2.37-15.99]) were associated with increased risk of dying.

INTERPRETATION

Risk communication and hospital preparedness are key factors to reduce mortality from H1N1 infection. Protective effects of seasonal influenza vaccination for the virus need to be investigated.

FUNDING

None.

How necessary is a fast testkit for mitigation of pandemic flu?

It is widely feared that a novel, highly pathogenic, human transmissible influenza virus may evolve that could cause the next global pandemic. Mitigating the spread of such an influenza pandemic would require not only the timely administration of antiviral drugs to those infected, but also the implementation of suitable intervention policies for stunting the spread of the virus. Towards this end, mathematical modelling and simulation studies are crucial as they allow us to evaluate the predicted effectiveness of the various intervention policies before enforcing them. Diagnosis plays a vital role in the overall pandemic management framework by detecting and distinguishing the pathogenic strain from the less threatening seasonal strains and other influenza-like illnesses. This allows treatment and intervention to be deployed effectively, given limited antiviral supplies and other resources. However, the time required to design a fast and accurate testkit for novel strains may limit the role of diagnosis. Herein, we aim to investigate the cost and effectiveness of different diagnostic methods using a stochastic agent-based city-scale model, and then address the issue of whether conventional testing approaches, when used with appropriate intervention policies, can be as effective as fast testkits in containing a pandemic outbreak. We found that for mitigation purposes, fast and accurate testkits are not necessary as long as sufficient medication is given, and are generally recommended only when used with extensive contact tracing and prophylaxis. Additionally, in the event of insufficient medication and fast testkits, the use of slower, conventional testkits together with proper isolation policies while waiting for the diagnostic results can be an equally effective substitute.

Studies needed to address public health challenges of the 2009 H1N1 influenza pandemic: insights from modeling

The 2009 influenza pandemic (H1N1pdm) has completed its first wave in many northern and southern hemisphere populations and many northern hemisphere populations are reporting substantial activity indicating the start of a second wave this autumn. As the global epidemiology of this novel strain unfolds, substantial policy challenges will continue to present themselves for the next 12 to 18 months. Here, we anticipate six public health challenges and identify data that are required for public health decision making. In particular, we suggest studies that will generate data not otherwise available from routine surveillance. Representative serological surveys stand out as a critical source of data with which to reduce uncertainty around policy choices for both pharmaceutical and non-pharmaceutical interventions after the initial wave has passed. Also, monitoring the time course of incidence of severe H1N1pdm cases will give a clear picture of variability in underlying transmissibility of the virus during population wide changes in behavior such as school vacations and other non-pharmaceutical interventions. In addition, we address low resource settings where routine surveillance for influenza has not been established and suggest alternative ways to collect data for the 2009 (and beyond) influenza H1N1 pandemic.

Anthropogenic factors and the risk of highly pathogenic avian influenza H5N1: prospects from a spatial-based model

Beginning in 2003, highly pathogenic avian influenza (HPAI) H5N1 virus spread across Southeast Asia, causing unprecedented epidemics. Thailand was massively infected in 2004 and 2005 and continues today to experience sporadic outbreaks. While research findings suggest that the spread of HPAI H5N1 is influenced primarily by trade patterns, identifying the anthropogenic risk factors involved remains a challenge. In this study, we investigated which anthropogenic factors played a role in the risk of HPAI in Thailand using outbreak data from the “second wave” of the epidemic (3 July 2004 to 5 May 2005) in the country. We first performed a spatial analysis of the relative risk of HPAI H5N1 at the subdistrict level based on a hierarchical Bayesian model. We observed a strong spatial heterogeneity of the relative risk. We then tested a set of potential risk factors in a multivariable linear model. The results confirmed the role of free-grazing ducks and rice-cropping intensity but showed a weak association with fighting cock density. The results also revealed a set of anthropogenic factors significantly linked with the risk of HPAI. High risk was associated strongly with densely populated areas, short distances to a highway junction, and short distances to large cities. These findings highlight a new explanatory pattern for the risk of HPAI and indicate that, in addition to agro-environmental factors, anthropogenic factors play an important role in the spread of H5N1. To limit the spread of future outbreaks, efforts to control the movement of poultry products must be sustained.

Effectiveness and cost-effectiveness of vaccination against pandemic influenza (H1N1) 2009

BACKGROUND

Decisions on the timing and extent of vaccination against pandemic (H1N1) 2009 virus are complex.

OBJECTIVE

To estimate the effectiveness and cost-effectiveness of pandemic influenza (H1N1) vaccination under different scenarios in October or November 2009.

DESIGN

Compartmental epidemic model in conjunction with a Markov model of disease progression.

DATA SOURCES

Literature and expert opinion.

TARGET POPULATION

Residents of a major U.S. metropolitan city with a population of 8.3 million.

TIME HORIZON

Lifetime.

PERSPECTIVE

Societal.

INTERVENTIONS

Vaccination in mid-October or mid-November 2009.

OUTCOME MEASURES

Infections and deaths averted, costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness.

RESULTS OF BASE-CASE ANALYSIS

Assuming each primary infection causes 1.5 secondary infections, vaccinating 40% of the population in October or November would be cost-saving. Vaccination in October would avert 2051 deaths, gain 69 679 QALYs, and save $469 million compared with no vaccination; vaccination in November would avert 1468 deaths, gain 49 422 QALYs, and save $302 million.

RESULTS OF SENSITIVITY ANALYSIS

Vaccination is even more cost-saving if longer incubation periods, lower rates of infectiousness, or increased implementation of nonpharmaceutical interventions delay time to the peak of the pandemic. Vaccination saves fewer lives and is less cost-effective if the epidemic peaks earlier than mid-October.

LIMITATIONS

The model assumed homogenous mixing of case-patients and contacts; heterogeneous mixing would result in faster initial spread, followed by slower spread. Additional costs and savings not included in the model would make vaccination more cost-saving.

CONCLUSION

Earlier vaccination against pandemic (H1N1) 2009 prevents more deaths and is more cost-saving. Complete population coverage is not necessary to reduce the viral reproductive rate sufficiently to help shorten the pandemic.

PRIMARY FUNDING SOURCE

Agency for Healthcare Research and Quality and National Institute on Drug Abuse.

Mortality from pandemic A/H1N1 2009 influenza in England: public health surveillance study

OBJECTIVE

To establish mortality from pandemic A/H1N1 2009 influenza up to 8 November 2009.

DESIGN

Investigation of all reported deaths related to pandemic A/H1N1 in England.

SETTING

Mandatory reporting systems established in acute hospitals and primary care.

PARTICIPANTS

Physicians responsible for the patient.

MAIN OUTCOME MEASURES

Numbers of deaths from influenza combined with mid-range estimates of numbers of cases of influenza to calculate age specific case fatality rates. Underlying conditions, time course of illness, and antiviral treatment.

RESULTS

With the official mid-range estimate for incidence of pandemic A/H1N1, the overall estimated case fatality rate was 26 (range 11-66) per 100 000. It was lowest for children aged 5-14 (11 (range 3-36) per 100 000) and highest for those aged >or=65 (980 (range 300-3200) per 100 000). In the 138 people in whom the confirmed cause of death was pandemic A/H1N1, the median age was 39 (interquartile range 17-57). Two thirds of patients who died (92, 67%) would now be eligible for the first phase of vaccination in England. Fifty (36%) had no, or only mild, pre-existing illness. Most patients (108, 78%) had been prescribed antiviral drugs, but of these, 82 (76%) did not receive them within the first 48 hours of illness.

CONCLUSIONS

Viewed statistically, mortality in this pandemic compares favourably with 20th century influenza pandemics. A lower population impact than previous pandemics, however, is not a justification for public health inaction. Our data support the priority vaccination of high risk groups. We observed delayed antiviral use in most fatal cases, which suggests an opportunity to reduce deaths by making timely antiviral treatment available, although the lack of a control group limits the ability to extrapolate from this observation. Given that a substantial minority of deaths occur in previously healthy people, there is a case for extending the vaccination programme and for continuing to make early antiviral treatment widely available.

Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies

BACKGROUND

Individual strategies in pandemic preparedness plans may not reduce the impact of an influenza pandemic.

METHODS

We searched modeling publications through PubMed and associated references from 1990 to 30 September 2009. Inclusion criteria were modeling papers quantifying the effectiveness of combination strategies, both pharmaceutical and non-pharmaceutical.

RESULTS

Nineteen modeling papers on combination strategies were selected. Four studies examined combination strategies on a global scale, 14 on single countries, and one on a small community. Stochastic individual-based modeling was used in nine studies, stochastic meta-population modeling in five, and deterministic compartmental modeling in another five. As part of combination strategies, vaccination was explored in eight studies, antiviral prophylaxis and/or treatment in 16, area or household quarantine in eight, case isolation in six, social distancing measures in 10 and air travel restriction in six studies. Two studies suggested a high probability of successful influenza epicenter containment with combination strategies under favorable conditions. During a pandemic, combination strategies delayed spread, reduced overall number of cases, and delayed and reduced peak attack rate more than individual strategies. Combination strategies remained effective at high reproductive numbers compared with single strategy. Global cooperative strategies, including redistribution of antiviral drugs, were effective in reducing the global impact and attack rates of pandemic influenza.

CONCLUSION

Combination strategies increase the effectiveness of individual strategies. They include pharmaceutical (antiviral agents, antibiotics and vaccines) and non-pharmaceutical interventions (case isolation, quarantine, personal hygiene measures, social distancing and travel restriction). Local epidemiological and modeling studies are needed to validate efficacy and feasibility.

Optimizing allocation for a delayed influenza vaccination campaign

During unexpected infectious disease outbreaks, public health agencies must make effective use of limited resources. Vaccine distribution may be delayed and staggered through time, as underscored by the 2009 H1N1 influenza pandemic. Using a mathematical model parametrized with data from the 2009 H1N1 pandemic, we found that optimal allocations of vaccine among people in different age groups and people with high-risk conditions depends on the schedule of vaccine availability relative to the progress of the epidemic. For the projected schedule of H1N1 vaccine availability, the optimal strategy to reduce influenza-related deaths is to initial target high-risk people, followed by school-aged children (5-17) and then young adults (18-44). The optimal strategy to minimize hospitalizations, however, is to target ages 5-44 throughout the vaccination campaign, with only a tiny amount of vaccine used on high-risk people. We find that optimizing at each vaccine release time independently does not give the overall optimal strategy. In this manuscript, we derive policy recommendations for 2009 H1N1 vaccine allocation using a mathematical model. In addition, our optimization procedures, which consider staggered releases over the entire epidemic altogether, are applicable to other outbreaks where not all supplies are available initially.

Management of blood supplies during an influenza pandemic

BACKGROUND

Blood supplies are delicate resources, particularly vulnerable to incidents affecting the health of donors. The critical impact of a pandemic on the availability of red blood cells (RBCs) has been demonstrated in previous research; however, a detailed estimate of the expected deficit is missing. This has become a priority issue in the face of the current influenza pandemic.

STUDY DESIGN AND METHODS

Data from several major blood donation services were used to analyze management of blood supplies in Germany. Routine management of RBCs was extrapolated to epidemic and pandemic situations using computer simulations with a mathematical model that allows for analysis of deficits in blood supplies.

RESULTS

Routine management and distribution of RBCs are driven by supply, which has marked fluctuations but does not appear to have seasonality. There seems to be a remarkable elasticity in the demand for RBCs that helps to mitigate minor crises in supply, but this is likely to be overstretched during a severe pandemic.

CONCLUSION

The supply-driven management of RBCs in Germany implies that assessment of severity of shortages due to a pandemic depends on detailed knowledge about the fraction of transfusions that do not allow for postponement. Pandemic preparedness should include criteria for prioritization of transfusions.

Novel swine-origin influenza virus A (H1N1): the first pandemic of the 21st century

An influenza epidemic was detected in April 2009 at the border between the United States and Mexico. The virus was identified soon after to be a swine-origin influenza virus A (S-OIV A) (H1N1). This virus has an HA gene that is derived from the 1918 swine influenza virus and other genes from human, avian, and Eurasian swine influenza viruses. Clinically, it behaves similarly to seasonal influenza. The only differentiating characteristics are vomiting and diarrhea in a quarter of infected patients, which are rare in seasonal influenza. On June 11, 2009, the World Health Organization declared the first pandemic of the 21st century, caused by S-OIV A (H1N1). Vaccination is the only way to dampen this pandemic. Many questions await answers, including the clinical impact of the pandemic, optimal doses of vaccine, and the future destiny of the virus. A breakthrough in vaccinology against influenza is needed to address the recurring influenza pandemic.

Adaptive strategies of the influenza virus polymerase for replication in humans

Transmission of influenza viruses into the human population requires surmounting barriers to cross-species infection. Changes in the influenza polymerase overcome one such barrier. Viruses isolated from birds generally contain polymerases with the avian-signature glutamic acid at amino acid 627 in the PB2 subunit. These polymerases display restricted activity in human cells. An adaptive change in this residue from glutamic acid to the human-signature lysine confers high levels of polymerase activity in human cells. This mutation permits escape from a species-specific restriction factor that targets polymerases from avian viruses. A 2009 swine-origin H1N1 influenza A virus recently established a pandemic infection in humans, even though the virus encodes a PB2 with the restrictive glutamic acid at amino acid 627. We show here that the 2009 H1N1 virus has acquired second-site suppressor mutations in its PB2 polymerase subunit that convey enhanced polymerase activity in human cells. Introduction of this polymorphism into the PB2 subunit of a primary avian isolate also increased polymerase activity and viral replication in human and porcine cells. An alternate adaptive strategy has also been identified, whereby introduction of a human PA subunit into an avian polymerase overcomes restriction in human cells. These data reveal a strategy used by the 2009 H1N1 influenza A virus and identify other pathways by which avian and swine-origin viruses may evolve to enhance replication, and potentially pathogenesis, in humans.

Modeling the critical care demand and antibiotics resources needed during the Fall 2009 wave of influenza A(H1N1) pandemic

While the H1N1 pandemic is reaching high levels of influenza activity in the Northern Hemisphere, the attention focuses on the ability of national health systems to respond to the expected massive influx of additional patients. Given the limited capacity of health care providers and hospitals and the limited supplies of antibiotics, it is important to predict the potential demand on critical care to assist planning for the management of resources and plan for additional stockpiling. We develop a disease model that considers the development of influenza-associated complications and incorporate it into a global epidemic model to assess the expected surge in critical care demands due to viral and bacterial pneumonia. Based on the most recent estimates of complication rates, we predict the expected peak number of intensive care unit beds and the stockpile of antibiotic courses needed for the current pandemic wave. The effects of dynamic vaccination campaigns, and of variations of the relative proportion of bacterial co-infection in complications and different length of staying in the intensive care unit are explored.

Epidemic dynamics at the human-animal interface

Few infectious diseases are entirely human-specific: Most human pathogens also circulate in animals or else originated in nonhuman hosts. Influenza, plague, and trypanosomiasis are classic examples of zoonotic infections that transmit from animals to humans. The multihost ecology of zoonoses leads to complex dynamics, and analytical tools, such as mathematical modeling, are vital to the development of effective control policies and research agendas. Much attention has focused on modeling pathogens with simpler life cycles and immediate global urgency, such as influenza and severe acute respiratory syndrome. Meanwhile, vector-transmitted, chronic, and protozoan infections have been neglected, as have crucial processes such as cross-species transmission. Progress in understanding and combating zoonoses requires a new generation of models that addresses a broader set of pathogen life histories and integrates across host species and scientific disciplines.

Modeling gene sequences over time in 2009 H1N1 influenza A virus populations

Background

A sudden emergence of Influenza A Virus (IAV) infections with a new pandemic H1N1 IAV is taking place since April of 2009. In order to gain insight into the mode of evolution of these new H1N1 strains, we performed a Bayesian coalescent Markov chain Monte Carlo (MCMC) analysis of full-length neuraminidase (NA) gene sequences of 62 H1N1 IAV strains (isolated from March 30^th to by July 28^th, 2009).

Results

The results of these studies revealed that the expansion population growth model was the best to fit the sequence data. A mean of evolutionary change of 7.84 × 10^-3 nucleotide substitutions per site per year (s/s/y) was obtained for the NA gene. A significant contribution of first codon position to this mean rate was observed. Maximum clade credibility trees revealed a rapid diversification of NA genes in different genetic lineages, all of them containing Oseltamivir-resistant viruses of very recent emergence. Mapping of naturally occurring amino acid substitutions in the NA protein from 2009 H1N1 IAV circulating in 62 different patients revealed that substitutions are distributed all around the surface of the molecule, leaving the hydrophobic core and the catalytic site essentially untouched.

Conclusion

High evolutionary rates and fast population growth have contributed to the initial transmission dynamics of 2009 H1N1 IAV. Naturally occurring substitutions are preferentially located at the protein surface and do not interfere with the NA active site. Antigenic regions relevant for vaccine development can differ from previous vaccine strains and vary among patients.

Detection of pandemic influenza A/H1N1/2009 virus by real-time reverse transcription polymerase chain reaction

The first case of pandemic influenza A/H1N1/2009 infection was reported in Mexico in mid-April, 2009, and to date the new H1N1 virus has spread to over 160 countries. Therefore, it is important to obtain reliable epidemiological data on the spread of this virus by novel molecular methods can be developed in detection of this new infectious agent. A new method was developed for detection of the pandemic influenza A/H1N1/2009 using real-time reverse transcription polymerase chain reaction (RT-PCR). Direct comparison with the specific primers and probes recommended by the World Health Organization (WHO) demonstrates that the new method has a much greater sensitivity, and may thus be employed as a rapid, alternative method in detecting of the pandemic influenza A/H1N1/2009 virus.

Livestock infectious diseases and zoonoses

Infectious diseases of livestock are a major threat to global animal health and welfare and their effective control is crucial for agronomic health, for safeguarding and securing national and international food supplies and for alleviating rural poverty in developing countries. Some devastating livestock diseases are endemic in many parts of the world and threats from old and new pathogens continue to emerge, with changes to global climate, agricultural practices and demography presenting conditions that are especially favourable for the spread of arthropod-borne diseases into new geographical areas. Zoonotic infections that are transmissible either directly or indirectly between animals and humans are on the increase and pose significant additional threats to human health and the current pandemic status of new influenza A (H1N1) is a topical example of the challenge presented by zoonotic viruses. In this article, we provide a brief overview of some of the issues relating to infectious diseases of livestock, which will be discussed in more detail in the papers that follow.

Early assessment of anxiety and behavioral response to novel swine-origin influenza A(H1N1)

BACKGROUND

Since late April, 2009, a novel influenza virus A (H1N1), generally referred to as the "swine flu," has spread around the globe and infected hundreds of thousands of people. During the first few days after the initial outbreak in Mexico, extensive media coverage together with a high degree of uncertainty about the transmissibility and mortality rate associated with the virus caused widespread concern in the population. The spread of an infectious disease can be strongly influenced by behavioral changes (e.g., social distancing) during the early phase of an epidemic, but data on risk perception and behavioral response to a novel virus is usually collected with a substantial delay or after an epidemic has run its course.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we report the results from an online survey that gathered data (n = 6,249) about risk perception of the Influenza A(H1N1) outbreak during the first few days of widespread media coverage (April 28-May 5, 2009). We find that after an initially high level of concern, levels of anxiety waned along with the perception of the virus as an immediate threat. Overall, our data provide evidence that emotional status mediates behavioral response. Intriguingly, principal component analysis revealed strong clustering of anxiety about swine flu, bird flu and terrorism. All three of these threats receive a great deal of media attention and their fundamental uncertainty is likely to generate an inordinate amount of fear vis-a-vis their actual threat.

CONCLUSIONS/SIGNIFICANCE

Our results suggest that respondents' behavior varies in predictable ways. Of particular interest, we find that affective variables, such as self-reported anxiety over the epidemic, mediate the likelihood that respondents will engage in protective behavior. Understanding how protective behavior such as social distancing varies and the specific factors that mediate it may help with the design of epidemic control strategies.

Early assessment of anxiety and behavioral response to novel swine-origin influenza A(H1N1)

BACKGROUND

Since late April, 2009, a novel influenza virus A (H1N1), generally referred to as the "swine flu," has spread around the globe and infected hundreds of thousands of people. During the first few days after the initial outbreak in Mexico, extensive media coverage together with a high degree of uncertainty about the transmissibility and mortality rate associated with the virus caused widespread concern in the population. The spread of an infectious disease can be strongly influenced by behavioral changes (e.g., social distancing) during the early phase of an epidemic, but data on risk perception and behavioral response to a novel virus is usually collected with a substantial delay or after an epidemic has run its course.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we report the results from an online survey that gathered data (n = 6,249) about risk perception of the Influenza A(H1N1) outbreak during the first few days of widespread media coverage (April 28-May 5, 2009). We find that after an initially high level of concern, levels of anxiety waned along with the perception of the virus as an immediate threat. Overall, our data provide evidence that emotional status mediates behavioral response. Intriguingly, principal component analysis revealed strong clustering of anxiety about swine flu, bird flu and terrorism. All three of these threats receive a great deal of media attention and their fundamental uncertainty is likely to generate an inordinate amount of fear vis-a-vis their actual threat.

CONCLUSIONS/SIGNIFICANCE

Our results suggest that respondents' behavior varies in predictable ways. Of particular interest, we find that affective variables, such as self-reported anxiety over the epidemic, mediate the likelihood that respondents will engage in protective behavior. Understanding how protective behavior such as social distancing varies and the specific factors that mediate it may help with the design of epidemic control strategies.

Estimated epidemiologic parameters and morbidity associated with pandemic H1N1 influenza

BACKGROUND

In the face of an influenza pandemic, accurate estimates of epidemiologic parameters are required to help guide decision-making. We sought to estimate epidemiologic parameters for pandemic H1N1 influenza using data from initial reports of laboratory-confirmed cases.

METHODS

We obtained data on laboratory-confirmed cases of pandemic H1N1 influenza reported in the province of Ontario, Canada, with dates of symptom onset between Apr. 13 and June 20, 2009. Incubation periods and duration of symptoms were estimated and fit to parametric distributions. We used competing-risk models to estimate risk of hospital admission and case-fatality rates. We used a Markov Chain Monte Carlo model to simulate disease transmission.

RESULTS

The median incubation period was 4 days and the duration of symptoms was 7 days. Recovery was faster among patients less than 18 years old than among older patients (hazard ratio 1.23, 95% confidence interval 1.06-1.44). The risk of hospital admission was 4.5% (95% CI 3.8%-5.2%) and the case-fatality rate was 0.3% (95% CI 0.1%-0.5%). The risk of hospital admission was highest among patients less than 1 year old and those 65 years or older. Adults more than 50 years old comprised 7% of cases but accounted for 7 of 10 initial deaths (odds ratio 28.6, 95% confidence interval 7.3-111.2). From the simulation models, we estimated the following values (and 95% credible intervals): a mean basic reproductive number (R0, the number of new cases created by a single primary case in a susceptible population) of 1.31 (1.25-1.38), a mean latent period of 2.62 (2.28-3.12) days and a mean duration of infectiousness of 3.38 (2.06-4.69) days. From these values we estimated a serial interval (the average time from onset of infectiousness in a case to the onset of infectiousness in a person infected by that case) of 4-5 days.

INTERPRETATION

The low estimates for R0 indicate that effective mitigation strategies may reduce the final epidemic impact of pandemic H1N1 influenza.

Adaptive vaccination strategies to mitigate pandemic influenza: Mexico as a case study

BACKGROUND

We explore vaccination strategies against pandemic influenza in Mexico using an age-structured transmission model calibrated against local epidemiological data from the Spring 2009 A(H1N1) pandemic.

METHODS AND FINDINGS

In the context of limited vaccine supplies, we evaluate age-targeted allocation strategies that either prioritize youngest children and persons over 65 years of age, as for seasonal influenza, or adaptively prioritize age groups based on the age patterns of hospitalization and death monitored in real-time during the early stages of the pandemic. Overall the adaptive vaccination strategy outperformed the seasonal influenza vaccination allocation strategy for a wide range of disease and vaccine coverage parameters.

CONCLUSIONS

This modeling approach could inform policies for Mexico and other countries with similar demographic features and vaccine resources issues, with regard to the mitigation of the S-OIV pandemic. We also discuss logistical issues associated with the implementation of adaptive vaccination strategies in the context of past and future influenza pandemics.

Post-exposure prophylaxis during pandemic outbreaks

BACKGROUND

With the rise of the second pandemic wave of the novel influenza A (H1N1) virus in the current season in the Northern Hemisphere, pandemic plans are being carefully re-evaluated, particularly for the strategic use of antiviral drugs. The recent emergence of oseltamivir-resistant in treated H1N1 patients has raised concerns about the prudent use of neuraminidase inhibitors for both treatment of ill individuals and post-exposure prophylaxis of close contacts.

METHODS

We extended an established population dynamical model of pandemic influenza with treatment to include post-exposure prophylaxis of close contacts. Using parameter estimates published in the literature, we simulated the model to evaluate the combined effect of treatment and prophylaxis in minimizing morbidity and mortality of pandemic infections in the context of transmissible drug resistance.

RESULTS

We demonstrated that, when transmissible resistant strains are present, post-exposure prophylaxis can promote the spread of resistance, especially when combined with aggressive treatment. For a given treatment level, there is an optimal coverage of prophylaxis that minimizes the total number of infections (final size) and this coverage decreases as a higher proportion of infected individuals are treated. We found that, when treatment is maintained at intermediate levels, limited post-exposure prophylaxis provides an optimal strategy for reducing the final size of the pandemic while minimizing the total number of deaths. We tested our results by performing a sensitivity analysis over a range of key model parameters and observed that the incidence of infection depends strongly on the transmission fitness of resistant strains.

CONCLUSION

Our findings suggest that, in the presence of transmissible drug resistance, strategies that prioritize the treatment of only ill individuals, rather than the prophylaxis of those suspected of being exposed, are most effective in reducing the morbidity and mortality of the pandemic. The impact of post-exposure prophylaxis depends critically on the treatment level and the transmissibility of resistant strains and, therefore, enhanced surveillance and clinical monitoring for resistant mutants constitutes a key component of any comprehensive plan for antiviral drug use during an influenza pandemic.

An update on swine-origin influenza virus A/H1N1: a review

Influenza viruses cause annual epidemics and occasional pandemics that have claimed the lives of millions. The emergence of new strains will continue to pose challenges to public health and the scientific communities. The recent flu pandemic caused by a swine-origin influenza virus A/H1N1 (S-OIV) presents an opportunity to examine virulence factors, the spread of the infection and to prepare for major influenza outbreaks in the future. The virus contains a novel constellation of gene segments, the nearest known precursors being viruses found in swine and it probably arose through reassortment of two viruses of swine origin. Specific markers for virulence can be evaluated in the viral genome, PB1-F2 is a molecular marker of pathogenicity but is not present in the new S-OIV. While attention was focused on a threat of an avian influenza H5N1 pandemic emerging from Asia, a novel influenza virus of swine origin emerged in North America, and is now spreading worldwide. However, S-OIV demonstrates that even serotypes already encountered in past human pandemics may constitute new pandemic threats. There are concerns that this virus may mutate or reassort with existing influenza viruses giving rise to more transmissible or more pathogenic viruses. The 1918 Spanish flu pandemic virus was relatively mild in its first wave and acquired more virulence when it returned in the winter. Thus preparedness on a global scale against a potential more virulent strain is highly recommended. Most isolates of the new S-OIVs are susceptible to neuraminidase inhibitors, and currently a vaccine against the pandemic strain is being manufactured and will be available this fall. This review summarizes the current information on the new pandemic swine-origin influenza virus A/H1N1.

Pandemic influenza vaccines - the challenges

Recent years' enzootic spread of highly pathogenic H5N1 virus among poultry and the many lethal zoonoses in its wake has stimulated basic and applied pandemic vaccine research. The quest for an efficacious, affordable and timely accessible pandemic vaccine has been high on the agenda. When a variant H1N1 strain of swine origin emerged as a pandemic virus, it surprised many, as this subtype is well-known to man as a seasonal virus. This review will cover some difficult vaccine questions, such as the immunological challenges, the new production platforms, and the limited supply and global equity issues.

The severity of pandemic H1N1 influenza in the United States, from April to July 2009: a Bayesian analysis

BACKGROUND

Accurate measures of the severity of pandemic (H1N1) 2009 influenza (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources.

METHODS AND FINDINGS

We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data--medically attended cases in Milwaukee or self-reported influenza-like illness (ILI) in New York--were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information, and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated an sCFR of 0.048% (95% credible interval [CI] 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately 7-9 x lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5-17 y. sCHR appears to be lowest in persons aged 5-17; our data were too sparse to allow us to determine the group in which it was the highest.

CONCLUSIONS

These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with the greatest impact in children aged 0-4 and adults 18-64. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the total proportion of the population symptomatically infected were lower than assumed.

Diagnosis of influenza viruses with special reference to novel H1N1 2009 influenza virus

On 15 April and 17 April 2009, novel swineorigin influenza A (H1N1) virus was identifi ed in specimens obtained from two epidemiologically unlinked patients in the United States. The ongoing outbreak of novel H1N1 2009 influenza (swine influenza) has caused more than 3,99,232 laboratory confi rmed cases of pandemic influenza H1N1 and over 4735 deaths globally. This novel 2009 influenza virus designated as H1N1 A/swine/California/04/2009 virus is not zoonotic swine flu and is transmitted from person to person and has higher transmissibility then that of seasonal influenza viruses. In India the novel H1N1 virus infection has been reported from all over the country. A total of 68,919 samples from clinically suspected persons have been tested for influenza A H1N1 across the country and 13,330 (18.9%) of them have been found positive with 427 deaths. At the All India Institute of Medical Sciences, New Delhi India, we tested 1096 clinical samples for the presence of novel H1N1 influenza virus and seasonal influenza viruses. Of these 1096 samples, 194 samples (17.7%) were positive for novel H1N1 influenza virus and 197 samples (18%) were positive for seasonal influenza viruses. During outbreaks of emerging infectious diseases accurate and rapid diagnosis is critical for minimizing further spread through timely implementation of appropriate vaccines and antiviral treatment. Since the symptoms of novel H1N1 influenza infection are not specifi c, laboratory confi rmation of suspected cases is of prime importance.

On the origin of influenza A hemagglutinin

Recent advances in phylogenetic methods have produced some reassessments of the ages of the most recent common ancestor of hemagglutinin proteins in known strains of influenza A. This paper applies Bayesian phylogenetic analysis implemented in BEAST to date the nodes on the influenza A hemagglutinin tree. The most recent common ancestor (MRCA) of influenza A hemagglutinin proteins is located with 95% confidence between 517 and 1497 of the Common Era (AD), with the center of the probability distribution at 1056 AD. The implications of this revised dating for both historical and current epidemiology are discussed. Influenza A can be seen as an emerging disease of mediaeval and early modern times.

Influenza A(H1N1)v pandemic in the dialysis population: first wave results from an international survey

BACKGROUND

After the first cases of influenza A(H1N1)v in Mexico and the USA became public, Fresenius Medical Care established a case-based reporting of cases for all of its dialysis clinics located in Europe, Middle East, Africa and Latin America. This paper aims to describe mortality rates of patients on dialysis and to assess the risk profiles.

METHODS

The survey was developed in Lotus Notes with a secure browser-based form. The form was open to 602 Fresenius Medical Care clinics located in Europe, Middle East, Africa and Latin America.

RESULTS

As of 3 September 2009, 306 cases have been reported by 85 clinics located in Argentina, Chile, Brazil, UK and Spain. The mean age was 52.7 +/- 17.7 years. The majority of cases (70.6%) were from 20- to 44-year-old and 45- to 64-year-old subgroups. Moreover, 35.3% had no associated comorbidity, 20.3% had two and 4.6% three comorbidities, with heart disease being the most frequent. Fever was the most common symptom, present in 94.4% of the cases, followed by cough (78.8%) and muscle and joint pain (69.3%). Eighty-seven percent were treated with antiviral agents, the majority with oseltamivir. One hundred and three patients (34%) were admitted to hospital because of influenza. Pneumonia was reported for 69 cases, out of which 52 patients belonged to a high-risk group. Mortality rate of all the patients (confirmed, probable and suspected cases) was around 5%.

CONCLUSION

End-stage renal disease patients should be included in first ranks of the priority list for the influenza A (H1N1)v vaccine, as already advocated by some healthcare authorities.

A Serine12Stop mutation in PB1-F2 of the 2009 pandemic (H1N1) influenza A: a possible reason for its enhanced transmission and pathogenicity to humans

As the scientific community scrambles to define the ancestry and lineages of the eight segments of new pandemic H1N1 strain, we looked for unique genetic events in this virus's genome to explain the newly found enhanced virulence and transmissibility among humans. Genome annotations of this virus identified a stop mutation replacing serine at codon 12 (S12Stop) of the PB1-F2 protein, a virulence factor in influenza A viruses. Here, we discuss the significance of this finding and how it may contribute to host specialization, explaining the virtual absence of the H1N1 influenza A virus strain in pig populations. This finding is expected to lead to a better understanding of the transmission and pathogenesis of the 2009 pandemic strain.

Assessment of intervention strategies against a novel influenza epidemic using an individual-based model

OBJECTIVES

The objective of this study was to assess intervention strategies against a novel influenza epidemic through simulations of various scenarios in Sapporo city, Hokkaido, Japan. A series of interventions were examined: administration of antiviral drugs by two approaches [targeted antiviral prophylaxis (TAP) and school-age targeted antiviral prophylaxis (STAP)], school closure, restraint, and combinations of these four interventions.

METHODS

In order to generate a more realistic situation, we constructed an individual-based model (IBM) for the transmission of influenza in which each individual was assigned personal information on the basis of the National Census and Employment Status Survey of Sapporo city. In addition, data on high-risk casual contact groups commuting in crowded trains and buses were obtained from a census on transportation modes and introduced into the model. Observational data from previous pandemics were used for the epidemiological parameters.

RESULTS

Both TAP and STAP interventions were highly effective in suppressing the spread of infection during the early period of an outbreak, but STAP was inferior to TAP in terms of the ripple effect of the administration of antiviral drugs. School closure and restraint were able to bring about a delay in the peak of infection. The combination of TAP, school closure, and restraint interventions were highly effective in decreasing the total number of patients and shortening the epidemic period.

CONCLUSIONS

Based on the simulation results, we recommend implementing TAP together with both school closure and restraint as strategies against a future novel influenza outbreak.

Immunization with live attenuated influenza viruses that express altered NS1 proteins results in potent and protective memory CD8+ T-cell responses

The generation of vaccines that induce long-lived protective immunity against influenza virus infections remains a challenging goal. Ideally, vaccines should elicit effective humoral and cellular immunity to protect an individual from infection or disease. Cross-reactive T- and B-cell responses that are elicited by live virus infections may provide such broad protection. Optimal induction of T-cell responses involves the action of type I interferons (IFN-I). Influenza virus expressed nonstructural protein 1 (NS1) functions as an inhibitor of IFN-I and promotes viral growth. We wanted to examine the priming of CD8(+) T-cell responses to influenza virus in the absence of this inhibition of IFN-I production. We generated recombinant mouse-adapted influenza A/PR/8/34 viruses with NS1 truncations and/or deletions that also express the gp33-41 epitope from lymphocytic choriomeningitis virus. Intranasal infection of mice with the attenuated viruses primed long-lived T- and B-cell responses despite significantly reduced viral replication in the lungs compared to wild-type virus. Antigen-specific CD8(+) T cells expanded upon rechallenge and generated increased protective memory T-cell populations after boosting. These results show that live attenuated influenza viruses expressing truncated NS1 proteins can prime protective immunity and may have implications for the design of novel modified live influenza virus vaccines.

Pandemic H1N1 2009 influenza A virus induces weak cytokine responses in human macrophages and dendritic cells and is highly sensitive to the antiviral actions of interferons

In less than 3 months after the first cases of swine origin 2009 influenza A (H1N1) virus infections were reported from Mexico, WHO declared a pandemic. The pandemic virus is antigenically distinct from seasonal influenza viruses, and the majority of human population lacks immunity against this virus. We have studied the activation of innate immune responses in pandemic virus-infected human monocyte-derived dendritic cells (DC) and macrophages. Pandemic A/Finland/553/2009 virus, representing a typical North American/European lineage virus, replicated very well in these cells. The pandemic virus, as well as the seasonal A/Brisbane/59/07 (H1N1) and A/New Caledonia/20/99 (H1N1) viruses, induced type I (alpha/beta interferon [IFN-alpha/beta]) and type III (IFN-lambda1 to -lambda3) IFN, CXCL10, and tumor necrosis factor alpha (TNF-alpha) gene expression weakly in DCs. Mouse-adapted A/WSN/33 (H1N1) and human A/Udorn/72 (H3N2) viruses, instead, induced efficiently the expression of antiviral and proinflammatory genes. Both IFN-alpha and IFN-beta inhibited the replication of the pandemic (H1N1) virus. The potential of IFN-lambda3 to inhibit viral replication was lower than that of type I IFNs. However, the pandemic virus was more sensitive to the antiviral IFN-lambda3 than the seasonal A/Brisbane/59/07 (H1N1) virus. The present study demonstrates that the novel pandemic (H1N1) influenza A virus can readily replicate in human primary DCs and macrophages and efficiently avoid the activation of innate antiviral responses. It is, however, highly sensitive to the antiviral actions of IFNs, which may provide us an additional means to treat severe cases of infection especially if significant drug resistance emerges.

From where did the 2009 'swine-origin' influenza A virus (H1N1) emerge?

The swine-origin influenza A (H1N1) virus that appeared in 2009 and was first found in human beings in Mexico, is a reassortant with at least three parents. Six of the genes are closest in sequence to those of H1N2 'triple-reassortant' influenza viruses isolated from pigs in North America around 1999-2000. Its other two genes are from different Eurasian 'avian-like' viruses of pigs; the NA gene is closest to H1N1 viruses isolated in Europe in 1991-1993, and the MP gene is closest to H3N2 viruses isolated in Asia in 1999-2000. The sequences of these genes do not directly reveal the immediate source of the virus as the closest were from isolates collected more than a decade before the human pandemic started. The three parents of the virus may have been assembled in one place by natural means, such as by migrating birds, however the consistent link with pig viruses suggests that human activity was involved. We discuss a published suggestion that unsampled pig herds, the intercontinental live pig trade, together with porous quarantine barriers, generated the reassortant. We contrast that suggestion with the possibility that laboratory errors involving the sharing of virus isolates and cultured cells, or perhaps vaccine production, may have been involved. Gene sequences from isolates that bridge the time and phylogenetic gap between the new virus and its parents will distinguish between these possibilities, and we suggest where they should be sought. It is important that the source of the new virus be found if we wish to avoid future pandemics rather than just trying to minimize the consequences after they have emerged. Influenza virus is a very significant zoonotic pathogen. Public confidence in influenza research, and the agribusinesses that are based on influenza's many hosts, has been eroded by several recent events involving the virus. Measures that might restore confidence include establishing a unified international administrative framework coordinating surveillance, research and commercial work with this virus, and maintaining a registry of all influenza isolates.

Influenza--insights from mathematical modelling

BACKGROUND

When the first cases of a new infectious disease appear, questions arise about the further course of the epidemic and about the appropriate interventions to be taken to protect individuals and the public as a whole. Mathematical models can help answer these questions. In this article, the authors describe basic concepts in the mathematical modelling of infectious diseases, illustrate their use with a simple example, and present the results of influenza models.

METHOD

Description of the mathematical modelling of infectious diseases and selective review of the literature.

RESULTS

The two fundamental concepts of mathematical modelling of infectious diseases-the basic reproduction number and the generation time-allow a better understanding of the course of an epidemic. Modelling studies based on past influenza epidemics suggest that the rise of the epidemic curve can be slowed at the beginning of the epidemic by isolating ill persons and giving prophylactic medications to their contacts. Later on in the course of the epidemic, restricting the number of contacts (e.g., by closing schools) may mitigate the epidemic but will only have a limited effect on the total number of persons who contract the disease.

CONCLUSION

Mathematical modelling is a valuable tool for understanding the dynamics of an epidemic and for planning and evaluating interventions.

Evolutionary trends of A(H1N1) influenza virus hemagglutinin since 1918

The Pandemic (H1N1) 2009 is spreading to numerous countries and causing many human deaths. Although the symptoms in humans are mild at present, fears are that further mutations in the virus could lead to a potentially more dangerous outbreak in subsequent months. As the primary immunity-eliciting antigen, hemagglutinin (HA) is the major agent for host-driven antigenic drift in A(H3N2) virus. However, whether and how the evolution of HA is influenced by existing immunity is poorly understood for A(H1N1). Here, by analyzing hundreds of A(H1N1) HA sequences since 1918, we show the first evidence that host selections are indeed present in A(H1N1) HAs. Among a subgroup of human A(H1N1) HAs between 1918∼2008, we found strong diversifying (positive) selection at HA₁ 156 and 190. We also analyzed the evolutionary trends at HA₁ 190 and 225 that are critical determinants for receptor-binding specificity of A(H1N1) HA. Different A(H1N1) viruses appeared to favor one of these two sites in host-driven antigenic drift: epidemic A(H1N1) HAs favor HA₁ 190 while the 1918 pandemic and swine HAs favor HA₁ 225. Thus, our results highlight the urgency to understand the interplay between antigenic drift and receptor binding in HA evolution, and provide molecular signatures for monitoring future antigenically drifted 2009 pandemic and seasonal A(H1N1) influenza viruses.

Estimate of Novel Influenza A/H1N1 cases in Mexico at the early stage of the pandemic with a spatially structured epidemic model

Determining the number of cases in an epidemic is fundamental to properly evaluate several disease features of high relevance for public health policies such as mortality, morbidity or hospitalization rates. Surveillance efforts are however incomplete especially at the early stage of an outbreak due to the ongoing learning process about the disease characteristics. An example of this is represented by the number of H1N1 influenza cases in Mexico during the first months of the current pandemic. Several estimates using backtrack calculation based on imported cases from Mexico in other countries point out that the actual number of cases was likely orders of magnitude larger than the number of confirmed cases. Realistic computational models fed with the best available estimates of the basic disease parameters can provide an ab-initio calculation of the number of cases in Mexico as other countries. Here we use the Global Epidemic and Mobility (GLEaM) model to obtain estimates of the size of the epidemic in Mexico as well as of imported cases at the end of April and beginning of May. We find that the reference range for the number of cases in Mexico on April 30th is 121,000 to 1,394,000 in good agreement with the recent estimates by Lipsitch et al. [M. Lipsitch, PloS One 4:e6895 (2009)]. The number of imported cases from Mexico in several countries is found to be in good agreement with the surveillance data.