The 2018–2019 weak El Niño: Predicting the risk of a dengue outbreak in Machala, Ecuador

Petrova, Desislava; Rodó, Xavier; Sippy, Rachel; Ballester, Joan; Méjía, Raúl; Beltrán-Ayala, Efraín; Borbor-Córdova, Mercy J.; Vallejo, García; Olmedo, Alfredo J.; Stewart-Ibarra, Anna M.; Lowe, Rachel

doi:10.1002/joc.6744

Cited by 11 publications

(9 citation statements)

References 37 publications

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“…However, the study area experienced near-normal rainfall in the minor season of 2014 and 2017. Petrova et al [64] described 2016 and 2018 as El Nino years. Perhaps, the climate variability driver, EL Nino, could cause wetness in 2016 and 2018.…”

Section: Standardized Anomaly Index For Minor Seasonal Rainfallmentioning

confidence: 99%

Variability of the Minor Season Rainfall over Southern Ghana (1981–2018)

Braimah

Asante

Ahiataku

et al. 2022

Advances in Meteorology

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The monitoring of rainfall variability over recent decades has become a necessity due to its devastating effects such as floods and droughts, which render humans vulnerable across different parts of the West African region. The current study seeks to provide a good understanding of variability within the minor rainfall season over southern Ghana by employing statistical tools to quantify variability in rainfall. Daily rainfall data from 1981 to 2018 for seventeen (17) synoptic weather stations across southern Ghana are used for this analysis. We perform trend and descriptive statistics of rainfall amount and extreme indices intending to identify the areas with the greatest variability in rainfall. Further, for five recent years (2014–2018), we do an interpolation of the ground station rainfall data and compute anomalies. We find increasing trends of rainfall in the minor rainy season for 16 out of the 17 stations, with rainfall increasing between 0.10 mm and 4.30 mm each season. For extreme rainfall indices, the 17 stations show nonsignificant trends of very wet and extremely wet days. We also find that the middle parts of Ghana have the highest rainfall amounts (262.7 mm/season–400.2 mm/season), while the East Coast has the lowest (125.2 mm/season–181.8 mm/season). Over the whole of southern Ghana, we find high variability in rainfall amount with the coefficient of variations (CV) between 25.3% and 70.8% and moderate to high variability in rainfall frequency (CV = 14.0%–48.8%). The results of rainfall anomalies show that the middle parts had an above-normal rainfall amount. In the same period, the transition areas experienced below-normal rainfall. Our finding of high variability in the minor rainfall season has implications for agricultural productivity in Ghana and countries in the West African region, which rely heavily on rain-fed agriculture. Hence, this study recommends more research to understand the causes of variability in the West African monsoon and how this will change in the region.

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Section: Standardized Anomaly Index For Minor Seasonal Rainfallmentioning

confidence: 99%

Variability of the Minor Season Rainfall over Southern Ghana (1981–2018)

Braimah

Asante

Ahiataku

et al. 2022

Advances in Meteorology

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“… 6 Recent research in Machala in southern coastal Ecuador has highlighted the need for integrated surveillance 13 and predictions in the same region have been discussed in the context of El Niño Southern Oscillation climatic phenomena. 36 37 In the present study, we estimated that 84% (95% CrI: 75%–91%) of individuals aged 0–60 years had been exposed to DENV in a tropical region of coastal Ecuador. However, DENV seroprevalence increased rapidly with age reaching 97% (95% CrI: 93%–99%) by 60 years, reflecting cumulative exposures over a 30-year period since DENV re-emerged in the region in the late 1980s.…”

Section: Discussionmentioning

confidence: 69%

Age-dependent seroprevalence of dengue and chikungunya: inference from a cross-sectional analysis in Esmeraldas Province in coastal Ecuador

et al. 2020

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ObjectivesThere are few population-based estimates for prevalence of past exposure to dengue and chikungunya viruses despite common epidemiological features. Here, we have developed a novel statistical method to study patterns of age-dependent prevalence of immunity in a population following exposures to two viruses which share similar epidemiological features including mode of transmission and induction of long-lasting immunity. This statistical technique accounted for sociodemographic characteristics associated with individuals and households.SettingsThe data consist of a representative sample from an ongoing longitudinal birth cohort set-up in a tropical district in coastal Ecuador (Esmeraldas).ParticipantsWe collected data and blood samples from 319 individuals belonging to 152 households following epidemics of the infections in 2015 in Latin America.Primary outcomePlasma was tested for the presence of specific IgG antibodies to dengue and chikungunya viruses by commercial ELISA and defined a bivariate binary outcome indicating individuals’ past exposure status to dengue and chikungunya (ie, presence/absence of IgG antibodies to dengue or chikungunya or both).ResultsDengue seroprevalence increased rapidly with age reaching 97% (95% credible interval (CrI): 93%–99%) by 60 years. Chikungunya seroprevalence peaked at 42% (95% CrI: 18%–66%) around 9 years of age and averaged 27% (95% CrI: 8.7%–51.6%) for all ages. Rural areas were more likely to be associated with dengue-only exposure while urban areas and shorter distance to the nearest household were associated with exposures to both. Women living in urban settings were more likely to be chikungunya seropositive while rural men were more likely to be dengue seropositive.ConclusionDengue seroprevalence was strongly age dependent consistent with endemic exposure while that of chikungunya peaked in childhood consistent with the recent emergence of the virus in the study area. Our findings will inform control strategies for the two arboviruses in Ecuador including recommendations by the WHO on dengue vaccination.

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“…21 Models have been developed predicting seasonal dengue risk using ENSO. 46 Our findings on the association of climate and Aedes vector indices would be a step forward in the process due to the ability to quantify the risk of occurrence of Aedes vectors before the emergence of dengue epidemics. Dengue vector control is challenging and requires planning and meticulous resource allocation.…”

Section: Discussionmentioning

confidence: 96%