Disease spreading through human travel networks has been a topic of great interest in recent years, as witnessed during outbreaks of influenza A (H1N1) or SARS pandemics. One way to stop spreading over the airline network are travel restrictions for major airports or network hubs based on the total number of passengers of an airport. Here, we test alternative strategies using edge removal, cancelling targeted flight connections rather than restricting traffic for network hubs, for controlling spreading over the airline network. We employ a SEIR metapopulation model that takes into account the population of cities, simulates infection within cities and across the network of the top 500 airports, and tests different flight cancellation methods for limiting the course of infection. The time required to spread an infection globally, as simulated by a stochastic global spreading model was used to rank the candidate control strategies. The model includes both local spreading dynamics at the level of populations and long-range connectivity obtained from real global airline travel data. Simulated spreading in this network showed that spreading infected 37% less individuals after cancelling a quarter of flight connections between cities, as selected by betweenness centrality. The alternative strategy of closing down whole airports causing the same number of cancelled connections only reduced infections by 18%. In conclusion, selecting highly ranked single connections between cities for cancellation was more effective, resulting in fewer individuals infected with influenza, compared to shutting down whole airports. It is also a more efficient strategy, affecting fewer passengers while producing the same reduction in infections.
A substantial recrudescent wave of pandemic influenza A/H1N1 that began in December 2011 is ongoing and has not yet peaked in Mexico, following a 2-year period of sporadic transmission. Mexico previously experienced three pandemic waves of A/H1N1 in 2009, associated with higher excess mortality rates than those reported in other countries, and prompting a large influenza vaccination campaign. Here we describe changes in the epidemiological patterns of the ongoing 4th pandemic wave in 2011-12, relative to the earlier waves in 2009. The analysis is intended to guide public health intervention strategies in near real time.
We analyzed demographic and geographic data on all hospitalizations with acute respiratory infection (ARI) and laboratory-confirmed A/H1N1 influenza, and inpatient deaths, from a large prospective surveillance system maintained by the Mexican Social Security medical system during 01-April 2009 to 10-Feb 2012. We characterized the age and regional patterns of A/H1N1-positive hospitalizations and inpatient-deaths relative to the 2009 A/H1N1 influenza pandemic. We also estimated the reproduction number (R) based on the growth rate of the daily case incidence by date of symptoms onset.
A total of 5,795 ARI hospitalizations and 186 inpatient-deaths (3.2%) were reported between 01-December 2011 and 10-February 2012 (685 A/H1N1-positive inpatients and 75 A/H1N1-positive deaths). The nationwide peak of daily ARI hospitalizations in early 2012 has already exceeded the peak of ARI hospitalizations observed during the major fall pandemic wave in 2009. The mean age was 34.3 y (SD=21.3) among A/H1N1 inpatients and 43.5 y (SD=21) among A/H1N1 deaths in 2011-12. The proportion of laboratory-confirmed A/H1N1 hospitalizations and deaths was higher among seniors >=60 years of age (Chi-square test P<0.001) and lower among younger age groups (Chi-square test, P<0.03) for the 2011-2012 pandemic wave, compared to the earlier waves in 2009. The reproduction number of the winter 2011-12 wave in central Mexico was estimated at 1.2-1.3, similar to that reported for the fall 2009 wave, but lower than that of spring 2009.
We have documented a substantial and ongoing increase in the number of ARI hospitalizations during the period December 2011-February 2012 and an older age distribution of laboratory-confirmed A/H1N1 influenza hospitalizations and deaths, relative to 2009 A/H1N1 pandemic patterns. The gradual change in the age distribution of A/H1N1 infections in the post-pandemic period is reminiscent of historical pandemics and indicates either a gradual drift in the A/H1N1 virus, and/or a build-up of immunity among younger populations.
The Distributed Surveillance Taskforce for Real-time Influenza Burden Tracking and Evaluation (DiSTRIBuTE) project began as a pilot effort initiated by the International Society for Disease Surveillance (ISDS) in autumn 2006 to create a collaborative electronic emergency department (ED) syndromic influenza-like illness (ILI) surveillance network based on existing state and local systems and expertise. DiSTRIBuTE brought together health departments that were interested in: 1) sharing aggregate level data; 2) maintaining jurisdictional control; 3) minimizing barriers to participation; and 4) leveraging the flexibility of local systems to create a dynamic and collaborative surveillance network. This approach was in contrast to the prevailing paradigm for surveillance where record level information was collected, stored and analyzed centrally. The DiSTRIBuTE project was created with a distributed design, where individual level data remained local and only summarized, stratified counts were reported centrally, thus minimizing privacy risks. The project was responsive to federal mandates to improve integration of federal, state, and local biosurveillance capabilities. During the proof of concept phase, 2006 to 2009, ten jurisdictions from across North America sent ISDS on a daily to weekly basis year-round, aggregated data by day, stratified by local ILI syndrome, age-group and region. During this period, data from participating U.S. state or local health departments captured over 13% of all ED visits nationwide. The initiative focused on state and local health department trust, expertise, and control. Morbidity trends observed in DiSTRIBuTE were highly correlated with other influenza surveillance measures. With the emergence of novel A/H1N1 influenza in the spring of 2009, the project was used to support information sharing and ad hoc querying at the state and local level. In the fall of 2009, through a broadly collaborative effort, the project was expanded to enhance electronic ED surveillance nationwide.
We report preliminary results and a summary of a bottom-up approach to identify new, active, nontoxic, small-molecule antivirals designed to have а novel mechanism of action. We employed the procedure to identify 3-mercapto-1,2,4-triazoles derivatives as potential NP inhibitors in silico and subsequently demonstrated the in vitro efficacy of the molecules against various strains of the influenza A virus. The most efficacious compounds were successfully tested in an in vivo influenza challenge experiment.
Infection of pigs with influenza viruses is a cause of considerable economic loss for pig farmers as well as a potential human health concern – as evidenced by the identification of genetic material derived from swine-adapted influenza viruses in an novel strain of H1N1 influenza virus in 2009. A study was conducted investigating the prevalence of influenza virus infection in a selection of 143 English pig herds between April 2008 and April 2009, which found evidence of recent virus circulation in over half of these herds (n=75). Farms which were sampled in the Summer months were found to have lower odds of recent virus circulation, as were farms containing pigs kept in straw yards. Additionally, farms containing pigs kept indoors and farms containing high numbers of finisher pigs per water space were found to have higher odds of recent virus circulation. It is hoped that further studies will expand on these findings, and may allow targeting of surveillance for influenza viruses in the English pig population.
Severity of seasonal influenza A epidemics is related to the antigenic novelty of the predominant viral strains circulating each year. Support for a strong correlation between epidemic severity and antigenic drift comes from infectious challenge experiments on vaccinated animals and human volunteers, field studies of vaccine efficacy, prospective studies of subjects with laboratory-confirmed prior infections, and analysis of the connection between drift and severity from surveillance data. We show that, given data on the antigenic and sequence novelty of the hemagglutinin protein of clinical isolates of H3N2 virus from a season along with the corresponding data from prior seasons, we can accurately predict the influenza severity for that season. This model therefore provides a framework for making projections of the severity of the upcoming season using assumptions based on viral isolates collected in the current season. Our results based on two independent data sets from the US and Hong Kong suggest that seasonal severity is largely determined by the novelty of the hemagglutinin protein although other factors, including mutations in other influenza genes, co-circulating pathogens and weather conditions, might also play a role. These results should be helpful for the control of seasonal influenza and have implications for improvement of influenza surveillance.
In fall 2009 the emergency department of a clinic in Greece with increased patient visits due to influenza-like illness observed a particular pattern in the complete blood count (CBC) of these patients. In 90% of all patients with probable influenza, lymphopenia and/or monocytosis were present. Relative lymphopenia with or without monocytosis appears to be a laboratory marker for H1N1 virus infection, a finding that could play a major role in early identifying and treating patients with new influenza A. A ratio of lymphocytes to monocytes below 2 is proposed as a screening tool for influenza infection instead of rapid tests.
The 3D-structure of the major surface viral antigen from the recent H1N1 pandemic influenza virus (A/Darwin/2001/2009) was determined to 2.8 Å resolution. The structure was used to analyze changes in the HA that have emerged during the first 11 months of the pandemic and have raised public health concerns. Receptor binding properties of this protein reveals a strict preference for human-type receptors.
Using notification data, diffusion of pandemic human influenza A (H1N1) 2009 in Hong Kong was explored with geographic information system (GIS) methodology. Point data were displayed and then analysed with interpolation and the application of SaTScan™. Beginning from 6 initial foci, the spatial distribution has remained heterogeneous at the end of the first three months, with students functioning as the main disseminators. Our study showed that routinely collected surveillance data could be effectively used for describing the epidemic, which could support the development of interventions at local levels.
Influenza A(H1N1)v has spread rapidly in all parts of the globe in 2009 as a true pandemic, although fortunately a clinically mild one. The relevant evolutionary steps for the new virus to adapt to human populations occurred very early during the pandemic, before the end of April. Of the several resulting clades or clusters, clade 7 appeared later and proved more successful, substituting all other early clades before the bulk of the worldwide infections occurred.
Homeless are deprived people of developed countries that have a particularly low vaccine coverage and are exposed to vaccine preventable infectious diseases. We report here the efficiency of a voluntary based one-day snapshot influenza vaccination in homeless shelter of Marseille, France, which allowed to obtain a 46.9% H1N1 pandemic vaccine coverage while at the same time only 6% of the French population has been vaccinated.
We studied the epidemic trend following the introduction of the pandemic A(H1N1) 2009 in the subtropical Réunion Island. There, the pandemic wave started from week 30 and lasted until week 38, with an estimated attack rate of 12.85 % for symptomatic infections. The best estimate for the initial reproduction number was Ri = 1.26 [1.08; 1.49]. It results that the herd immunity necessary to stop the epidemic growth is of the same magnitude than the attack rate. Thus, a second wave before the 2010 austral winter seems unlikely, unless a viral mutation.
Background: The world is currently confronting the first influenza pandemic of the 21st century. Influenza vaccination is an effective preventive measure, but the unique epidemiological features of swine-origin influenza A (H1N1) (pH1N1) introduce uncertainty as to the best strategy for prioritization of vaccine allocation. We sought to determine optimal prioritization of vaccine distribution among different age and risk groups within the Canadian population, to minimize influenza-attributable morbidity and mortality.
Methodology/Principal Findings: We developed a deterministic, age-structured compartmental model of influenza transmission, with key parameter values estimated from data collected during the initial phase of the epidemic in Ontario, Canada. We examined the effect of different vaccination strategies on attack rates, hospitalizations, intensive care unit admissions, and mortality. In all scenarios, prioritization of high-risk groups (individuals with underlying chronic conditions and pregnant women) markedly decreased the frequency of severe outcomes. Preferential vaccination of age groups at increased risk of severe outcomes following infection resulted in decreased mortality compared to targeting vaccine to age groups with higher transmission, at a cost of higher population-level attack rates. All simulations were sensitive to the timing of the epidemic peak in relation to vaccine availability, with vaccination having the greatest impact when it was implemented well in advance of the epidemic peak.
Conclusions/Significance: Our model simulations suggest that vaccine should be allocated to high-risk groups, regardless of age, followed by age groups at increased risk of severe outcomes. Vaccination may significantly reduce influenza-attributable morbidity and mortality, but the benefits are dependent on epidemic dynamics, time for program roll-out, and vaccine uptake.
Introduction: Emerging data suggest that receipt of the seasonal influenza vaccine may be associated with an enhanced risk of infection with pandemic (H1N1) 2009 (pH1N1). We sought to evaluate different seasonal vaccination strategies during a pandemic in the presence of varying levels of pH1N1 infection risk following seasonal influenza vaccine receipt.
Methods: We developed a deterministic, age-structured compartmental model of influenza transmission in the presence of two circulating strains (pH1N1 and seasonal). We examined the effect of different seasonal vaccination strategies on total influenza-attributable mortality in the Canadian population for the 2009-2010 influenza season.
Results: Seasonal vaccination strategies that focused on individuals aged ≥65 or delayed seasonal vaccine delivery until January tended to minimize mortality. In the presence of low levels (<2%) of co-circulating seasonal influenza, mortality estimates were sensitive to the seasonal vaccine-associated relative risk (RR), with small increases in RR resulting in enhanced mortality compared to the no seasonal vaccination option. Timing of the peak of pH1N1 activity and the amount of circulating seasonal influenza modified the impact of enhanced risk on total mortality.
Discussion: In the presence of uncertainty surrounding enhanced risk of pH1N1 acquisition with seasonal vaccine receipt, delaying seasonal vaccine delivery or restricting vaccine to individuals aged ≥65 may reduce overall influenza-attributable mortality in the Canadian population.
Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially-resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we describe a significant improvement in the efficiency of an individual-based stochastic disease simulation framework that has been used for multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations.
A serosurvey conducted in a sample of first quarter pregnant women in France at week 48-49 of 2009 exhibit a seroprevalence level of 10.6%. It has been extrapolated in male and female population living in France mainland, aged 20-39 yr, that 1,712,000, 95%CI (1,112,700 – 2,311,300) people were recently infected by H1N1pdm (recently vaccinated women were excluded from analysis). From week 36 to 46-47 of 2009, 336,288, 95%CI (207,303-421,299) patients visited their general practitioners with clinical influenza in France, mainland. We then extrapolated the proportion of symptomatic H1N1pdm influenza in both males and females aged 20-39 yr who visited their GP to be 19.6%. Surprisingly, 8 months after having alerted at a global level for H1N1pdm, there is still no published data on seroprevalence in any countries. Therefore, there is still no published estimation of the proportion of asymptomatic infections due to the pandemic strain. We have launched in France a weekly repeated seroprevalence survey in pregnant women who were volunteers to give their blood for H1N1pdm hemagglutination inhibition (HI) serosurvey during their first term of their pregnancy  . By comparing our data to cumulated figures of incident cases of clinical influenza provided by the French Sentinelles system  we provide estimate of the proportion of patients with symptomatic influenza presentation which led them to visiting their general practitioner.
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.
Much of the observed wintertime increase of mortality in temperate regions is attributed to seasonal influenza. A recent re-analysis of laboratory experiments indicates that absolute humidity strongly modulates the airborne survival and transmission of the influenza virus. Here we extend these findings to the human population level, showing that the onset of increased wintertime influenza-related mortality in the United States is associated with anomalously low absolute humidity levels during the prior weeks. We then use an epidemiological model, in which observed absolute humidity conditions temper influenza transmission rates, to successfully simulate the seasonal cycle of observed influenza-related mortality. The model results indicate that direct modulation of influenza transmissibility by absolute humidity alone is sufficient to produce this observed seasonality. These findings provide epidemiological support for the hypothesis that absolute humidity drives seasonal variations of influenza transmission in temperate regions.
This work contributes informed estimates to the current debate about the pandemic (H1N1) 2009 mass immunization program’s economic merits. We performed a cost-utility analysis of the (H1N1) 2009 mass immunization program in Ontario, Canada’s most populous province. The analysis is based on a simulation model of a pandemic (H1N1) 2009 outbreak, surveillance data, and administrative data. We consider no immunization versus mass immunization reaching 30% of the population. Immunization program costs are expected to be $118 million in Ontario. Our analysis indicates this program will reduce influenza cases by 50%, preventing 35 deaths, and cutting treatment costs in half. A pandemic (H1N1) 2009 immunization program is likely to be highly cost-effective.
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.
The emergence of the novel A/H1N1 virus has made pandemic preparedness a crucial issue for public health worldwide. Although the epidemiological aspects of the three 20th century influenza pandemics have been widely investigated, little is known about population behaviour in a pandemic situation. Such knowledge is however critical, notably for predicting population compliance with non pharmaceutical interventions. This paper reviews the relevant scientific literature for the 1918-1920, 1957-1958, 1969-1969 influenza epidemics and the 2003 SARS outbreak. Although the evidence base of most non pharmaceutical interventions (NPIs) and personal protection measures is debated, it appears on the basis of past experience that NPIs implemented the most systematically, the earliest, and for the longest time could reduce overall mortality rates and spread out epidemic peaks. Adequate, transparent, and targeted communication on the part of public health authorities would be also of crucial importance in the event of a serious influenza pandemic.
A molecular model of the swine influenza A/H1N1 ( also called H1N1pdm) type-I neuraminidase was built using the pathogenic avian H5N1 type-I neuraminidase as a basis, due to the higher sequence identity between A/H1N1 and H5N1 (91.47%) compared to Spanish H1N1 (88.37%) neuraminidase. All-atom molecular dynamics (MD) simulations of all three neuraminidases were performed, either as apo-structures or with commercial antiviral drugs Tamiflu or Relenza separately bound; the simulations allowed for the identification of both conserved and unique drug-protein interactions across all three proteins. Specifically, conserved networks of hydrogen bonds stabilizing the drugs in the sialic acid binding site of the simulated neuraminidases are analyzed, providing insight into how disruption due to mutations may lead to increased drug resistance. In addition, a possible mechanism through which the residue 294 mutation acquires drug resistance is proposed by mapping the mutation site onto an electrostatic pathway which may play a role in controlling drug access to the binding pocket of neuraminidase, establishing a starting point for further investigations of neuraminidase drug resistance.