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EARLY WARNING SYSTEM FOR DENGUEHEMORRHAGIC FEVER (DHF) EPIDEMICS IN

MAKASSAR*

Halmar Halide 1 , Rais 1 and PeterRidd 2

1 Physics Dept. FMIPA Unhas, Makassar 90245, Indonesia2School of Engineering and Physical Sciences,

James Cook University, Townsville, 4811 Australia*Oral presentation at the 54 Th Anniversary of UniversitasHasanuddin,16-17 th August 2010, Makassar - Indonesia.

The paper is then published in Jurnal Matematika dan SainsITB vol 16 (1): pp. 26-34 year 2011 (it is free on theinternet)


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Introduction:What are the problems?

DHF is escalating and spreading

DHF is a costly disease, i.e. US$ 139 per case (4) almost twice the minimum monthly salary of US$79 (5)

DHF has no vaccine available (6)

DHF mosquito-control fails to prevent outbreaks


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Figure 1. DH/DHF cases around theworld from 1955-1999 (1))

Figure 2. DHF cases and places affectedin Indonesia from 1968-2003 (2)

DHF is escalating and spreading

Figure 3. Projected Dengue Fever spreads under warmer temperature.

Estimated population at risk in year 1990(A) and 2085 (B) (3).


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Figure 4. Fogging activity (depicted in arrows) has no-clear effecton preventing DHF outbreaks (2)

DHF mosquito-control fails to prevent outbreaks


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How should we response? be prepared for any outbreak by inventing atimely and accurate early warning system

Systems available at present require:

extensive data (7) and high computingpower (3).


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Aims of this study:To develop an early warning system for accurately predicting DHF outbreaks atsufficient lead times.

Here an outbreak is defined when thenumber of cases above 50% quartile (8)


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Data and Model

Model formulation : Multiple linear regression.

Predictant: present DHF case;Predictors: past meteo-climate dataand DHF cases.Predictors are selected using astepwise method (at significantlevel of 0.95).

Model cross-validation : Leaveone-out

Model skill : Peirce scoremeasures (9),(10)

SPSS, MATLAB and Visual Basic

packages for computation .Figure 5. Meteorological, climatological

DHF cases in Makassar (11) .


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1999 2000 2001 2002 2003 2004 2005 2006-50

0

50

100

150

200

250

300

350

Year

D H F c a s e s

data

P1P6

P12

Figure 6. Out-of-sample predictions(11)

Prediction Skill: time series


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Figure 7. Prediction skill using peirce skill score for both

the regression (o) and no-skill models (x)(11)

Prediction Skill: skill measures

0 2 4 6 8 10 12

-0.5

0

0.5

1

Leadtime(months)

P e i r c e

S c o r e


10/12Figure 8. Three months ahead DHF early warning system (12)

Early warning system


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Conclusion:

An early warning system has been developedusing a simple model. The model is able topredict DHF outbreaks up to six month inadvance using past data. The system is a useful

tool for managing DHF epidemics(13)

.

Acknowledgement:We thank Mr. M. A. Abdi, Mr. B. Hargiyono, Dr. H. Ishak,and the CPC-NCEP-NOAA and JAMSTEC for data used.


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References:(1) D. Gubler, 2002 Trends Microbiol 10: 100-103.(2) Ndoen et al ., 2004http://www.pitt.edu/~super1/

lecture/lec17391/index.htm(3) Hales et al ., 2002. Lancet 360: 830-834.(4) Shepard et al., 2004 Vaccine 42: 1275-1280(5) D. Widarti, 2006http://www.ilo.org/public/english/

region/asro/jakarta/download/wagediah.pdf (6) Chadee et al ., 2005 Trop Med Int Health 10:748-754.

(7) Kuhn et al ., 2005. WHO report.(8). Nisalak et al ., 2003 Am J. Trop Med Hyg 68:191-202.(9) D.S. Wilks, 1995. Statistical methods in the atmospheric

sciences . Academic Press, San Diego.(10) D. B. Stephenson, 2000. Weather Forecast 15: 221-232.(11) Halide, H. and P. Ridd, 2008.. Int. J.Env. Health Res.

18 (4): 253-265.(12) Rais, 2010. Sistem Peringatan Dini DBD (kasus kota

Makassar), Thesis S1, Jur. Fisika FMIPA Unhas.(13) Halide, H., 2010. In: Handbook of Disease outbreaks:

Prevention, Detection and Control (Editors: A. Holmgrenand G. Borg), Nova Publisher, New York.

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