environmental health research l b a amazonian environmen t society the lba project, environmental...

Environmental Health

Research

Environmental Health

Research

L B AL B A

Amazonian

Environment

Amazonian

Environment

SocietySociety

The LBA Project, Environmental Health Research and Society

The LBA Project, Environmental Health Research and Society

Determinants of Health and DiseaseDeterminants of Health and Disease

I - Biophysical Factors in the Environment

•Climate•Climate

•Hydrology•Hydrology

•Vegetation•Vegetation

•Topography•Topography

•Animal diversity (vectors and reservoirs•Animal diversity (vectors and reservoirs

II - Social-Economic Conditions

• Income• Income

•Education / Information•Education / Information

•Place of residence•Place of residence

•Health services•Health services

III - Human Behaviour

Focalização das EndemiasFocalização das Endemias

Combinação de elementos ambientais (clima, vegetação, relevo) e sociais (demografia, uso

da terra), formando “paisagens típicas”, propícias à transmissão de endemias.

Combinação de elementos ambientais (clima, vegetação, relevo) e sociais (demografia, uso

da terra), formando “paisagens típicas”, propícias à transmissão de endemias.

Exemplos:

Cólera no Rio Negro Cólera no Rio Negro

Febre Amarela Silvestre Febre Amarela Silvestre

Doença de Chagas e Esquistossomose na Amazônia Doença de Chagas e Esquistossomose na Amazônia

Hepatite no Amazonas Hepatite no Amazonas

Calazar em Roraima Calazar em Roraima

Fatores Ambientais na Amazônia

Fatores Ambientais na Amazônia

Clima:

Temperatura Temperatura Precipitação Precipitação Umidade Relativa Umidade Relativa

Ciclo Hidrológico

Cobertura da Terra (“Land Cover”):

Ambiente Construído Ambiente Construído

Vegetação (Tipo, Fenologia, Distribuição Espacial

Vegetação (Tipo, Fenologia, Distribuição Espacial

Geomorfologia

Fauna (Reservatórios e Vetores)

Determinant Factors in Vector–Borne Diseases

Determinant Factors in Vector–Borne Diseases

Survival / Activity / Cycle

Biological Susceptibility

Biological Susceptibility

Exposure to Vector

Exposure to Vector

Disease AgentDisease Agent

Vector Population

Vector Population

Vector Borne Disease

Vector Borne Disease

Climate / Weather

Climate / Weather

Climate / Weather

Climate / Weather

Climate / Weather

Climate / Weather

eg. Transportation

Genetic FactorsGenetic Factors

ImmunizationImmunization

Previous Exposure

Previous Exposure

Human BehaviourHuman Behaviour

DiagnosisDiagnosis

Medical CareMedical Care

ReportingReporting

EducationEducationType of EcosystemType of Ecosystem

Natural Predators

Natural Predators

Control Activities

Control Activities

Place of ResidencePlace of Residence

IncomeIncome

Social Development

Social Development

EconomyEconomyPublic Health System

Public Health System

eg.

migration

Conceptual Model for the Assessment of the Impacts of Climate Variability on Infectious

Diseases

Conceptual Model for the Assessment of the Impacts of Climate Variability on Infectious

Diseases

PUBLIC HEALTH INTERVENTIONS

PUBLIC HEALTH INTERVENTIONS

BIOLOGY OF VECTORS AND

DISEASE AGENTS

BIOLOGY OF VECTORS AND

DISEASE AGENTSVector control

Treatment of cases

PrecipitationTemperature

RunoffRelative humidity

Changes in habitatsChanges in animal

reservoirsChange in microclimates DEMOGRAPHY

BEHAVIOURINCOME

MOBILITYCULTURE

INFORMATIONOCCUPATIONINSTITUTIONS

DEMOGRAPHYBEHAVIOUR

INCOMEMOBILITYCULTURE

INFORMATIONOCCUPATIONINSTITUTIONS

HUMAN EXPOSURE

HUMAN EXPOSURE

INFECTIOUS DISEASES

INFECTIOUS DISEASES

CLIMATE VARIABILITYCLIMATE VARIABILITY

LAND COVER CHANGES

LAND COVER CHANGES

LAND USE PRACTICES

LAND USE PRACTICES

HYDRO–METEOROLOGICAL PARAMETERS

HYDRO–METEOROLOGICAL PARAMETERS

Interfaces Between Public Health Research and the LBA Project


II - Micro-Meteorology

• Influences of physical factors (temperature, relative humidity, evapotranspiration, radiation, wind) on vector development and survival rate

• Influences of physical factors (temperature, relative humidity, evapotranspiration, radiation, wind) on vector development and survival rate

• Influences of temperature on the developmental cycle of pathogenic organisms

• Influences of temperature on the developmental cycle of pathogenic organisms

I - Climatology

• Climate forecasts used for the prediction of outbreaks (eg. “Climate-Health Early Warning Systems”)

• Climate forecasts used for the prediction of outbreaks (eg. “Climate-Health Early Warning Systems”)

• Extreme conditions changing human exposure (eg. drought causing human migration)

• Extreme conditions changing human exposure (eg. drought causing human migration)

III - Hydrology

• Formation / destruction of vector habitats (stagnant ponds, streamflow, overland runoff)

• Formation / destruction of vector habitats (stagnant ponds, streamflow, overland runoff)

IV - Land Use and Land Cover Changes

• Changes in habitats of reservoirs and vectors• Changes in habitats of reservoirs and vectors

• Proxies for local demographic variations and human exposure• Proxies for local demographic variations and human exposure

V - Atmospheric Chemistry

• Smoke from forest fires affecting respiratory conditions• Smoke from forest fires affecting respiratory conditions

• Atmospheric aerosols affecting mosquito survival (eg. reduction of ultraviolet radiation incidence in breeding sites)

• Atmospheric aerosols affecting mosquito survival (eg. reduction of ultraviolet radiation incidence in breeding sites)



VECTOR–BORNE DISEASE INCIDENCEeg. malaria

VECTOR–BORNE DISEASE INCIDENCEeg. malaria

PRECIPITATION ANOMALYPRECIPITATION ANOMALY

VECTOR POPULATION DENSITY

VECTOR POPULATION DENSITY

CLIMATE SYSTEM

VARIABILITY

CLIMATE SYSTEM

VARIABILITY

Physical LinkagesPossible Associations

LIFE–CYCLE OF MALARIA PARASITE AND VECTORSLIFE–CYCLE OF MALARIA PARASITE AND VECTORS

LAND USE PRACTICELAND USE PRACTICE

DEFORESTATIONDEFORESTATION

INCREASE IN MALARIA INCIDENCE

INCREASE IN MALARIA INCIDENCE

INCREASE IN MEAN TEMPERATURE

INCREASE IN MEAN TEMPERATURE

Physical LinkagesPossible Associations

Precipitation Anomaly Deforestati

on

CLIMATE

Hydrological CycleHydrological Cycle

Forest FiresForest Fires

LAND USE

PHYSICAL PARAMETERSeg. temperature; humidity

VECTOR BIOLOGYeg. reproduction; growth; longevity

MALARIA INCIDENCE

Dem

og

rap

hy

Beh

avio

ur

Dem

og

rap

hy

Beh

avio

ur

FLUTUAÇÕES CLIMÁTICAS

FLUTUAÇÕES CLIMÁTICAS

Eventos Meteorológi

cos Extremos

Eventos Meteorológi

cos Extremos

Acidentes e

Traumas

Acidentes e

Traumas

Abundância e Disseminação de

Vetores e Patógenos

Abundância e Disseminação de

Vetores e Patógenos

Transmissão de Doenças Infecciosas

Transmissão de Doenças Infecciosas

Precipitation

Precipitation

Soil Type

Soil Type

Evapotranspiration

Evapotranspiration

InfiltrationInfiltration

RunoffRunoff

Stream Flow

Stream Flow

Depression

Storage

Depression

Storage

Vegetation Cover

Vegetation Cover

Topography

Topography

Leaf area index and turnover

Leaf area index and turnover

Interception

Interception

TemperatureTemperature

Temperature

Temperature

Litter fallLitter fall

Through fallThrough fall

ErosivityErosivity

Overland flow

Overland flow EvaporationEvaporation

Permanent and

temporary pools

Permanent and

temporary pools

Adults

Adults

Larvae

Larvae

Hydrological Model and Vector

Hydrological Model and Vector

Interactions of Vulnerability Factors and Climates Impacts on a Landscape SettingInteractions of Vulnerability Factors and Climates Impacts on a Landscape Setting

Landform

VegetationAtmosphere

Hydrology

Landform

VegetationAtmosphere

Hydrology

Atmosphere

Hydrology Landform Vegetation

Atmosphere

Hydrology Landform Vegetation

VegetationLandform

Hydrology Atmosphere

VegetationLandform

Hydrology Atmosphere

PopulationPopulation

Ecological ServicesEcological Services

Food ProductionFood Production

Social Services

Social Services

Infrastructure &

Buildings

Infrastructure &

Buildings

VulnerabilityVulnerability



InfrastructureInfrastructure

EcosystemNatural Landscape

(eg. rainforest)

Modified Landscape(eg. agroecosystem)

Built (“Cultural”) Landscape(eg. urban)



Climate System

LandscapeLandscape

Climate SystemLandscapeLandscape

Lan

dsca

pe

Lan

dsca

pe

Lan

dsca

pe

Lan

dsca

pe

REDUÇÃO DA MALÁRIA

AUMENTO DA MALÁRIA

SURTOS DE PESTE BUBÔNICA

SURTOS DE LEPTOSPIROSE

LARVAS DE MOSQUITO

ARRASTADAS

CRIAÇÃO DE MOSQUITOS

AUMENTO DA POPULAÇÃO DE

ROEDORES RESERVATÓRIO

S

MÁ DRENAGEM

ESCOAMENTO SUPERFICIAL

POÇAS D’ÁGU

A

AUMENTO DA PRODUTIVIDA

DE ECOSSISTÊMIC

A

COLETA DE LIXO

DEFICIENTE

FLORESTA TROPICAL

SEMI–ÁRIDO

SEMI–ÁRIDO

FAVELAS URBANAS

Sistema Climático

Variáveis Meteorológicas

Precipitação

ENOS e Malária na Indonésia, 1997

ENOS e Malária na Indonésia, 1997

EPIDEMIAS DE MALÁRIAEPIDEMIAS DE MALÁRIA

Seca(70% de redução na precipitação)

Formação de poças temporárias

Aumento da população de Anopheles

Redução da produtividade agrícola

Escassez de alimentos

Má nutrição

Redução da imunidade

Migração de não–imunes

Exposição de hospedeiros vulneráveis

ENOSENOS

Precipitation (deviation from historical means) and cases of Leptospirosis in the rainy season (Jan/Jun) in the municipality of São Miguel, Rio Grande do Norte,

Brazil – 1985–1996

Precipitation (deviation from historical means) and cases of Leptospirosis in the rainy season (Jan/Jun) in the municipality of São Miguel, Rio Grande do Norte,

Brazil – 1985–1996

36

190 188

40 1 0 1 0 0 0 0

-65,9

20,4 21,414,0

6,51,4

-21,1 -16,8 -17,9 -19,7

57,363,4

0

20

40

60

80

100

120

140

160

180

200

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

-80,0

-60,0

-40,0

-20,0

0,0

20,0

40,0

60,0

80,0

Cases of Leptospirosis

Precipitation (% Deviation from Means)

Cas

es o

f L

epto

spir

osi

s

Pre

cip

itat

ion

(%

Dev

iati

on

fro

m M

ean

s)

Malaria Positive Smears for 1000 Population in the State of Roraima, Northern Brazil – 1962–

1997

Malaria Positive Smears for 1000 Population in the State of Roraima, Northern Brazil – 1962–

1997

0

20

40

60

80

100

120

140

160

180

2001

96

2

19

64

19

66

19

68

19

70

19

72

19

74

19

76

19

78

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

El Niño yearsEl Niño years

1980

9,74

18,66

12,09

14,79

13,69

7,56 7,85

10,08

17,56

15,26

21,48

10,17

0,00

5,00

10,00

15,00

20,00

25,00

1981

14,1212,02 11,59

7,39

8,83

6,63

10,58

11,34

18,02

11,03

10,29 9,52

0,00

5,00

10,00

15,00

20,00

1983

9,44

10,40 10,30

7,45

12,35 12,67

11,22

14,73

9,82

14,77 16,77

21,49

0,00

5,00

10,00

15,00

20,00

25,00

1982

20,43

16,96

26,87

16,66

16,1714,76

8,90

8,27

8,67

7,78

8,72

9,17

0,00

5,00

10,00

15,00

20,00

25,00

30,00

Annual Parasite Index for the State of Roraima

1980–1983


1980–1983

1987

6,21

8,16

5,826,40

6,99

5,41

6,77

4,57

5,79

5,07

7,09

6,45

0,001,002,003,004,005,006,007,008,009,00

1986

7,609,12

6,28

5,83

4,74

4,685,26

7,79

6,70

9,22

7,96

3,89

0,00

2,00

4,00

6,00

8,00

10,00

1985

12,52

5,23 6,689,41

11,78 11,80

10,23

7,668,63 7,79

14,63

19,95

0,00

5,00

10,00

15,00

20,00

25,00

1984

11,7318,24

20,20

6,91

8,52

7,07 6,00

8,84

8,54

13,08 13,91

11,95

0,00

5,00

10,00

15,00

20,00

25,00


1984–1987


1984–1987

1991

13,3312,87 11,96

9,86 9,10

7,54 7,56

11,21

11,16

7,767,958,88

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

1990

11,368,80

17,25

13,14

13,01

12,72

9,78

10,67

6,70

7,03

8,09

11,40

0,00

5,00

10,00

15,00

20,00

1989

12,3212,17

6,509,08

15,63

10,91

9,26

6,73

7,92

7,809,58

10,66

0,002,004,006,008,00

10,0012,0014,0016,0018,00

1988

7,617,53

13,24

8,259,97

9,03

4,665,61

4,05

4,95

5,05

10,67

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00


1988–1991


1988–1991

1992

14,53

7,86

9,16

6,28

9,22

6,49

10,12

8,848,55

10,24

7,939,00

0,002,004,006,008,00

10,0012,0014,0016,00

1993

4,224,02

5,73 6,05

4,20

5,56

6,79

6,99

7,26

5,84

7,56 7,48

0,001,002,003,004,005,006,007,008,00

1994

10,81

9,768,51

5,48 5,81

10,25

9,69

14,98

6,15

7,10

5,38

13,29

0,002,004,006,008,00

10,0012,0014,0016,00

1995

13,05

16,6513,33

18,40

22,09

10,18

11,24

11,57

10,93

9,71

12,7115,79

0,00

5,00

10,00

15,00

20,00

25,00


1992–1995


1992–1995

1996

7,238,49 8,00

8,61

6,87

15,52

14,83

15,1315,22

11,45

20,61

13,32

0,00

5,00

10,00

15,00

20,00

25,00

1997

11,35

7,63

5,76

8,30

8,34

7,367,52

5,73

7,78

7,66

13,08

9,10

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

1998

8,53

5,15

4,33

5,53

5,476,076,70

10,39

11,72

8,156,41

4,24

0,00

2,004,00

6,00

8,00

10,0012,00

14,00


1996–1998


1996–1998

0

1000

2000

3000

4000

5000

6000

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

1995 1996 1997

Cases of Malaria in the State of Roraima, Northern Brazil

1995 –1996 – 1997

Cases of Malaria in the State of Roraima, Northern Brazil

1995 –1996 – 1997

IPA for Malaria and SOI in Roraima1980 a 1985

IPA for Malaria and SOI in Roraima1980 a 1985

0

5

10

15

20

25

30

jan

/80

ma

i/8

set/

80

jan

/81

ma

i/8

set/

81

jan

/82

ma

i/8

set/

82

jan

/83

ma

i/8

set/

83

jan

/84

ma

i/8

set/

84

jan

/85

ma

i/8

set/

85

-10

-8

-6

-4

-2

0

2

4IPA SOI

0

5

10

15

20

25

jan

/85

ab

r/85

jul/

85

ou

t/85

jan

/86

ab

r/86

jul/

86

ou

t/86

jan

/87

ab

r/87

jul/

87

ou

t/87

jan

/88

ab

r/88

jul/

88

ou

t/88

jan

/89

ab

r/89

jul/

89

ou

t/89

jan

/90

ab

r/90

jul/

90

ou

t/90

-5

-4

-3

-2

-1

0

1

2

3

4

IPA SOI

IPA for Malaria and SOI in Roraima1985-1990


0

5

10

15

20

25

jan

/91

ma

i/9

set/

91

jan

/92

ma

i/9

set/

92

jan

/93

ma

i/9

set/

93

jan

/94

ma

i/9

set/

94

jan

/95

ma

i/9

set/

95

jan

/96

ma

i/9

set/

96

jan

/97

ma

i/9

set/

97

jan

/98

ma

i/9

set/

98

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

IPA SOI



0

5.000

10.000

15.000

20.000

25.000

30.000

1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 19970

5.000

10.000

15.000

20.000

25.000

30.000Imported CasesAutochtonous Cases

Cases of Malaria in the State of Maranhão, Northeastern Brazil, 1977–1997

Cases of Malaria in the State of Maranhão, Northeastern Brazil, 1977–1997

Impacts of ENSO-Driven Droughts in Rural Landscapes of the Brazilian Northeastern

and Amazonian Regions

Impacts of ENSO-Driven Droughts in Rural Landscapes of the Brazilian Northeastern

and Amazonian Regions

NORTHEASTERNNORTHEASTERN AMAZONIANAMAZONIAN

Dominant Plant PhysiognomyDominant Plant Physiognomy ScrublandScrubland Rainforest & savannaRainforest & savanna

Fire HazardFire Hazard NoNo YesYes

Water AvailableWater Available Critically decreasedCritically decreased Slightly affectedSlightly affected

Population DensityPopulation Density HighHigh LowLow

Food ProductionFood Production Extremely reducedExtremely reduced Slightly reduced (focally)Slightly reduced (focally)

TransportationTransportation NormalNormal ImpairedImpaired

Reactive Human MigrationReactive Human Migration Yes (eg. to the Amazon)Yes (eg. to the Amazon) NoNo

Vector-borne DiseasesVector-borne Diseases Plague; dengue fever;

leishmaniasis

Plague; dengue fever;

leishmaniasis

Malaria; arbovirus; leishmaniasis;

dengue

Malaria; arbovirus; leishmaniasis;

dengue

Other DiseasesOther DiseasesDiarrheal diseases;

malnutrition; cholera;

leptospirosis

Diarrheal diseases; malnutrition;

cholera; leptospirosis

Respiratory ailments; cholera

Respiratory ailments; cholera

Social Vulnerability to drought in Northeastern Brazil

Social Vulnerability to drought in Northeastern Brazil Semi-arid regionSemi-arid region

Subsistence farmingSubsistence farming

Low incomeLow income

No employmentNo employment

No access to climate prediction

information

No access to climate prediction

information

No Food Surplus

No Food Surplus

Changes in Epidemiological

Profile

Changes in Epidemiological

Profile

Crop loss

Crop loss

No Governmen

tal Assistance

No Governmen

tal Assistance

MigrationMigration

Rural Populati

on

Rural Populati

on

DroughtDrought

No WaterNo Water

Poor Hygiene

Poor Hygiene

Increase in infant mortality due to diarrhea

Increase in infant mortality due to diarrheaMalnutrition of childrenMalnutrition of children

Spread of visceral leishmaniasis to

cities

Spread of visceral leishmaniasis to

cities

Number of Cases of Visceral Leishmaniases in the State of Maranhão, Brazil – 1982–1996

Number of Cases of Visceral Leishmaniases in the State of Maranhão, Brazil – 1982–1996

41

159

569

422

135

68

42

172

91

61

89

537 534

263

144

0

100

200

300

400

500

600

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

Nu

mb

er o

f C

ases

Number of Cases of Visceral Leishmaniases in the State of Piauí, Brazil – 1980–1996

Number of Cases of Visceral Leishmaniases in the State of Piauí, Brazil – 1980–1996

11

68

244

312

435

326

125

46 47

162

201

86

173

697

778

407

239

0

100

200

300

400

500

600

700

800

900

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

Nu

mb

er o

f C

ases

As far as human infectious diseases are concerned the Amazon functions as a “Regional Nosological Unit” due to its unique ecological and social characteristics.

As far as human infectious diseases are concerned the Amazon functions as a “Regional Nosological Unit” due to its unique ecological and social characteristics.

The cycles of many infectious diseases in Amazonia are closely linked to the structure and functioning of the natural ecosystems.

The cycles of many infectious diseases in Amazonia are closely linked to the structure and functioning of the natural ecosystems.

Anthropogenic changes in these systems are causing changes in their “disease systems” such as the intensification of transmission; geographical expansion; changes in vector populations; emergence of new diseases or extinction.

Anthropogenic changes in these systems are causing changes in their “disease systems” such as the intensification of transmission; geographical expansion; changes in vector populations; emergence of new diseases or extinction.

Most anthropogenic interventions that change the disease systems also change the geophysiology of Amazonia.

Most anthropogenic interventions that change the disease systems also change the geophysiology of Amazonia.

The forecasting of changes in the ecological systems of Amazonia can be useful for making predictions about changes in the regional epidemiological profiles.

The forecasting of changes in the ecological systems of Amazonia can be useful for making predictions about changes in the regional epidemiological profiles.

environmental health research l b a amazonian environmen t society the lba project, environmental...

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