The Mosquito, the Virus, the Climate: An Unforeseen Réunion in 2018

Abstract

The 2018 outbreak of dengue in the French overseas department of Réunion was unprecedented in size and spread across the island. This research focuses on the cause of the outbreak, asserting that climate played a large role in the proliferation of the Aedes albopictus mosquitoes, which transmitted the disease, and led to the dengue outbreak in early 2018. A stage-structured model was run using observed temperature and rainfall data to simulate the life cycle and abundance of the Ae. albopictus mosquito. Further, the model was forced with bias-corrected subseasonal forecasts to determine if the event could have been forecast up to 4 weeks in advance. With unseasonably warm temperatures remaining above 25°C, along with large tropical-cyclone-related rainfall events accumulating 10-15 mm per event, the modeled Ae. albopictus mosquito abundance did not decrease during the second half of 2017, contrary to the normal behavior, likely contributing to the large dengue outbreak in early 2018. Although subseasonal forecasts of rainfall for the December-January period in Réunion are skillful up to 4 weeks in advance, the outbreak could only have been forecast 2 weeks in advance, which along with seasonal forecast information could have provided enough time to enhance preparedness measures. Our research demonstrates the potential of using state-of-the-art subseasonal climate forecasts to produce actionable subseasonal dengue predictions. To the best of the authors' knowledge, this is the first time subseasonal forecasts have been used this way.

Projecting the risk of mosquito-borne diseases in a warmer and more populated world: a multi-model, multi-scenario intercomparison modelling study

“…The first two models consist of vectorial capacity models including basic vector to human interactions coupled with stage-structured datadriven dynamic models to describe the population dynamics of Ae aegypti (UMEÅ-aegypti) and Ae albopictus (UMEÅ-albopictus). [27][28][29] These models account for the effects of daily temperature, precipitation, and daylight length in the ecological processes of mosquito populations and for the spatiotemporal dynamics of mosquito populations. The statistical dengue model (DGM) is a generalised additive mixed model that simulates dengue incidence as a function of temperature, precipitation, relative humidity, and population density.…”

The 2022 Europe report of the Lancet Countdown on health and climate change: towards a climate resilient future

“…This indicator uses a mechanistic model to estimate the basic reproduction rate ( R 0 ) and length of transmission season for dengue combining information on temperature, rainfall, mosquito abundance, and human population density. 48 , 49 Overall, in the period 1986–2020, ( R 0 ) has increased by 17·3% in Europe compared with 1951–1985 ( figure 3B ). This pattern is also observed for chikungunya and Zika virus.…”

Effect of El Niño–Southern Oscillation and local weather on Aedes vector activity from 2010 to 2018 in Kalutara district, Sri Lanka: a two-stage hierarchical analysis

“…A modelling study in Réunion established a positive association between weather variables and Breteau index using a process-based modelling approach and evaluated the capacity of the climate information in predicting Aedes vector activities with a lead time up to 4 weeks. 38 A study in the Gampaha, Western Province, Sri Lanka, using data for 1 year, found a statistically significant increase only for ovitrap index and not for the vector indices during the two monsoonal periods. 39 Similarly, a study in Hong Kong showed that ovitrap indices were positively correlated with the mean air temperature with a lag up to 22 days and total rainfall with a lag up to 15 days before the ovitrap measurement.…”