Spatiotemporal distributions of reported cases of the avian influenza H5N1 (bird flu) in Southern China in early 2004

Risk factor modelling of the spatio-temporal patterns of highly pathogenic avian influenza (HPAIV) H5N1: a review

Highly pathogenic avian influenza virus (HPAIV) H5N1 continues to impact on smallholder livelihoods, to constrain development of the poultry production sector, and to cause occasional human fatalities. HPAI H5N1 outbreaks have occurred in a variety of ecological systems with economic, agricultural and environmental differences. This review aimed to identify common risk factors amongst spatial modelling studies conducted in these different agro-ecological systems, and to identify gaps in our understanding of the disease's spatial epidemiology. Three types of variables with similar statistical association with HPAI H5N1 presence across studies and regions were identified: domestic waterfowl, several anthropogenic variables (human population density, distance to roads) and indicators of water presence. Variables on socio-economic conditions, poultry trade, wild bird distribution and movements were comparatively rarely considered. Few studies have analysed the HPAI H5N1 distribution in countries such as Egypt and Indonesia, where HPAIV H5N1 continues to circulate extensively.

Alignment free characterization of the influenza-A hemagglutinin genes by the ISSCOR method

Analyses and visualizations by the ISSCOR method of the influenza virus hemagglutinin genes of three different A-subtypes revealed some rather striking temporal (for A/H3N3), and spatial relationships (for A/H5N1) between groups of individual gene subsets. The application to the A/H1N1 set revealed also relationships between the seasonal H1, and the swine-like novel 2009 H1v variants in a quick and unambiguous manner. Based on these examples we consider the application of the ISSCOR method for analysis of large sets of homologous genes as a worthwhile addition to a toolbox of genomics-it allows a rapid diagnostics of trends, and possibly can even aid an early warning of newly emerging epidemiological threats.

A GIS model predicting potential distributions of a lineage: a test case on hermit spiders (Nephilidae: Nephilengys)

BACKGROUND

Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters.

METHODOLOGY/PRINCIPAL FINDINGS

We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World), N. livida (Madagascar), N. malabarensis (S-SE Asia), and N. papuana (Australasia). For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range), a large part of Brazil and the Guianas (area of synanthropic spread), and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (sub)tropics.

CONCLUSIONS

Our model is a customizable GIS tool intended to predict current and future potential distributions of globally distributed terrestrial lineages. Its predictive potential may be tested in foreseeing species distribution shifts due to habitat destruction and global climate change.

Risk signals of an influenza pandemic caused by highly pathogenic avian influenza subtype H5N1: spatio-temporal perspectives

Highly pathogenic avian influenza (HPAI) subtype H5N1 is a trans-boundary animal disease that has crossed the animal-human species barrier and over the past decade has had a considerable impact on the poultry industry, wild bird populations and on human health. Understanding the spatio-temporal patterns of H5N1 outbreaks can provide visual clues to the dynamics of disease spread and of areas at risk, and thus improve the cost-effectiveness of disease control and prevention. This study describes the characteristics and investigates the temporal, spatial and space-time dynamics of H5N1 outbreaks in domestic poultry between December 2003 and December 2009 using a global database. The study found that the start date of the epidemic wave was postponed, the duration of the epidemic was prolonged and its magnitude reduced over time, but the disease transmission cycle was not efficiently interrupted. Two 'hot-spot' regions of H5N1 outbreaks were identified: well-documented locations in East and Southeast Asia, as well as a novel location at the boundaries of Europe and Africa, where enhanced surveillance should be conducted. The risk of a pandemic due to H5N1 remains high.

Spatial distribution and risk factors of highly pathogenic avian influenza (HPAI) H5N1 in China

Highly pathogenic avian influenza (HPAI) H5N1 was first encountered in 1996 in Guangdong province (China) and started spreading throughout Asia and the western Palearctic in 2004-2006. Compared to several other countries where the HPAI H5N1 distribution has been studied in some detail, little is known about the environmental correlates of the HPAI H5N1 distribution in China. HPAI H5N1 clinical disease outbreaks, and HPAI virus (HPAIV) H5N1 isolated from active risk-based surveillance sampling of domestic poultry (referred to as HPAIV H5N1 surveillance positives in this manuscript) were modeled separately using seven risk variables: chicken, domestic waterfowl population density, proportion of land covered by rice or surface water, cropping intensity, elevation, and human population density. We used bootstrapped logistic regression and boosted regression trees (BRT) with cross-validation to identify the weight of each variable, to assess the predictive power of the models, and to map the distribution of HPAI H5N1 risk. HPAI H5N1 clinical disease outbreak occurrence in domestic poultry was mainly associated with chicken density, human population density, and elevation. In contrast, HPAIV H5N1 infection identified by risk-based surveillance was associated with domestic waterfowl density, human population density, and the proportion of land covered by surface water. Both models had a high explanatory power (mean AUC ranging from 0.864 to 0.967). The map of HPAIV H5N1 risk distribution based on active surveillance data emphasized areas south of the Yangtze River, while the distribution of reported outbreak risk extended further North, where the density of poultry and humans is higher. We quantified the statistical association between HPAI H5N1 outbreak, HPAIV distribution and post-vaccination levels of seropositivity (percentage of effective post-vaccination seroconversion in vaccinated birds) and found that provinces with either outbreaks or HPAIV H5N1 surveillance positives in 2007-2009 appeared to have had lower antibody response to vaccination. The distribution of HPAI H5N1 risk in China appears more limited geographically than previously assessed, offering prospects for better targeted surveillance and control interventions.

Risk factors and clusters of Highly Pathogenic Avian Influenza H5N1 outbreaks in Bangladesh

Between March 2007 and July 2009, 325 Highly Pathogenic Avian Influenza (HPAI, subtype H5N1) outbreaks in poultry were reported in 154 out of a total of 486 sub-districts in Bangladesh. This study analyzed the temporal and spatial patterns of HPAI H5N1 outbreaks and quantified the relationship between several spatial risk factors and HPAI outbreaks in sub-districts in Bangladesh. We assessed spatial autocorrelation and spatial dependence, and identified clustering sub-districts with disease statistically similar to or dissimilar from their neighbors. Three significant risk factors associated to HPAI H5N1 virus outbreaks were identified; the quadratic log-transformation of human population density [humans per square kilometer, P=0.01, OR 1.15 (95% CI: 1.03-1.28)], the log-transformation of the total commercial poultry population [number of commercial poultry per sub-district, P<0.002, OR 1.40 (95% CI: 1.12-1.74)], and the number of roads per sub-district [P=0.02, OR 1.07 (95% CI: 1.01-1.14)]. The distinct clusters of HPAI outbreaks and risk factors identified could assist the Government of Bangladesh to target surveillance and to concentrate response efforts in areas where disease is likely to occur. Concentrating response efforts may help to combat HPAI more effectively, reducing the environmental viral load and so reducing the number of disease incidents.

Persistence of highly pathogenic avian influenza H5N1 virus defined by agro-ecological niche

The highly pathogenic avian influenza (HPAI) H5N1 virus has spread across Eurasia and into Africa. Its persistence in a number of countries continues to disrupt poultry production, impairs smallholder livelihoods, and raises the risk a genotype adapted to human-to-human transmission may emerge. While previous studies identified domestic duck reservoirs as a primary risk factor associated with HPAI H5N1 persistence in poultry in Southeast Asia, little is known of such factors in countries with different agro-ecological conditions, and no study has investigated the impact of such conditions on HPAI H5N1 epidemiology at the global scale. This study explores the patterns of HPAI H5N1 persistence worldwide, and for China, Indonesia, and India includes individual provinces that have reported HPAI H5N1 presence during the 2004-2008 period. Multivariate analysis of a set of 14 agricultural, environmental, climatic, and socio-economic factors demonstrates in quantitative terms that a combination of six variables discriminates the areas with human cases and persistence: agricultural population density, duck density, duck by chicken density, chicken density, the product of agricultural population density and chicken output/input ratio, and purchasing power per capita. The analysis identifies five agro-ecological clusters, or niches, representing varying degrees of disease persistence. The agro-ecological distances of all study areas to the medoid of the niche with the greatest number of human cases are used to map HPAI H5N1 risk globally. The results indicate that few countries remain where HPAI H5N1 would likely persist should it be introduced.

Identifying spatio-temporal patterns of transboundary disease spread: examples using avian influenza H5N1 outbreaks

Characterizing spatio-temporal patterns among epidemics in which the mechanism of spread is uncertain is important for generating disease spread hypotheses, which may in turn inform disease control and prevention strategies. Using a dataset representing three phases of highly pathogenic avian influenza H5N1 outbreaks in village poultry in Romania, 2005-2006, spatiotemporal patterns were characterized. We first fit a set of hierarchical Bayesian models that quantified changes in the spatio-temporal relative risk for each of the 23 affected counties. We then modeled spatial synchrony in each of the three epidemic phases using non-parametric covariance functions and Thin Plate Spline regression models. We found clear differences in the spatio-temporal patterns among the epidemic phases (local versus regional correlated processes), which may indicate differing spread mechanisms (for example wild bird versus human-mediated). Elucidating these patterns allowed us to postulate that a shift in the primary mechanism of disease spread may have taken place between the second and third phases of this epidemic. Information generated by such analyses could assist affected countries in determining the most appropriate control programs to implement, and to allocate appropriate resources to preventing contact between domestic poultry and wild birds versus enforcing bans on poultry movements and quarantine. The methods used in this study could be applied in many different situations to analyze transboundary disease data in which only location and time of occurrence data are reported.

Influenza A H5N1 immigration is filtered out at some international borders

BACKGROUND

Geographic spread of highly pathogenic influenza A H5N1, the bird flu strain, appears a necessary condition for accelerating the evolution of a related human-to-human infection. As H5N1 spreads the virus diversifies in response to the variety of socioecological environments encountered, increasing the chance a human infection emerges. Genetic phylogenies have for the most part provided only qualitative evidence that localities differ in H5N1 diversity. For the first time H5N1 variation is quantified across geographic space.

METHODOLOGY AND PRINCIPAL FINDINGS

We constructed a statistical phylogeography of 481 H5N1 hemagglutinin genetic sequences from samples collected across 28 Eurasian and African localities through 2006. The MigraPhyla protocol showed southern China was a source of multiple H5N1 strains. Nested clade analysis indicated H5N1 was widely dispersed across southern China by both limited dispersal and long distance colonization. The UniFrac metric, a measure of shared phylogenetic history, grouped H5N1 from Indonesia, Japan, Thailand and Vietnam with those from southeastern Chinese provinces engaged in intensive international trade. Finally, H5N1's accumulative phylogenetic diversity was greatest in southern China and declined beyond. The gradient was interrupted by areas of greater and lesser phylogenetic dispersion, indicating H5N1 migration was restricted at some geopolitical borders. Thailand and Vietnam, just south of China, showed significant phylogenetic clustering, suggesting newly invasive H5N1 strains have been repeatedly filtered out at their northern borders even as both countries suffered recurring outbreaks of endemic strains. In contrast, Japan, while successful in controlling outbreaks, has been subjected to multiple introductions of the virus.

CONCLUSIONS

The analysis demonstrates phylogenies can provide local health officials with more than hypotheses about relatedness. Pathogen dispersal, the functional relationships among disease ecologies across localities, and the efficacy of control efforts can also be inferred, all from viral genetic sequences alone.