Ulisses E. C. Confalonieri Roberta Costa Dias Ulisses E. C. Confalonieri Roberta Costa Dias Climate Variability, Land Use and Malaria in the Amazon: Preliminary.

Slides:



Advertisements
Similar presentations
1 Modelling malaria in Africa driven by DEMETER forecasts Anne Jones Department of Geography University of Liverpool Liverpool UK
Advertisements

Centre for Atmospheric Sciences Indian Institute of Technology Delhi Hauz Khas, New Delhi – S K Dash Some Evidences of Climate Changes in India.
Vulnerability and Adaptation to Climate Change-Induced Malaria and Cholera in the Lake Victoria Region (AF91) P.Z. Yanda, R.Y.M. Kangalawe, R.J. Sigalla.
AIACC Regional Study AS07 Southeast Asia Regional Vulnerability to Changing Water Resources and Extreme Hydrological due to Climate Change.
The Role of Climate Change in Spreading Disease Marie Pizzorno Dept. of Biology Cell Biology/Biochemistry Program.
WHAT’S all the Buzz about? Vector-borne Diseases and Climate Change Linh Pham, Ph.D., NIEHS.
Health Effect of Climatic Change: Malaysian Senarios
Analysis of Malaria Incidence, Altitude, and Rainfall a Study in the Timor Tengah Selatan (TTS) District, West Timor, Indonesia ERMI NDOEN* AND TITIK RESPATI.
List seven land biomes that are found on Earth.
Nidal Salim, Walter Wildi Institute F.-A. Forel, University of Geneva, Switzerland Impact of global climate change on water resources in the Israeli, Jordanian.
Weather, climate and health
OBJECTIVES : Research: Conduct research, both empirical and conceptual, aimed at generating knowledge about climate/health associations and appropriate.
Dennis P. Lettenmaier Alan F. Hamlet JISAO Center for Science in the Earth System Climate Impacts Group and Department of Civil and Environmental Engineering.
Professor John Agard UWI Environment in Development.
Climate change and health. Climate Change and Health The topic will evolve and advance rapidly these first two decades of this century. Researchers are.
Climate Change, GIS, and Vector- Borne Disease Jessica Beckham February 10, 2011.
Sub-Saharan Africa Class 1. Approximately 600 million people.
Climate and Food Security Thank you to the Yaqui Valley and Indonesian Food Security Teams at Stanford 1.Seasonal Climate Forecasts 2.Natural cycles of.
Understanding Drought
1 2. Basic Concepts of Disease in Populations Peter Davies/Cord Heuer.
Chapter1: Introduction and Overview
Modelling of malaria variations using time series methods Ali-Akbar Haghdoost MD, Ph.D. in epidemiology and biostatistics faculty of Medicine, and Physiology.
CHAPTER 6ENVIRONMENTAL HEALTH ERADICATING A PARASITIC NIGHTMARE CHAPTER 6 ENVIRONMENTAL HEALTH ERADICATING A PARASITIC NIGHTMARE Human health is intricately.
Environmental Changes and Infectious Disease William R. Barnett PUBH 605.
Dengue virus Climate changes might play an important role in sustaining the transmission cycle between vectors and human hosts and the spread of transmission.
Epistemology of desertification and the ecosystem service paradigm Maurizio Sciortino ECSAC Conference August 2012.
GLOBAL, REGIONAL, AND INTERNATIONAL HEATH CONCERNS.
Trends and spatial patterns of drought incidence in the Omo-Ghibe River Basin, Ethiopia Policy Brief Degefu MA. & Bewket W.
1 5 th International Inter-Guianas Conference October 23-25, 2002, Guyana ADEK University of Suriname & University of Copyright 2002, Department.
Epidemiologic Triads Dr. Abdulaziz Ali Almezam Dr. Salwa A. Tayel & Dr. Mohammad Afzal Mahmood KSU Department of Family & Community Medicine September,
LaVerne E. Ragster, Ph.D. 5 th Annual Health Disparities Institute Caribbean Exploratory Research (NIMHD) Center University of the Virgin Islands.
Presented by Binaya Pasakhala Assessing Vulnerability of People’s Livelihood in Far-western Nepal: Implications on Adaptation to Climate Change.
Public Health and Ecological Forecasting Ben Zaitchik Johns Hopkins University.
Dissecting the Transmission Biology of Vector-Borne Diseases Derrick Mathias, PhD, MPH Department of Entomology & Plant Pathology College of Agriculture.
Earth System Models NASA TOPS -- Terrestrial Observation and Prediction System (predictive capabilities of over 30 variables describing land surface conditions.
Climate Change Vulnerability Projection in Georgia Earth Science and Climate Change Conference June 16-18, 2015 Alicante, Spain J. Marshall Shepherd Department.
Wildlife Response to Environmental Arctic Change November, 2008 Wildlife Conservation Society ABR Inc. UAF Institute of Arctic Biology UAF International.
Rainforest revision. Here is the answer: what is the question?  Adaptation  Emergent  Forest floor  Sustainable development  Eco tourism  Cattle.
KU Koech – IAIA-27 THE 27 TH IAIA CONFERENCE- 2007, SEOUL, KOREA IMPACT ASSESSMENT OF KENYA’S BIODIVERSITY AND AGRICULTURE: CONTRIBUTIONS OF METEOROLOGICAL.
Dr Mark Cresswell Impacts: Disease 69EG6517 – Impacts & Models of Climate Change.
HYDROELECTRIC POWER AND FERC. HYDRO 101A ”Water Runs Down Hill”
Participants: Ulisses E.C. Confalonieri, MD; DVM; DSc (Principal Investigator) Mércia E. Arruda, DSc (Co-PI) Brazil.
1Climate Change and Disaster Risk Science and impacts Session 1 World Bank Institute Maarten van Aalst.
Using Population Data to Address the Human Dimensions of Population Change D.M. Mageean and J.G. Bartlett Jessica Daniel 10/27/2009.
Spatial Science & Health Risk Mapping Dr Mark Cresswell.
Epidemiologic Triads Dr. Salwa A. Tayel & Dr. Mohammad Afzal Mahmood KSU Department of Family & Community Medicine September, September 2013Epidemiological.
ASSESSMENT OF THE ANNUAL VARIATION OF MALARIA AND THE CLIMATE EFFECT BASED ON KAHNOOJ DATA BETWEEN 1994 AND 2001 Conclusions 1. One month lag between predictors.
Watersheds and Wetlands CHAPTER 1. Lesson 1.5 Factors That Affect Wetlands and Watersheds Human Activities Watershed Quality Health of U.S. Watersheds.
Mexico Participants: Two full time researchers (ISAT). Three part time researchers (ISAT). Two MSc. students (epidemiology and environmental health at.
THE FUTURE CLIMATE OF AMAZONIA Carlos Nobre 1, Marcos Oyama 2, Gilvan Sampaio 1 1 CPTEC/INPE, 2 IAE/CTA LBA ECO São Paulo / 2005 November.
THE RELATIONSHIP BETWEEN THE CLIMATE, THE VECTOR AND THE DISEASE Prepared by: Shamsul Ridzuan IDRIS Program for Spatial and Urban Management National Institute.
Indicators for Climate Change over Mauritius Mr. P Booneeady Pr. SDDV Rughooputh.
1/10 The 51th Annual Hubbard Brook Cooperators' Meeting July 9-10, 2014 The teleconnection of Merrimack hydrology to AMO and NAO oceanic indices Rouzbeh.
Modelling of malaria variations using time series methods
Climate Change Linkages to Public Health in our community
Epidemiologic Triads Dr. Salwa A. Tayel & Prof. Ashry Gad Mohamed
Modelling of malaria variations using time series methods
A study of Malaria in the flood prone coastal city Surat Dr
The effect of climate and global change on African water resources
Mosquito-borne diseases
INDONESIA’S CLIMATE & FUTURE CLIMATE VISION
Climate in Brazil: present and perspective for the future
CITY VULNERABILITY ASSESSMENT
LUCIA – Land Use, Climate and Infections in the Western Amazonia
Global & Regional Climate Change
Introduction to Meteorology
Environmental modeling application domains
Health Impact due to Climate Change.
Drought Management and Water Scarcity Adaptation
Kreshna GOPAL C. Prakash KHEDUN Anoop SOHUN
Presentation transcript:

Ulisses E. C. Confalonieri Roberta Costa Dias Ulisses E. C. Confalonieri Roberta Costa Dias Climate Variability, Land Use and Malaria in the Amazon: Preliminary Results from the State of Roraima, Brazil. Climate Variability, Land Use and Malaria in the Amazon: Preliminary Results from the State of Roraima, Brazil. Program on Global Environmental Changes and Health Department of Biological Sciences National School of Public Health Oswaldo Cruz Foundation Program on Global Environmental Changes and Health Department of Biological Sciences National School of Public Health Oswaldo Cruz Foundation by

Program on Global Environmental Changes and Health

VECTOR–BORNE DISEASE INCIDENCE eg. malaria VECTOR–BORNE DISEASE INCIDENCE eg. malaria PRECIPITATION ANOMALY VECTOR POPULATION DENSITY CLIMATE SYSTEM VARIABILITY Physical Linkages Possible Associations

LIFE–CYCLE OF MALARIA PARASITE AND VECTORS LAND USE PRACTICE DEFORESTATION INCREASE IN MALARIA INCIDENCE INCREASE IN MEAN TEMPERATURE Physical Linkages Possible Associations

Precipitation Anomaly Deforestation CLIMATE Hydrological Cycle Forest Fires LAND USE PHYSICAL PARAMETERS eg. temperature; humidity VECTOR BIOLOGY eg. reproduction; growth; longevity MALARIA INCIDENCE Demography Behaviour Demography Behaviour

Conceptual Model for the Assessment of the Impacts of Climate Variability on Infectious Diseases PUBLIC HEALTH INTERVENTIONS BIOLOGY OF VECTORS AND DISEASE AGENTS Vector control Treatment of cases Precipitation Temperature Runoff Relative humidity Changes in habitats Changes in animal reservoirs Change in microclimates DEMOGRAPHY BEHAVIOUR INCOME MOBILITY CULTURE INFORMATION OCCUPATION INSTITUTIONS DEMOGRAPHY BEHAVIOUR INCOME MOBILITY CULTURE INFORMATION OCCUPATION INSTITUTIONS HUMAN EXPOSURE INFECTIOUS DISEASES CLIMATE VARIABILITY LAND COVER CHANGES LAND USE PRACTICES HYDRO–METEOROLOGICAL PARAMETERS

Climate System Meteorological Variables Precipitation DECREASE IN MALARIA INCREASE IN MALARIA OUTBREAKS OF PLAGUE OUTBREAKS OF LEPTOSPIROSIS MOSQUITO LARVAE WASHED AWAY MOSQUITO BREEDING INCREASE IN POPULATION OF RODENTS (RESERVOIR) POOR DRAINAGE RUNOFF RAINFOREST POOLS SEMI-ARID INCREASE IN ECOSYSTEM PRODUCTIVITY SEMI-ARID POOR CARBAGE DISPOSAL URBAN SLUMS

Roraima

Annual Precipitations in the Stations of S. M. Boiacu, Fé e Esperança and Maloca do Contão

Precipitação Pluviométrica nas Estações Boqueirão e Faz. São João, 1985–1990

Precipitação Pluviométrica nas Estações Boqueirão e Faz. São João, 1990–1995

Precipitação Pluviométrica nas Estações de Surucucu e Fé e Esperança, 1985–1990

Precipitação Pluviométrica nas Estações Boqueirão e SOI, 1980–1985

Precipitação Pluviométrica nas Estações Boqueirão e SOI, 1985–1990

Methodology ( I ) I – Malaria Rate per Month for Each Municipality:  2 municipalities up to 1983  8 municipalities from 1984 to 1996  15 municipalities after 1996 II – Precipitation Data from 51 Rain Gauge Stations:  15 with reliable data from 1980 onwards

Methodology ( II )  To compare ENSO indices (SOI; SST3) with malaria incidence at state and municipal level.  To compare rainfall intensity and duration with malaria incidence (measured by IPA) for every municipality.

Annual Parasite Index for the State of Roraima – 1980–1998

Annual Parasite Index for Calendar Year and June/May Periods in Roraima ( )

IPA for Malaria and SOI in Roraima 1980 a 1985

IPA for Malaria and SOI in Roraima

IPA for Malaria and SOI in Roraima

Malária x Precipitação em Bonfim 1985–1990

Malária x Precipitação em S. M. Boiacu 1985–1990

Methodology ( III )  To perform a cluster analysis of rain gauge stations from historical precipitation data.  To match the precipitation data above with the dominant ecosystem in order to have specific ECOREGIONS defined.  To analyze the malaria incidence data for each ecoregion as related to climate variation, land use/demographic events and disease control activities.

Conclusions  Malaria in Roraima is an endemic disease with a seasonal pattern: the high transmission season is November through January and the low transmission period from June to August.  Malaria incidence in RR decreases with ENSO due to the low humidity associated with the precipitation anomaly (drought).