Transmissibility of swine flu at Fort Dix, 1976

Passive immunotherapies for the next influenza pandemic

Influenzavirus is among the most relevant candidates for a next pandemic. We review here the phylogeny of former influenza pandemics, and discuss candidate lineages. After briefly reviewing the other existing antiviral options, we discuss in detail the evidences supporting the efficacy of passive immunotherapies against influenzavirus, with a focus on convalescent plasma.

Quantifying transmissibility of SARS-CoV-2 and impact of intervention within long-term healthcare facilities

Estimates of the basic reproduction number (R 0) for COVID-19 are particularly variable in the context of transmission within locations such as long-term healthcare (LTHC) facilities. We sought to characterize the heterogeneity of R 0 across known outbreaks within these facilities. We used a unique comprehensive dataset of all outbreaks that occurred within LTHC facilities in British Columbia, Canada as of 21 September 2020. We estimated R 0 in 18 LTHC outbreaks with a novel Bayesian hierarchical dynamic model of susceptible, exposed, infected and recovered individuals, incorporating heterogeneity of R 0 between facilities. We further compared these estimates to those obtained with standard methods that use the exponential growth rate and maximum likelihood. The total size of outbreaks varied dramatically, with range of attack rates 2%-86%. The Bayesian analysis provided an overall estimate of R 0 = 2.51 (90% credible interval 0.47-9.0), with individual facility estimates ranging between 0.56 and 9.17. Uncertainty in these estimates was more constrained than standard methods, particularly for smaller outbreaks informed by the population-level model. We further estimated that intervention led to 61% (52%-69%) of all potential cases being averted within the LTHC facilities, or 75% (68%-79%) when using a model with multi-level intervention effect. Understanding of transmission risks and impact of intervention are essential in planning during the ongoing global pandemic, particularly in high-risk environments such as LTHC facilities.

C, Galloway D, Schweizer ML, Guclu H, Cousins J, Lingle C, Yearwood GMH, Li K, Calderone P, Noble E, Gao H, Rainey J, Uzicanin A, Read JM. Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.

Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions. Fewer, but longer, contacts were reported in surveys, relative to the generally short proximal interactions captured by wearable sensors. When adjusted for expectations of proportionate mixing, though, the two methods produced highly similar, assortative age-mixing matrices. These aggregate mixing matrices, when used in simulation, resulted in similar estimates of risk of infection by age. While proximity sensors and survey methods may not be interchangeable for capturing individual contacts, they can generate highly correlated data on age-specific mixing patterns relevant to the dynamics of respiratory virus transmission.

Epidemiological analysis of an outbreak of an adenovirus type 7 infection in a boot camp in China

BACKGROUND

An outbreak of respiratory disease associated with adenovirus type 7 occurred in a boot camp in China and was characterized by many cases, severe symptoms, and intrapulmonary infection in many patients.

METHODS

We implemented a series of comprehensive preventive and control measures. We analyzed the incubation period and generation time by using the maximum likelihood method, assessed the symptom period and hospitalization duration using the Kaplan-Meier method, and estimated the basic reproductive number and dormitory transmission rate by using established methods.

RESULTS

The epidemic lasted for 30 days, and 375 individuals were affected. Overall, 109 patients were hospitalized, and 266 individuals were isolated and treated. The median incubation period was 5.2 days (95% confidence interval [CI]: 5.0 to 5.4 days). The median generation time was 7.3 days (95% CI: 7.1 to 7.6 days). The median symptom period was 6 days (95% CI: 6 to 7 days). The median hospitalization duration was 9 days (95% CI: 9 to 11 days). The basic reproductive number was 5.1 (95% CI: 4.6 to 5.6), and the dormitory transmission rate was 0.15 (95% CI: 0.12 to 0.18).

CONCLUSION

Patients in the early stage of the epidemic were treated as having a regular cold and were not isolated; therefore, the virus continued to be transmitted to other susceptible individuals.

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

Background

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

Materials and Methods

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

Results

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

Conclusion

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

Sowing the Seeds of a Pandemic? Mammalian Pathogenicity and Transmissibility of H1 Variant Influenza Viruses from the Swine Reservoir

Emergence of genetically and antigenically diverse strains of influenza to which the human population has no or limited immunity necessitates continuous risk assessments to determine the likelihood of these viruses acquiring adaptations that facilitate sustained human-to-human transmission. As the North American swine H1 virus population has diversified over the last century by means of both antigenic drift and shift, in vivo assessments to study multifactorial traits like mammalian pathogenicity and transmissibility of these emerging influenza viruses are critical. In this review, we examine genetic, molecular, and pathogenicity and transmissibility data from a panel of contemporary North American H1 subtype swine-origin viruses isolated from humans, as compared to H1N1 seasonal and pandemic viruses, including the reconstructed 1918 virus. We present side-by-side analyses of experiments performed in the mouse and ferret models using consistent experimental protocols to facilitate enhanced interpretation of in vivo data. Contextualizing these analyses in a broader context permits a greater appreciation of the role that in vivo risk assessment experiments play in pandemic preparedness. Collectively, we find that despite strain-specific heterogeneity among swine-origin H1 viruses, contemporary swine viruses isolated from humans possess many attributes shared by prior pandemic strains, warranting heightened surveillance and evaluation of these zoonotic viruses.

Comparative In Vitro and In Vivo Analysis of H1N1 and H1N2 Variant Influenza Viruses Isolated from Humans between 2011 and 2016

Influenza A virus pandemics are rare events caused by novel viruses which have the ability to spread in susceptible human populations. With respect to H1 subtype viruses, swine H1N1 and H1N2 viruses occasionally cross the species barrier to cause human infection. Recently isolated from humans (termed variants), swine viruses were shown to display great genetic and antigenic diversity, hence posing considerable public health risk. Here, we utilized in vitro and in vivo approaches to provide characterization of H1 subtype variant viruses isolated since the 2009 pandemic and discuss the findings in context with previously studied H1 subtype human isolates. The variant viruses were well adapted to replicate in the human respiratory cell line Calu-3 and the respiratory tracts of mice and ferrets. However, with respect to hemagglutinin (HA) activation pH, the variant viruses had fusion pH thresholds closer to that of most classical swine and triple-reassortant H1 isolates rather than viruses that had adapted to humans. Consistent with previous observations for swine isolates, the tested variant viruses were capable of efficient transmission between cohoused ferrets but could transmit via respiratory droplets to differing degrees. Overall, this investigation demonstrates that swine H1 viruses that infected humans possess adaptations required for robust replication and, in some cases, efficient respiratory droplet transmission in a mammalian model and therefore need to be closely monitored for additional molecular changes that could facilitate transmission among humans. This work highlights the need for risk assessments of emerging H1 viruses as they continue to evolve and cause human infections.IMPORTANCE Influenza A virus is a continuously evolving respiratory pathogen. Endemic in swine, H1 and H3 subtype viruses sporadically cause human infections. As each zoonotic infection represents an opportunity for human adaptation, the emergence of a transmissible influenza virus to which there is little or no preexisting immunity is an ongoing threat to public health. Recently isolated variant H1 subtype viruses were shown to display extensive genetic diversity and in many instances were antigenically distinct from seasonal vaccine strains. In this study, we provide characterization of representative H1N1v and H1N2v viruses isolated since the 2009 pandemic. Our results show that although recent variant H1 viruses possess some adaptation markers of concern, these viruses have not fully adapted to humans and require further adaptation to present a pandemic threat. This investigation highlights the need for close monitoring of emerging variant influenza viruses for molecular changes that could facilitate efficient transmission among humans.

Serial intervals of respiratory infectious diseases: a systematic review and analysis

The serial interval of an infectious disease represents the duration between symptom onset of a primary case and symptom onset of its secondary cases. A good evidence base for such values is essential, because they allow investigators to identify epidemiologic links between cases and serve as an important parameter in epidemic transmission models used to design infection control strategies. We reviewed the literature for available data sets containing serial intervals and for reported values of serial intervals. We were able to collect data on outbreaks within households, which we reanalyzed to infer a mean serial interval using a common statistical method. We estimated the mean serial intervals for influenza A(H3N2) (2.2 days), pandemic influenza A(H1N1)pdm09 (2.8 days), respiratory syncytial virus (7.5 days), measles (11.7 days), varicella (14.0 days), smallpox (17.7 days), mumps (18.0 days), rubella (18.3 days), and pertussis (22.8 days). For varicella, we found an evidence-based value that deviates substantially from the 21 days commonly used in transmission models. This value of the serial interval for pertussis is, to the best of our knowledge, the first that is based on observations. Our review reveals that, for most infectious diseases, there is very limited evidence to support the serial intervals that are often cited.

Estimates of the reproduction number for seasonal, pandemic, and zoonotic influenza: a systematic review of the literature

BACKGROUND

The potential impact of an influenza pandemic can be assessed by calculating a set of transmissibility parameters, the most important being the reproduction number (R), which is defined as the average number of secondary cases generated per typical infectious case.

METHODS

We conducted a systematic review to summarize published estimates of R for pandemic or seasonal influenza and for novel influenza viruses (e.g. H5N1). We retained and summarized papers that estimated R for pandemic or seasonal influenza or for human infections with novel influenza viruses.

RESULTS

The search yielded 567 papers. Ninety-one papers were retained, and an additional twenty papers were identified from the references of the retained papers. Twenty-four studies reported 51 R values for the 1918 pandemic. The median R value for 1918 was 1.80 (interquartile range [IQR]: 1.47-2.27). Six studies reported seven 1957 pandemic R values. The median R value for 1957 was 1.65 (IQR: 1.53-1.70). Four studies reported seven 1968 pandemic R values. The median R value for 1968 was 1.80 (IQR: 1.56-1.85). Fifty-seven studies reported 78 2009 pandemic R values. The median R value for 2009 was 1.46 (IQR: 1.30-1.70) and was similar across the two waves of illness: 1.46 for the first wave and 1.48 for the second wave. Twenty-four studies reported 47 seasonal epidemic R values. The median R value for seasonal influenza was 1.28 (IQR: 1.19-1.37). Four studies reported six novel influenza R values. Four out of six R values were <1.

CONCLUSIONS

These R values represent the difference between epidemics that are controllable and cause moderate illness and those causing a significant number of illnesses and requiring intensive mitigation strategies to control. Continued monitoring of R during seasonal and novel influenza outbreaks is needed to document its variation before the next pandemic.

The Eurasian genes of the 2009 pandemic influenza virus: an integrative perspective on their conveyance to and assimilation in America

The formation of pandemic influenza genotypes varied phylogeographically and ecophylogenetically throughout their fully recognized recent 100-years natural history, involving consistently avian plus human genes, and at times swine genes. The last four traceable pandemic strains (PSs) included two American H1N1 viruses with genomes predominantly containing swine genes, of which at least one genome originated from both America and Eurasia; and two non-H1N1 Asian viruses with genomes entirely originating from Asia, and having no swine genes. This study explores whether there is a particular interhemispheric system underlying such divergence, and its properties. Unlike the assumption that transport of live pigs from Eurasia to America facilitated the formation of the 2009 H1N1 PS in America, it is suggested that conveyance of Eurasian swine genes to America, and their assimilation therein, took place through a distinct, perfectly natural ecophylogenetic machinery. The latter conjunctively involves, foremost, a native Asian duck-swine-man interface, a Holarctic chain of certain migratory Anas ducks, a native American turkey-swine-man interface, and two specific clades of American influenza A viruses. Likewise, the described machinery could have readily given rise to the 1918 H1N1, and, presumably, earlier American PSs, altogether constituting private cases of a much broader, self-sustained, permanent phylogeographic system.

Does homologous reinfection drive multiple-wave influenza outbreaks? Accounting for immunodynamics in epidemiological models

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We model the primary immune responses to influenza infection in humans.

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We examine the interplay between immunological and epidemiological dynamics.

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The model explains cases of homologous reinfection reported during past pandemics.

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Three epidemic profiles can arise depending on the degree of population mixing.

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A substantial proportion of infected host would remain unprotected after the 2009 influenza pandemic.

Epidemiological models of influenza transmission usually assume that recovered individuals instantly develop a fully protective immunity against the infecting strain. However, recent studies have highlighted host heterogeneity in the development of this immune response, characterized by delay and even absence of protection, that could lead to homologous reinfection (HR). Here, we investigate how these immunological mechanisms at the individual level shape the epidemiological dynamics at the population level. In particular, because HR was observed during the successive waves of past pandemics, we assess its role in driving multiple-wave influenza outbreaks. We develop a novel mechanistic model accounting for host heterogeneity in the immune response. Immunological parameters are inferred by fitting our dynamical model to a two-wave influenza epidemic that occurred on the remote island of Tristan da Cunha (TdC) in 1971, and during which HR occurred in 92 of 284 islanders. We then explore the dynamics predicted by our model for various population settings. We find that our model can explain HR over both short (e.g. week) and long (e.g. month) time-scales, as reported during past pandemics. In particular, our results reveal that the HR wave on TdC was a natural consequence of the exceptional contact configuration and high susceptibility of this small and isolated community. By contrast, in larger, less mixed and partially protected populations, HR alone cannot generate multiple-wave outbreaks. However, in the latter case, we find that a significant proportion of infected hosts would remain unprotected at the end of the pandemic season and should therefore benefit from vaccination. Crucially, we show that failing to account for these unprotected individuals can lead to large underestimation of the magnitude of the first post-pandemic season. These results are relevant in the context of the 2009 A/H1N1 influenza post-pandemic era.

Influence of extreme weather and meteorological anomalies on outbreaks of influenza A (H1N1)

Biological experiments and epidemiological evidence indicate that variations in environment have important effect on the occurrence and transmission of epidemic influenza. It is therefore important to understand the characteristic patterns of transmission for prevention of disease and reduction of disease burden. Based on case records, we analyzed the environmental characteristics including climate variables in Changsha, and then constructed a meteorological anomaly susceptive-infective-removal (SIR) model on the basis of the results of influenza A (H1N1) transmission. The results showed that the outbreak of influenza A (H1N1) in Changsha showed significant correlation with meteorological conditions; the spread of influenza was sensitive to meteorological anomalies, and that the outbreak of influenza A (H1N1) in Changsha was influenced by a combination of absolute humidity anomalous weather conditions, contact rates of the influenza patients and changes in population movements. These findings will provide helpful information regarding prevention strategies under different conditions, a fresh understanding of the emergence and re-emergence of influenza outbreaks, and a new perspective on the transmission dynamics of influenza.

The R0 package: a toolbox to estimate reproduction numbers for epidemic outbreaks

Background

Several generic methods have been proposed to estimate transmission parameters during an outbreak, especially the reproduction number. However, as of today, no dedicated software exists that implements these methods and allow comparisons.

Results

A review of generic methods used to estimate transmissibility parameters during outbreaks was carried out. Most methods used the epidemic curve and the generation time distribution. Two categories of methods were available: those estimating the initial reproduction number, and those estimating a time dependent reproduction number. We implemented five methods as an R library, developed sensitivity analysis tools for each method and provided numerical illustrations of their use. A comparison of the performance of the different methods on simulated datasets is reported.

Conclusions

This software package allows a standardized and extensible approach to the estimation of the reproduction number and generation interval distribution from epidemic curves.

Swine flu. Mexico's handling of A/H1N1 in comparative perspective

Emerging infectious diseases (EIDs) pose international security threats because of their potential to inflict harm upon humans, crops, livestock, health infrastructure, and economies. Despite the scale of this threat, there are inherent limitations in preventing and controlling EIDs, including the scope of current disease surveillance efforts. All of this leads to the following questions in the context of Mexico's recent swine flu experience: What were the cultural, political, and economic challenges to Influenza A/H1N1 virus response in Mexico? By way of comparison, what can we learn from the U.S. experience in 1976 with A/New Jersey/76 (Hsw1N1), later referred to as H1N1? This article explores the comparative political economy of Mexico's handling of influenza virus A/H1N1 outbreak in 2009. Research provides notable observations-based on the strengths and weaknesses of each country's response--that can be used as a starting point of discussion for the design of effective EIDs surveillance programs in developing and middle-income countries. In the U.S., the speed and efficiency of the 1976 U.S. mobilization against H1N1 was laudable. Although the U.S. response to the outbreak is seldom praised, the unity of the scientific and political communities demonstrated the national ability to respond to the situation. Mexico's strongest characteristics were its transparency, as well as the cooperation the country exhibited with other nations, particularly the U.S. and Canada. While Mexico showed savvy in its effective management of public and media relations, as the article details, political, economic, and cultural problems persisted.

The modes of evolutionary emergence of primal and late pandemic influenza virus strains from viral reservoir in animals: an interdisciplinary analysis

Based on a wealth of recent findings, in conjunction with earliest chronologies pertaining to evolutionary emergences of ancestral RNA viruses, ducks, Influenzavirus A (assumingly within ducks), and hominids, as well as to the initial domestication of mallard duck (Anas platyrhynchos), jungle fowl (Gallus gallus), wild turkey (Meleagris gallopavo), wild boar (Sus scrofa), and wild horse (Equus ferus), presumed genesis modes of primordial pandemic influenza strains have multidisciplinarily been configured. The virological fundamentality of domestication and farming of those various avian and mammalian species has thereby been demonstrated and broadly elucidated, within distinctive coevolutionary paradigms. The mentioned viral genesis modes were then analyzed, compatibly with common denominators and flexibility that mark the geographic profile of the last 18 pandemic strains, which reputedly emerged since 1510, the antigenic profile of the last 10 pandemic strains since 1847, and the genomic profile of the last 5 pandemic strains since 1918, until present. Related ecophylogenetic and biogeographic aspects have been enlightened, alongside with the crucial role of spatial virus gene dissemination by avian hosts. A fairly coherent picture of primary and late evolutionary and genomic courses of pandemic strains has thus been attained, tentatively. Specific patterns underlying complexes prone to generate past and future pandemic strains from viral reservoir in animals are consequentially derived.

Influenza transmission in households during the 1918 pandemic

Analysis of historical data has strongly shaped our understanding of the epidemiology of pandemic influenza and informs analysis of current and future epidemics. Here, the authors analyzed previously unpublished documents from a large household survey of the "Spanish" H1N1 influenza pandemic, conducted in 1918, for the first time quantifying influenza transmissibility at the person-to-person level during that most lethal of pandemics. The authors estimated a low probability of person-to-person transmission relative to comparable estimates from seasonal influenza and other directly transmitted infections but similar to recent estimates from the 2009 H1N1 pandemic. The authors estimated a very low probability of asymptomatic infection, a previously unknown parameter for this pandemic, consistent with an unusually virulent virus. The authors estimated a high frequency of prior immunity that they attributed to a largely unreported influenza epidemic in the spring of 1918 (or perhaps to cross-reactive immunity). Extrapolating from this finding, the authors hypothesize that prior immunity partially protected some populations from the worst of the fall pandemic and helps explain differences in attack rates between populations. Together, these analyses demonstrate that the 1918 influenza virus, though highly virulent, was only moderately transmissible and thus in a modern context would be considered controllable.

Structural basis and sequence co-evolution analysis of the hemagglutinin protein of pandemic influenza A/H1N1 (2009) virus

Severe pandemic influenza A H1N1 (2009) infection, especially in the lower respiratory tract, is often associated with the virus carrying a D222G substitution in the hemagglutinin (HA) protein of the virus. The mechanism for this association has not been fully explored. In the in vitro binding assay, it was found that clinical isolates carrying D222G substitution exhibit higher binding avidity to 2,3-linked sialic acids than the wild-type virus. The receptor binding pocket of the pandemic influenza (H1N1) HA was found to be smaller than those of other influenza A strains, allowing tighter binding of the virus with the receptor, yet also inducing steric stress for the binding. Our homology modeling and molecular docking calculations implicated that residue 222 may affect the positioning of the conserved Q223 residue, hence modulating flexibility of the binding pocket and steric hindrance during receptor binding. The molecular property of residue 222 can also directly influence the 'lysine fence' via the polarity of the amino acid residue where D222G substitution will enhance the electrostatic interactions between the receptor and the protein. The potential importance of residue 222 was illustrated by evolutionary analysis, which showed that this site is under intense selection pressure during adaptation of the virus to human host. Our findings provide a useful reference for follow-up studies in monitoring the ongoing evolution of the pandemic influenza A H1N1 (2009) virus.

Comparing three basic models for seasonal influenza

In this paper we report the use of the open source Spatiotemporal Epidemiological Modeler (STEM, www.eclipse.org/stem) to compare three basic models for seasonal influenza transmission. The models are designed to test for possible differences between the seasonal transmission of influenza A and B. Model 1 assumes that the seasonality and magnitude of transmission do not vary between influenza A and B. Model 2 assumes that the magnitude of seasonal forcing (i.e., the maximum transmissibility), but not the background transmission or flu season length, differs between influenza A and B. Model 3 assumes that the magnitude of seasonal forcing, the background transmission, and flu season length all differ between strains. The models are all optimized using 10 years of surveillance data from 49 of 50 administrative divisions in Israel. Using a cross-validation technique, we compare the relative accuracy of the models and discuss the potential for prediction. We find that accounting for variation in transmission amplitude increases the predictive ability compared to the base. However, little improvement is obtained by allowing for further variation in the shape of the seasonal forcing function.

A pandemic influenza modeling and visualization tool

The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a visual analytics toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects of the pandemic on the population through a geographical spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak.

Explaining rapid reinfections in multiple-wave influenza outbreaks: Tristan da Cunha 1971 epidemic as a case study

Influenza usually spreads through the human population in multiple-wave outbreaks. Successive reinfection of individuals over a short time interval has been explicitly reported during past pandemics. However, the causes of rapid reinfection and the role of reinfection in driving multiple-wave outbreaks remain poorly understood. To investigate these issues, we focus on a two-wave influenza A/H3N2 epidemic that occurred on the remote island of Tristan da Cunha in 1971. Over 59 days, 273 (96%) of 284 islanders experienced at least one attack and 92 (32%) experienced two attacks. We formulate six mathematical models invoking a variety of antigenic and immunological reinfection mechanisms. Using a maximum-likelihood analysis to confront model predictions with the reported incidence time series, we demonstrate that only two mechanisms can be retained: some hosts with either a delayed or deficient humoral immune response to the primary influenza infection were reinfected by the same strain, thus initiating the second epidemic wave. Both mechanisms are supported by previous empirical studies and may arise from a combination of genetic and ecological causes. We advocate that a better understanding and account of heterogeneity in the human immune response are essential to analysis of multiple-wave influenza outbreaks and pandemic planning.

Influenza pandemics

The recent H1N1 pandemic that emerged in 2009 has illustrated how swiftly a new influenza virus can circulate the globe. Here we explain the origins of the 2009 pandemic virus, and other twentieth century pandemics. We also consider the impact of the 2009 pandemic in the human population and the use of vaccines and antiviral drugs. Thankfully this outbreak was much less severe than that associated with Spanish flu in 1918. We describe the viral factors that affect virulence of influenza and speculate on the future course of this virus in humans and animals.

Pathogenesis of pandemic influenza A (H1N1) and triple-reassortant swine influenza A (H1) viruses in mice

The pandemic H1N1 virus of 2009 (2009 H1N1) continues to cause illness worldwide, primarily in younger age groups. To better understand the pathogenesis of these viruses in mammals, we used a mouse model to evaluate the relative virulence of selected 2009 H1N1 viruses and compared them to a representative human triple-reassortant swine influenza virus that has circulated in pigs in the United States for over a decade preceding the current pandemic. Additional comparisons were made with the reconstructed 1918 virus, a 1976 H1N1 swine influenza virus, and a highly pathogenic H5N1 virus. Mice were inoculated intranasally with each virus and monitored for morbidity, mortality, viral replication, hemostatic parameters, cytokine production, and lung histology. All 2009 H1N1 viruses replicated efficiently in the lungs of mice and possessed a high degree of infectivity but did not cause lethal disease or exhibit extrapulmonary virus spread. Transient weight loss, lymphopenia, and proinflammatory cytokine and chemokine production were present following 2009 H1N1 virus infection, but these levels were generally muted compared with a triple-reassortant swine virus and the 1918 virus. 2009 H1N1 viruses isolated from fatal cases did not demonstrate enhanced virulence in this model compared with isolates from mild human cases. Histologically, infection with the 2009 viruses resulted in lesions in the lung varying from mild to moderate bronchiolitis with occasional necrosis of bronchiolar epithelium and mild to moderate peribronchiolar alveolitis. Taken together, these studies demonstrate that the 2009 H1N1 viruses exhibited mild to moderate virulence in mice compared with highly pathogenic viruses.

Model or meal? Farm animal populations as models for infectious diseases of humans

In recent decades, theory addressing the processes that underlie the dynamics of infectious diseases has progressed considerably. Unfortunately, the availability of empirical data to evaluate these theories has not grown at the same pace. Although laboratory animals have been widely used as models at the organism level, they have been less appropriate for addressing issues at the population level. However, farm animal populations can provide empirical models to study infectious diseases at the population level.

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.

Clinical and epidemiologic characteristics of an outbreak of novel H1N1 (swine origin) influenza A virus among United States military beneficiaries

BACKGROUND

A novel swine-origin influenza A (H1N1) virus was identified in March 2009 and subsequently caused worldwide outbreaks. The San Diego region was an early focal point of the emerging pandemic. We describe the clinical and epidemiologic characteristics of this novel strain in a military population to assist in future outbreak prevention and control efforts.

METHODS

We performed an epidemiologic evaluation of novel H1N1 virus infections diagnosed in San Diego County among 96,258 local US military beneficiaries. The structured military medical system afforded the ability to obtain precise epidemiologic information on the impact on H1N1 virus infection in a population. The novel H1N1 virus was confirmed using real-time reverse transcriptase polymerase chain reaction (rRT-PCR).

RESULTS

From 21 April through 8 May 2009, 761 patients presented with influenza-like illness and underwent rRT-PCR testing. Of these patients, 97 had confirmed novel H1N1 virus infection, with an incidence rate of 101 cases per 100,000 persons. The median age of H1N1 patients with H1N1 virus infection was 21 years (interquartile range, 15-25 years). Fever was a universal symptom in patients with H1N1 virus infection; other symptoms included cough (present in 96% of patients), myalgia or arthralgia (57%), and sore throat (51%). Sixty-eight (70%) of our patients had an identifiable epidemiologic link to another confirmed patient. The largest cluster of cases of H1N1 virus infection occurred on a Navy ship and involved 32 (8%) of 402 crew members; the secondary attack rate was 6%-14%. The rapid influenza testing that was used during this outbreak had a sensitivity of 51% and specificity of 98%, compared with rRT-PCR. Only 1 patient was hospitalized, and there were no deaths.

CONCLUSIONS

A novel H1N1 influenza A virus caused a significant outbreak among military beneficiaries in San Diego County, including a significant cluster of cases onboard a Navy ship. The outbreak described here primarily affected adolescents and young adults and resulted in a febrile illness without sequelae.

Pandemic influenza vaccines

Since their compositions remain uncertain, universal pandemic vaccines are yet to be created. They would aim to protect globally against pandemic influenza viruses that have not yet evolved. Thus they differ from seasonal vaccines to influenza virus, which are updated annually in spring to incorporate the latest circulating viruses, and are then produced and delivered before the peak influenza season starts in late fall and winter. The efficacy of seasonal vaccines is linked to their ability to induce virus-neutralizing antibodies, which provide subtype-specific protection against influenza A viruses. If pandemic vaccines were designed to resemble current vaccines in terms of composition and mode of action, they would have to be developed, tested, and mass-produced after the onset of a pandemic, once the causative virus had been identified. The logistic problems of generating a pandemic vaccine from scratch, conducting preclinical testing, and producing billions of doses within a few months for global distribution are enormous and may well be insurmountable. Alternatively, the scientific community could step up efforts to generate a universal vaccine against influenza A viruses that provides broadly cross-reactive protection through the induction of antibodies or T cells to conserved regions of the virus.

Quantifying the transmission potential of pandemic influenza

This article reviews quantitative methods to estimate the basic reproduction number of pandemic influenza, a key threshold quantity to help determine the intensity of interventions required to control the disease. Although it is difficult to assess the transmission potential of a probable future pandemic, historical epidemiologic data is readily available from previous pandemics, and as a reference quantity for future pandemic planning, mathematical and statistical analyses of historical data are crucial. In particular, because many historical records tend to document only the temporal distribution of cases or deaths (i.e. epidemic curve), our review focuses on methods to maximize the utility of time-evolution data and to clarify the detailed mechanisms of the spread of influenza.

First, we highlight structured epidemic models and their parameter estimation method which can quantify the detailed disease dynamics including those we cannot observe directly. Duration-structured epidemic systems are subsequently presented, offering firm understanding of the definition of the basic and effective reproduction numbers. When the initial growth phase of an epidemic is investigated, the distribution of the generation time is key statistical information to appropriately estimate the transmission potential using the intrinsic growth rate. Applications of stochastic processes are also highlighted to estimate the transmission potential using similar data. Critically important characteristics of influenza data are subsequently summarized, followed by our conclusions to suggest potential future methodological improvements.