Transmission of the highly pathogenic avian influenza virus H5N1 within flocks during the 2004 epidemic in Thailand.
ABSTRACT This present study is the first to quantify the transmission of avian influenza virus H5N1 within flocks during the 2004 epidemic in Thailand. It uses the flock-level mortality data to estimate the transmission-rate parameter ( beta ) and the basic reproduction number (R(0)). The point estimates of beta varied from 2.26/day (95% confidence interval [CI], 2.01-2.55) for a 1-day infectious period to 0.66/day (95% CI, 0.50-0.87) for a 4-day infectious period, whereas the accompanying R(0) varied from 2.26 (95% CI, 2.01-2.55) to 2.64 (95% CI, 2.02-3.47). Although the point estimates of beta of backyard chickens and fighting cocks raised together were lower than those of laying hens and broiler chickens, this difference was not statistically significant. These results will enable us to assess the control measures in simulation studies. They also indicate that, for the elimination of the virus, a critical proportion of the susceptible poultry population in a flock (i.e., 80% of the population) needs to be vaccinated.
Article: Quantifying Transmission of Highly Pathogenic and Low Pathogenicity H7N1 Avian Influenza in Turkeys.[show abstract] [hide abstract]
ABSTRACT: Outbreaks of avian influenza in poultry can be devastating, yet many of the basic epidemiological parameters have not been accurately characterised. In 1999-2000 in Northern Italy, outbreaks of H7N1 low pathogenicity avian influenza virus (LPAI) were followed by the emergence of H7N1 highly pathogenic avian influenza virus (HPAI). This study investigates the transmission dynamics in turkeys of representative HPAI and LPAI H7N1 virus strains from this outbreak in an experimental setting, allowing direct comparison of the two strains. The fitted transmission rates for the two strains are similar: 2.04 (1.5-2.7) per day for HPAI, 2.01 (1.6-2.5) per day for LPAI. However, the mean infectious period is far shorter for HPAI (1.47 (1.3-1.7) days) than for LPAI (7.65 (7.0-8.3) days), due to the rapid death of infected turkeys. Hence the basic reproductive ratio, [Formula: see text] is significantly lower for HPAI (3.01 (2.2-4.0)) than for LPAI (15.3 (11.8-19.7)). The comparison of transmission rates and [Formula: see text] are critically important in relation to understanding how HPAI might emerge from LPAI. Two competing hypotheses for how transmission rates vary with population size are tested by fitting competing models to experiments with differing numbers of turkeys. A model with frequency-dependent transmission gives a significantly better fit to experimental data than density-dependent transmission. This has important implications for extrapolating experimental results from relatively small numbers of birds to the commercial poultry flock size, and for how control, including vaccination, might scale with flock size.PLoS ONE 01/2012; 7(9):e45059. · 4.09 Impact Factor
Article: Improving Risk Models for Avian Influenza: The Role of Intensive Poultry Farming and Flooded Land during the 2004 Thailand Epidemic.[show abstract] [hide abstract]
ABSTRACT: Since 1996 when Highly Pathogenic Avian Influenza type H5N1 first emerged in southern China, numerous studies sought risk factors and produced risk maps based on environmental and anthropogenic predictors. However little attention has been paid to the link between the level of intensification of poultry production and the risk of outbreak. This study revised H5N1 risk mapping in Central and Western Thailand during the second wave of the 2004 epidemic. Production structure was quantified using a disaggregation methodology based on the number of poultry per holding. Population densities of extensively- and intensively-raised ducks and chickens were derived both at the sub-district and at the village levels. LandSat images were used to derive another previously neglected potential predictor of HPAI H5N1 risk: the proportion of water in the landscape resulting from floods. We used Monte Carlo simulation of Boosted Regression Trees models of predictor variables to characterize the risk of HPAI H5N1. Maps of mean risk and uncertainty were derived both at the sub-district and the village levels. The overall accuracy of Boosted Regression Trees models was comparable to that of logistic regression approaches. The proportion of area flooded made the highest contribution to predicting the risk of outbreak, followed by the densities of intensively-raised ducks, extensively-raised ducks and human population. Our results showed that as little as 15% of flooded land in villages is sufficient to reach the maximum level of risk associated with this variable. The spatial pattern of predicted risk is similar to previous work: areas at risk are mainly located along the flood plain of the Chao Phraya river and to the south-east of Bangkok. Using high-resolution village-level poultry census data, rather than sub-district data, the spatial accuracy of predictions was enhanced to highlight local variations in risk. Such maps provide useful information to guide intervention.PLoS ONE 01/2012; 7(11):e49528. · 4.09 Impact Factor
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ABSTRACT: The modelling of contact processes between hosts is of key importance in epidemiology. Current studies have mainly focused on networks with stationary structures, although we know these structures to be dynamic with continuous appearance and disappearance of links over time. In the case of moving individuals, the contact network cannot be established. Individual-based models (IBMs) can simulate the individual behaviours involved in the contact process. However, with very large populations, they can be hard to simulate and study due to the computational costs. We use the moment approximation (MA) method to approximate a stochastic IBM with an aggregated deterministic model. We illustrate the method with an application in animal epidemiology: the spread of the highly pathogenic virus H5N1 of avian influenza in a poultry flock. The MA method is explained in a didactic way so that it can be reused and extended. We compare the simulation results of three models: 1. an IBM, 2. a MA, and 3. a mean-field (MF). The results show a close agreement between the MA model and the IBM. They highlight the importance for the models to capture the displacement behaviours and the contact processes in the study of disease spread. We also illustrate an original way of using different models of the same system to learn more about the system itself, and about the representation we build of it.PLoS ONE 01/2012; 7(12):e51760. · 4.09 Impact Factor