presentation: observatories in health

Pr. Thérèse Libourel

(Thanks to Mireille Fargette and Roger Frutos)

Observatories

in Health

Between health, spaces, time and

data and knowledge processing

Tri-National Scientific Workshop

Climate change: Observation, Analysis and Health

Indonesia – Thailand – France

2

Aims

Experimental case

Background: pathosystem and environment

Scientific Observatory: General model

Scientific Observatory: structure and life cycle

Conclusion

Outline




3

Aims

Faced with social issues, how to observe, understand, model the dynamics of diseases (transmitted by vectors) in a perspective of decision support?

Our goal is to set up a think tank around the concept of scientific observatory in support of health

management.

Take advantage of the synergy between scientists from different fields in order to take into account the added value of scientific expertise to clarify the definition and the fundamental constitutive principles of such systems.




4

Aims

Evolution of knowledge and technologies

Several initiatives

WHO Mondial Health Observatory

Health statistics and information systems

Many countries, ex France:

Regional Health Observatory

One Health initiative

Atlas of health and climate




5

Aims

Experimental case




Conclusion

Outline




6

Experimental Case

Chikungunya Virus (CHIKV), a mosquito-borne pathogen from the alphavirus genus transmitted by Aedes mosquitoes causes acute infection in human. Modeling the dynamic of this disease in Asia, where the CHIKV is actively propagating, is essential to develop prevention strategies for regions with high risk of propagation, including Europe where the vector A. albopictus is now well established.

Montpellier, France - UMR Espace Dev ; Laboratoire de physique industrielle et traitement de

l’information ; Intelligence in Life – R&D Clinique SARL ; Centre d’étude des Pathogènes et Biotechnologies pour la Santé, CPBS ; Institut des Sciences de l’Evolution de Montpellier – ISEM

; Intertryp, CIRAD Indonesia - Center for Tropical Medicine, Faculty of Medicine, Gadjah Mada University,

Yogyakarta ;Su koharjo Regency Health Center, Center of Java, Sukoharjo.

UML diagrams 1) Contemplative description of the system 2) Transition to dynamic modelisation

Modelling 1) Agent oriented programming (Netlogo) 2) Mathematical modelling of epidemic by compartiments

Geographic information system (GIS) integration




Methodology

7

Experimental Case




Non infected

infected

immunised

Sensible Exposed

Infected Resistant

Exposed

Infected

Human

Chimera

Human/Virus

Mosquito

Chimera Mosquito/

Virus

Chimera

Mosquito/Virus

Chimera Human/

Virus

mouvements

mouvements

mouvements

mouvements

Development, mouvements, reproduction

Development,

mouvements, reproduction

Into host

Sensible

Class diagram of the Chikungunya patho-system

Clinical Analyses (biology)

Geography / environment / anthropic actions / ecology

Sampling

8

Experimental Case




Interactions

Chimers

- State diagram

- Diagram of interactions

- Sequence diagram

- Mathematical model

Implementation

in a simulation

platform

(Netlogo)

9

Experimental Case




Non infected

infected

immunisé

Susceptible Exposed

Infected Resistant

Susceptible

Exposed

Infected

10

Experimental Case




V

H

Nh, human population. Nh = Sh + Eh + Ih +Rh. Sh (Sensible), Eh (Exposed), Ih (Infected), Rh (Resistant).

B*βmh: rate of infective mosquito bites. C*βhm: rate of mosquito contamination, B & C: Average daily biting.

Mosquito population: Lm (larvae), Sm (Sensible), Em (exposed), Im (infected).

K: biotic capacity of the environment defines using Breteau index, BI=(Nb of positive containers/Nb of inspected houses )*10.

Dumont Y, et al. (2008) Math Biosci. 213(1):80-91.

11

Experimental case




Health System

Seaports and

factories

Vector control

12

Aims

Experimental case




Conclusion

Outline




13

Pathosystem and environment

Seminar 2015 Tri-National Scientific Workshop



14

Pathosystem and environment




Bourdillon (2005)

15

Aims

Experimental case




Conclusion

Outline




16

General Model

A health observatory aims to observe (monitor, analyze,

understand) the dynamics of the diseases and their impact on an portion of representative space of a territorial entity. It is a place

of production, exchange, and sharing of information and

knowledge that is in the long term.

It must ensure a minimum diagnostic functions to assess the

implemented actions. It should be also associated with

prognostic features, to provide all the capabilities to alert and

guide short and medium term managers in their decision making

and their interventions.




17

General Model




Aims

Experimental case




Conclusion

Outilne

18




19

Scientific Observatory: structure




20

Scientific Observatory: Life cycle

Theorical**Model

Observa1on*model

Acquisi1on

Analysis*

Analysis*

Tracking*Model* Acquisi1on*

Sequence'research Sequence'Tracking''




21

Technical Aspects




22

Challenges




Acquisition (new sensors)

Interoperability

Big and Open Data.

Experts knowledge

Disease, Place, Environment

Ontologies

Place, Environment Data

Clinical Data

Health

Knowledge base

New Sensors

Outline

23




Aims

Experimental case




Conclusion

24

Conclusion

The proposal emphasizes the health question

behind the creation of the observatory.

Scientific observatories are a key element for health

challenges.

The scientific network based on several fields of

science is a "real brain” constantly thinking.

Role of institutional and decisional systems ?

The sustainability of the observatory is related to this

question ?




25

Emmanuel Cornillot Patrice Ravel Guilhem Kister

Thérèse Libourel Aurélie Merlin Mireille Fargette

Laurent Gavotte Catherine Moulia Roger Frutos Yannick Baldie

Christian Devaux Laurence Briant Nathalie Chazal

Tri Baskoro Tunggul Satoto Erna Andayani

Susi Damayanti People from RT03 and RT04 (Sukoharjo) and from RT42 (Yogyakarta)

26




Terima kasih

Merci beaucoup

presentation: observatories in health

Documents

regional health observatory

support of health management

ex france

cirad indonesia center

experimental case background

information systems

center of java

dynamic modelisation