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BIOMETEOROLOGY, HEALTH
    WARNING SYSTEMS AND
  GEOGRAPHIC INFORMATION
       TECHNOLOGIES


GEOBIOMET RESEARCH GROUP
UNIVERSITY OF CANTABRIA - Pablo Fdez-Arroyabe
INDEX

1. BIOMETEOROLOGY

2. WEATHER & HEALTH

3. GIS & BIOMETEOROLOGY: PRONBIOMET

4. MAIN OUTCOMES

5. 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

    AND

HUMAN HEALTH
Physiological
VARIABLES   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 VARIABLES
VARIABLES



            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 EFFECTS
VARIABLES
                    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 EFFECTS
VARIABLES


                     +              +              +


            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 EFFECTS
VARIABLES




            - 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 ON
BIOMETEOROLOGICAL
  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 the
cartographic 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- hours
differences of the partial oxygen density in the air (PODA
index), with a resolution of 0.5 degree (55 km).
Air temperature


           Air humidity

               Atmospheric
 GIS           Pressure

MODEL              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.

                                                                                     CUBA
EAST 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 WESTPACIFIC


NORTH
AMERICA




CUBA




                                       AUSTRALIA AND NEW ZEALAND




SOUTH
AMERICA                              EUROPE
HOW TO READ THE MAPS?
Biomet. Conditions      Low Latitude       Middle        High Latitude
                                          Latitude
Extreme hyperoxia          > 10.0          > 20.0           > 30.0

Very strong hyperoxia    8.1 to 10.0    16.1 to 20.0     24.1 to 30.0

Strong hyperoxia         6.1 to 8.0     12.1 to 16.0     18.1 to 24.0

Moderate hyperoxia       4.1 to 6.0      8.1 to 12.0     12.1 to 18.0

Weak hyperoxia           2.1 to 4.0       4.1 to 8.0      6.1 to 12.0

THE NEUTRAL ZONE         -2.0 to 2.0     -4.0 to 4.0      -6.0 to 6.0

Weak hypoxia            -2.1 to -4.0     -4.1 to -8.0    -6.1 to -12.0

Moderate hypoxia        -4.1 to -6.0    -8.1 to -12.0    -12.1 to -18.0

Strong hypoxia          -6.1 to -8.0    -12.1 to -16.0   -18.1 to -24.0

Very strong hypoxia     -8.1 to -10.0   -16.1 to -20.0   -24.1 to -30.0

Extreme 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
                                                                                                                   11
3
g/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
                                                                                                                   20
3
g/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
                                                                                                                         12
3
g/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 DISEASES
HTA-CEF-MIG = HIPERTENSION, CEFALEAS, MIGRAÑAS
CAI = 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        4-0
2005    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      4–7
2006    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       2-0
2007    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 2005-2007

33 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 MUCH

FOR YOUR ATTENTION

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Biometeorology, health warning system and Geographic Information Tecnologies

  • 1. BIOMETEOROLOGY, HEALTH WARNING SYSTEMS AND GEOGRAPHIC INFORMATION TECHNOLOGIES GEOBIOMET RESEARCH GROUP UNIVERSITY OF CANTABRIA - Pablo Fdez-Arroyabe
  • 2. INDEX 1. BIOMETEOROLOGY 2. WEATHER & HEALTH 3. GIS & BIOMETEOROLOGY: PRONBIOMET 4. MAIN OUTCOMES 5. CONCLUSIONS
  • 3. BIOMETEOROLOGY BIOMETEOROLOGY WHERE? WHEN? ANSWERS BIOMETEOROLOGY is an interdisciplinary science that study relationships between atmospheric processes and living organisms
  • 4. 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
  • 5. BIOMETEOROLOGY International Journal Bulletin International Congress
  • 6. BIOMETEOROLOGY ANIMAL, VEGETAL AND HUMAN
  • 7. 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
  • 8. VARIABILITY AND CHANGE CLIMATE VARIABILITY a changing state in a non lineal system where inside variables do not ever reach a balance state
  • 9. VARIABILITY AND CHANGE CLIMATE VARIABILITY and CHANGE in relation to human´s health ?
  • 10. VARIABILITY AND CHANGE CLIMATE VARIABILITY SCALES LONG TERM VARIABILITY (Inter decadal or seasonal) SHORT TERM VARIABILITY (Weekly, daily) MICRO VARIABILITY (Hourly, minutes)
  • 11. BIOMETEOROLOGY ADAPTATION
  • 12. ATMOSPHERE AND HUMAN HEALTH
  • 13. Physiological VARIABLES 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
  • 14. 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
  • 15. 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.
  • 16. 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
  • 17. 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
  • 18. OTHER VARIABLES VARIABLES 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.
  • 19. COMBINED EFFECTS VARIABLES 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
  • 20. COMBINED EFFECTS VARIABLES + + + 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
  • 21. COMBINED EFFECTS VARIABLES - 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
  • 23. 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 the cartographic representation of biometeorological indicators such as DOA index that is successfully implemented in health warning systems such as Pronbiomet
  • 24. HEAT WAVES HWS AND SPATIAL INFORMATION USA 2005 Kalstein, L.
  • 26.
  • 27. THE FUNDAMENTS CHANGE Yes HEALTH ADAPTATION? No DISEASES
  • 28. HEALTH WARNING SYSTEMS BIOMETEOROLOGICAL GIS FORECAST DEVELOPMENT
  • 30. 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- hours differences of the partial oxygen density in the air (PODA index), with a resolution of 0.5 degree (55 km).
  • 31. Air temperature Air humidity Atmospheric GIS Pressure MODEL Oxygen Density
  • 32. 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. CUBA EAST 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
  • 33. THE MODEL DAILY OUTPUTS EAST ASIA AND WESTPACIFIC NORTH AMERICA CUBA AUSTRALIA AND NEW ZEALAND SOUTH AMERICA EUROPE
  • 34. HOW TO READ THE MAPS? Biomet. Conditions Low Latitude Middle High Latitude Latitude Extreme hyperoxia > 10.0 > 20.0 > 30.0 Very strong hyperoxia 8.1 to 10.0 16.1 to 20.0 24.1 to 30.0 Strong hyperoxia 6.1 to 8.0 12.1 to 16.0 18.1 to 24.0 Moderate hyperoxia 4.1 to 6.0 8.1 to 12.0 12.1 to 18.0 Weak hyperoxia 2.1 to 4.0 4.1 to 8.0 6.1 to 12.0 THE NEUTRAL ZONE -2.0 to 2.0 -4.0 to 4.0 -6.0 to 6.0 Weak hypoxia -2.1 to -4.0 -4.1 to -8.0 -6.1 to -12.0 Moderate hypoxia -4.1 to -6.0 -8.1 to -12.0 -12.1 to -18.0 Strong hypoxia -6.1 to -8.0 -12.1 to -16.0 -18.1 to -24.0 Very strong hypoxia -8.1 to -10.0 -16.1 to -20.0 -24.1 to -30.0 Extreme hypoxia < -10.0 < -20.0 < -30.0
  • 35. BIOMETEOROLOGICAL FORECASTING BASED ON GIS RESULTS
  • 36. DATE: 17 / 11 / 2007 HYPEROXIA
  • 37. DATE: 20 / 11 / 2007 HYPOXIA
  • 38.
  • 39. BRAIN VASCULAR DISEASES BILBAO (October – November 2007) ENFERMEDADES CEREBRO VASCULARES en BILBAO (Octubre - Noviembre 2007) 10 15 6 13 Nº asistencias 2 11 3 g/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
  • 40. MIGRAINES, HYPERTENSION ANDCEFALEAS BILBAO (October - November 2007) ENFERMEDADES HIPERTENSITIVAS y CEFALEAS en BILBAO (Octubre - Novirmbre 2007) 10 28 6 24 2 Nº asistencias 20 3 g/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
  • 41. HEART RELATED DISEASES BILBAO (October – November 2007) CARDIOPATIAS ISQUEMICAS en BILBAO (Octubre - Novirmbre 2007) 10 20 18 6 16 2 14 12 3 g/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
  • 42. ECV = BRAIN VASCULAR DISEASES HTA-CEF-MIG = HIPERTENSION, CEFALEAS, MIGRAÑAS CAI = 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 4-0 2005 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
  • 43. 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 4–7 2006 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
  • 44. 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 2-0 2007 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
  • 45. BIOMETEOROLOGICAL FORECASTING RESULTS PERIOD 2005-2007 33 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
  • 47. A NETWORK OF VALIDATORS IS CREATED TO DETERMINE HOW USEFUL IS EACH HEALTH WARNING SYSTEM CREATION PROMOTION IMPROVEMENT VALIDATION
  • 48. 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
  • 49. CONCLUSIONS GEOGRAPHIC INFORMATION SYSTEMS ARE NECESSARY IN ORDER TO DEVELOP EARLY HEALTH WARNING SYSTEMS BASED ON BIOMETEOROLOGICAL FORECASTING
  • 50. THANK YOU VERY MUCH FOR YOUR ATTENTION