Epidemiology Patterns Of Dengue In The Caribbean
Under Climate ChangeA. M. D. Amarakoon**, Anthony A. Chen,
Michael A. Taylor, Rainaldo F. CrosbourneClimate Studies Group Mona, UWI, Jamaica
Samuel C. Rawlins, Karen Polson
Caribbean Epidemiology Centre, Trinidad & Tobago
Wilma Bailey, Charmaine Thomas-Heslop
Department of Geography, UWI, Jamaica
[** SPEAKER]
The Threat of Dengue Fever - Assessment of Impacts and
Adaptation to Climate Change in Human Health in the Caribbean
An AIACC Project at The University of the West Indies,
Mona and Caribbean Epidemiology Centre
PROJECT: AIACC-SIS06
THE CARIBBEAN
OBJECTIVES To determine the extent of the association
between climate and the incidence of dengue across the Caribbean Region.
To explore possible adaptation options
The approaches selected to achieve the objectives:
Investigate the influence of climate, through temperature and precipitation, on the epidemics
Investigate the seasonality (seasonal variability of the epidemic)
Investigate the degree of association of dengue epidemics with ENSO events
Examine, briefly, some adaptation options.
Previous studies/events that influenced the selected approaches:
• Hales et al (1996), Poveda et al (2000), Gagnon et al (2001)
• Koopman et al (1991), Focks et al (1995)
• Ropelewski and Halpart (1996), Chen et al (1997), Malmgren et al (1998), Taylor (1999), Chen and Taylor (2001)
• AIACC V & A workshop, Trieste, Italy, June 2002
DATA & METHODOLOGY• The data acquired for the CCID project by the CSGM provided the bulk of the
climate data: Temperature (maximum, minimum and mean) and Precipitation, daily or monthly values
• CAREC provided the epidemiology data in the form of reported dengue cases and vector indices, annual, 4-week period, monthly, quarterly values. More attention was focused on reported dengue cases
• Data analysis: Time series analysis of annual reported cases and their rates of change, mean temperature, mean precipitation, temperature and precipitation anomalies; Study of the climatology of temperature, precipitation, and reported cases; Performance of statistical significance tests (Fisher’s exact test using suitable contingency tables) for observed correlations, wherever applicable.
• ENSO year (El Niño & La Niña) classification: NOAA-CDC MEI index {EN: 1982/83, 1986/87, 1992/93, 1997/98. LN: 1988/89, 1998+/00} Supplementary: 1994/95 • Main study period: 1980 to 2001
El Niño La NiñaMEI
Caribbean- Reported Cases
-6000
-4000
-2000
0
2000
4000
6000
8000
10000
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Annual totals
Rate of change
CAREC 4-WEEK ACCUMULATION (1995-2001)
0
1000
2000
3000
4000
5000
6000
1 2 3 4 5 6 7 8 9 10 11 12 13
4- Week period
Acc
um
ula
ted
rep
ort
ed c
ases
Average 4-weekperiod accumulation
Jn D
En+1En
T & T Annual Reported Cases and Rate of Increase
-3000
-2000
-1000
0
1000
2000
3000
4000
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Year
Annual Totals
Rate of Increase
Some Case Studies: T & T
Temp Anomalies (Piarco)
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
Temp Anomalies
Time Series of Temperature Anomalies: 1980 to 2001
Rainfall Anomalies (Piarco)
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
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
19
98
20
00
Rainfall Anomalies
Time Series of Rainfall Anomalies: 1970 to 2001
-100
100
300
500
700
900
1100
4-Week period reported cases in T & T: 1995 to 1999
4-Week period rainfall: 1995 to 1999
Time Series of Reported Cases & Rainfall (mm) in 4-Week Periods
95Jan 96Jan 97Jan 98Jan 99Jan 99Dec
MONTHLY VARIATION OF MEAN T (T & T: 1995-1999)
25.5
26
26.5
27
27.5
28
28.5
29
29.5
0 2 4 6 8 10 12 14MONTH
ME
AN
T in
oC
1995
1996
1997
1998
1999
Average House Index: 1996-2001
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Average Index: 1996-2001
A sample of Monthly Variability in House Index: Port of Spain City Co-operation
Some Results For JamaicaMONTHLY VARIATION OF RAINFALL (JAMAICA: 1993,
1995, 1997 & 1998)
-50
0
50
100
150
200
250
300
350
0 2 4 6 8 10 12 14
MONTH
RA
INF
AL
L i
n m
m
1997
1998
1995
1993
4-WEEK VARIATION OF CASES (JAMAICA: 1995, 1997, 1998 and 2001)
-100
0
100
200
300
400
500
600
700
800
900
0 5 10 15 20
4-WEEK PERIODS
RE
PO
RT
ED
CA
SE
S
1995: cases 1778
1997: cases 17
1998: cases 1255
2001: cases 39
Monthly Mean Temperature in C
24
25
26
27
28
29
30
31
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1993
1995
1997
1998
Reported Cases
Jn D
-2000
-1500
-1000
-500
0
500
1000
1500
2000
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Totals
Rate of incearse
4-WEEK VARIATION OF CASES (SURINAM:1995-2001)
-50
0
50
100
150
200
250
300
0 5 10 15 20
4-WEEK PERIODS
RE
PO
RTE
D C
AS
ES
1995: cases 129
1996: cases 677
1997: cases 90
1998: cases148
1999: cases 695
2000: cases 1205
2001: cases 760
4-WEEK VARIATION OF CASES (BAHAMAS: 1998)
-50
0
50
100
150
200
250
300
0 5 10 15 20
4-WEEK PERIODSR
EP
OR
TE
D C
AS
ES
1998: cases 336
D
DAu
SE N
Statistical Significance Level of ENSO Associations (* with 1994/95)
REGION El Niño
(N)
El Niño+1
(N+1)
N &N+1 La Niña
Caribbean
(8 Epeds)
88% 64% 92% **
(94%)*
-
T & T
(8 Epeds)
64% 88% 92% **
(80%)*
-
Barbados
(6 Epeds)
74% 74% 90% **
(95%)*
-
Jamaica
(5 Epeds)
53% 80%
(90%)*
79%
(89%)*
-
Results Summary In general, across the region, 19-nineties are observed to be more prone to the epidemic than 19-eighties. There is a periodicity of about 4 to 3 years in the 19-eighties and 3 to 2 years in the 19-nineties with more frequent outbursts. May be due to the fact that, in the 19-ninetees, temperatures were warmer and rainfall was less abundant, for example, as indicated by the anomalies for T & T. These conditions reduce the incubation period and increase the disease transmission rate.
The epidemic shows a well defined seasonality over the region. It occurs in the latter half of the year. The warmer and drier conditions (less abundance in rainfall) appear to trigger the epidemic with the onset of the rainfall, which subsequently & speedily develops. Longer spells of less abundant rainfall and warmer temperatures appear to enhance the probability of the epidemic.
There is a tendency for the spread to get narrower, from south east to north in the region. Perhaps, this may be due to the warmer & moist climate (tropical warm moist climate, more suitable for vector breeding and propagation) that persists in the SE, in contrast to the tropical climate with seasonal rainfall in the central and the nothern part.
The periodicity seen roughly agrees with the periodicity of ENSOs
SYNOPSIS Significance: The work discussed forms a part of the
retrospective component of the AIACC Dengue Project-SIS06. May be stated that, exciting features of the dengue epidemic & evidence of climate influence are seen. Namely;
(i) Periodicity & Seasonality.
(ii) The influence of the temperature and rainfall.
(Iii) Significant association with El Niño episodes (N & N+1 together).
We cannot change the Climate Change!
But adaptation measures could be provided to minimize the impacts
Impacts on Vector
A: Temperature Increase: Increase in numbers, increased frequency of blood meals, and expanded spatial distribution including highland areas. Also increases rate of extrinsic incubation( period lowers)
B: Precipitation: Either increase or decrease in larval habitats (very heavy rainfall could flush out habitats). Humidity increase may increase survival. Flooding, and hence stagnant water, could increase small habitats.
Droughts could result in possible decrease in larval habitats, but storage of water increases
COMMON SCENARIOS
(POTENTIAL BREEDING PLACES)
Possible Adaptation Options
Intensify public awareness through propaganda and education
Devise early warning systems coupled to climate forecasts
Make the public health sector more efficient and effective on issues concerning vector borne diseases (vector control, surveillance, health education)
If socioeconomic (SE) conditions, attitudes and practices are contributing factors, make attempts to improve/change them.
“Public Awareness & Education”
One of the best Adaptation Options:
Examples of Adaptation: Venice Trip in June 2002
CONSTRAINTS
Time series of dengue data spanned only 20 years, which limited the number of ENSO episodes to 4. The influence (+ve or –ve) introduced by migration activities taking place, spraying and serotypes/dengue types have not been considered. Need to complete a socioeconomic & a KAP survey, which presumably will occur soon.