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Transcript
THE RELATIONSHIP BETWEEN
THE CLIMATE, THE VECTOR
AND THE DISEASE
Erasmus Mundus Conference – Higher Education and Climate
Change
26-27 February 2009
Central European University, Budapest, Hungary
Prepared by:
Shamsul Ridzuan IDRIS
Program for Spatial and Urban Management
National Institute of Public Administration
MALAYSIA
OUTLINE
•
•
•
•
•
•
INTRODUCTION
THE CLIMATE, THE VECTOR & THE DISEASE
USING GIS AND RS IN PREDICTING AEDES
INCIDENCES AND CONTROL THE VECTOR
MAPS PREDICT PLACES WITH RISK OF
DENGUE
PROBLEMS IN MAPPING THE VECTOR
SUMMARY
2
INTRODUCTION
Estimating the Effects of Climate Change on Health
Pathway through which climate change may affect health
Source: Adapted from Patz et al. (2000)
3
Our CLIMATE is changing
West Nile Virus Incidences in United States in 2007
Map produced by USGS: http://diseasemaps.usgs.gov/
4
Continue…
GIS to fight dengue epidemic in Bangkok
•30 August 2007 Bangkok, Thailand, August 28, 2007:
Authorities in Bangkok are resorting to a GIS to ease the
dengue epidemic in the Thai capital.
•Bangkok governor Apirak Kosayodhin said, a longer rainy
season and changing temperatures have favored the
breeding of the mosquito that transmit the fatal disease.
•Since Jan. 1, there were 3,089 cases of dengue in
Bangkok, four of which were fatal. The governor added the
GIS will help the city officials to find critical epidemic areas
and allow them to refine their focus in fighting the
infections.
5
Continue…
Climate Change Observation - Malaysia
• Highest temperature 40.1° C (Apr 1998)
• Highest rainfall 159.4 mm/hour (Oct 2006)
• Big flood incidences Dec 2004, Dec 2005,
Apr 2006. May 2006, Dec 2006, Jan 2007,
Apr 2008. Aug 2008, Sept 2008
• Occurrence of El-Niño (1997/98), La Niña
(2007,2009)
6
Malaysia’s CLIMATE is changing
• Increase temperature and rainfall in Malaysia
Source from Meteorological Dept. Malaysia
7
THE VECTOR
• Mapping using GIS and Remote Sensing can
differentiate incidences according to species of
mosquito, breeding grounds and type of disease
• Species of interest
– Culex – Malaria/WNV/JE
– Aedes – Dengue/Chikungunya
– Anopheles - Malaria
8
Common communicable diseases
sensitive to climate
Climate is the primary factor in epidemic
• Cholera, Malaria
Climate plays significant role
• Meningococcal meningitis, leishmaniasis, dengue,
Japanese encephalitis, Rift valley fever, Ross river
virus, St. Louis encephalitis, Murray valley fever
Source from WHO, (2004)
9
THE DISEASE
• Increase incidences of vector diseases
• Reduce in reported Malaria cases
• Increase in reported Dengue fever
Dengue Fever In Malaysia from 1980 to 2006
Malaria in Malaysia from 1961 to 2006
45000
600,000
40000
500,000
300,000
malaria
200,000
Number of Cases
400,000
30000
25000
Dengue Fever
20000
15000
10000
100,000
5000
0
Years
19
75
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
0
19
61
19
70
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
Number cases
35000
Years
Source: Adapted from Ishak R., 2007
10
Continue…
Source: Ministry of Health, Malaysia
11
Malaria in Year 2100
Possible Pattern of Malaria in Worst Cases Senario in Malaysia
from Year 1960 to 2100
600,000
Number of Malaria Cases
500,000
400,000
300,000
200,000
100,000
80
20
60
20
45
20
35
20
25
20
15
20
06
20
00
20
90
19
80
19
70
19
19
61
0
Year
Malaria
With Control measures
Without Control measures
Source: Adapted from Ishak R., 2007
12
Dengue Fever in Year 2100
Dengue Fever In Malaysia from Year 1980 to 2100
700000
Number of Cases
600000
500000
400000
300000
200000
100000
00
21
80
20
70
20
60
20
50
20
45
20
40
20
35
20
30
20
25
20
20
20
15
20
10
20
06
20
05
20
00
20
95
19
90
19
85
19
19
80
0
Years
Dengue Fever
with Control Measures
Without Control Measures
Source: Adapted from Ishak R., 2007
13
USING GIS AND RS IN PREDICTING AEDES
INCIDENCES AND CONTROL THE VECTOR
• To understand that disease surveillance and mapping of
potential risk area can be addressed by GIS and RS
technologies
• To track mosquito and larval density in specific zones and
predict disease patterns
• To link and update information on the environment, weather
condition and disease incidences
• To facilitate health authority to undertake specific measures
to reduce and control the vector
14
MAPS PREDICT PLACES WITH RISK OF
DENGUE
• Dengue Risk Map with
different categories of risk
• Mapping produced on
smaller residential area
(Subang Jaya)
• To identify the area where a
dengue outbreak is going to
occur (prevention)
• Mitigation measure - vector
control
Dengue Risk Map prepared in Umor et al. (2007)
15
Continue…
Dengue Risk Map Methodology Concept
Source: Adapted from Umor et al. 2007
16
Continue…
• Dengue Risk Map with the point case
location of recorded dengue incidences
Source: Adapted from Umor et al. 2007
17
PROBLEMS IN MAPPING THE VECTOR
• Stagnant water/water bodies in small
stream/ditches/drainage system under a tree canopy will
be difficult to detect using RS. These are important
habitats for early stages of mosquito life. It is mostly
located near to residential areas and human population.
• The collection of data on mosquito breeding ground is
labour intensive and need to be properly geo-referenced
18
Continue…
• Mosquito breeding in freshwater wetlands can be a
complex problem and must be considered on a case by
case basis.
• Mosquito management in such sites should aim to
minimize population numbers, or reduce them to a
tolerable or nonthreatening level. However, different
species, various types of habitat and a range of
environmental conditions will have to be addressed
• Despite the availability of chemical insecticide,
Larvivorous fish are more practical for use in wetlands as
Biological Agent
19
SUMMARY
• Previous study revealed that environmental changes have
a major contribution to the pattern of disease incidences
and distribution
• Adaptations to climate change (autonomous or planned
responses that reduce the vulnerability of populations to
the consequences of climate change) are often not
addressed
• Little effort has previously been directed to describing and
understanding the geographical variations in likely impacts
Source: Adapted from McMichael et al. (2003)
20
SUMMARY
Continue…
• Climate variability in Malaysia is very much influenced by
the monsoon (intra-seasonal/inter-annual) and ENSO
(Tangang et al. (2007))
• Consistent with other places, generally temperature in
Malaysia is rising and long-term trend of precipitation are
more variable
• If ocean warming affect the monsoon system,
characteristics of climate variability in Malaysia will be
affected
• How global warming alter local rainfall distribution,
disease and vector outbreak need further investigation
21
THANK YOU
 [email protected]
22
REFERENCES:
1)
2)
3)
4)
5)
6)
7)
Malaysian Remote Sensing Agency http://www.remotesensing.gov.my/
Malaysia Meteorological Department http://www.met.gov.my
Ministry of Health http://www.moh.gov.my/MohPortal/
Hassan, Kumar & Kumarenthiran, 2008, “Climate Change Scenario and
the Impact of Global Warming on the Winter Monsoon”, paper presented
at the Second National Conference on Extreme Weather and Climate
Change Understanding Science and Risk Reduction, 14-15 Oct 2008,
Putrajaya, from http://www.met.gov.my/ClimateChange2008/
Ishak, R., 2007, “Health Effect of Climatic Change: Malaysian Scenarios”,
paper presented at National Seminar on Socio-economic Impacts of
Extreme Weather and Climate Change, 21-22 June 2007, Putrajaya, from
http://www.met.gov.my/ClimateChange2007/
McMicheal et al., 2003, “Global Climate Change, Chap 20, Comparative
Quantification of Health Risk”, from
www.who.int/publications/cra/chapters/volume2/1543-1650.pdf
Tangang et al, 2007, “Climate variability, climate change and Extreme
Weather Events in Malaysia”, paper presented at National Seminar on
Socio-economic Impacts of Extreme Weather and Climate Change, 21-22
June 2007, Putrajaya, from http://www.met.gov.my/ClimateChange2007/
23
REFERENCES:
8)
9)
10)
Umor, S.M., Mokhtar, M, Surip, N and Ahmad, A, 2007, “Generating a
Dengue Risk Map (DRM) Based on Environmental Factors using
Remote Sensing and GIS Technology”, paper presented at Conference
of the Asian Association of Remote Sensing, 12-16 November 2007,
PWTC, Malaysia.
Malaysian Meteorological Department, 2006: Report on heavy rainfall
that caused floods in Johor, Melaka, Negeri Sembilan and Pahang during
the period 17th -20th December 2006.
Malaysian Meteorological Department, 2007: Report on the second
heavy rainfall episode that caused floods in Johor and southern Pahang
during the period 11th -14th January 2007.
24