No abstract

Background Cross-border malaria is a significant obstacle to achieving malaria control and elimination worldwide. Objective This study aimed to build a cross-border surveillance system that can make comparable and qualified data available to all parties involved in malaria control between French Guiana and Brazil. Methods Data reconciliation rules based on expert knowledge were defined and applied to the heterogeneous data provided by the existing malaria surveillance systems of both countries. Visualization dashboards were designed to facilitate progressive data exploration, analysis, and interpretation. Dedicated advanced open source and robust software solutions were chosen to facilitate solution sharing and reuse. Results A database gathering the harmonized data on cross-border malaria epidemiology is updated monthly with new individual malaria cases from both countries. Online dashboards permit a progressive and user-friendly visualization of raw data and epidemiological indicators, in the form of time series, maps, and data quality indexes. The monitoring system was shown to be able to identify changes in time series that are related to control actions, as well as differentiated changes according to space and to population subgroups. Conclusions This cross-border monitoring tool could help produce new scientific evidence on cross-border malaria dynamics, implementing cross-border cooperation for malaria control and elimination, and can be quickly adapted to other cross-border contexts.

During the HAPEX-Sahel experiment ( 199 1-94), water redistribution processes were studied at the meso-scale (10 000 h2) near Niamey, Niger. A project now under way at ORSTOM aims at modelling the regional water balance through a spatial approach combining GIS data organization and distributed hydrological modelling. The main objective is to extend the surface water balance, by now available only on a few, small (around 1 km2) unconnected endoreic catchments, to a more significant part of the HAPEX-Sahel square degree, a 1500 h2 region called SSZ that includes most of the environmental and hydrology measurqnent sites. GIS architecture and model design consistently consider data and processes at the local, catchment scale, and at the regional scale. The GIS includes spatial and temporal hydrological data (rainfall, surface runoff, ground water), thematic maps (topography, soil, geomorphology, vegetation) and multi-temporal remote sensing data (SPOT, aerial pictures). The GIS supports the simulation of the composite effect at the regional scale of highly variable and discontinuous component hydrologic processes operating at the catchment scale, in order to simulate interannual aquifer recharge and response to climatic scenarios at the regional scale.

No abstract

The French Critical Zone research infrastructure, OZCAR-RI, gathers 20 observatories sampling various compartments of the critical zone, each having developed their own data management and distribution systems. A common information system (Theia/OZCAR IS) was built to make their in situ observation FAIR (findable, accessible, interoperable, reusable). The IS architecture was designed after consultation of the users, data producers and IT teams involved in data management. A common data model based on various metadata standards was defined to create information fluxes between observatories' ISs and the Theia/OZCAR IS. Controlled vocabularies were defined to develop a data discovery web portal offering a faceted search with various criteria, including variables names and categories that were harmonized in a thesaurus published on the web. This paper describes the IS architecture, the pivot data model and open-source solutions used to implement data discovery, and future steps to implement data downloading and interoperability services.