Kathryn Glass

Dynamic patterns of avian and human influenza in east and southeast Asia

The seasonal patterns of human influenza in temperate regions have been well documented; however, much less attention has been paid to patterns of infection in the tropical and subtropical areas of east and southeast Asia. During the period 1997-2006, this region experienced several outbreaks of highly pathogenic avian influenza A (H5N1) in hosts including wild and domestic poultry, human beings, and other mammals. H5N1 is thought to be a likely source of a pandemic strain of human influenza. Incidence of both human influenza and avian influenza in human beings shows evidence of seasonality throughout east and southeast Asia, although the seasonal patterns in tropical and subtropical areas are not as simple or as pronounced as those in temperate regions around the world. The possibility of a human being becoming co-infected with both human and avian strains of influenza is not restricted to a short season, although the risks do appear to be greatest during the winter months.

Pandemic (H1N1) 2009 Influenza Community Transmission Was Established in One Australian State When the Virus Was First Identified in North America

Background In mid-June 2009 the State of Victoria in Australia appeared to have the highest notification rate of pandemic (H1N1) 2009 influenza in the world. We hypothesise that this was because community transmission of pandemic influenza was already well established in Victoria at the time testing for the novel virus commenced. In contrast, this was not true for the pandemic in other parts of Australia, including Western Australia (WA). Methods We used data from detailed case follow-up of patients with confirmed infection in Victoria and WA to demonstrate the difference in the pandemic curve in two Australian states on opposite sides of the continent. We modelled the pandemic in both states, using a susceptible-infected-removed model with Bayesian inference accounting for imported cases. Results Epidemic transmission occurred earlier in Victoria and later in WA. Only 5% of the first 100 Victorian cases were not locally acquired and three of these were brothers in one family. By contrast, 53% of the first 102 cases in WA were associated with importation from Victoria. Using plausible model input data, estimation of the effective reproductive number for the Victorian epidemic required us to invoke an earlier date for commencement of transmission to explain the observed data. This was not required in modelling the epidemic in WA. Conclusion Strong circumstantial evidence, supported by modelling, suggests community transmission of pandemic influenza was well established in Victoria, but not in WA, at the time testing for the novel virus commenced in Australia. The virus is likely to have entered Victoria and already become established around the time it was first identified in the US and Mexico.

Interpreting time-series analyses for continuous-time biological models—measles as a case study

An increasing number of recent studies involve the fitting of mechanistic models to ecological time-series. In some cases, it is necessary for these models to be discrete-time approximations of continuous-time processes. We test the validity of discretization in the case of measles, where time-series models have recently been developed to estimate ecological parameters directly from data. We find that a non-homogeneous contact function is necessary to capture the host-parasite interaction in a discrete-time model, even in the absence of heterogeneities due to spatial or age structure. We derive a mathematical relationship describing the expected departure from mass-action transmission in terms of the epidemiological parameters in the model, and identify conditions under which the discretization process may fail.

How much would closing schools reduce transmission during an influenza pandemic

Background: When deciding whether to close schools during an influenza pandemic, authorities must weigh the likely benefits against the expected social disruption. Although schools have been closed to slow the spread of influenza, there is limited evidence as to the impact on transmission of disease. Methods: To assess the benefits of closing schools for various pandemic scenarios, we used a stochastic mathematical model of disease transmission fitted to attack rates from past influenza pandemics. We compared these benefits with those achieved by other interventions targeted at children. Results: Closing schools can reduce transmission among children considerably, but has only a moderate impact on average transmission rates among all individuals (both adults and children) under most scenarios. Much of the benefit of closing schools can be achieved if schools are closed by the time that 2% of children are infected; if the intervention is delayed until 20% of children are infected, there is little benefit. Immunization of all school children provides only a slight improvement over closing schools, indicating that schools are an important venue for transmission between children. Relative attack rates in adults and children provide a good indication of the likely benefit of closing schools, with the greatest impact seen for infections with high attack rates in children. Conclusions: Closing schools is effective at reducing transmission between children but has only a moderate effect on average transmission rates in the wider population unless children are disproportionately affected.

Foodborne Illness, Australia, Circa 2000 and Circa 2010

Overall incidence of foodborne gastroenteritis declined but remains high, and the incidence of salmonellosis and campylobacteriosis increased.

The effects of strain heterology on the epidemiology of equine influenza in a vaccinated population

We assess the effects of strain heterology (strains that are immunologically similar but not identical) on equine influenza in a vaccinated population. Using data relating to individual animals, for both homologous and heterologous vaccinees, we estimate distributions for the latent and infectious periods, quantify the risk of becoming infected in terms of the quantity of cross–reactive antibodies to a key surface protein of the virus (haemagglutinin) and estimate the probability of excreting virus (i.e. becoming infectious) given that infection has occurred. The data suggest that the infectious period, the risk of becoming infected (for a given vaccine–induced level of cross–reactive antibodies) and the probability of excreting virus are increased for heterologously vaccinated animals when compared with homologously vaccinated animals. The data are used to parameterize a modified susceptible, exposed, infectious and recovered/resistant (SEIR) model, which shows that these relatively small differences combine to have a large effect at the population level, where populations of heterologous vaccinees face a significantly increased risk of an epidemic occurring.

Avian Influenza H5N1 Transmission in Households, Indonesia

Background Disease transmission patterns are needed to inform public health interventions, but remain largely unknown for avian influenza H5N1 virus infections. A recent study on the 139 outbreaks detected in Indonesia between 2005 and 2009 found that the type of exposure to sources of H5N1 virus for both the index case and their household members impacted the risk of additional cases in the household. This study describes the disease transmission patterns in those outbreak households. Methodology/Principal Findings We compared cases (n = 177) and contacts (n = 496) in the 113 sporadic and 26 cluster outbreaks detected between July 2005 and July 2009 to estimate attack rates and disease intervals. We used final size household models to fit transmission parameters to data on household size, cases and blood-related household contacts to assess the relative contribution of zoonotic and human-to-human transmission of the virus, as well as the reproduction number for human virus transmission. The overall household attack rate was 18.3% and secondary attack rate was 5.5%. Secondary attack rate remained stable as household size increased. The mean interval between onset of subsequent cases in outbreaks was 5.6 days. The transmission model found that human transmission was very rare, with a reproduction number between 0.1 and 0.25, and the upper confidence bounds below 0.4. Transmission model fit was best when the denominator population was restricted to blood-related household contacts of index cases. Conclusions/Significance The study only found strong support for human transmission of the virus when a single large cluster was included in the transmission model. The reproduction number was well below the threshold for sustained transmission. This study provides baseline information on the transmission dynamics for the current zoonotic virus and can be used to detect and define signatures of a virus with increasing capacity for human-to-human transmission.

Spatial dynamics of an epidemic of severe acute respiratory syndrome in an urban area

OBJECTIVE To map risk of exposure to severe acute respiratory syndrome (SARS) in an urban area and assess the ability of traditional interventions to control dispersion of the disease. METHODS Data on the Beijing SARS epidemic were used to map spatial clusters of identified contacts and to estimate transmission of SARS using a model with a time-dependent transmission rate. RESULTS The estimated transmission rate decreased dramatically from 20 to 30 April 2003. The total number of cases in the epidemic in Beijing was estimated to be 2521. Hierarchical clustering revealed that risk-exposures were widespread, but clustered in a pattern that is distinctly related to the Beijing urban ring roads. CONCLUSION Traditional control measures can be very effective at reducing transmission of SARS. Spatial patterns of risk-exposures can inform disease surveillance, prediction and control by identifying spatial target areas on which interventions should be focused.

The effect of heterogeneity in measles vaccination on population immunity

High overall vaccination levels sometimes hide pockets of poor coverage. We adopted a meta-population framework to model local aggregation of populations, and used this to investigate the effects of vaccination heterogeneity. A recent survey of antibody levels in a community with low vaccination levels in The Netherlands enabled us to assess the relative importance of local and long-range infective contacts, and thus identify feasible levels of aggregation in the meta-population model. In the aggregated model, we found that heterogeneity in vaccination coverage can lead to a much increased rate of infection among unvaccinated individuals, with a simultaneous drop in the average age at infection.

Modelling equine influenza 1: a stochastic model of within-yard epidemics.

This paper demonstrates that a simple stochastic model can capture the features of an epidemic of equine influenza in unvaccinated horses. When the model is modified to consider vaccinated horses, we find that vaccination dramatically reduces the incidence and size of epidemics. Although occasional larger outbreaks can still occur, these are exceptional. We then look at the effects of vaccination on a yard of horses, and in particular at the relationship between pre-challenge antibody level and quantity of virus shed when challenged with the virus. While on average, a high antibody level implies that less virus will be shed during the infectious period, we identify a high degree of heterogeneity in the response of horses with similar pre-challenge antibody levels. We develop a modified model that incorporates some heterogeneity in levels of infectivity, and compare this with the simpler model.