Spatio-temporal modeling of the African swine fever epidemic in the Russian Federation, 2007-2012.

In 2007 African swine fever (ASF) entered Georgia and in the same year the disease entered the Russian Federation. From 2007 to 2012 ASF spread throughout the southern region of the Russian Federation. At the same time several cases of ASF were detected in the central and northern regions of the Russian Federation, forming a northern cluster of outbreaks in 2011. This northern cluster is of concern because of its proximity to mainland Europe. The aim of this study was to use details of recorded ASF outbreaks and human and swine population details to estimate the spatial distribution of ASF risk in the southern region of the European part of the Russian Federation. Our model of ASF risk was comprised of two components. The first was an estimate of ASF suitability scores calculated using maximum entropy methods. The second was an estimate of ASF risk as a function of Euclidean distance from index cases. An exponential distribution fitted to a frequency histogram of the Euclidean distance between consecutive ASF cases had a mean value of 156 km, a distance greater than the surveillance zone radius of 100-150 km stated in the ASF control regulations for the Russian Federation. We show that the spatial and temporal risk of ASF expansion is related to the suitability of the area of potential expansion, which is in turn a function of socio-economic and geographic variables. We propose that the methodology presented in this paper provides a useful tool to optimize surveillance for ASF in affected areas.

Effects of Bayluscide on Bithynia siamensis goniomphalos, the first intermediate host of the human liver fluke, Opisthorchis viverrini, in laboratory and field trials.

The molluscicidal effects of Bayluscide (niclosamide) were investigated on Bithynia siamensis goniomphalos, the first intermediate host of human liver fluke, Opisthorchis viverrini. Lethal concentrations of 50% (LC(50)) and 95% (LC(95)) against young and adult males were 0.38 and 0.80, 0.42 and 0.86 ppm, respectively. The LC(50) and LC(95) against young and adult females were 0.42 and 0.86, 0.46 and 0.97 ppm, respectively. No significant differences in mortality rate between sexes or snail size (p > 0.05) was detected. Bayluscide-related tissue damage in B. siamensis goniomphalos included detachment of cilia of the epithelial layer of the digestive tract and decreased number of calcium cells. In tests of lethal concentrations of Bayluscide on non-target animals, no lethal effect was observed on Filopaludina martensi martensi (Viviparous snail) but high mortality rates were recorded in Puntius gonionotus fingerling, Ricefish (Oryzias mekongensis) and shrimp (Macrobrachium lanchesteri), but lower in guppy fish (Poecilia reticulata) after 24h exposure. For field trials, sufficient Bayluscide was sprayed in 3 roadside ditches to result in final concentrations of 5, 10 or 20 ppm, with mortality rates on B. siamensis goniomphalos of 10.94, 20.00 and 31.25%, respectively. Non-target snails died in small numbers but no effect was observed in other aquatic vertebrate animals. Field trials of Bayluscide on B. siamensis goniomphalos revealed low mortality rates, suggesting the need for application methods of higher efficacy or that Bayluscide is not suitable for application to operculate snails or snails which are able to escape by burying in mud.

Mapping risk of bovine fasciolosis in the south of Brazil using Geographic Information Systems.

Fasciolosis, caused by Fasciola hepatica, is an endemic disease of ruminants that occurs in several countries of South America where it can lead to decreased production and fertility and, in severe cases, animal death. Although very prevalent, information on the epidemiology of the disease is incomplete in Brazil. The objective of the present study was to define the prevalence of F. hepatica in the livers of cattle from slaughterhouses and correlate the data with the animal's origin (climate and altitude) using a Geographic Information System (GIS). The data was used to create an epidemiological map of fasciolosis by state (Rio Grande do Sul, Santa Catarina, Paraná), by municipality (n=530) and by year (2003-2008). Information was analyzed using a databank from slaughterhouses with Federal Inspection Services of the Ministry of Agriculture. The highest cattle infection rate was found in the two most Southern states of Rio Grande do Sul (18.7%) and Santa Catarina (10.1%). Animals from the Campanha region of Rio Grande do Sul and from the central coast area of Santa Catarina had prevalences of greater than 40%. Cattle from low altitudes municipalities were significantly more likely to have the disease (p<0.05). No significant differences were found between high or low prevalence and ambient temperatures. Risk maps resulting from this study provide information on the epidemiology and transmission of F. hepatica in Southern Brazil needed for design of appropriate control measures to control economic impacts. F. hepatica may represent an important source of zoonotic infection of humans as well; therefore these findings may be complemented by future studies on human infections in high risk areas.

An essential need: creating opportunities for veterinary students and graduates to gain an appreciation of responsibilities and opportunities in global veterinary issues.

Globalisation trends and bioterrorism issues have led to new concerns relating to public health, animal health, international trade and food security. There is an imperative to internationalise and strengthen global public health capacity by renewed emphasis on veterinary public health in veterinary education and increasing opportunities for elective experiential learning in public practice programmes for veterinary students. Recent experience with a US-Brazil Higher Education Consortia Program is used as an example of potential ways in which veterinary students can gain an appreciation for global veterinary issues.

Biology-based mapping of vector-borne parasites by geographic information systems and remote sensing.

Application of growing degree day-water budget analysis and satellite climatology to vector-borne parasites will be reviewed to demonstrate the value of using the unique thermal-hydrological preferences and limits of tolerance of individual parasite-vector systems to define the environmental niche of disease agents in the landscape by modern geospatial analysis methods. Applications of geospatial modeling will be illustrated by examples on fascioliasis, malaria, leprosy and leishmaniasis.

Biology-based mapping of vector-borne parasites by Geographic Information Systems and Remote Sensing.

Applications of growing degree day-water budget analysis and satellite climatology to vector-borne parasites are reviewed to demonstrate the value of using the unique thermal-hydrological preferences and limits of tolerance of individual parasite-vector systems to define the environmental niche of disease agents in the landscape by modern geospatial analysis methods.

Modeling the distribution of Schistosoma mansoni and host snails in Uganda using satellite sensor data and Geographical Information Systems.

The potential value of MODIS satellite sensor data on Normalized Difference Vegetation Index (NDVI) and land surface temperatures (LST) for describing the distribution of the Schistosoma mansoni-"Biomphalaria pfeifferi"/Biomphalaria sudanica parasite-snail system in inland Uganda, were tested by developing annual and seasonal composite models, and iteratively analysing for their relationship with parasite and snail distribution. The dry season composite model predicted an endemic area that produced the best fit with the distribution of schools with > or =5% prevalence. NDVI values of 151-174, day temperatures of 26-36 degrees C, and night temperatures of 15-20 degrees C were used as criteria for the prediction model. Using the same approach with host snail data indicated that most of Uganda is suitable "B. pfeifferi"/B. sudanica habitat, except for possibly the north-eastern region of the country. The parasite, however, appears to be restricted in its distribution in both the north-eastern and the south-western regions of Uganda. The absence of disease in the south-west can not be attributed to the absence of snail hosts. Results suggest a combination of satellite sensor data on temperature and standard climate data on precipitation, as the best ecological determinants of the S. mansoni-"B. pfeifferi"/B. sudanica system. Satellite composite models and logistic regression analysis, suggest low night time temperature as one of the significant factors inhibiting S. mansoni transmission in the south-western highland areas of Uganda. The developed models are, however, unique, representing species-specific ecologic preferences of the S. mansoni-"B. Pfeifferi"/B. sudanica system in inland Uganda. Further validation studies are needed to test the value of the model in other countries in East Africa.

Use of Geographic Information Systems in the development of prediction models for onchocerciasis control in Ethiopia.

A risk assessment model was developed for onchocerciasis distribution and its control in Ethiopia using Geographic Information System (GIS) methods. GIS data analysis was done to generate 3 separate risk models using selected environmental features of (1) earth observing satellite data on Normalized Difference Vegetation Index (NDVI) and midday Land Surface Temperature (LST) prepared from AVHRR sensor data of the Global land 1-km project for the years 1992 and 1995, (2) FAO agroclimatic databases from the Crop Production System Zone (CPSZ) of the Intergovernmental Authority on Development (IGAD) sub-region of East Africa, and (3) a climate-based forecast index based on the growing degree days (GDD) and water budget concepts. Parasitological data used for the analysis were published and unpublished reports of onchocerciasis surveillance made between 1969 and 2000 in various parts of the country. Analysis of queries based on 1992 and 1995 annual wet and dry season data of the Global land 1-km project resulted in a predictive value of 95.1%, 94.0% and 96.3%, respectively, using data values extracted from buffers centered on sites above 5% prevalence. The model based on CPSZ data predicted an endemic area that best fit the distribution of sites over 5% prevalence; the query was based on CPSZ values of average altitude (442-2134 m), annual mean temperature (18-28 degrees C), annual rainfall (822-1980 mm), annual potential evapotranspiration (1264-1938 mm), rain minus potential evapotranspiration (-124 - 792 mm), average NDVI x 100 (2000-5000) and average terrain percent slope (9-34). The climate-based model based on GDD and water-budget predicted high risk to severe risk areas in the western and southwestern parts of the country. All three of the models predicted suitable areas for the transmission of onchocerciasis outside known endemic areas, suggesting the need for ground-based validation and potential application to current community-directed treatment programs with ivermectin (CDTI) for control of onchocerciasis in Ethiopia.

Geographical Information Systems risk assessment models for zoonotic fascioliasis in the South American Andes region.

The WHO recognises Fasciola hepatica to be an important human health problem. The Andean countries of Peru, Bolivia and Chile are those most severely affected by this distomatosis, though areas of Ecuador, Colombia and Venezuela are also affected. As part of a multidisciplinary project, we present results of use of a Geographical Information Systems (GIS) forecast model to conduct an epidemiological analysis of human and animal fasciolosis in the central part of the Andes mountains. The GIS approach enabled us to develop a spatial and temporal epidemiological model to map the disease in the areas studied and to classify transmission risk into low, moderate and high risk areas so that areas requiring the implementation of control activities can be identified. Current results are available on a local scale for: (1) the northern Bolivian Altiplano, (2) Puno in the Peruvian Altiplano, (3) the Cajamarca and Mantaro Peruvian valleys, and (4) the Ecuadorian provinces of Azuay, Cotopaxi and Imbabura. Analysis of results demonstrated the validity of a forecast model that combines use of climatic data to calculate of forecast indices with remote sensing data, through the classification of Normalized Difference Vegetation Index (NDVI) maps.

Modeling the biocoenose of parasitic diseases using remote sensing and geographic information systems.

Application of growing degree day-water budget analysis concepts to snail-borne diseases are reviewed to demonstrate use of the unique thermal-hydrological preferences and limits of tolerance of individual parasite-vector systems to define the environmental niche of disease agents in the landscape by modern geospatial analysis tools.

[A minimum medical GIS database (MMDb) for Europe]. / Minimum medical GIS database (MMDb) per l'Europa.

Geographic information systems (GIS) and remote sensing (RS) technologies are being used increasingly to study the spatial and temporal patterns of some parasitic diseases of medical and veterinary importance. At the same time, the incorporation of GIS in this field shows the scarcity of the data and images available, which sometime discourage researchers that still look at GIS as a system too difficult and unusable for medical study. Aware of this problem and supported by success of earlier MMDb's for Africa, Asia and South America, the authors' aim is to construct and offer an MMDb for Europe. The initial MMDb is composed with vector images covering an area situated from -11 degrees-70 degrees N to 58 degrees-30 degrees E. Specifically, data layers include: a) Global Moderate-Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16 days at 250 m spatial resolution designed to provide consistent spatial and temporal comparisons of vegetation conditions, supplied in the MMDb as seasonal and annual composite images from 2000 to 2003, b) MODIS Land Surface Temperature (LST) calculated from daytime and nighttime observations at 8 day intervals at 1 km spatial resolution, supplied in the MMDb as seasonal and annual composites images for day (maximum) temperatures, night (minimum) temperatures from 2000 to 2003, c) GTOPO30 Digital Elevation Model (DEM) at 1 km spatial resolution, d) United States Geological Survey (USGS) Land use/land cover scheme, e) USGS actual and potential evapotranspiration supplied for all 12 months as a grid at 50 km spatial resolution, f) USGS precipitation showing the amount of rainfall for all 12 months supplied as a grid at 50 km spatial resolution, g) USGS shapefiles of administrative and political boundaries, cities, towns, villages, lakes, rivers, streams, road, railroads and more. The MMDb projection will be in geographic latitude-longitude, decimal degree format. This global format is most commonly used for public access map database resources and can be readily re-projected as needed for compatibility with various national mapping systems. There is no "required" software, and end users need only common commercial GIS software packages that have mutual import-export functions. Additionally, the MMDb is meant to be a dynamic resource that end users may improve and modify with other regional data.

Use of remote sensing and geographical information systems to identify environmental features that influence the distribution of paramphistomosis in sheep from the southern Italian Apennines.

A geographic information system (GIS) was constructed using remote sensing (RS) and landscape feature data together with Calicophoron daubneyi positive survey records from 197 georeferenced ovine farms with animals pasturing in a 3971 km(2) area of the southern Italian Apennines. The objective was to study the spatial distribution of this rumen fluke, identify environmental features that influence its distribution, and develop a preliminary risk assessment model. The GIS for the study area was constructed utilizing the following environmental variables: normalized difference vegetation index (NDVI), land cover, elevation, slope, aspect, and total length of rivers. These variables were then calculated for "buffer zones" consisting of the areas included in a circle of 3 km diameter centered on 197 farms. The environmental data obtained from GIS and RS and from data taken by the veterinarians on the field (stocking rate and presence of streams, springs and brooks on pasture) were analyzed by univariate (Spearman and ANOVA) and multivariate (discriminant) statistical analyses using the farm coprological status (positive/negative) as the dependent variable. Sheep on 32 of the 197 (16.2%) farms, were positive for C. daubneyi, with an average intensity of 52 epg. A multivariate stepwise discriminant analysis model was developed that included moors and heathland, sclerophyllous and coniferous forest vegetation, autumn-winter NDVI and presence of streams, springs and brooks on pasture. The variables entered in the model were also correlated with C. daubneyi positive farms in the univariate tests and are consistent with the environmental requirements of C. daubneyi and its snail intermediate host.

Mapping the potential distribution of Phlebotomus martini and P. orientalis (Diptera: Psychodidae), vectors of kala-azar in East Africa by use of geographic information systems.

The distribution of two principal vectors of kala-azar in East Africa, Phlebotomus martini and Phlebotomus orientalis were analysed using geographic information system (GIS) based on (1) earth observing satellite sensor data: Normalized Difference Vegetation Index (NDVI) and midday Land Surface Temperature (LST) derived from advanced very high resolution radiometer (AVHRR) of the global land 1km project of United States Geological Survey (USGS), (2) agroclimatic data from the FAO Crop Production System Zone (CPSZ) of the Intergovernmental Authority on Development (IGAD) sub-region, and (3) the FAO 1998 soils digital map for the IGAD sub-region. The aim was to produce a predictive risk model for the two vectors. Data used for the analysis were based on presence and absence of the two species from previous survey collections in the region (mainly Ethiopia, Kenya and Somalia). Annual, wet season and dry season models were constructed. Although all models resulted in more than 85% positive predictive values for both species, the best fit for the distribution of P. martini was the dry season composite (NDVI 0.07-0.38 and LST 22-33 degrees C) with a predictive value of 93.8%, and the best fit for P. orientalis was the wet season composite (NDVI -0.01 to 0.34 and LST 23-34 degrees C) with a predictive value of 96.3%. The two seasonal composites models derived from satellite data were largely similar with best fit models developed based on the CPSZ climate data: average altitude (12-1900m), average annual mean temperature (15-30 degrees C), annual rainfall (274-1212mm), average annual potential evapotranspiration (1264-1938mm) and readily available soil moisture (62-113mm) for P. martini; and average altitude (200-2200m), annual rainfall (180-1050mm), annual mean temperature (16-36 degrees C) and readily available soil moisture (67-108mm) for P. orientalis. Logistic regression analysis indicated LST dry season composite of the satellite data, average altitude, mean annual temperature and readily available soil moisture of the CPSZ data as the best ecological determinants for P. martini while LST annual composite was the only important ecological determinant for P. orientalis. Spearman's rank correlation revealed several factors to be important determinants for the distribution of the two vectors. None of the soil types analysed appeared to be important determinant for the two species in East Africa, unlike in Sudan where P. orientalis is mainly associated with eutric vertisol (black cotton clay soil).

GIS prediction model of malaria transmission in Jiangsu province.

OBJECTIVES: To perform GIS spatial analysis on malaria transmission patterns in Jiangsu after setting up a malaria database and developing GIS model of malaria transmission in Jiangsu province. METHODS: The epidemiological GIS database of malaria in Jiangsu province was established using ArcView 3.0a software. The climate data covering Jiangsu province and its peripheral area were extracted from the FAOCLIM database, the total growing degree days (TGDD) for Plasmodium vivax were calculated, and spatial distribution for TGDD was analyzed by ArcVeiw 3.0a. RESULTS: The predicted malaria distribution map based on TGDD was created, which showed that the transmission of malaria decreased gradually from west to east, which can be divided into three belts according to the degree of transmission. The 14-year mean morbidity distribution map of malaria in Jiangsu showed that the middle and west parts of Jiangsu is the most serious endemic area. The morbidity in the areas along the Taihu valley, such as Suzhou, Wuxi and Changzhou, as well as Nantong and a few of northern counties are the lowest. The morbidity of other places is at the middle level. The 14-year mean morbidity distribution map of malaria is correlated with predicted malaria distribution map for TGDD. CONCLUSION: It is possible to monitor the malaria transmission by GIS predicted model based on TGDD.

A cross-sectional coprological survey of liver flukes in cattle and sheep from an area of the southern Italian Apennines.

A cross-sectional coprological survey of liver flukes (Fasciola hepatica and Dicrocoelium dendriticum) was conducted on 81 bovine farms and 197 ovine farms with animals pasturing in an area (3971 km(2)) of the southern Italian Apennines. The farms were selected to be uniformly distributed throughout the study area using geographical information system (GIS) software. Between June 1999 and March 2000, faecal samples were collected from 975 cattle and 3940 sheep and examined using a modified McMaster technique. The results were subjected to statistical analysis and point distribution maps (PDMs) were drawn by GIS. Cattle of 9 of the 81 (11.1%) farms were positive for F. hepatica and of 43 (53.1%) for D. dendriticum. Sheep of 8 of the 197 (4.1%) farms were positive for F. hepatica and of 133 (67.5%) for D. dendriticum. Co-infection was found in cattle of 2 (2.5%) farms, and in sheep of 8 (4.1%) farms. The findings of the present survey show that D. dendriticum was the predominant liver fluke found in cattle and sheep with respect to egg count numbers for both farms and animals. In addition, the general trends of the PDMs show that D. dendriticum was widely and homogeneously spread throughout the study area, whereas F. hepatica was present only in a few concentrated zones of the study area that had both positive bovine and positive ovine farms.

Use of landsat TM satellite surveillance data to measure the impact of the 1998 flood on snail intermediate host dispersal in the lower Yangtze River Basin.

To assess the impact of the 1998 flood on snail distribution in the lower Yangtze River Basin, two study areas were selected, one in the Poyang Lake region, and the other along the Yangtze River in Jiangsu province. Using image analysis software, geocoded Landsat TM data were used to create TNDVI maps based on the formula TNDVI=Sqrt[(band4-band3/band4+band3)+0.5]. The images taken in the flood season were classified to produce a map depicting water and land. The images taken during springtime were processed and classified based on TNDVI. Composite images were created based on the time difference analysis, combining the flood season maps and spring vegetation maps to produce a map in which potential snail habitats were identified. When compared with ground survey data collected in the spring of 2000, the correspondence rate between potential snail habitats identified by image analysis of 1998-1999 Landsat TM data and ground survey data was over 90% in both regions. Results indicate that ecology based Landsat TM image analysis provides a new way to predict snail distribution under specific environmental conditions associated with the extent of the annual flood season.

[Application of multifactor spatial composite model to predict transmission tendency of malaria at national level].

OBJECTIVE: To predict the transmission tendency of malaria at national level by application of geographic information system(GIS) technique. METHODS: With the assistance of ArcView 3.0 a software and its spatial analyst extension, the surface spatial analysis on three natural factors, namely, total growing degree days(TGDD), precipitation and relative humidity, were conducted individually. The map calculation was preformed based on the three factors' ratio of 5:3:2 resulted from the Delphi investigation. RESULTS: The individual maps and composition map of TGDD, precipitation and relative humidity were created, respectively, based on the spatial composite model, which were used to predict the transmission tendency of malaria at national level. CONCLUSION: The high risk areas for malaria transmission, predicted by the spatial composite model based on the multilayers of environmental factors, are correlated with the previous reports. This will, therefore, provide information for predicting malaria transmission by multiple factors in a larger area.

A global network for the control of snail-borne disease using satellite surveillance and geographic information systems.

At a team residency sponsored by the Rockefeller Foundation in Bellagio, Italy, 10-14 April 2000 an organizational plan was conceived to create a global network of collaborating health workers and earth scientists dedicated to the development of computer-based models that can be used for improved control programs for schistosomiasis and other snail-borne diseases of medical and veterinary importance. The models will be assembled using GIS methods, global climate model data, sensor data from earth observing satellites, disease prevalence data, the distribution and abundance of snail hosts, and digital maps of key environmental factors that affect development and propagation of snail-borne disease agents. A work plan was developed for research collaboration and data sharing, recruitment of new contributing researchers, and means of access of other medical scientists and national control program managers to GIS models that may be used for more effective control of snail-borne disease. Agreement was reached on the use of compatible GIS formats, software, methods and data resources, including the definition of a 'minimum medical database' to enable seamless incorporation of results from each regional GIS project into a global model. The collaboration plan calls for linking a 'central resource group' at the World Health Organization, the Food and Agriculture Organization, Louisiana State University and the Danish Bilharziasis Laboratory with regional GIS networks to be initiated in Eastern Africa, Southern Africa, West Africa, Latin America and Southern Asia. An Internet site, www.gnosisGIS.org, (GIS Network On Snail-borne Infections with special reference to Schistosomiasis), has been initiated to allow interaction of team members as a 'virtual research group'. When completed, the site will point users to a toolbox of common resources resident on computers at member organizations, provide assistance on routine use of GIS health maps in selected national disease control programs and provide a forum for development of GIS models to predict the health impacts of water development projects and climate variation.

New tools: potential medical applications of data from new and old environmental satellites.

The last 40 years, beginning with the first TIROS (television infrared observational satellite) launched on 1 April 1960, has seen an explosion of earth environmental satellite systems and their capabilities. They can provide measurements in globe encircling arrays or small select areas, with increasing resolutions, and new capabilities. Concurrently there are expanding numbers of existing and emerging infectious diseases, many distributed according to areal patterns of physical conditions at the earth's surface. For these reasons, the medical and remote sensing communities can beneficially collaborate with the objective of making needed progress in public health activities by exploiting the advances of the national and international space programs. Major improvements in applicability of remotely sensed data are becoming possible with increases in the four kinds of resolution: spatial, temporal, radiometric and spectral, scheduled over the next few years. Much collaborative research will be necessary before data from these systems are fully exploited by the medical community.