Flying Over an Infected Landscape: Distribution of Highly Pathogenic Avian Influenza H5N1 Risk in South Asia and Satellite Tracking of Wild Waterfowl

Highly pathogenic avian influenza (HPAI) H5N1 virus persists in Asia, posing a threat to poultry, wild birds, and humans. Previous work in Southeast Asia demonstrated that HPAI H5N1 risk is related to domestic ducks and people. Other studies discussed the role of migratory birds in the long distance spread of HPAI H5N1. However, the interplay between local persistence and long-distance dispersal has never been studied. We expand previous geospatial risk analysis to include South and Southeast Asia, and integrate the analysis with migration data of satellite-tracked wild waterfowl along the Central Asia flyway. We find that the population of domestic duck is the main factor delineating areas at risk of HPAI H5N1 spread in domestic poultry in South Asia, and that other risk factors, such as human population and chicken density, are associated with HPAI H5N1 risk within those areas. We also find that satellite tracked birds (Ruddy Shelduck and two Bar-headed Geese) reveal a direct spatio-temporal link between the HPAI H5N1 hot-spots identified in India and Bangladesh through our risk model, and the wild bird outbreaks in May–June–July 2009 in China (Qinghai Lake), Mongolia, and Russia. This suggests that the continental-scale dynamics of HPAI H5N1 are structured as a number of persistence areas delineated by domestic ducks, connected by rare transmission through migratory waterfowl

Pathogen–host–environment interplay and disease emergence

Gaining insight in likely disease emergence scenarios is critical to preventing such events from happening. Recent focus has been on emerging zoonoses and on identifying common patterns and drivers of emerging diseases. However, no overarching framework exists to integrate knowledge on all emerging infectious disease events. Here, we propose such a conceptual framework based on changes in the interplay of pathogens, hosts and environment that lead to the formation of novel disease patterns and pathogen genetic adjustment. We categorize infectious disease emergence events into three groups: (i) pathogens showing up in a novel host, ranging from spill-over, including zoonoses, to complete species jumps; (ii) mutant pathogens displaying novel traits in the same host, including an increase in virulence, antimicrobial resistance and host immune escape; and (iii) disease complexes emerging in a new geographic area, either through range expansion or through long distance jumps. Each of these categories is characterized by a typical set of drivers of emergence, matching pathogen trait profiles, disease ecology and transmission dynamics. Our framework may assist in disentangling and structuring the rapidly growing amount of available information on infectious diseases. Moreover, it may contribute to a better understanding of how human action changes disease landscapes globally

The Programme Against African Trypanosomiasis Information System (PAATIS)

African trypanosomes are tsetse-transmitted protozoa that inhabit the extracellular compartment of host blood. They cause fatal sleeping sickness in people, and Nagana, a wasting and generally fatal disease, in cattle. While trypanosomes are most common to Africa (about 30% of Africa's cattle graze on the fringe of the tsetse habitat), some species have spread beyond its boarders to Asia, the Middle East and South America. The African Trypanosomes, volume one of World Class Parasites, is written for researchers, students and scholars who enjoy reading research that has a major impact on human health, or agricultural productivity, and against which we have no satisfactory defense. It is intended to supplement more formal texts that cover taxonomy, life cycles, morphology, vector distribution, symptoms and treatment. It integrates vector, pathogen and host biology and celebrates the diversity of approach that comprises modern parasitological research.info:eu-repo/semantics/publishe

A contribution towards simplifying area-wide tsetse surveys using medium resolution meteorological satellite data

A raster or grid-based Geographic Information System with data on tsetse, trypanosomiasis, animal production, agriculture and land use has recently been developed in Togo. The area-wide sampling of tsetse fly, aided by satellite imagery, is the subject of two separate papers. This paper follows on a first paper, published in this journal, describing the generation of digital tsetse distribution and abundance maps and how these accord with the local climatic and agro-ecological setting. Such maps when combined with data on the disease, the hosts and their owners, should contribute to the knowledge of the spatial epidemiology of trypanosomiasis and assist planning of integrated control operations. Here we address the problem of generating tsetse distribution and abundance maps from remotely sensed data, using a restricted amount of field data. Different discriminant analysis models have been applied using contemporary tsetse data and remotely sensed, low resolution data acquired from the National Oceanographic and Atmospheric Administration (NOAA) and Meteosat platforms. The results confirm the potential of satellite data application and multivariate analysis for the prediction of the tsetse distribution and abundance. This opens up new avenues because satellite predictions and field data may be combined to strengthen and/or substitute one another. The analysis shows how the strategic incorporation of satellite imagery may minimize field collection of data. Field surveys may be modified and conducted in two stages, first concentrating on the expected fly distribution limits and thereafter on fly abundance. The study also shows that when applying satellite data, care should be taken in selecting the optimal number of predictor variables because this number varies with the amount of training data for predicting abundance and on the homogeneity of the distribution limits for predicting fly presence. Finally, it is suggested that in addition to the use of contemporary training data and predictor variables, training and predicted data sets should refer to the same eco-geographic zone

The spatial pattern of trypanosomosis prevalence predicted with the aid of satellite imagery

Information on the spatial pattern of African animal trypanosomosis forms a prerequisite for rational disease management, but few data exist for any country in the continent. The present study describes a raster or grid-based Geographic Information System for Togo, a country representative of subhumid West Africa, with data layers on tsetse, trypanosomosis, animal production, agriculture and land use. The paper shows how trypanosomosis prevalence and packed cell volume (PCV) map displays may be predicted from correlations between representative field data and environmental and satellite data acquired from the National Oceanographic and Atmospheric Administration (NOAA) and Meteosat platforms. Discriminant analytical methods were used to assess the relationship between the amount of field data used and the accuracy of the predictions obtained. The accuracy of satellite derived predictions decreases from tsetse abundance to trypanosomosis prevalence to PCV value. The predictions improve when eco-climatic and epidemiological predictors are combined. In Togo, and probably elsewhere, the patterns of trypanosomosis prevalence and PCV are much influenced by animal husbandry and other anthropogenic factors. Additional predictor variables, incorporating these influences might therefore further improve the models

Patterns of spread and persistence of foot-and-mouth disease types A, O and Asia-1 in Turkey: a meta-population approach.

Despite significant control efforts, foot-and-mouth disease (FMD) persists in Turkey, and new strains of serotypes A, O and Asia-1 are periodically reported to enter the country from the east. The status of FMD in Turkey is important regionally because the country forms a natural bridge between Asia where the disease is endemic, and Europe which has disease-free status. This study analysed spatial and temporal patterns of FMD occurrence in Turkey to explore factors associated with the disease's persistence and spread. Annual records of FMD distribution in Turkish provinces throughout 1990-2002, grouped by serotype (O, A and Asia 1), were analysed using geostatistical techniques to explore their spatial and temporal patterns. A meta-population model was used to test how disease status, expressed in terms of presence/absence, extinction, and colonization, and measured at the province level throughout the periods 1990-1996 and 1997 2002, could be predicted using province-level data on: ruminant livestock numbers; meat production-demand discrepancy (as a surrogate measure of animal and animal products marketing, i.e. long-distance contagion through the traffic of mainly live animals to urban centres); and the disease prevalence distribution as recorded for the previous year. A drastic overall reduction in FMD occurrence was observed from the period 1990-1996 to 1997-2002 when the disease was shown to retract into persistence islands. FMD occurrence was associated with host abundance, short distance contagion from adjacent provinces, and meat production-demand discrepancies. With FMD retracting into identified provinces, a shift in predictors of FMD occurrence was observed with a lower contribution of short-distance contagion, and a relatively higher association with meat production-demand discrepancies leading to live animal transport over long distances, and hence presenting opportunities for identifying critical-control points. The pattern of persistence differed according to serotype groups and is discussed in relation to their differential affinity to cattle and small ruminant hosts