An Assessment of the Impact of An Assessment of the Impact of Climate Features on Dengue Fever Climate Features on Dengue Fever and its Vectors in Five Caribbean and its Vectors in Five Caribbean

Countries (AIACC Project)Countries (AIACC Project)

ByByS C Rawlins PhD, S C Rawlins PhD, Emeritus ScientistEmeritus Scientist

c/o Caribbean Epidemiology Centre, c/o Caribbean Epidemiology Centre, TrinidadTrinidad

IntroductionIntroduction

In the last two decades there has been In the last two decades there has been an unprecedented increase in the an unprecedented increase in the occurrence and severity of dengue occurrence and severity of dengue fever (DF) in Caribbean countries. fever (DF) in Caribbean countries.

Any tool useful to predicting outbreaks Any tool useful to predicting outbreaks and implementing enhanced and implementing enhanced prevention strategies – adaptation – prevention strategies – adaptation – would be most welcome. would be most welcome.

Introduction contd.Introduction contd.

Dengue in the Caribbean and El Nino years and year after an El Nino - El Nino +1

El Nino

El Nino + 1

Caribbean CountriesCaribbean Countries

Introduction Contd.Introduction Contd.

Already, we have examined the impact of Already, we have examined the impact of climate change features especially climate change features especially warming conditions on retrospective warming conditions on retrospective dengue fever data in the Caribbean dengue fever data in the Caribbean region.region.

We have shown some association in the We have shown some association in the increased occurrence of DF and warming increased occurrence of DF and warming periods in some Caribbean Epidemiology periods in some Caribbean Epidemiology Centre (CAREC) Member Countries (CMCs) Centre (CAREC) Member Countries (CMCs)

Caribbean countriesCaribbean countries

Fig. 2 Seasonal variation of dengue Fever Cases for 3 Epidemic Years in Selected CAREC Member Countries

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Prospective Studies, 2002-2004 Prospective Studies, 2002-2004

. In this present study we are examining . In this present study we are examining prospectively the occurrence of DF and prospectively the occurrence of DF and population features of the vector with population features of the vector with varying climate features such as varying climate features such as temperature and precipitation.temperature and precipitation.

Here, we are examining the patterns of Here, we are examining the patterns of reported dengue fever cases in the reported dengue fever cases in the Caribbean region – mainly CMCs with a Caribbean region – mainly CMCs with a population of just over 6 - 7 millions – to population of just over 6 - 7 millions – to demonstrate any climate-related patterns demonstrate any climate-related patterns of disease presentation over 2002 - 2004 of disease presentation over 2002 - 2004

Design and MethodsDesign and Methods

Data on reported monthly dengue fever Data on reported monthly dengue fever (DF) cases, vector – (DF) cases, vector – Aedes aegyptiAedes aegypti – – indices, and climatic indicators were indices, and climatic indicators were collected prospectively for a 12 month collected prospectively for a 12 month period beginning early 2003 in 5 period beginning early 2003 in 5 Caribbean countriesCaribbean countries

Jamaica, Trinidad and Tobago (T&T), Jamaica, Trinidad and Tobago (T&T), Barbados, St Vincent and the Grenadines Barbados, St Vincent and the Grenadines (SVG) and St Kitts/Nevis (SKN).(SVG) and St Kitts/Nevis (SKN).

Data were analyzed by ANOVA for Data were analyzed by ANOVA for evidence of climate impact on DF cases evidence of climate impact on DF cases and vector indices.and vector indices.

St Vincent ResultsSt Vincent Results

SVGSVG data showed minor fluctuations data showed minor fluctuations of vector breteau (BIs) and house of vector breteau (BIs) and house indices (HIs) with precipitation indices (HIs) with precipitation

Dryer periods coincided with low Dryer periods coincided with low vector HIs of 9-22%. In wet periods, vector HIs of 9-22%. In wet periods, both indices were higher – HIs (17-both indices were higher – HIs (17-72%) and BIs (31-55). 72%) and BIs (31-55).

Temperature varied slightly (23-Temperature varied slightly (23-32˚C) throughout the year.32˚C) throughout the year.

St Kitts/Nevis ResultsSt Kitts/Nevis Results

SKN SKN vector data showed a bimodal vector data showed a bimodal pattern with peaks of HIs and BIs in pattern with peaks of HIs and BIs in May-June and October-December, May-June and October-December, the latter associated with significant the latter associated with significant precipitation.precipitation.

Mean monthly temperatures only Mean monthly temperatures only varied between 26 -29˚C (Fig. 4).varied between 26 -29˚C (Fig. 4).

Trinidad and Tobago Trinidad and Tobago T&T T&T data for 2002 and 2003 showed data for 2002 and 2003 showed

distinct dry and wet seasonal patterns distinct dry and wet seasonal patterns In 2002 dry periods (January-May), there In 2002 dry periods (January-May), there

were low BIs (21– 29), and mean monthly were low BIs (21– 29), and mean monthly DF cases of 290.4. DF cases of 290.4.

Increases in BIs (32-44), (P=0.000) and Increases in BIs (32-44), (P=0.000) and mean monthly DF cases (695/month) mean monthly DF cases (695/month) coincided with the wetter period (June – coincided with the wetter period (June – December). December).

Temperature varied slightly 22-25˚C (min) Temperature varied slightly 22-25˚C (min) to 31 -33˚C (max) for the period. to 31 -33˚C (max) for the period.

Rainfall, Temperature, Breteau index and Dengue cases, Trinidad (2002-2004.

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Conclusions 1Conclusions 1

Patterns from SKN, SVG and T&T Patterns from SKN, SVG and T&T data discerned a correlation of data discerned a correlation of seasonal effect on BIs and in T&T on seasonal effect on BIs and in T&T on DF transmission DF transmission

. Temperature variations did not . Temperature variations did not seem to be significant, but may have seem to be significant, but may have affected the onset of precipitation affected the onset of precipitation and in turn, vector production, an and in turn, vector production, an increase in indices and DF cases increase in indices and DF cases

Conclusions 2Conclusions 2

The data confirm the usefulness of The data confirm the usefulness of recognizing the wet season as a risk recognizing the wet season as a risk factor for DF transmission in the factor for DF transmission in the region region

Utilising this knowledge for Utilising this knowledge for preparation of early warning systems preparation of early warning systems for DF prevention will be vital for DF prevention will be vital