Modelling the impact of the El Nino Southern Oscillation (ENSO) on the dynamics of Dengue outbreaks in Argentina between 2018 and 2024.
- 1National Research Council of Argentina
Abstract
BackgroundDengue fever has become an epidemiological concern worldwide, with 531,617 cases reported in Argentina during the 2023-2024 season. The El Nino- Southern Oscillation (ENSO) phenomenon has been linked to changes in dengue dynamics. This study assessed the relationships among ENSO, local climatic variables, and dengue outbreaks in Argentina from 2018 to 2024.
MethodsA nationwide spatiotemporal analysis was conducted using dengue cases and monthly mean temperature, relative humidity, and rainfall. The Southern Oscillation Index (SOI) was used as the ENSO indicator (El Nino phase=< -0.5, neutral phase= -0.5 to 0.5, and La Nina phase= > 0.5). We fitted Hierarchical Bayesian models with Integrated Nested Laplace Approximation (INLA). A Negative Binomial distribution of dengue cases was used to account for overdispersion. Spatial dependence was modeled by using the Besag-York-Mollie 2 (BYM2) structure, adjusted for population.
ResultsThe final model explained 53.7% of the variation in Argentinas departmental monthly dengue cases during the study period. Exposure-response curves of posterior probability and 95% credible intervals suggested that dengue risk increased when monthly mean temperatures were between 20{degrees} and 30{degrees} Celsius during the El Nino or neutral phase, with less consistent effects during the La Nina phase. Humidity >50% was associated with increased dengue risk during the La Nina phase, with less steep or absent associations during El Nino or neutral phases. Negative SOI scores were associated with an increased risk of dengue after controlling for the covariates.
ConclusionDengue outbreaks in Argentina were independently associated with temperatures between 20 and 30 {degrees}C during the El Nino and neutral phases, humidity > 50% during the La Nina phase, and the El Nino phase of the ENSO. Incorporating ENSO indices into predictive models could enhance early warning systems and timely public health interventions in Argentina.
HIGHLIGHTSO_LIThis study linked the El Nino phenomenon to Dengue fever outbreaks in Argentina. C_LIO_LIOther predictors of increased risk were monthly mean temperatures between 20{degrees} and 30{degrees} Celsius during the El Nino and neutral phases, and humidity > 50% during the La Nina phase. C_LIO_LIThere was a high degree of spatial residual variance, not accounted for by the factors considered in the model, in dengue risk, which was increased in some northern and southern provinces of Argentina. C_LI
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BibTeX
@misc{lodigiani2026modelling,
title = {{Modelling the impact of the El Nino Southern Oscillation (ENSO) on the dynamics of Dengue outbreaks in Argentina between 2018 and 2024.}},
author = {C. Lodigiani and A. Enet and M. Arrua and G. Lakkis and L. Moreno Lell and C. Panzarella and S. Otero and O. Bellizzi and M. Bullo and S. Perez-Lloret},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.03.26362163},
url = {https://www.medrxiv.org/content/10.64898/2026.09.03.26362163v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Modelling the impact of the El Nino Southern Oscillation (ENSO) on the dynamics of Dengue outbreaks in Argentina between 2018 and 2024.
AU - C. Lodigiani
AU - A. Enet
AU - M. Arrua
AU - G. Lakkis
AU - L. Moreno Lell
AU - C. Panzarella
AU - S. Otero
AU - O. Bellizzi
AU - M. Bullo
AU - S. Perez-Lloret
PY - 2026
DA - 2026/09/03
PB - medRxiv
DO - 10.64898/2026.09.03.26362163
UR - https://www.medrxiv.org/content/10.64898/2026.09.03.26362163v1
AB - BackgroundDengue fever has become an epidemiological concern worldwide, with 531,617 cases reported in Argentina during the 2023-2024 season. The El Nino- Southern Oscillation (ENSO) phenomenon has been linked to changes in dengue dynamics. This study assessed the relationships among ENSO, local climatic variables, and dengue outbreaks in Argentina from 2018 to 2024. MethodsA nationwide spatiotemporal analysis was conducted using dengue cases and monthly mean temperature, relative humidity, and rainfall. The Southern Oscillation Index (SOI) was used as the ENSO indicator (El Nino phase=< -0.5, neutral phase= -0.5 to 0.5, and La Nina phase= > 0.5). We fitted Hierarchical Bayesian models with Integrated Nested Laplace Approximation (INLA). A Negative Binomial distribution of dengue cases was used to account for overdispersion. Spatial dependence was modeled by using the Besag-York-Mollie 2 (BYM2) structure, adjusted for population. ResultsThe final model explained 53.7% of the variation in Argentinas departmental monthly dengue cases during the study period. Exposure-response curves of posterior probability and 95% credible intervals suggested that dengue risk increased when monthly mean temperatures were between 20{degrees} and 30{degrees} Celsius during the El Nino or neutral phase, with less consistent effects during the La Nina phase. Humidity >50% was associated with increased dengue risk during the La Nina phase, with less steep or absent associations during El Nino or neutral phases. Negative SOI scores were associated with an increased risk of dengue after controlling for the covariates. ConclusionDengue outbreaks in Argentina were independently associated with temperatures between 20 and 30 {degrees}C during the El Nino and neutral phases, humidity > 50% during the La Nina phase, and the El Nino phase of the ENSO. Incorporating ENSO indices into predictive models could enhance early warning systems and timely public health interventions in Argentina. HIGHLIGHTSO_LIThis study linked the El Nino phenomenon to Dengue fever outbreaks in Argentina. C_LIO_LIOther predictors of increased risk were monthly mean temperatures between 20{degrees} and 30{degrees} Celsius during the El Nino and neutral phases, and humidity > 50% during the La Nina phase. C_LIO_LIThere was a high degree of spatial residual variance, not accounted for by the factors considered in the model, in dengue risk, which was increased in some northern and southern provinces of Argentina. C_LI
ER -