Biology subjects

Poletti, P.

Publications and source records attributed to Poletti, P..

5 recordsLinked to original sources

bioRxiv2026

End-of-outbreak determination under seasonal transmission

At the apparent end of an infectious disease outbreak, policymakers must decide when to relax interventions, balancing epidemiological safety and economic efficiency. Here, we extend a renewal equation framework for estimating the risk of additional cases to scenarios with seasonal transmission, such as Aedes-borne virus transmission in temperate settings. In simulations, we demonstrate that the time of year is key to when it is safe to relax interventions under seasonal transmission: measures can be relaxed sooner if the last observed case occurs towards the end of the transmission season. We apply our framework to the 2017 chikungunya outbreak in Italy, integrating incidence data with estimates of temperature suitability for transmission, and further extend our approach to account for case under-reporting. Our model incorporating an end-of-season decline in transmission indicates a lower risk of additional cases late in the outbreak than a model based on incidence alone: assuming 60% case reporting, the seasonal model reaches a 1% risk threshold 22 days after the last observed case, compared with 39 days for the incidence-only model. Incorporating seasonality in model-based assessments of transmission risks at the end of an outbreak can therefore support more timely and reliable decision making.

ecology↗

bioRxiv2025

Evaluating Field Trial Designs for Genetically Modified Mosquito Interventions: An In-Silico Simulation Approach

Mosquito control strategies based on the mass release of modified males, such as genetically modified mosquitoes (GMMs), aim to suppress wild populations by impairing reproduction. Evaluating these interventions requires resource-intensive field trials, but a lack of standardized implementation practices, particularly regarding release ratios of modified males to wild female mosquitoes and trial timing, has led to variable outcomes. This studys objective is to propose a modeling tool for the "in-silico" simulation of trial designs before field implementation. To this aim, we developed an agent-based model of mosquito population dynamics. As a case study, we calibrated the model using 2019-2023 Aedes aegypti surveillance data from Miami-Dade County, Florida, and compared two GMM trial designs as illustrative examples. Our results show that depending on the implementation choices (e.g., trial start date and duration, release ratio), trials yield highly variable outcomes. For example, changing the start date while fixing all other implementation details can lead to effectiveness between 50% and 90%. Our findings suggest that "in-silico" simulation is a valuable tool for improving trial protocol design, allowing stakeholders to test strategies and reduce outcome uncertainty before committing to a fieldwork experiment.

ecology↗

bioRxiv2025

Mapping the habitat suitability of Culex pipiens in Europe using ensemble bioclimatic modelling

Anthropogenic pressure on natural ecosystems has profoundly influenced the dynamics of disease vectors, altering their distribution and phenology, and increased the risk of vector-borne diseases. Culex pipiens is a widespread mosquito species and an important vector of zoonotic pathogens in Europe, including West Nile virus. Understanding Cx. pipiens distribution is essential to orient monitoring and mitigation strategies for vector-borne disease risk. Here, we employed an ensemble modelling framework to investigate the climatic and environmental determinants of Cx. pipiens distribution in continental Europe. We integrated high-resolution occurrence data from entomological surveillance with bioclimatic, topographic, and anthropogenic variables. Our findings identified imperviousness as the most influential predictor of Cx. pipiens distribution, with a strong association with human-modified low-elevation areas that reflects its adaptability to anthropogenic environments. The ensemble prediction approach we employed demonstrated higher predictive accuracy and transferability compared to individual models during independent block validation. These results emphasize the need to incorporate anthropogenic factors into disease vector distribution models to support evidence-based surveillance and control strategies, while also offering updated, robust, and spatially explicit predictions of the habitat suitability for Cx. pipiens in Europe. Overall, this study highlights the role of human modification of the natural environment in shaping Cx. pipiens distribution, extending previous knowledge on the role of urban areas.

ecology↗

bioRxiv2022

Spatiotemporal Distribution of Vector Mosquito Species in Maricopa County, Arizona: The highest West Nile virus disease incidence area in the United States in 2021

Mosquito-borne diseases are a major global public health concern and mosquito surveillance systems are essential for the implementation of effective mosquito control strategies. The objective of our study is to determine the spatiotemporal distribution of vector mosquito species in Maricopa County, AZ from 2011 to 2021, and to identify the hotspot areas for West Nile virus (WNV) and St. Louis Encephalitis virus (SLEV) transmission in 2021. The Maricopa County Mosquito Control surveillance system utilizes BG-Sentinel and EVS-CDC traps throughout the entire urban and suburban areas of the county. We estimated specific mosquito species relative abundance per unit area using the Kernel density estimator in ArcGIS 10.2. We calculated the distance between all traps in the surveillance system and created a 4 km buffer radius around each trap to calculate the extent to which each trap deviated from the mean number of Cx. quinquefasciatus and Cx. tarsalis collected in 2021. Our results show that vector mosquito species are widely distributed and abundant in the urban areas of Maricopa County. A total of 691,170 Culex quinquefasciatus, 542,733 Culex tarsalis, and 292,305 Aedes aegypti were collected from 2011 to 2022. The relative abundance of Ae. aegypti was highly seasonal peaking in the third and fourth quarters of the year. Culex quinquefasciatus, on the other hand, was abundant throughout the year with several regions consistently yielding high numbers of mosquitoes. Culex tarsalis was abundant but it only reached high numbers in well-defined areas bordering natural and rural areas. We also detected high levels of heterogeneity in the risk of WNV and SLEV transmission to humans disregarding traps geographical proximity. The well-defined species-specific spatiotemporal and geographical patterns found in this study can be used to inform vector control operations.

ecology↗

bioRxiv2018

Quantifying the risk of local Zika virus transmission in the continental US during the 2015-2016 ZIKV epidemic

BackgroundLocal mosquito-borne Zika virus (ZIKV) transmission has been reported in two counties of the continental United State (US), prompting the issuance of travel, prevention, and testing guidance across the continental US. Large uncertainty, however, surrounds the quantification of the actual risk of ZIKV introduction and autochthonous transmission across different areas of the US.\n\nMethodWe present a framework for the projection of ZIKV autochthonous transmission in the continental US during the 2015-2016 epidemic, using a data-driven stochastic and spatial epidemic model accounting for seasonal, environmental and detailed population data. The model generates an ensemble of travel-related case counts and simulate their potential to trigger local transmission at individual level.\n\nResultsWe estimate the risk of ZIKV introduction and local transmission at the county level and at the 0.025{degrees} x 0.025{degrees} cell level across the continental US. We provide a risk measure based on the probability of observing local transmission in a specific location during a ZIKV epidemic modeled after the one observed during the years 2015-2016. The high spatial and temporal resolutions of the model allow us to generate statistical estimates of the number of ZIKV introductions leading to local transmission in each location. We find that the risk is spatially heterogeneously distributed and concentrated in a few specific areas that account for less than 1% of the continental US population. Locations in Texas and Florida that have actually experienced local ZIKV transmission are among the places at highest risk according to our results. We also provide an analysis of the key determinants for local transmission, and identify the key introduction routes and their contributions to ZIKV spread in the continental US.\n\nConclusionsThis framework provides quantitative risk estimates, fully captures the stochas-ticity of ZIKV introduction events, and is not biased by the under-ascertainment of cases due to asymptomatic infections. It provides general information on key risk determinants and data with potential uses in defining public health recommendations and guidance about ZIKV risk in the US.

epidemiology↗