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.

Vectorial transmission of Chagas disease has been decreasing over the past few decades because of effective vector control programs in the southern cone of South America. However, the disease is still actively transmitted within the Gran Chaco region. In this area, vector populations are abundant and highly prevalent in poor rural houses. This study analyses the spatial pattern of rural house infestation by Triatoma infestans in a 56,000 km(2) area in the province of La Rioja, Argentina, before the re-initiation of systematic activity on vector control intervention. Data on 5,045 rural houses show that infestation has high spatial heterogeneity, with highly infested localities concentrated in a few areas. House infestation has a negative significant relationship with locality size. Rural houses in the region are highly dispersed and this feature has been and will remain a challenge for any vigilance system to be installed in the region.

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The impact of control activities against Triatoma infestans (Klug) (Hemiptera: Reduviidae) in South America has a marked contrast within and outside the Gran Chaco region. Development of a geographic information system, as part of an improvement in control program activities, allowed analysis of the spatial pattern of house infestations by T. infestans before and after house spraying with deltamethrin in the San Martin Department (an arid Chaco region of central Argentina). The overall peridomestic infestation index decreased from 48.2 to 28.2% after insecticide application. House infestation was spatially clustered in regions with low or high infestation levels that were located east and southwest of the department, respectively. This pattern was detected both before and after the insecticide application. Three environmental variables calculated from a temporal series of MODIS imagery (average of night temperature, maximum of day temperature, and temporal variation of vegetation index) were capable of correctly discriminating 96% of the places belonging to either high or low house infestation observed after the insecticide application.

After elimination of the Aedes aegypti vector in South America in the 1960s, dengue outbreaks started to reoccur during the 1990s; strongly in Argentina since 1998. In 2016, Córdoba City had the largest dengue outbreak in its history. In this article we report this outbreak including spatio-temporal analysis of cases and vectors in the city. A total of 653 dengue cases were recorded by the laboratory-based dengue surveillance system and georeferenced by their residential addresses. Case maps were generated from the epidemiological week 1 (beginning of January) to week 19 (mid-May). Dengue outbreak temporal evolution was analysed globally and three specific, high-incidence zones were detected using Knox analysis to characterising its spatio-temporal attributes. Field and remotely sensed data were collected and analysed in real time and a vector presence map based on the MaxEnt approach was generated to define hotspots, towards which the pesticide- based strategy was then targeted. The recorded pattern of cases evolution within the community suggests that dengue control measures should be improved.