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Biometeorology, health warning system and Geographic Information Tecnologies
 

Biometeorology, health warning system and Geographic Information Tecnologies

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Presentation by Pablo Fernández Arroyabe from Geobiomet Research Group, University of Cantabria on Esri European User Conference 2011.

Presentation by Pablo Fernández Arroyabe from Geobiomet Research Group, University of Cantabria on Esri European User Conference 2011.

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    Biometeorology, health warning system and Geographic Information Tecnologies Biometeorology, health warning system and Geographic Information Tecnologies Presentation Transcript

    • BIOMETEOROLOGY, HEALTH WARNING SYSTEMS AND GEOGRAPHIC INFORMATION TECHNOLOGIESGEOBIOMET RESEARCH GROUPUNIVERSITY OF CANTABRIA - Pablo Fdez-Arroyabe
    • INDEX1. BIOMETEOROLOGY2. WEATHER & HEALTH3. GIS & BIOMETEOROLOGY: PRONBIOMET4. MAIN OUTCOMES5. CONCLUSIONS
    • BIOMETEOROLOGY BIOMETEOROLOGY WHERE? WHEN? ANSWERS BIOMETEOROLOGY is an interdisciplinary science that study relationships between atmospheric processes and living organisms
    • BIOMETEOROLOGY Funded on Augut 29th 1956 at the UNESCO headquarters in Paris: - Dr. S.W. Tromp - Dutch Geologist - Dr. H. Ungeheuer – German meteorologist - Several experts on human physiology from USA Dr. Sargent (USA) was the first president of ISB
    • BIOMETEOROLOGY International Journal Bulletin International Congress
    • BIOMETEOROLOGY ANIMAL, VEGETAL AND HUMAN
    • BIOMETEOROLOGY HEALTH AND ADAPTATION From a Biometeorological point of view The inability to adapt to a new atmospheric variability and change can generate HEALTH CRISIS
    • VARIABILITY AND CHANGE CLIMATE VARIABILITY a changing state in a non lineal system where inside variables do not ever reach a balance state
    • VARIABILITY AND CHANGE CLIMATE VARIABILITY and CHANGE in relation to human´s health ?
    • VARIABILITY AND CHANGE CLIMATE VARIABILITY SCALES LONG TERM VARIABILITY (Inter decadal or seasonal) SHORT TERM VARIABILITY (Weekly, daily) MICRO VARIABILITY (Hourly, minutes)
    • BIOMETEOROLOGY ADAPTATION
    • ATMOSPHERE ANDHUMAN HEALTH
    • PhysiologicalVARIABLES TEMPERATURE thermoregulation LOW TEMPERATURES HIGH TEMPERATURES ♦ HEART FREQUENCY INCREMENT ♦ MUSCULAR FIBRILATION ♦ SWEATING INCREMENT ♦ SKIN VASOCONSTRICTION ♦ HYPERVENTILATION Fuente: CAMARA DIEZ, E. (2006) Variables meteorológicas y salud. Documentos de Sanidad Ambiental. Comunidad de Madrid
    • VARIABLES TEMPERATURE EXTREME COLD EXTREME HOT Hypothermia DIRECT EFFECTS Frostbite Dermatitis and edemas Sun burns Fractures Sun stroke Heat syncope Heat exhaustion INDIRECT EFFECTS Heat waves
    • VARIABLES ATMOSPHERIC PRESSURE Air is a GAS which weight is higher or lower depending on geographic location 1. Headaches Associated to high pressures and or sudden changes 2. Heart diseases 3. Spontaneous Pneumothorax 1. Gil Romea I, Moreno Mirallas MJ. Lesiones por frío. Arch Cir Gen Dig, 2000 Sep 5. 2. Jehle D, Moscati R. The incidente of spontaneous subarachnoid hemorrhage with change in barometric pressure. Am J Emerg Med 1994 Jan; 12 (1): 90-1. 3. Landers AT, Narotam PK. The effect of changes in barometric pressure on the risk of rupture of intracranial aneurysms. Br J Neurosurgery 1997 Jun; 11(3): 191-5.
    • VARIABLES WINDS and HEALTH COLD WINDS HOT WINDS Parasympathetic system Sympathetic system is Activity is stimulated (Psique) stimulated. Emotional disorders, Alteration of the depressions, suicides. respiratory dynamics Sirocco in Sahara, Increase of pain Föehn in The Alps sensitivity on rheumatic Chinook in Rocky mountains patients. Puelche in The Andes Austru in Rumania
    • VARIABLES ATMOSPHERIC HUMIDITY Amount of steam in the air (%) Rhinitis y Asthma because of mites (More important in places by the sea) Optimum conditions: tempertaure 20-25°and air hu midity about 75%. Asthma because of pollens
    • OTHER VARIABLESVARIABLES SUN RADIATION Amount of ultraviolet radiation Sun burns, skin cancer Amount of light Mood PRECIPITACION (rain,snow) Rainfall increase number of car accidents Snow storms Increase in the number of heart attacks and cerebro-vascular problems STORMS Accidents because of rays. Floodings risks, cold drops, landslides POSITIVE IONS It is related to headaches, nasal congestion, hoarseness, sore throat, incrrease in blood preassure.
    • COMBINED EFFECTSVARIABLES HUMIDITY AND HEAT WIND AND LOW Tª HEAT INDEX WIND CHILL + + + + + UNIVERSAL THERMAL PHYSIOLOGICAL EQUIVALENT CLIMATE INDEX TEMPERATURE UTCI PET Prof. Dr. GERD JENDRITZKY Prof. ANDREAS MATZARAKIS
    • COMBINED EFFECTSVARIABLES + + + 1. High pressure. Stability. 2. High temperatures 3. High relative humidity 4. High levels of pollution (SO2 NO2 particles…) 5. Demographic, social and personal aspects METEOROTROPIC BOMB
    • COMBINED EFFECTSVARIABLES - hormonal functions are modified - our neurotransmitters are affected - can alter cerebral biochemistry - affect to vasodilatation - modify capilar resistance - and many others… WE KNOW FEW ABOUT THE SPECIFIC MECHANISMS THAT TAKE PLACE IN THESE PROCESSESS FOR EACH PERSON
    • GIS ONBIOMETEOROLOGICAL FORECASTING
    • The use of GIS on Biometeorology has given the biometeorologist an excellent opportunity to develop early warning systems based on biometeorological forecasting. In this sense, the spatial component is a key issue in the study of heat waves impacts on mortality and also in the revision of spatial patterns and diffusion of some infectious diseases such as influenza or in thecartographic representation of biometeorological indicators such as DOA index that is successfully implemented in health warning systems such as Pronbiomet
    • HEAT WAVES HWS AND SPATIAL INFORMATION USA 2005 Kalstein, L.
    • ANOTHER GERMAN EXAMPLE, 2006
    • THE FUNDAMENTS CHANGE Yes HEALTH ADAPTATION? No DISEASES
    • HEALTH WARNING SYSTEMS BIOMETEOROLOGICAL GIS FORECAST DEVELOPMENT
    • METEOROGRAMS AT SPECIFIC POINTS
    • A model based on GIS exists since 1996 The first model (1996) used the daily surface synoptic data for the regional diagnostic of the PODA index at 00 and 12 GMT. An objective new numerical forecast model was developed in 2006. It takes on-line as input data the GFS information up to 180 hours in advance. The outputs are 16 bio-forecast maps and meteorograms for six different world regions.The model makes the bio-forecast maps with the 24- hoursdifferences of the partial oxygen density in the air (PODAindex), with a resolution of 0.5 degree (55 km).
    • Air temperature Air humidity Atmospheric GIS PressureMODEL Oxygen Density
    • The global monitoring of meteor-tropic effects on human health… … Such as fundament to mitigate the impacts of abrupt weather changes on health and society. CUBAEAST ASIA AND WEST PACIFIC ZONE NORTH AMERICA AND THE CARIBBEAN Luís B. Lecha, Center for Environmental Research & Services, Cuba Pablo Fernández de Arroyabe, University of Cantabria, Spain David Martín, University of Alicante, Spain EUROPE
    • THE MODEL DAILY OUTPUTS EAST ASIA AND WESTPACIFICNORTHAMERICACUBA AUSTRALIA AND NEW ZEALANDSOUTHAMERICA EUROPE
    • HOW TO READ THE MAPS?Biomet. Conditions Low Latitude Middle High Latitude LatitudeExtreme hyperoxia > 10.0 > 20.0 > 30.0Very strong hyperoxia 8.1 to 10.0 16.1 to 20.0 24.1 to 30.0Strong hyperoxia 6.1 to 8.0 12.1 to 16.0 18.1 to 24.0Moderate hyperoxia 4.1 to 6.0 8.1 to 12.0 12.1 to 18.0Weak hyperoxia 2.1 to 4.0 4.1 to 8.0 6.1 to 12.0THE NEUTRAL ZONE -2.0 to 2.0 -4.0 to 4.0 -6.0 to 6.0Weak hypoxia -2.1 to -4.0 -4.1 to -8.0 -6.1 to -12.0Moderate hypoxia -4.1 to -6.0 -8.1 to -12.0 -12.1 to -18.0Strong hypoxia -6.1 to -8.0 -12.1 to -16.0 -18.1 to -24.0Very strong hypoxia -8.1 to -10.0 -16.1 to -20.0 -24.1 to -30.0Extreme hypoxia < -10.0 < -20.0 < -30.0
    • BIOMETEOROLOGICAL FORECASTING BASED ON GIS RESULTS
    • DATE: 17 / 11 / 2007 HYPEROXIA
    • DATE: 20 / 11 / 2007 HYPOXIA
    • BRAIN VASCULAR DISEASES BILBAO (October – November 2007) ENFERMEDADES CEREBRO VASCULARES en BILBAO (Octubre - Noviembre 2007) 10 15 6 13 Nº asistencias 2 113g/m -2 9 -6 7 -10 5 -14 3 1-10 6-10 11-10 16-10 21-10 26-10 31-10 5-11 10-11 15-11 20-11 25-11 30-11 ECV DOA
    • MIGRAINES, HYPERTENSION ANDCEFALEAS BILBAO (October - November 2007) ENFERMEDADES HIPERTENSITIVAS y CEFALEAS en BILBAO (Octubre - Novirmbre 2007) 10 28 6 24 2 Nº asistencias 203g/m -2 16 -6 12 -10 8 -14 4 1-10 6-10 11-10 16-10 21-10 26-10 31-10 5-11 10-11 15-11 20-11 25-11 30-11 THA CEF DOA
    • HEART RELATED DISEASES BILBAO (October – November 2007) CARDIOPATIAS ISQUEMICAS en BILBAO (Octubre - Novirmbre 2007) 10 20 18 6 16 2 14 123g/m -2 10 -6 8 6 -10 4 -14 2 1-10 6-10 11-10 16-10 21-10 26-10 31-10 5-11 10-11 15-11 20-11 25-11 30-11 DOA CAI
    • ECV = BRAIN VASCULAR DISEASESHTA-CEF-MIG = HIPERTENSION, CEFALEAS, MIGRAÑASCAI = CARDIOPATIAS ISQUEMICAS FECHAS ∆ ECV HTA-CEF-MIG CAI 01/04 -7,3 6 -1 2-3 2-2 28/05 9,5 3 -1 3-3 0-4 19/06 8 3-4 5-8 2-4 15/07 6,3 3-2 2-6 4-02005 29/07 7,6 4-1 4-1 0-4 04/09 8,8 5 -7 3-7 3-1 22/11 6,2 0-4 5-6 4-2 30/12 -8,7 4-0 6-2 5-3
    • HTA-CEF- CAI FECHAS ∆ ECV MIG 03/03 -5,9 4–3 8 – 10 4–2 05/03 14,7 3–3 2–8 2–4 08/03 -6,7 2–4 3–6 3–4 04/04 -7,3 6–2 9–4 3–3 05/04 7 2–4 4–3 3–2 14/04 -8,6 5–3 5–5 0–0 18/05 7,7 4–0 8–7 4–72006 22/05 8,4 3–5 9–4 4–2 01/07 -5,7 8–4 4–3 0–0 20/09 -7,6 3–2 2–6 1–5 25/10 -7,5 4–3 2–7 3–3 15/11 -6,8 3–6 4–5 0–3 25/11 7,6 2–3 6–3 1–3 06/12 8 2–3 5–8 2–4 09/12 8,9 8–8 4–7 1–3
    • FECHAS ∆ ECV HTA-CEF-MIG CAI 12/02 6,7 5-3 6-7 1-4 16/02 -6 3-0 5-2 3- 4 05/03 8,6 2-3 4-2 1-3 14/05 9,7 3–6 6-2 2-1 02/07 -10 2-4 3-3 2-02007 14/07 7,9 0-2 7-0 3-5 16/08 8,6 4-0 1-4 3-0 18/09 6,4 2-4 9-3 3-4 18/11 -9,2 5-3 5-5 2-6 19/11 -7,9 3-5 5-9 6-3
    • BIOMETEOROLOGICAL FORECASTING RESULTS PERIOD 2005-200733 days with the highest DOA contrast 23 days (70%) ECV = > Pctil 66 25 days (75 %) HTA = > Pctil 66 28 days (84.8 %) CAI = > Pctil 66
    • CONCLUSIONS
    • A NETWORK OF VALIDATORS IS CREATED TO DETERMINE HOW USEFUL IS EACH HEALTH WARNING SYSTEM CREATION PROMOTION IMPROVEMENT VALIDATION
    • CONCLUSIONS BIOMETEOROLOGICAL FORECASTING DESIGN 1 – Development of BHWS must be simple and based on Geographic Information Technologies 2 - They should be designed based on the operative systems of the weather forecasting offices 3 – They can be applied to different regions of the world spatial information is absolutely neccesary 4 – They have to be based on an easy implementation 5 – Depends on access to medical information
    • CONCLUSIONS GEOGRAPHIC INFORMATION SYSTEMS ARE NECESSARY IN ORDER TO DEVELOP EARLY HEALTH WARNING SYSTEMS BASED ON BIOMETEOROLOGICAL FORECASTING
    • THANK YOU VERY MUCHFOR YOUR ATTENTION