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UID:pretalx-foss4g-asia-2024-BFP8PP@talks.geoinfo-lab.org
DTSTART;TZID=+07:20241217T094500
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DESCRIPTION:Introduction/Background:\nThe consequences of climate and envir
 onmental changes on health are now obvious to communities\, institutions a
 nd researchers alike. The impact of these changes must now be considered i
 n an operational way in health management\, in order to anticipate their e
 ffects\, prevent them or mitigate them where possible. In practice\, there
  is very little routine real-time use of space observation data in the pub
 lic health sector\, despite the increasing availability of space data. Ind
 eed\, space observation technologies have been constantly evolving since t
 he 1970s\, and now offer a wide range of data at different spatial\, tempo
 ral and radiometric resolutions. More recently\, access to data acquired b
 y satellite has greatly improved\, with free\, massive data and easier pro
 cessing. This offers the possibility of supporting health surveillance at 
 various scales\, which will be explored in this presentation using differe
 nt examples from South-East Asia.\n\nMain Aim/Purpose:\nThis presentation 
 aims at raising the issue of integrating environmental and climate change 
 indicators into health monitoring\, by presenting practical tools and case
  studies that are operational in Southeast Asia. It will provide an update
  on the needs for further operational implementation that will benefit hea
 lth monitoring.\n\nMethodology and Findings:\nThe presentation will focus 
 firstly on the development of a web platform that aims at modeling suitabl
 e climate and environmental conditions for leptospirosis through Earth obs
 ervation\, over the agglomeration of Yangon\, Myanmar. Leptospirosis is a 
 bacterial zoonosis that remains rarely diagnosed in Southeast Asia despite
  a high morbidity as shown in several active investigations. It is strongl
 y associated to water and seasons with epidemics following heavy rainfall 
 and flooding episodes. In the frame of the ECOMORE 2 Project (coordinated 
 by Institut Pasteur and funded by the French Agency for Development - AFD)
 \, the locations of leptospirosis confirmed cases (vs non-leptospirosis co
 ntrols) included in 2019 and 2020 were analyzed retrospectively. Time seri
 es of vegetation\, water\, and moisture indices from Sentinel-2 satellite 
 imagery (available at 10 meters spatial resolution\, every 5 days\, from t
 he European Space Agency\, Copernicus Program) were produced to describe t
 he dynamics of the environment around the locations of residence. This pro
 cess relies on the use of the Sen2Chain processing chain developed in Pyth
 on and open (https://framagit.org/espace-dev/sen2chain). The most relevant
  indices were used to build a spatiotemporal prediction model of positive 
 vs negative locations. This model was spatialized on homogeneous landscape
  units from the point of view of land use\, and describing the whole study
  area. The acquisition of Sentinel-2 images\, their processing and the mod
 elling were then automated as soon as a new image is available (every 5 da
 ys). An online platform\, named LeptoYangon (https://leptoyangon.geohealth
 research.org/)\, was developed with R and R-Shiny to display this dynamic 
 mapping of suitable environments and inform the epidemiologists and physic
 ians of the study\, in the frame of the ClimHealth project (funded by CNES
  and accredited by the Space Climate Observatory International Initiative)
 . This fully automated tool allows retrospective consultation at any date 
 since the first Sentinel-2 image was available in March 2016 (over 7 years
 ). By clicking on the map\, the user can select a landscape unit and view 
 the temporal dynamics of the risk for that unit (i.e. whether the risk is 
 increasing and decreasing). The user can also view the vegetation\, water 
 and moisture indicators to get an idea of the environmental data more spec
 ifically. This platform was designed to be used by epidemiologists and phy
 sicians to visualize the most at-risk areas and those where the risk is in
 creasing\, in order to raise physicians' awareness of leptospirosis (often
  confused with other fevers).\n\nDiscussion:\nImplementing this tool in ot
 her territories is facing 1) methodological challenges regarding the volum
 e of satellite data to be processed and 2) the need for detailed knowledge
  of the ecology of leptospirosis and exposure factors to adapt the models 
 in different contexts. However\, this already operational tool opens the w
 ay to the development of climate and environmental monitoring systems to i
 ncrease the vigilance of healthcare workers and populations to the risk of
  leptospirosis. This also shows the relevance of developing specific tools
  for other diseases associated to climate and environment. At a country or
  regional scale\, it is mainly meteorological variations and climatic anom
 alies that are relevant to the surveillance of certain diseases\, such as 
 dengue fever. The presentation will finally review the development of a na
 tional early warning system in Cambodia based on the acquisition of such c
 limatic data.
DTSTAMP:20260514T191118Z
LOCATION:Auditorium Hall 2
SUMMARY:Geospatial climate and environmental monitoring for health surveill
 ance - Vincent HERBRETEAU
URL:https://talks.geoinfo-lab.org/foss4g-asia-2024/talk/BFP8PP/
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