Claude FLAMAND Epidemiology unit, Institut Pasteur de la Guyane

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How climate is intertwined with dengue

fever outbreaks in French Guiana

8th July 2015 - Our Common Future under Climate Change

Increasing risks of epidemics, pandemics and diseases re-emergence in

a world in constant transition

- Climate and environmental changes

- Rapid population increase and human movements

- Evolution of pathogens (resistance to antibiotics, virulence, increase, …)

Climate changes on future distribution of vector-borne diseases are an

important area of epidemiologic research

Epidemics associated with Climate Changes

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Female mosquito

Aedes sp

Virus

Flavivirus

Human host

Climate

Environment

Human

Most important mosquito-borne viral disease

- Likely more important than malaria in terms of morbidity and economic impact

Acquired through the bite of Aedes aegypti

Tropical/Subtropical area

- 3.6 billion people at risk

- 390 million dengue infections per year

Four viral serotypes (DENV1 – DENV4)

Spectrum of clinical illness

- Influenza-like illness

- Fatal dengue hemorrhagic fever (DHF)

- Dengue shock syndrome (DSS)

No vaccine, no curative treatment

Vector control and treatment strategies

Dengue fever, an escalating public health concern

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Dengue fever in French Guiana

Circulation of 4 serotypes

Evolution from endemoepidemic to hyper-endemic state

4

0

200

400

600

800

1000

1200

0

50

100

150

200

250

300

1991-0

1

1991-0

7

1992-0

1

1992-0

7

1993-0

1

1993-0

7

1994-0

1

1994-0

7

1995-0

1

1995-0

7

1996-0

1

1996-0

7

1997-0

1

1997-0

7

1998-0

1

1998-0

7

1999-0

1

1999-0

7

2000-0

1

2000-0

7

2001-0

1

2001-0

7

2002-0

1

2002-0

7

2003-0

1

2003-0

7

2004-0

1

2004-0

7

2005-0

1

2005-0

7

2006-0

1

2006-0

7

2007-0

1

2007-0

7

2008-0

1

2008-0

7

2009-0

1

2009-0

7

2010-0

1

2010-0

7

2011-0

1

2011-0

7

2012-0

1

2012-0

7

2013-0

1

2013-0

7

To

tal n

um

ber o

f cases

Nu

mb

er o

f id

en

tifi

ed

sero

types

DEN-1 DEN-2 DEN-3 DEN-4 Biologically confirmed cases

Source : CNR arbovirus IPG, Cire Antilles-Guyane

2006 Outbreak (DENV2)

16 200 Clinical cases /204 hosp.

13% DHF, 4 deaths

2009 Outbreak (DENV-1, DENV-4)

13 900 CC/ 241 hosp., 1% DHF, 2 deaths

2010 : DENV-4, DENV-1

9 400 clinical cases

114 hosp., 2% DHF, 1 death

2012-2013 Outbreak (DENV2)

13 240 CC, 689 hosp (12%SD)

6 deaths

Motives and objectives

From outbreak detection to prediction

Relationship between climate and DF

- Higher occurrence of dengue in Nino years in America

- Relationship identified in FG

No climate based model for early warning system

Outbreak occurrence drivers remains poorly understood

- Niño conditions can be used as a proxi for epidemic risk ?

- Role of induced large scale atmospheric circulation modifications ?

- Impact of regional impacts (e.g. RR, Temp. ) on DF occurence ?

Investigate the impact of climate on DF outbreaks

Evaluate the potential of climate to forecast DF outbreaks

Ferreira, 2014

Gagnon, 2001

Type Source Period Time scale Spatial scale Parameters

Dengue Fever

cases INVS 1991 – 2013 Monthly French Guiana

Confirmed

cases

Gridded

atmospheric

reanalysis

ECMWF ERA-

INTERIM 1990 – 2013 6 h

Global

(0.75° x 0.75°)

Pressure

Wind speed

SST

Humidity

Meteorological

observations Meteo France 1990 – 2013 Daily Stations

Temperature

Rainfall

Humidity

Large scale

indexes NOAA 1990 - 2013 Monthly Oceans

Niño & NAO

indexes

EPI and NONEPI years ?

(tercile method on a 20-year

period)

Composite analysis

(EPI – NONEPI) over climate

parameters

Predictive Model

(Binomial logistic regression)

Data & Methods

Epidemiologic year-to-year variability and seasonnality

10 outbreaks : 1992, 1997, 1998, 2001, 2002, 2005, 2006, 2009, 2010, 2013

Annual monthly cycle showed strong seasonality

Composite analysis based on climate data

Primary assessment of climate impact on DF

July – August

Heating of the

Equatorial Pacific Sea

Surface Temperature

(SST) conditions

November

Increase in the

differences of

pressure conditions

between the Azores

High and the

Amazon Depression

Rainfall deficit over French Guiana during the dry

season preceeding the begining of outbreaks

Univariate Multivariate

Coef Std Err. p-val Coef Std Err. p-val

SLP difference Nov-1 index

By one hPa increase 0.30 0.15 0.047 0.42 0.20 0.030

SST Pacific Jul-1 Aug-1 index

By one °C increase 2.61 1.42 0.073 2.88 1.33 0.034

ROC scores

Towards a Predictive climate-based model

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Conclusion and Perspectives

First experience of forecasting DF outbreak in FG

- Good predictability obtained with a simple model

- Integrating the results in the risk assessment and preparedness

More evidences that climate becomes increasingly suitable for

dengue fever outbreaks but other factors to consider

- Increased travel, land use, vulnerability, mosquitoes resistance…

Need for multi data source simulations

- Using ensembles of disease models, climate models, population and

climate change scenarios

- To understand and anticipate indirect, long-term processes

- To evaluate the impact of mitigation strategies

Multi-disciplinary projects

- Entomologists , epidemiologists, human and animal health specialists,

climatologists-meteorologists, interface scientists, …)

www.pasteur-cayenne.fr 12

with the contribution of CNES, Aerology laboratory and Meteo France

Regional epidemiology unit of National Institute for Public Health Surveillance (Cire AG) Epi Surveillance

Medical entomology unit (IPG), IRD