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1
CLIMATE VARIABILITY AND ITS IMPACT ON DENGUE AND
MALARIA IN MEXICO Hurtado-Díaz M1,
Riojas-Rodríguez H1, Rothenberg SJ1,
Cifuentes-García E1, Gomez-Dantés H2 1 National
Institute of Public Health, 2 Mexican Institute
of Social Security
Malarias data in Pantelhó were from 1990 to
1998. There were 785 cases, with a mean rate of
51.6 per 100,000 inhabitants. The mean number of
cases per month is 7.2 with a maximum of 42. The
rate shows a diminishing trend during the period
and has two peaks in June 1991 and July 1998. We
do not see any relationship with the different
ENSO indexes. In the municipality of Tapachula
2396 cases of malaria were recorded during the
period 1998-2000. The average number of cases per
month was 47 and the average rate was 17.3 per
100 thousand inhabitants. The highest number of
cases occurred in June, 1988 (444 cases).
Table 2 Crude association between climate variables and mlaria cases (ln) Pantelhó, Chiapas Table 2 Crude association between climate variables and mlaria cases (ln) Pantelhó, Chiapas Table 2 Crude association between climate variables and mlaria cases (ln) Pantelhó, Chiapas
Variable Coefficient p value
Pluvial Precipitation 0.0018 0.073
Precipitation (1 month lag) 0.0015 0.12
El Niño 3 -0.04 0.56
There is evidence that annual and decennial
climate variation has a direct influence on
vector-borne parasitic diseases.1 2 3 4 5 In
Mexico, exist papers on the influence of climate
factors 6 7 8 9 10 however no papers were found
on climate variability and its influence on
health. In this project we are going to examine
the relation between climatic variables
(temperature and precipitation), El Niño
Southern Oscillation (ENSO) indexes and incidence
of malaria and dengue in Mexico, to obtain the
methodology for analyzing the complex relations
between climate factors and human diseases.
We selected the states of Veracruz (Veracruz Port
and San Andres Tuxtla) for dengue and Chiapas
(Pantelhó and Suchiate) for malaria, based on
the number of cases. To construct the databases,
we request from the surveillance system on vector
borne diseases, the number of monthly cases of
dengue and malaria by municipality and from
meteorological stations near to municipalities of
study, monthly data of temperature and
precipitation. We used exploratory, univariated
and bivariated analysis (cross correlations) to
observe possible links between diseases, climatic
variables and ENSO. To explore the variables that
explain the variation in the number of cases, we
created a linear regression model taking the
natural logarithm of cases per month as the
dependent variable
Malaria cases, Precipitation and ENSO
IndexSuchiate 1998-2002
Malaria cases, Precipitation and ENSO
IndexTapachula 1998-2000
Cases of Dengue and Precipitation by
MonthVeracruz 1995-2002
In Veracruz, 3939 cases occurred in a period of
91 months (1995-2002. There were important spikes
in September of 1996 (663 cases) and October of
1997 (508 cases). We found a significant
association (p lt 0.05) between number of cases of
dengue and precipitation of the previous month
and the number of cases of dengue with the ENSO
variables, although the coefficient is positive,
it is not significant. In San Andrés Tuxtla we
have been able to establish the association
between precipitation and the increase of cases.
This occurs annually with peaks in certain
months that are potentially associated with the
presence of ENSO, as we have observed this trend.
We already collected climatic and health data at
the community level with weekly frequency. We
also compiled data from the year 2002-2003,
related to the most recent El Niño event, in
order to have two events in our data series and
draw inferences from such series. The
statistical methods that we have used are
relatively simple, but at this time we are using
autoregressive integrated moving average (ARIMA)
models to analyze the data with greater
precision. These are preliminary results and we
are incorporating in the this stage of the
analysis variables of migration, social
vulnerability and data from vector control
program, to know the effect that has the climate
variability in the incidence of these diseases.
El Niño Index, Pluvial Precipitation and Dengue
Cases Veracruz 1995-2002
1 Bouma, MJ, Dye C., 1997. Cycles of Malaria
associated with El Niño in Venezuela. JAMA, 178
(21) 1772-1774. 2 Bouma, MP., Poveda, GR,
Chavasse D, Quiñones M, Cox J, Patz J. Predicting
high-risk years for malaria in Colombia using
parameters of El Niño Southern Oscillation. Tro.
Med. Int Health 1997 Dec 2 (12)1122-7 3
Sánchez Tarrago N. (editor) El fenómeno
climatológico El Niño y sus efectos en la salud.
Reporte técnico de vigilancianidad de análisis y
tendencias en salud, Ministerio de Salud Pública,
La Habana Cuba, Vol. 3., no. 3, April 27, 1998
ISSN 1028-4362. 4 http//www.infomed.sld.cu/insti
tuciones/uats/uats/RTV/rtv0398.htm 5 Proveda GJ.
Evidencias de la asociación entre brotes
epidémicos de malaria en Colombia y el fenómeno
El Niño-Oscilación Sur. Revista de la Academia
Colombiana de Ciencias Exactas, Físicas y
Naturales ISSN 0370-3908, Vol. XXI (81) pp.
409-419, November 1997. 6 Rodríguez MH,
Gonzales-Cerón L., Hernández JE, ENTEL JA,
Villareal C. Kain KC, Wirtz RA, Different
prevalences of plasmodium vivax phenotypes VK210
and VK 247 associated with the distribution of
Anopheles albimanus and Anopheles
pseudopunctipennis in Mexico. Am J. Trop Med Hyg
2000, Jan 62 (1) 122-7 7 Herrera-Basto E,
Prevost DR, Zarate ML, Silva JL, Sepúlveda Amor
J. First reported outbreak of classical dengue
fever at 1,700 meters above sea level in Guerrero
State, Mexico Jun 1988. Am J. Trop Med Hyg 1992
Jun 46 (6) 649-53. 8 Rodríguez AD, Rodríguez
MH, Hernández JE, Dister SW, Beck LR, Rejmankova
E, Roberts DR. Landscape surrounding human
settlements and Anopheles albimanus (Diptera
Culicidae) abundance in Southern Chiapas, Mexico.
J. Med Entomol 1996, 33 (1) 39-48. 9
Fernández-Salas I, Roberts DR. Rodríguez MH,
Marina-Fernández CF Fernández-Salas. Bionomics of
larval populations of Anopheles
pseudopunctipennis in the Tapachula foothills
area, southern Mexico. J. Am Most Control Assoc
1994 Dec 10 (4) 477-86. 10 Koopman JS,
Prevots DR, Vca marin MA et al. Determinants and
predictors of dengue infection in Mexico. Am J
Epidemiol 1991 Jun 1 133 (11) 1168-78
Table 1 Table 1 Table 1 Table 1 Table 1
Crude association between climate variables and dengue cases (ln) Crude association between climate variables and dengue cases (ln) Crude association between climate variables and dengue cases (ln) Crude association between climate variables and dengue cases (ln) Crude association between climate variables and dengue cases (ln)
Veracruz Port and San Andrés Tuxtla, Veracruz Veracruz Port and San Andrés Tuxtla, Veracruz Veracruz Port and San Andrés Tuxtla, Veracruz Veracruz Port and San Andrés Tuxtla, Veracruz Veracruz Port and San Andrés Tuxtla, Veracruz
Variable Veracruz Veracruz San Andrés Tuxtla San Andrés Tuxtla
Variable Coefficient p value Coefficient p value
Precipitation 2 0.04 0.0016 0.07
Precipitation (1 month lag) 0.0048 0.0001 0.02 0.03
Mixed index 0.074 0.622 ----- -----
Mixed index (3 months lag) 0.2 0.2 ----- -----
El Niño 3 -0.23 0.02 0.06 0.7
El Niño 3 (3 months lag) 0.17 0.1 0.0002 0.7
This work was partially granted by Inter-American
Institute for Global Change Research. We would
like to give thanks also to the personnel of
Secretary of Health in Veracruz and Chiapas for
its cooperation.