Climate variability impacts on dengue and vulnerability in the caribbean
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CLIMATE VARIABILITY IMPACTS ON DENGUE AND VULNERABILITY IN THE CARIBBEAN Dharmaratne Amarakoon ** , Anthony Chen, Roxann Stennett C limate S tudies G roup M ona , UWI , Jamaica Samuel C. Rawlins, David Chadee UWI, St. Augustine Campus & Ministry of Health, Trinidad

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CLIMATE VARIABILITY IMPACTS ON DENGUE AND VULNERABILITY IN THE CARIBBEAN

Dharmaratne Amarakoon**, Anthony Chen, Roxann Stennett

ClimateStudiesGroupMona, UWI, Jamaica

Samuel C. Rawlins, David Chadee

UWI, St. Augustine Campus & Ministry of Health, Trinidad

2nd AIACC REGIONAL MEETING, Buenos Aires, Argentina: August 24-27, 2004


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QUESTIONS THAT ARE BEING ANSWERED THE CARIBBEAN

  • What was the geographical distribution and the nature of dengue patterns in the Caribbean?

  • What was the nature of the climate variability in the Caribbean over the last few decades?

  • What are the factors that may impact Dengue epidemics, revealed from other studies?

  • What were the impacts of climate variability on DENGUE seen in the Caribbean?

  • What communities are expected to be potentially vulnerable and possible reasons for the vulnerability?

  • How could the results from this impact study be utilized to reduce vulnerability?


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DATA THE CARIBBEAN & 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; Studyof the climatology of temperature, precipitation, and reported cases; Performance of statistical significance tests for observed correlations and multiple linear regression, wherever applicable.

  • ENSO year (El Niño & La Niña) classification: NOAA-CDCMEI index and NCEP/CPC Quarterly SST index

    {EN: 1982/83, 1986/87, 1992/93, 1997/98. LN: 1988/89, 1998+/00}

    Supplementary: 1994/95

  • Main study period: 1980 to 2001


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THE CARIBBEAN THE CARIBBEAN

Incidence of Dengue


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Figure b THE CARIBBEAN

Jn

D

Figure a

En

En+1



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Seasonality of the Epidemics and Relation to THE CARIBBEAN

Climate Parameters

___________________________________________________________

Country Year Epidemic Peak Temperature Precipitation

Peak Peak

___________________________________________________________

T and T1995 August (weak) Apr. to Nov Jun. to Sep.

1996 September (strong) Apr. to Dec. May to Oct.

1997 December (strong) May to Dec. July and Nov.

1998 July to Sep. (strong) March to Nov. May to Sep.

1999 September (weak) Apr. to Dec. Jul. to Oct.

Barbados1995 October (strong) Apr. to Nov. Jul. to Oct.

1996 September (weak) Apr. to Nov. May to Nov.

1997 November (strong) Apr. to Nov. June to Nov.

1998 Aug. to Sep. (weak) Apr. to Oct. Jul. to Nov.

1999 November (weak) Apr. to Nov. Jun. to Nov.

_____________________________________________________________


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Recent analysis of Caribbean temperature by Peterson and Taylor et al (2002) show increasing trend


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Time Series of Rainfall and Temperature anomalies at Taylor et al (2002) show increasing trend

Piarco in Trinidad


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TIME SERIES ANALYSIS OF TEMPERATURE AND RAINFALL Taylor et al (2002) show increasing trend


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IMPACTS SEEN IN OTHER STUDIES Taylor et al (2002) show increasing trend

  • Hales et al.,(1996)- Association of upsurges of dengue in south pacific islands with ENSO events.

  • Gagnon et al.,(2001)- Statistically significant correlation (>90% confidence level) between dengue epidemics and El Nino events in French Guiana, Indonesia, Colombia and Surinam.

  • Poveda et al.,(2000)- Association of dengue peaks in Colombia during El Nino+1 years due to temperature increases and stagnant water collected for use during drought.

  • Campione-Piccardo et al.,(2003)-Monthly reports of dengue cases and virus isolates following the rainfall with a lag of two to three months, in Trinidad and Tobago.

  • Focks et al.,(1995)- Possibility of shortening of EIP (Extrinsic Incubation Period) at higher temperatures.

  • Koopman et al.,(1991)-Possibility of higher transmission rates of dengue at shorter incubation periods.

  • Wegbreit (1997)-Statistically significant relationship between temperature and dengue incidence rates in T & T, given a lag of about six months.



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LAG CORRELATION RESULTS ( AND RAINFALLMultiple Regression)


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[Wegbreit (1997)] AND RAINFALL



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RESULTS SUMMARY 2003: T & T

  • There is a well defined seasonality in the epidemics.

  • Probability of epidemics during El Nino and El Nino+1 years is high.

  • Both temperature and rainfall influence dengue outbreaks. Inter-annual variability is more associated with temperature (warming) and intra-annual variability is linked more to rainfall variability.


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SCENARIOS LEADING TO VULNERABILITY 2003: T & T(POTENTIAL BREEDING PLACES)


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POTENTIALLY VULNERABLE COMMUNITIES 2003: T & T

  • Having no knowledge of the disease and vulnerabilty.

  • With poor environmental conditions, including sanitation.

  • That are densely populated.

  • Without suitable water supplies (pipe borne water) which results in water collection in containers for longer periods of use.


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POSSIBLE REASONS FOR VULNERABILITY 2003: T & T

  • Lack of resources (funds, manpower).

  • Absence of active vector eradication programmes (no regular spraying, no use of bacteria like BT [Bacilus Thuringien]).

  • Absence of relevant education programmes on awareness.

  • Absence of procedures to monitor the communities and environmental conditions and upkeep.

  • Socio-economic status of communities (poverty, high population density).

  • Insufficient knowledge on vector dynamics and virus replication.


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How could the results from this impact study be utilized to reduce vulnerability?Develop early warning systems based on the seasonality, lag and future climate predictions, leading to effective programmes on public awareness and education.


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Best Option to reduce Vulerability reduce vulnerability:

“Public Awareness & Education”

CLEAN-UPORPAY-UP!


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Thank you reduce vulnerability


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