Based on an agreement between the Ministry of Health and the National Space Activities Commission in Argentina, an integrated informatics platform for dengue risk using geospatial technology for the surveillance and prediction of risk areas for dengue fever has been designed. The task was focused on developing stratification based on environmental (historical and current), viral, social and entomological situation for >3,000 cities as part of a system. The platform, developed with open-source software with pattern design, following the European Space Agency standards for space informatics, delivers two products: a national risk map consisting of point vectors for each city/town/locality and an approximate 50 m resolution urban risk map modelling the risk inside selected high-risk cities. The operative system, architecture and tools used in the development are described, including a detailed list of end users' requirements. Additionally, an algorithm based on bibliography and landscape epidemiology concepts is presented and discussed. The system, in operation since September 2011, is capable of continuously improving the algorithms producing improved risk stratifications without a complete set of inputs. The platform was specifically developed for surveillance of dengue fever as this disease has reemerged in Argentina but the aim is to widen the scope to include also other relevant vector-borne diseases such as chagas, malaria and leishmaniasis as well as other countries belonging to south region of Latin America.

Understanding factors that shape ranges of species is central in evolutionary biology. Species distribution models have become important tools to test biogeographical, ecological and evolutionary hypotheses. Moreover, from an ecological and evolutionary perspective, these models help to elucidate the spatial strategies of species at a regional scale. We modelled species distributions of two phylogenetically, geographically and ecologically close Tupinambis species (Teiidae) that occupy the southernmost area of the genus distribution in South America. We hypothesized that similarities between these species might have induced spatial strategies at the species level, such as niche differentiation and divergence of distribution patterns at a regional scale. Using logistic regression and MaxEnt we obtained species distribution models that revealed interspecific differences in habitat requirements, such as environmental temperature, precipitation and altitude. Moreover, the models obtained suggest that although the ecological niches of Tupinambis merianae and T. rufescens are different, these species might co-occur in a large contact zone. We propose that niche plasticity could be the mechanism enabling their co-occurrence. Therefore, the approach used here allowed us to understand the spatial strategies of two Tupinambis lizards at a regional scale.

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Soil-Transmitted Helminths (STH) are highly prevalent Neglected Tropical Disease in Ethiopia, an estimated 26 million are infected. Geographic Information Systems and Remote Sensing (RS) technologies assist data mapping and analysis, and the prediction of the spatial distribution of infection in relation to environmental variables. The influence of socioeconomic, environmental and soil characteristics on hookworm infection at the individual and household level is explored in order to identify spatial patterns of infection in rural villages from Zenzelema (Amhara region). Inhabitants greater than 5 years old were recruited in order to assess the presence of STH. Socioeconomic and hookworm infection variables at the household level and environmental variables and soil characteristics using RS were obtained. The dominant STH found was hookworm. Individuals which practiced open defecation and those without electricity had a significant higher number of hookworm eggs in their stool. Additionally, adults showed statistically higher hookworm egg counts than children. Nonetheless, the probability of hookworm infection was not determined by socioeconomic conditions but by environmental characteristics surrounding the households, including a combination of vigorous vegetation and bare soil, high temperatures, and compacted soils (high bulk density) with more acidic pH, given a pH of 6.0 is optimal for hatching of hookworm eggs. The identification of high-risk environmental areas provides a useful tool for planning, targeting and monitoring of control measures, including not only children but also adults when hookworm is concerned.

Chagas continues to be a relevant public health problem in Latin America. In this work, we present a spatiotemporal analysis applied for the evaluation and planning of Chagas vector control strategies. We analysed the spatial distribution of the vector Triatoma infestans infestation related to ongoing control interventions cycles in rural communities near Añatuya, Santiago del Estero, Argentina. A geographical information system was developed for the spatial analysis obtaining, for each house, variables that describe the history of spraying and infestation at each time of interventions. Bi-dimensional histograms were used to describe the spatiotemporal pattern of these activities and peri-domestic infestation at the last intervention was modelled by a neural network model. We qualitatively evaluate control programmes considering the history of infestation and spraying from a spatiotemporal point of view, incorporating new ways of visualising this information. Predictions are based on novel, non-linear models and spatiotemporal indices, which should be useful for strategically allocating Chagas control resources in the future and thus help to better plan spraying strategies.

The Bormida River Basin, located in the northwestern region of Italy, has been strongly contaminated by the ACNA chemical factory. This factory was in operation from 1892 to 1998, and contamination from the factory has had deleterious consequences on the water quality, agriculture, natural ecosystems and human health. Attempts have been made to remediate the site. The aims of this study were to use high-resolution satellite images combined with a classical remote sensing methodology to monitor vegetation conditions along the Bormida River, both upstream and downstream of the ACNA chemical factory site, and to compare the results obtained at different times before and after the remediation process. The trends of the Normalised Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) along the riverbanks are used to assess the effect of water pollution on vegetation. NDVI and EVI values show that the contamination produced by the ACNA factory had less severe effects in the year 2007, when most of the remediation activities were concluded, than in 2006 and 2003. In 2007, the contamination effects were noticeable up to 6 km downstream of the factory, whereas in 2003 and 2006 the influence range was up to about 12 km downstream of the factory. The results of this study show the effectiveness of remediation activities that have been taking place in this area. In addition, the comparison between NDVI and EVI shows that the EVI is more suitable to characterise the vegetation health and can be considered an additional tool to assess vegetation health and to monitor restoration activities.

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Background: In Argentina, Aedes aegypti represents an important public health threat, since it is the vector responsible for the transmission of dengue, chikungunya, zika and yellow fever. Mundo Sano Foundation has been carrying out periodic surveys of immature vector stages in several cities of northern Argentina. The main tool to mitigate their spread is through vector control. The identification of vector "hot spots" is an important key to design preventive program tools. Geostatistical techniques such as spatial autocorrelation (SAC) and kriging interpolation can be used to predict vector abundance in unsampled areas using data obtained from monitored sites. The knowledge of the spatial autocorrelation of vector abundance is fundamental and it can also be used to design disease surveillance strategies: To determine the characteristics of chemical control; to select ovitrap placement (distance between samples); and to determine the optimum sample size, among others. It is important to analyze the effect of the variation of the scale in the observed phenomenon. Methods: This paper analyzes a two years series of weekly oviposition data from 25 ovitraps distributed in the urban area of a small city (104 measurements were collected for each ovitrap). We aim to understand how the relationship between sites measurements varies considering its relative location in the city, for different temporal sampling frequency or temporal resolution (TR). Different similarity measures between curves and graphic representations of these relationships, are explored. Among these, an innovative use of polar graphs-a tool commonly used to detect changes in satellite images-is examined. We evaluate variograms and SAC for multitemporal data (oviposition curves) at each TR. Results: Similarity between curves does not show spatial continuity in relation to the spatial arrangement of ovitraps, may be due to the effect of processes that are only observable at the microhabitat scale or due to sociodemographic factors. As the temporal resolution is greater in a given area, a greater number of ovitraps are needed to capture the spatial heterogeneity of the abundance of the vector. At the maximum TR analyzed, the minimum distance of spatial correlations was set at 1000 m. This has implications on the quantity of ovitraps per area unit required in the field in order to obtain a good description of the population dynamics of Ae. aegypti at the peridomestic level. Conclusion: The results would indicate that when varying the time scale of analysis, the spatial scale should be modified accordingly to adapt to the new data structure. The ability to predict ecological phenomena depends on the relationships between spatial and temporal scales. The approach and innovative statistical tools described in this study, based on empirical data from a field study, may be used by different Ae. aegypti monitoring and control programs in order to design and implement tailor-made interventions. It would allows to support not only the selection of field samples, a...