AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission

Abstract

Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. in the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for Aedes-borne diseases' environmental suitability (AeDeS) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies. Human society is more and more interconnected every year by communication technologies, travel and supply chains. As a consequence, increasing movement of humans, animals, pathogens, vectors, goods, and capital across borders creates both risks and opportunities 1. Like climate, epidemics do not mind political borders, and can impact social stability and human health. In the last couple of decades, the appearance of a variety of new epidemics, such as the SARS coronavirus in 2003, the avian influenza (H1N1) in 2009, the Ebola virus in western Africa (2014-2016), the Zika virus in the Americas (2015-2016), and the novel coronavirus (SARS-CoV-2) identified in late December 2019 in Wuhan (China) and still ongoing, amongst others, demonstrates how fast emerging infectious diseases can spread, sometimes causing damage at national or regional scale, and other times-like the present SARS-CoV-2 pandemic-impacting the entire world 2. Multiple infectious diseases are climate-sensitive, with climate acting as a key driver of spatio-temporal patterns of infections, related to seasonal, year-to-year, and longer-term shifts in populations at risk 3. Climate

Are Temperature Suitability and Socioeconomic Factors Reliable Predictors of Dengue Transmission in Brazil?

“…Because temperature is a critical exogenous driver for disease transmission by vectors (27), global climate change may substantially alter the spatial pattern in distribution and prevalence of dengue (11,51). In countries where the autochthonous transmission of dengue is established, increasing temperatures may intensify transmission by favoring vectors' survival, reproduction, and biting rates (6).…”

“…Most mechanistic approaches in MBDs have integrated the temperature effect on transmission traits to predict global geographical patterns, not considering lower-scale socioeconomic variations (26). Recently, a multi-model climate-driven approach has been proposed to forecast Aedes-borne diseases and support surveillance operations (27). Albeit integrating many transmission-related socioeconomic factors might turn intractable in a process-based procedure, the absence of these critical drivers still brings uncertainty to transmission potential estimation (26).…”

Are temperature suitability and socioeconomic factors reliable predictors of dengue transmission in Brazil?

“…Because temperature drives the suitability for dengue transmission (25) global climate change may substantially alter the spatial pattern in the distribution and prevalence of dengue (11,46). In countries where the autochthonous transmission of dengue is established, the rising temperatures may intensify transmission by favoring vectors’ survival, reproduction, and biting rates (6).…”

“…Most of the mechanistic approaches in mosquito-borne diseases have integrated the temperature effect on transmission traits to predict global geographical patterns, not considering lower scale socio-economic variations or considering it merely as additional factors (24). Recently, a multi-model climate-driven approach has also been proposed to forecast Aedes -borne diseases and support surveillance operations (25). Albeit integrating many transmission-related factors might turn intractable in a process-based procedure, the absence of key drivers still brings uncertainty to the estimated transmission potential (24).…”

Estimating and forecasting the burden and spread of SARS-CoV2 first wave in Colombia

“…The ability to generate nowcasts, forecasts, and the early identification of epidemic events can help to develop early-warning systems, which is important to timely implement effective control policies in developing countries [4, 5, 6]. In recent years, the interest in generating real-time epidemic forecasts to help the control and management of infectious diseases has grown, prompted by a succession of global and regional outbreaks of infectious diseases such as Zika, Ebola among others [7, 8, 9]. The current availability of epidemiological and digital data streams, enhanced by process-based models that incorporate climate, demography, and mobility among other factors, can provide a basis to evaluate the impact and effectiveness of intervention strategies in changing environments [10, 11, 12].…”