Eben Kenah

The Transmissibility and Control of Pandemic Influenza A (H1N1) Virus

Flus Tricky Tricks After vaccination against influenza A virus, single-point mutations are selected in hemagglutinin (the virus molecule that binds to sialic acid molecules on the surface of host cells) that escape neutralization by polyclonal antibody responses. Hensley et al. (p. 734) have discovered that in mice these mutations increased the viruss avidity for sialic acid. Amino acid substitutions that occur during reiterations of immune escape and avidity modulation can thus drive antigenic variation. This constant evolution of influenza viruses requires us to change vaccine components annually, and, for equine influenza, Park et al. (p. 726) show that as the match between virus and vaccine strains drifts apart with time, the probability of becoming infected and the length of the infectious period increase to the point where outbreaks occur. Nevertheless, even imperfect vaccines may be of benefit to a population because increasing the proportion of vaccinated individuals can supply enough herd immunity to offset a poor antigenic match, especially if used in conjunction with antiviral drugs. For humans, Yang et al. (p. 729, published online 10 September) estimate that the rate of transmission within U.S. households puts influenza A 2009 H1N1 (the current pandemic “swine flu”) in the higher range of transmissibility, compared to past seasonal and pandemic strains. Thus, to achieve mitigation this fall, children should be the first recipients of vaccine, followed by adults—aiming overall for 70% coverage of the population. A detailed picture of the pandemic potential of swine-origin influenza offers guidance for effective mitigation strategies. Pandemic influenza A (H1N1) 2009 (pandemic H1N1) is spreading throughout the planet. It has become the dominant strain in the Southern Hemisphere, where the influenza season has now ended. Here, on the basis of reported case clusters in the United States, we estimated the household secondary attack rate for pandemic H1N1 to be 27.3% [95% confidence interval (CI) from 12.2% to 50.5%]. From a school outbreak, we estimated that a typical schoolchild infects 2.4 (95% CI from 1.8 to 3.2) other children within the school. We estimated the basic reproductive number, R0, to range from 1.3 to 1.7 and the generation interval to range from 2.6 to 3.2 days. We used a simulation model to evaluate the effectiveness of vaccination strategies in the United States for fall 2009. If a vaccine were available soon enough, vaccination of children, followed by adults, reaching 70% overall coverage, in addition to high-risk and essential workforce groups, could mitigate a severe epidemic.

Foodborne Transmission of Nipah Virus, Bangladesh

TOC summary line: Nipah virus was likely transmitted from fruit bats to humans by drinking fresh date palm sap.

Recurrent Zoonotic Transmission of Nipah Virus into Humans, Bangladesh, 2001-2007

More than half of identified cases result from person-to-person transmission.

Second look at the spread of epidemics on networks

In an important paper, Newman [Phys. Rev. E66, 016128 (2002)] claimed that a general network-based stochastic Susceptible-Infectious-Removed (SIR) epidemic model is isomorphic to a bond percolation model, where the bonds are the edges of the contact network and the bond occupation probability is equal to the marginal probability of transmission from an infected node to a susceptible neighbor. In this paper, we show that this isomorphism is incorrect and define a semidirected random network we call the epidemic percolation network that is exactly isomorphic to the SIR epidemic model in any finite population. In the limit of a large population, (i) the distribution of (self-limited) outbreak sizes is identical to the size distribution of (small) out-components, (ii) the epidemic threshold corresponds to the phase transition where a giant strongly connected component appears, (iii) the probability of a large epidemic is equal to the probability that an initial infection occurs in the giant in-component, and (iv) the relative final size of an epidemic is equal to the proportion of the network contained in the giant out-component. For the SIR model considered by Newman, we show that the epidemic percolation network predicts the same mean outbreak size below the epidemic threshold, the same epidemic threshold, and the same final size of an epidemic as the bond percolation model. However, the bond percolation model fails to predict the correct outbreak size distribution and probability of an epidemic when there is a nondegenerate infectious period distribution. We confirm our findings by comparing predictions from percolation networks and bond percolation models to the results of simulations. In the Appendix, we show that an isomorphism to an epidemic percolation network can be defined for any time-homogeneous stochastic SIR model.

Date palm sap linked to Nipah virus outbreak in Bangladesh, 2008.

INTRODUCTION We investigated a cluster of patients with encephalitis in the Manikgonj and Rajbari Districts of Bangladesh in February 2008 to determine the etiology and risk factors for disease. METHODS We classified persons as confirmed Nipah cases by the presence of immunoglobulin M antibodies against Nipah virus (NiV), or by the presence of NiV RNA or by isolation of NiV from cerebrospinal fluid or throat swabs who had onset of symptoms between February 6 and March 10, 2008. We classified persons as probable cases if they reported fever with convulsions or altered mental status, who resided in the outbreak areas during that period, and who died before serum samples were collected. For the case-control study, we compared both confirmed and probable Nipah case-patients to controls, who were free from illness during the reference period. We used motion-sensor-infrared cameras to observe bats contact of date palm sap. RESULTS We identified four confirmed and six probable case-patients, nine (90%) of whom died. The median age of the cases was 10 years; eight were males. The outbreak occurred simultaneously in two communities that were 44 km apart and separated by a river. Drinking raw date palm sap 2-12 days before illness onset was the only risk factor most strongly associated with the illness (adjusted odds ratio 25, 95% confidence intervals 3.3-∞, p<0.001). Case-patients reported no history of physical contact with bats, though community members often reported seeing bats. Infrared camera photographs showed that Pteropus bats frequently visited date palm trees in those communities where sap was collected for human consumption. CONCLUSION This is the second Nipah outbreak in Bangladesh where date palm sap has been implicated as the vehicle of transmission. Fresh date palm sap should not be drunk, unless effective steps have been taken to prevent bat access to the sap during collection.

Increasing Incidence of Post-Kala-Azar Dermal Leishmaniasis in a Population-Based Study in Bangladesh

Post-kala-azar dermal leishmaniasis (PKDL) occurs after kala-azar treatment and acts as a durable infection reservoir. On the basis of active case finding among 22,699 respondents, 813 (3.6%) had had kala-azar since 2002, of whom 79 (9.7%) developed PKDL. Eight additional patients with PKDL had no history of kala-azar. Annual kala-azar incidence peaked at 85 cases per 10,000 person-years in 2004 and fell to 46 cases per 10,000 person-years in 2007, but PKDL incidence rose from 1 case per 10,000 person-years in 2002-2004 to 21 cases per 10,000 person-years in 2007. The rising PKDL incidence threatens the regional visceral leishmaniasis elimination initiative and underscores the urgent need for more effective PKDL diagnosis and treatment.

The global transmission and control of influenza.

New strains of influenza spread around the globe via the movement of infected individuals. The global dynamics of influenza are complicated by different patterns of influenza seasonality in different regions of the world. We have released an open-source stochastic mathematical model of the spread of influenza across 321 major, strategically located cities of the world. Influenza is transmitted between cities via infected airline passengers. Seasonality is simulated by increasing the transmissibility in each city at the times of the year when influenza has been observed to be most prevalent. The spatiotemporal spread of pandemic influenza can be understood through clusters of global transmission and links between them, which we identify using the epidemic percolation network (EPN) of the model. We use the model to explain the observed global pattern of spread for pandemic influenza A(H1N1) 2009–2010 (pandemic H1N1 2009) and to examine possible global patterns of spread for future pandemics depending on the origin of pandemic spread, time of year of emergence, and basic reproductive number (). We also use the model to investigate the effectiveness of a plausible global distribution of vaccine for various pandemic scenarios. For pandemic H1N1 2009, we show that the biggest impact of vaccination was in the temperate northern hemisphere. For pandemics starting in the temperate northern hemisphere in May or April, vaccination would have little effect in the temperate southern hemisphere and a small effect in the tropics. With the increasing interconnectedness of the worlds population, we must take a global view of infectious disease transmission. Our open-source, computationally simple model can help public health officials plan for the next pandemic as well as deal with interpandemic influenza.

Reproductive numbers, epidemic spread and control in a community of households.

Many of the studies on emerging epidemics (such as SARS and pandemic flu) use mass action models to estimate reproductive numbers and the needed control measures. In reality, transmission patterns are more complex due to the presence of various social networks. One level of complexity can be accommodated by considering a community of households. Our study of transmission dynamics in a community of households emphasizes five types of reproductive numbers for the epidemic spread: household-to-household reproductive number, leaky vaccine-associated reproductive numbers, perfect vaccine reproductive number, growth rate reproductive number, and the individual reproductive number. Each of those carries different information about the transmission dynamics and the required control measures, and often some of those can be estimated from the data while others cannot. Simulations have shown that under certain scenarios there is an ordering for those reproductive numbers. We have proven a number of ordering inequalities under general assumptions about the individual infectiousness profiles. Those inequalities allow, for instance, to estimate the needed vaccine coverage and other control measures without knowing the various transmission parameters in the models. Along the way, we have also shown that in choosing between increasing vaccine efficacy and increasing coverage levels by the same factor, preference should go to efficacy.

Clinical and Immunological Aspects of Post–Kala-Azar Dermal Leishmaniasis in Bangladesh

We conducted active surveillance for kala-azar and post-kala-azar dermal leishmaniasis (PKDL) in a population of 24,814 individuals. Between 2002 and 2010, 1,002 kala-azar and 185 PKDL cases occurred. Median PKDL patient age was 12 years; 9% had no antecedent kala-azar. Cases per 10,000 person-years peaked at 90 for kala-azar (2005) and 28 for PKDL (2007). Cumulative PKDL incidence among kala-azar patients was 17% by 5 years. Kala-azar patients younger than 15 years were more likely than older patients to develop PKDL; no other risk factors were identified. The most common lesions were hypopigmented macules. Of 98 untreated PKDL patients, 48 (49%) patients had resolution, with median time of 19 months. Kala-azar patients showed elevated interferon-γ (IFNγ), tumor necrosis factor-α (TNFα), and interleukin 10 (IL-10). Matrix metalloproteinase 9 (MMP9) and MMP9/tissue inhibitor of matrix metalloproteinase-1 (TIMP1) ratio were significantly higher in PKDL patients than in other groups. PKDL is frequent in Bangladesh and poses a challenge to the current visceral leishmaniasis elimination initiative in the Indian subcontinent.

Epidemic Percolation Networks, Epidemic Outcomes, and Interventions

Epidemic percolation networks (EPNs) are directed random networks that can be used to analyze stochastic “Susceptible-Infectious-Removed” (SIR) and “Susceptible-Exposed-Infectious-Removed” (SEIR) epidemic models, unifying and generalizing previous uses of networks and branching processes to analyze mass-action and network-based S(E)IR models. This paper explains the fundamental concepts underlying the definition and use of EPNs, using them to build intuition about the final outcomes of epidemics. We then show how EPNs provide a novel and useful perspective on the design of vaccination strategies.