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CLIMATE VARIABILITY AND ITS IMPACT ON DENGUE AND MALARIA IN MEXICO

Dengue Cases. Pluvial Precipitation. Malaria Cases. Pluvial Precipitation. Malaria cases. Pluvial Precipitation. Mixed Index. Mixed Index. Mixed Index. January 1995. July 2002. March 2001. Months. January 1998. January 1998. December 2003. Months. Months.

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CLIMATE VARIABILITY AND ITS IMPACT ON DENGUE AND MALARIA IN MEXICO

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  1. Dengue Cases Pluvial Precipitation Malaria Cases Pluvial Precipitation Malaria cases Pluvial Precipitation Mixed Index Mixed Index Mixed Index January 1995 July 2002 March 2001 Months January 1998 January 1998 December 2003 Months Months 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 Malaria’s 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). 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 < 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/instituciones/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 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.

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