Influenza Infectious Dose May Explain the High Mortality of the Second and Third Wave of 1918–1919 Influenza Pandemic

Background

It is widely accepted that the shift in case-fatality rate between waves during the 1918 influenza pandemic was due to a genetic change in the virus. In animal models, the infectious dose of influenza A virus was associated to the severity of disease which lead us to propose a new hypothesis. We propose that the increase in the case-fatality rate can be explained by the dynamics of disease and by a dose-dependent response mediated by the number of simultaneous contacts a susceptible person has with infectious ones.

Methods

We used a compartment model with seasonality, waning of immunity and a Holling type II function, to model simultaneous contacts between a susceptible person and infectious ones. In the model, infected persons having mild or severe illness depend both on the proportion of infectious persons in the population and on the level of simultaneous contacts between a susceptible and infectious persons. We further allowed for a high or low rate of waning immunity and volunteer isolation at different times of the epidemic.

Results

In all scenarios, case-fatality rate was low during the first wave (Spring) due to a decrease in the effective reproduction number. The case-fatality rate in the second wave (Autumn) depended on the ratio between the number of severe cases to the number of mild cases since, for each 1000 mild infections only 4 deaths occurred whereas for 1000 severe infections there were 20 deaths. A third wave (late Winter) was dependent on the rate for waning immunity or on the introduction of new susceptible persons in the community. If a group of persons became voluntarily isolated and returned to the community some days latter, new waves occurred. For a fixed number of infected persons the overall case-fatality rate decreased as the number of waves increased. This is explained by the lower proportion of infectious individuals in each wave that prevented an increase in the number of severe infections and thus of the case-fatality rate.

Conclusion

The increase on the proportion of infectious persons as a proxy for the increase of the infectious dose a susceptible person is exposed, as the epidemic develops, can explain the shift in case-fatality rate between waves during the 1918 influenza pandemic.     

A biological model for influenza transmission: pandemic planning implications of asymptomatic infection and immunity

Background

The clinical attack rate of influenza is influenced by prior immunity and mixing patterns in the host population, and also by the proportion of infections that are asymptomatic. This complexity makes it difficult to directly estimate R₀ from the attack rate, contributing to uncertainty in epidemiological models to guide pandemic planning. We have modelled multiple wave outbreaks of influenza from different populations to allow for changing immunity and asymptomatic infection and to make inferences about R₀.

Data and Methods

On the island of Tristan da Cunha (TdC), 96% of residents reported illness during an H3N2 outbreak in 1971, compared with only 25% of RAF personnel in military camps during the 1918 H1N1 pandemic. Monte Carlo Markov Chain (MCMC) methods were used to estimate model parameter distributions.

Findings

We estimated that most islanders on TdC were non-immune (susceptible) before the first wave, and that almost all exposures of susceptible persons caused symptoms. The median R₀ of 6.4 (95% credibility interval 3.7–10.7) implied that most islanders were exposed twice, although only a minority became ill in the second wave because of temporary protection following the first wave. In contrast, only 51% of RAF personnel were susceptible before the first wave, and only 38% of exposed susceptibles reported symptoms. R₀ in this population was also lower [2.9 (2.3–4.3)], suggesting reduced viral transmission in a partially immune population.

Interpretation

Our model implies that the RAF population was partially protected before the summer pandemic wave of 1918, arguably because of prior exposure to interpandemic influenza. Without such protection, each symptomatic case of influenza would transmit to between 2 and 10 new cases, with incidence initially doubling every 1–2 days. Containment of a novel virus could be more difficult than hitherto supposed.     

Novel Pandemic Influenza A(H1N1) Viruses Are Potently Inhibited by DAS181, a Sialidase Fusion Protein

Background

The recent emergence of a novel pandemic influenza A(H1N1) strain in humans exemplifies the rapid and unpredictable nature of influenza virus evolution and the need for effective therapeutics and vaccines to control such outbreaks. However, resistance to antivirals can be a formidable problem as evidenced by the currently widespread oseltamivir- and adamantane-resistant seasonal influenza A viruses (IFV). Additional antiviral approaches with novel mechanisms of action are needed to combat novel and resistant influenza strains. DAS181 (Fludase™) is a sialidase fusion protein in early clinical development with in vitro and in vivo preclinical activity against a variety of seasonal influenza strains and highly pathogenic avian influenza strains (A/H5N1). Here, we use in vitro, ex vivo, and in vivo models to evaluate the activity of DAS181 against several pandemic influenza A(H1N1) viruses.

Methods and Findings

The activity of DAS181 against several pandemic influenza A(H1N1) virus isolates was examined in MDCK cells, differentiated primary human respiratory tract culture, ex-vivo human bronchi tissue and mice. DAS181 efficiently inhibited viral replication in each of these models and against all tested pandemic influenza A(H1N1) strains. DAS181 treatment also protected mice from pandemic influenza A(H1N1)-induced pathogenesis. Furthermore, DAS181 antiviral activity against pandemic influenza A(H1N1) strains was comparable to that observed against seasonal influenza virus including the H274Y oseltamivir-resistant influenza virus.

Conclusions

The sialidase fusion protein DAS181 exhibits potent inhibitory activity against pandemic influenza A(H1N1) viruses. As inhibition was also observed with oseltamivir-resistant IFV (H274Y), DAS181 may be active against the antigenically novel pandemic influenza A(H1N1) virus should it acquire the H274Y mutation. Based on these and previous results demonstrating DAS181 broad-spectrum anti-IFV activity, DAS181 represents a potential therapeutic agent for prevention and treatment of infections by both emerging and seasonal strains of IFV.     

Signs of the 2009 Influenza Pandemic in the New York-Presbyterian Hospital Electronic Health Records

Background

In June of 2009, the World Health Organization declared the first influenza pandemic of the 21^st century, and by July, New York City''s New York-Presbyterian Hospital (NYPH) experienced a heavy burden of cases, attributable to a novel strain of the virus (H1N1pdm).

Methods and Results

We present the signs in the NYPH electronic health records (EHR) that distinguished the 2009 pandemic from previous seasonal influenza outbreaks via various statistical analyses. These signs include (1) an increase in the number of patients diagnosed with influenza, (2) a preponderance of influenza diagnoses outside of the normal flu season, and (3) marked vaccine failure. The NYPH EHR also reveals distinct age distributions of patients affected by seasonal influenza and the pandemic strain, and via available longitudinal data, suggests that the two may be associated with distinct sets of comorbid conditions as well. In particular, we find significantly more pandemic flu patients with diagnoses associated with asthma and underlying lung disease. We further observe that the NYPH EHR is capable of tracking diseases at a resolution as high as particular zip codes in New York City.

Conclusion

The NYPH EHR permits early detection of pandemic influenza and hypothesis generation via identification of those significantly associated illnesses. As data standards develop and databases expand, EHRs will contribute more and more to disease detection and the discovery of novel disease associations.     

Complex patterns of human antisera reactivity to novel 2009 H1N1 and historical H1N1 influenza strains

Background

During the 2009 influenza pandemic, individuals over the age of 60 had the lowest incidence of infection with approximately 25% of these people having pre-existing, cross-reactive antibodies to novel 2009 H1N1 influenza isolates. It was proposed that older people had pre-existing antibodies induced by previous 1918-like virus infection(s) that cross-reacted to novel H1N1 strains.

Methodology/Principal Findings

Using antisera collected from a cohort of individuals collected before the second wave of novel H1N1 infections, only a minority of individuals with 1918 influenza specific antibodies also demonstrated hemagglutination-inhibition activity against the novel H1N1 influenza. In this study, we examined human antisera collected from individuals that ranged between the ages of 1 month and 90 years to determine the profile of seropositive influenza immunity to viruses representing H1N1 antigenic eras over the past 100 years. Even though HAI titers to novel 2009 H1N1 and the 1918 H1N1 influenza viruses were positively associated, the association was far from perfect, particularly for the older and younger age groups.

Conclusions/Significance

Therefore, there may be a complex set of immune responses that are retained in people infected with seasonal H1N1 that can contribute to the reduced rates of H1N1 influenza infection in older populations.     

Characterizing the epidemiology of the 2009 influenza A/H1N1 pandemic in Mexico

Background

Mexico''s local and national authorities initiated an intense public health response during the early stages of the 2009 A/H1N1 pandemic. In this study we analyzed the epidemiological patterns of the pandemic during April–December 2009 in Mexico and evaluated the impact of nonmedical interventions, school cycles, and demographic factors on influenza transmission.

Methods and Findings

We used influenza surveillance data compiled by the Mexican Institute for Social Security, representing 40% of the population, to study patterns in influenza-like illness (ILIs) hospitalizations, deaths, and case-fatality rate by pandemic wave and geographical region. We also estimated the reproduction number (R) on the basis of the growth rate of daily cases, and used a transmission model to evaluate the effectiveness of mitigation strategies initiated during the spring pandemic wave. A total of 117,626 ILI cases were identified during April–December 2009, of which 30.6% were tested for influenza, and 23.3% were positive for the influenza A/H1N1 pandemic virus. A three-wave pandemic profile was identified, with an initial wave in April–May (Mexico City area), a second wave in June–July (southeastern states), and a geographically widespread third wave in August–December. The median age of laboratory confirmed ILI cases was ∼18 years overall and increased to ∼31 years during autumn (p<0.0001). The case-fatality ratio among ILI cases was 1.2% overall, and highest (5.5%) among people over 60 years. The regional R estimates were 1.8–2.1, 1.6–1.9, and 1.2–1.3 for the spring, summer, and fall waves, respectively. We estimate that the 18-day period of mandatory school closures and other social distancing measures implemented in the greater Mexico City area was associated with a 29%–37% reduction in influenza transmission in spring 2009. In addition, an increase in R was observed in late May and early June in the southeast states, after mandatory school suspension resumed and before summer vacation started. State-specific fall pandemic waves began 2–5 weeks after school reopened for the fall term, coinciding with an age shift in influenza cases.

Conclusions

We documented three spatially heterogeneous waves of the 2009 A/H1N1 pandemic virus in Mexico, which were characterized by a relatively young age distribution of cases. Our study highlights the importance of school cycles on the transmission dynamics of this pandemic influenza strain and suggests that school closure and other mitigation measures could be useful to mitigate future influenza pandemics. Please see later in the article for the Editors'' Summary     

Capacity and Adaptations of General Practice during an Influenza Pandemic

Background

GPs play a major role in influenza epidemics, and most patients with influenza-like-illness (ILI) are treated in general practice or by primary care doctors on duty in out-of-hours services (OOH). Little is known about the surge capacity in primary care services during an influenza pandemic, and how the relationship between them changes.

Aim

To investigate how general practice and OOH services were used by patients during the 2009 pandemic in Norway and the impact of the pandemic on primary care services in comparison to a normal influenza season.

Materials

Data from electronic remuneration claims from all OOH doctors and regular GPs for 2009.

Methods

We conducted a registry-based study of all ILI consultations in the 2009 pandemic with the 2008/09 influenza season (normal season) as baseline for comparison.

Results

The majority (82.2%) of ILI consultations during the 2009 pandemic took place in general practice. The corresponding number in the 2008/09 season was 89.3%. Compared with general practice, the adjusted odds ratio for ILI with all other diagnoses as reference in OOH services was 1.23 (95% CI, 1.18, 1.27) for the 2008/2009 season and 1.87 (95% CI, 1.84, 1.91) for the pandemic influenza season. In total there was a 3.3-fold increase in ILI consultations during the pandemic compared to the 2008/09 season. A 5.5-fold increase of ILI consultations were observed in OOH services in comparison to the 2008/09 season. Children and young adults with ILI were the most frequent users of OOH services during influenza periods.

Conclusions

The autumn pandemic wave resulted in a significantly increased demand on primary care services. However, GPs in primary care services in Norway showed the ability to increase capacity in a situation with increased patient demand.     

Induction of Long-Term Protective Immune Responses by Influenza H5N1 Virus-Like Particles

Background

Recurrent outbreaks of highly pathogenic H5N1 avian influenza virus pose a threat of eventually causing a pandemic. Early vaccination of the population would be the single most effective measure for the control of an emerging influenza pandemic.

Methodology/Principal Findings

Influenza virus-like particles (VLPs) produced in insect cell-culture substrates do not depend on the availability of fertile eggs for vaccine manufacturing. We produced VLPs containing influenza A/Viet Nam1203/04 (H5N1) hemagglutinin, neuraminidase, and matrix proteins, and investigated their preclinical immunogenicity and protective efficacy. Mice immunized intranasally with H5N1 VLPs developed high levels of H5N1 specific antibodies and were 100% protected against a high dose of homologous H5N1 virus infection at 30 weeks after immunization. Protection is likely to be correlated with humoral and cellular immunologic memory at systemic and mucosal sites as evidenced by rapid anamnestic responses to re-stimulation with viral antigen in vivo and in vitro.

Conclusions/Significance

These results provide support for clinical evaluation of H5N1 VLP vaccination as a public health intervention to mitigate a possible pandemic of H5N1 influenza.     

An IDEA for Short Term Outbreak Projection: Nearcasting Using the Basic Reproduction Number

Background

Communicable disease outbreaks of novel or existing pathogens threaten human health around the globe. It would be desirable to rapidly characterize such outbreaks and develop accurate projections of their duration and cumulative size even when limited preliminary data are available. Here we develop a mathematical model to aid public health authorities in tracking the expansion and contraction of outbreaks with explicit representation of factors (other than population immunity) that may slow epidemic growth.

Methodology

The Incidence Decay and Exponential Adjustment (IDEA) model is a parsimonious function that uses the basic reproduction number R₀, along with a discounting factor to project the growth of outbreaks using only basic epidemiological information (e.g., daily incidence counts).

Principal Findings

Compared to simulated data, IDEA provides highly accurate estimates of total size and duration for a given outbreak when R₀ is low or moderate, and also identifies turning points or new waves. When tested with an outbreak of pandemic influenza A (H1N1), the model generates estimated incidence at the i+1^th serial interval using data from the i^th serial interval within an average of 20% of actual incidence.

Conclusions and Significance

This model for communicable disease outbreaks provides rapid assessments of outbreak growth and public health interventions. Further evaluation in the context of real-world outbreaks will establish the utility of IDEA as a tool for front-line epidemiologists.     

Pandemic Influenza (H1N1) 2009 Pneumonia: CURB-65 Score for Predicting Severity and Nasopharyngeal Sampling for Diagnosis Are Unreliable

Background

From the first case reports of pandemic influenza (H1N1) 2009 it was clear that a significant proportion of infected individuals suffered a primary viral pneumonia. The objective of this study was twofold; to assess the utility of the CURB-65 community acquired pneumonia (CAP) severity index in predicting pneumonia severity and ICU admission, and to assess the relative sensitivity of nasopharyngeal versus lower respiratory tract sampling for the detection of pandemic influenza (H1N1) CAP.

Methods

A retrospective cohort study of 70 patients hospitalised for pandemic influenza (H1N1) 2009 in an adult tertiary referral hospital. Characteristics evaluated included age, pregnancy status, sex, respiratory signs and symptoms, smoking and alcohol history, CURB-65 score, co-morbidities, disabling sequelae, length of stay and in-hospital mortality outcomes. Laboratory features evaluated included lymphocyte count, C-reactive protein (CRP), nasopharyngeal and lower respiratory tract pandemic influenza (H1N1) 2009 PCR results.

Results

Patients with pandemic (H1N1) 2009 influenza CAP differed significantly from those without pneumonia regarding length of stay, need for ICU admission, CRP and the likelihood of disabling sequelae. The CURB-65 score did not predict CAP severity or the need for ICU admission (only 2/11 patients admitted to ICU had CURB-65 scores of 2 or 3). Nasopharyngeal specimens for PCR were only 62.9% sensitive in CAP patients compared to 97.8% sensitivity for lower respiratory tract specimens.

Conclusions

The CURB-65 score does not predict severe pandemic influenza (H1N1) 2009 CAP or need for ICU admission. Lower respiratory tract specimens should be collected when pandemic (H1N1) 2009 influenza CAP is suspected.     

Impact of the 2009 H1N1 Pandemic on Age-Specific Epidemic Curves of Other Respiratory Viruses: A Comparison of Pre-Pandemic,Pandemic and Post-Pandemic Periods in a Subtropical City

Background

The 2009 H1N1 influenza pandemic caused offseason peaks in temperate regions but coincided with the summer epidemic of seasonal influenza and other common respiratory viruses in subtropical Hong Kong. This study was aimed to investigate the impact of the pandemic on age-specific epidemic curves of other respiratory viruses.

Methods

Weekly laboratory-confirmed cases of influenza A (subtypes seasonal A(H1N1), A(H3N2), pandemic virus A(H1N1)pdm09), influenza B, respiratory syncytial virus (RSV), adenovirus and parainfluenza were obtained from 2004 to 2013. Age-specific epidemic curves of viruses other than A(H1N1)pdm09 were compared between the pre-pandemic (May 2004 – April 2009), pandemic (May 2009 – April 2010) and post-pandemic periods (May 2010 – April 2013).

Results

There were two peaks of A(H1N1)pdm09 in Hong Kong, the first in September 2009 and the second in February 2011. The infection rate was found highest in young children in both waves, but markedly fewer cases in school children were recorded in the second wave than in the first wave. Positive proportions of viruses other than A(H1N1)pdm09 markedly decreased in all age groups during the first pandemic wave. After the first wave of the pandemic, the positive proportion of A(H3N2) increased, but those of B and RSV remained slightly lower than their pre-pandemic proportions. Changes in seasonal pattern and epidemic peak time were also observed, but inconsistent across virus-age groups.

Conclusion

Our findings provide some evidence that age distribution, seasonal pattern and peak time of other respiratory viruses have changed since the pandemic. These changes could be the result of immune interference and changing health seeking behavior, but the mechanism behind still needs further investigations.     

Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks

Background

Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power.

Results

We applied ARIMA and Random Forest time series models to incidence data of outbreaks of highly pathogenic avian influenza (H5N1) in Egypt, available through the online EMPRES-I system. We found that the Random Forest model outperformed the ARIMA model in predictive ability. Furthermore, we found that the Random Forest model is effective for predicting outbreaks of H5N1 in Egypt.

Conclusions

Random Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks. This result, along with those showing the concordance between bird and human outbreaks (Rabinowitz et al. 2012), provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data. Our analysis uncovers the time-series structure of outbreak severity for highly pathogenic avain influenza (H5N1) in Egypt.     

Using a Dynamic Model to Consider Optimal Antiviral Stockpile Size in the Face of Pandemic Influenza Uncertainty

Background

The Canadian National Antiviral Stockpile (NAS) contains treatment for 17.5% of Canadians. This assumes no concurrent intervention strategies and no wastage due to non-influenza respiratory infections. A dynamic model can provide a mechanism to consider complex scenarios to support decisions regarding the optimal NAS size under uncertainty.

Methods

We developed a dynamic model for pandemic influenza in Canada that is structured by age and risk to calculate the demand for antivirals to treat persons with pandemic influenza under a wide-range of scenarios that incorporated transmission dynamics, disease severity, and intervention strategies. The anticipated per capita number of acute respiratory infections due to viruses other than influenza was estimated for the full pandemic period from surveys based on criteria to identify potential respiratory infections.

Results

Our results demonstrate that up to two thirds of the population could develop respiratory symptoms as a result of infection with a pandemic strain. In the case of perfect antiviral allocation, up to 39.8% of the population could request antiviral treatment. As transmission dynamics, severity and timing of the emergence of a novel influenza strain are unknown, the sensitivity analysis produced considerable variation in potential demand (median: 11%, IQR: 2–21%). If the next pandemic strain emerges in late spring or summer and a vaccine is available before the anticipated fall wave, the median prediction was reduced to 6% and IQR to 0.7–14%. Under the strategy of offering empirical treatment to all patients with influenza like symptoms who present for care, demand could increase to between 65 and 144%.

Conclusions

The demand for antivirals during a pandemic is uncertain. Unless an accurate, timely and cost-effective test is available to identify influenza cases, demand for antivirals from persons infected with other respiratory viruses will be substantial and have a significant impact on the NAS.     

Estimated cumulative incidence of pandemic (H1N1) influenza among pregnant women during the first wave of the 2009 pandemic

Background

Hospitalization and lab confirmed cases of H1N1 have been reported during the first wave of the 2009 pandemic but these are not accurate measures of influenza incidence in the population. We estimated the cumulative incidence of pandemic (H1N1) influenza among pregnant women in the province of Manitoba during the first wave of the 2009 pandemic.

Methods

Two panels of stored frozen serum specimens collected for routine prenatal screening were randomly selected for testing before (March 2009, n = 252) and after (August 2009, n = 296) the first wave of the pandemic. A standard hemagglutination inhibition assay was used to detect the presence of IgG antibodies against the pandemic (H1N1) 2009 virus. The cumulative incidence of pandemic (H1N1) influenza was calculated as the difference between the point prevalence rates in the first and second panels.

Results

Of the specimens collected in March, 7.1% were positive for the IgG antibodies (serum antibody titre ≥ 1:40). The corresponding prevalence was 15.7% among the specimens collected in August. The difference indicated a cumulative incidence of 8.6% (95% confidence interval [CI] 3.2%–13.7%). The rate differed geographically, the highest being in the northern regions (20.8%, 95% CI 7.9%–31.8%), as compared with 4.0% (95% CI 0.0%–11.9%) in Winnipeg and 8.9% (95% CI 0.0%–18.8%) in the rest of the province.

Interpretation

We estimated that the cumulative incidence of pandemic (H1N1) influenza among pregnant women in Manitoba during the first wave of the 2009 pandemic was 8.6%. It was 20.8% in the northern regions of the province.During the first wave of the pandemic (H1N1) 2009, the province of Manitoba was more severely affected than almost any other Canadian province.¹ Pregnant women in particular had higher rates of laboratory-confirmed infection and of severe illness.² However, the number of laboratory-confirmed cases is not an accurate measure of the incidence of influenza in the population. The number and geographic distribution of confirmed cases are influenced by differences in access to medical care, physicians’ practices and other factors.³We estimated the cumulative incidence of pandemic (H1N1) influenza among pregnant women in the province of Manitoba during the first wave of the 2009 pandemic. We did this by measuring the point seroprevalence in random samples of pregnant women presenting for routine prenatal screening before and after the first wave.     

Effectiveness of pandemic H1N1-2009 vaccination in reducing laboratory confirmed influenza infections among military recruits in tropical Singapore

Background

Limited information is available about pandemic H1N1-2009 influenza vaccine effectiveness in tropical communities. We studied the effectiveness of a pandemic H1N1 vaccination program in reducing influenza cases in Singapore.

Methods

A surveillance study was conducted among military personnel presenting with febrile respiratory illness from mid-2009 to mid-2010. Consenting individuals underwent nasal washes, which were tested with RT-PCR and subtyped. A vaccination program (inactivated monovalent Panvax H1N1-2009 vaccine) was carried out among recruits. A Bayesian hierarchical model was used to quantify relative risks in the pre- and post-vaccination periods. An autoregressive generalised linear model (GLM) was developed to minimise confounding.

Results

Of 2858 participants, 437(15.3%), 60(2.1%), and 273(9.6%) had pandemic H1N1, H3N2, and influenza B. The ratio of relative risks for pandemic H1N1 infection before and after vaccination for the recruit camp relative to other camps was 0.14(0.016,0.49); for H3N2, 0.44(0.035,1.8); and for influenza B, 18(0.77,89). Using the GLM for the recruit camp, post-vaccination weekly cases decreased by 54%(37%,67%, p<0.001) from that expected without vaccination; influenza B increased by 66 times(9–479 times, p<0.001); with no statistical difference for H3N2 (p = 0.54).

Conclusions

Pandemic vaccination reduced H1N1-2009 disease burden among military recruits. Routine seasonal influenza vaccination should be considered.     

A Small Community Model for the Transmission of Infectious Diseases: Comparison of School Closure as an Intervention in Individual-Based Models of an Influenza Pandemic

Background

In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic.

Method

We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world.

Results

We showed that published individual based models estimate similar final attack rates over a range of values for R₀ in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R₀ values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure.

Conclusion

Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined.     

Diagnostic Approach for the Differentiation of the Pandemic Influenza A(H1N1)v Virus from Recent Human Influenza Viruses by Real-Time PCR

Background

The current spread of pandemic influenza A(H1N1)v virus necessitates an intensified surveillance of influenza virus infections worldwide. So far, in many laboratories routine diagnostics were limited to generic influenza virus detection only. To provide interested laboratories with real-time PCR assays for type and subtype identification, we present a bundle of PCR assays with which any human influenza A and B virus can be easily identified, including assays for the detection of the pandemic A(H1N1)v virus.

Principal Findings

The assays show optimal performance characteristics in their validation on plasmids containing the respective assay target sequences. All assays have furthermore been applied to several thousand clinical samples since 2007 (assays for seasonal influenza) and April 2009 (pandemic influenza assays), respectively, and showed excellent results also on clinical material.

Conclusions

We consider the presented assays to be well suited for the detection and subtyping of circulating influenza viruses.