A Warming Welcome? Belgium’s Increasing Suitability for Aedes albopictus

A Warming Welcome? 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Belgium’s Increasing Suitability for Aedes albopictus Daniele Da Re, Isra Deblauwe, Emmanuelle Inès Kern, Marie Hermy, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7057895/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Parasites & Vectors → Version 1 posted 7 You are reading this latest preprint version Abstract Aedes albopictus , commonly known as the Asian tiger mosquito, is an invasive species of significant public health concern due to its ability to transmit dengue, chikungunya, and Zika viruses. Since arriving in Europe in the late 1970s, this mosquito species has progressively expanded its range, with Belgium marking an important step in its northward spread. The increasing frequency of its introduction raises the urgent question of whether Ae. albopictus could become permanently present in the country. This study investigates the potential for the establishment of Ae. albopictus populations in Belgium using a mechanistic model and assessing the likelihood of successful establishment based on simulated introduction events. Our results indicate that the probability of establishment is highest in Flanders, particularly under scenarios of early and multiple introductions during the summer months, even though the interannual climatic variability still plays a major role in contributing to the establishment success. The establishment of Ae. albopictus in Belgium would introduce new epidemiological risks, as the species could facilitate the transmission of non-native viruses during particularly warm summers. While the transmission windows may remain limited compared to Mediterranean regions, continued introductions and climate change could expand these periods, increasing the likelihood of local outbreaks. Aedes albopictus Europe mechanistic model dynamAedes Figures Figure 1 Figure 2 Background Invasive mosquito species pose a major threat to global health by transmitting various pathogens to humans. One of the most notable invasive species in Europe is Aedes (Stegomyia) albopictus (Skuse, 1894) (Diptera: Culicidae), also known as the Asian tiger mosquito, which has been steadily spreading across the continent since its initial introduction in the late 1970s 1 , 2 . This species has already been responsible for arbovirus outbreaks, mostly in Mediterranean Europe, making its establishment a significant public health concern. Native to Southeast Asia, Ae. albopictus has successfully spread to numerous European countries, including Italy, France, and Germany, due to global trade, transportation, and favourable climatic conditions 3 . Invasive species follow a characteristic invasion curve, where early introductions are often hard to detect due to low population densities 4 . Over time, the population grows exponentially if left unchecked, making eradication efforts increasingly difficult and costly. Early intervention, when populations are still small and localised, provides the best opportunity for successful eradication. In Belgium, surveillance efforts such as the MEMO and MEMO + projects have been ongoing over the past decade, with a primary focus on detecting the introduction of Ae. albopictus and other invasive mosquito species 5 . These efforts have shown a marked increase in introduction events, particularly in the northern region of Belgium, Flanders. In 2023, overwintering activity was confirmed for the first time in the Flemish municipalities of Wilrijk and Lebbeke, marking a potential turning point in the species' invasion trajectory 6 , 7 . In 2024, overwintering was observed in three additional locations 8 (Fig. 1 ). Given the continuous influx of propagules in the country and the first evidence of overwintering populations, the key question we now face is whether the increasing frequency of introductions will lead to the widespread establishment of permanent populations in this area situated at the edge of the current species’ invasive range. We used the dynamAedes 9 model to explore the likelihood of Ae. albopictus establishment in Belgium under different simulation scenarios. We simulated a single introduction event by introducing either 500 or 1000 eggs on June 30 or July 15 for the years 2018, 2019, 2020, and 2021, hence allowing us to consider the interannual variability of climatic conditions (Table S1 ). We selected the egg introduction sizes based on the stochastic nature of the dynamAedes model, which limits the viability of establishment from very small founder populations (e.g., 1–5 adults), as these are highly likely to result in extinction due to demographic stochasticity. By introducing 500 and 1000 eggs as proxies for adult introductions, we aimed to reflect the average fecundity of Ae. albopictus females, which lay approximately 70 eggs per gonotrophic cycle 10 . These quantities correspond roughly to the reproductive output of 5–8 and 15–20 adult females, respectively, providing more statistically robust starting conditions for simulating potential establishment. The introduction event happened in all the pixels of a lattice grid of 2.5x2.5 km spatial resolution extending over the whole country. Being a stochastic model, we repeated each introduction scenario 50 times. For each iteration and introduction scenario, the model was run for one year, after which we evaluated the probability of successful introduction, i.e. overwintering. This was measured as the proportion of dynamAedes model iterations that resulted in a viable population one year after the initial introduction event 9 . To reduce the influence of short-term fluctuations and better reflect sustained successful introductions, we averaged the percentage of successful introductions over the final 30 days of each simulation. This smoothing approach reduced the impact of inherent stochastic variability and provided a more stable metric. In addition to these single introduction events, we simulated multiple introduction events. These consisted of an initial introduction of 500 or 1000 eggs on June 30 or July 15, followed by three random introductions of approximately 100 eggs each, continuing until September 15 of the same year (Table S1 ). As with the single introduction events, we assessed the probability of successful introduction over the final 30 days of each simulation. The dynamAedes model was informed using mechanistically downscaled temperature surfaces simulating mean daily air temperatures for 2018–2022 at high spatial resolution. These climatic surfaces were generated using the microclima R package 11 and derived by downscaling a regional climate model (from ERA5Land 12 at 9 km spatial resolution) with a Digital Elevation Model (DEM) at a 2.5 km spatial resolution. To enhance accuracy in urban environments, we also applied corrections for energy flux exchanges in built-up areas, accounting for the unique thermal dynamics of urban landscapes 11 . We quantitatively assessed the factors influencing the percentage of successful introductions across the different introduction scenarios using a generalised linear model (GLM) with a beta-binomial error distribution to account for overdispersion in the proportional count data. The model was specified as follows: Percentage of successful introduction ∼ introEggs + introMonth + introduction + introYear×Region (Eq. 1) where introEggs represents the number of eggs of the first introduction event, introMonth denotes the month of the first introduction event, introduction refers to the introduction type (single vs. multiple), and the interaction term introYear × Region captures spatiotemporal variability across years and regions. The baseline levels for the categorical predictors were set as 2018 for introYear, Brussels for Region, and multiple introductions for introduction. Model selection was based on AIC comparison and likelihood ratio tests, which indicated strong support for the beta-binomial model over a standard binomial model (ΔAIC = 23485). Model diagnostics using the DHARMa 13 package showed no inflation of residual outliers, slight underdispersion (dispersion = 0.96), and minimal deviation from uniformity, supporting the adequacy of the final model (Eq. 1). Additionally, we investigated the factors influencing the simulated egg abundance across the different introduction scenarios. Each simulation produced a stack of rasters representing daily counts of the various life stages per pixel, from the date of introduction through the assessment period in the following year. Since not all introductions led to viable populations, we first calculated the daily egg abundance at the 95th percentile of simulated values. This approach filtered out low-abundance cases, allowing us to focus on scenarios indicative of successful introductions. The resulting daily values were then aggregated weekly to generate a smoothed and temporally consistent measure of egg abundance for each pixel. For each pixel, the total number of eggs observed over the assessment period was used as the response variable. To account for broad-scale spatial and temporal variability, we specified a GLM with the same structure and predictors described in Eq. 1: Total weekly egg abundance ∼ introEggs + introMonth + introduction + introYear×Region (Eq. 2) Given the count nature of the response variable, we initially fitted the model using a Poisson distribution, but diagnostic checks indicated overdispersion. Therefore, we opted for a Negative Binomial GLM to better account for variability in the data. Simulations using the dynamAedes model revealed that the success of Ae. albopictus introduction in Belgium is strongly influenced by both introduction dynamics, namely the timing and number of eggs, and spatiotemporal variability in climatic conditions (Fig. 2 ; Table 1 ). Single introduction events led to successful introductions in some cases, but success was generally limited and highly dependent on early-season introductions (e.g., by June 30), which allowed more time for population growth and egg accumulation before winter. Higher introduction sizes (e.g., 1000 vs. 500 eggs) also improved the successful introduction probability. In contrast, scenarios with multiple introductions showed a slightly higher likelihood of overwintering, particularly when initial introductions occurred earlier and total egg input was greater. These simulation findings were supported by the beta-binomial generalised linear model (GLM), which identified significant positive effects of the number of eggs (β = 0.574, p < 0.001) and negative effects of later introduction months (β = -1.678, p < 0.001) and single introductions (β = -0.049, p < 0.001) on the probability of successful introduction. Spatial variation also played a role: Wallonia showed a significantly lower probability of successful introduction compared to the baseline region (Brussels), while Flanders did not differ significantly. Importantly, the interaction terms of the GLM model highlighted that the effects of time and space were not uniform, as the interactions were not always statistically significant (Table 1 ). The GLM model on the simulated egg abundance dynamics also supported this interpretation, showing a positive and significant estimate for the introduction of 1000 eggs to the baseline of 500 eggs, and a negative and significant estimate for the later introduction date (15th of July vs. 30th of June; Table 2 ). Single introductions also resulted in a negative and significant effect with respect to the baseline (Multiple). To complement the analysis of overwintering success, we investigated the spatial and temporal variability in air temperatures across the same pixels and time period. An ANOVA revealed significant effects of season, year, region, and their interaction on temperature (p < 0.001 for all factors; Table S2), confirming pronounced spatiotemporal heterogeneity. Post-hoc Tukey comparisons further demonstrated consistent temperature differences between regions, seasons, and years, with significant pairwise differences detected within each season and across regions (Table S3). Table 1 Parameter estimates from the Beta-Binomial Generalised Linear Model (GLM) assessing factors influencing the proportion of successful introductions of Aedes albopictus . The model includes the number of eggs in the first introduction event ( introEggs ), month of the first introduction ( introMonth ), type of introduction ( introduction , single vs. multiple), and the interaction between year and region ( introYear × Region ) to capture spatiotemporal variability. Baseline levels for categorical variables are set to 2018 ( introYear ), Brussels ( Region ), and multiple introductions ( introduction ). Estimates are presented on the log-odds scale with associated standard errors (SE), z-values, and p-values. The model was fitted using a beta-binomial distribution to account for overdispersion in the proportional response. Predictor Estimate Std. Error z value p-value (Intercept) -2.63605 0.049094 -53.7 < 0.0001 Eggs1000 eggs 0.574443 0.003956 145.2 < 0.0001 MonthNum7 -1.677836 0.004758 -352.7 < 0.0001 Single introduction -0.049376 0.003907 -12.6 < 0.0001 introYear2019 -4.467238 0.3814 -11.7 < 0.0001 introYear2020 1.251585 0.058313 21.5 < 0.0001 introYear2021 -3.053492 0.195284 -15.6 < 0.0001 RegionFlandres 0.037207 0.049231 0.8 0.4498 RegionWallonia -0.918129 0.049431 -18.6 < 0.0001 introYear2019 × RegionFlandres 0.972428 0.382158 2.5 0.0109 introYear2020 × RegionFlandres -0.013368 0.058602 -0.2 0.8195 introYear2021 × RegionFlandres 0.415163 0.195968 2.1 0.0341 introYear2019 × RegionWallonia -0.223655 0.386191 -0.6 0.5625 introYear2020 × RegionWallonia 0.462309 0.058776 7.9 < 0.0001 introYear2021 × RegionWallonia 0.164771 0.196959 0.8 0.4028 Table 2 Parameter estimates from the Negative Binomial Generalised Linear Model (GLM) assessing factors influencing total weekly Aedes albopictus egg abundance. The model includes the number of eggs in the first introduction event (introEggs), month of first introduction (introMonth), type of introduction (introduction, single vs. multiple), and the interaction between year and region (introYear × Region) to capture spatiotemporal variability. Baseline levels for categorical variables are set to 2018 ( introYear ), Brussels ( Region ), and multiple introductions ( introduction ). Estimates are presented on the log scale with associated standard errors (SE), z-values, and p-values. The model was fitted using a Negative Binomial distribution due to overdispersion detected in initial Poisson models. Predictor Estimate Std. Error z value p-value (Intercept) 11.504 0.0155 740.1 < 0.0001 introEggs1000 0.497 0.001 475.94 < 0.0001 introMonth7 -0.34 0.001 -326.2 < 0.0001 Single introduction -0.102 0.001 -97.78 < 0.0001 introYear2019 -1.344 0.0221 -60.93 < 0.0001 introYear2020 -0.456 0.0219 -20.78 < 0.0001 introYear2021 -3.287 0.0219 -149.8 < 0.0001 RegionFlandres 0.235 0.0156 15.08 < 0.0001 RegionWallonia -0.937 0.0156 -60.15 < 0.0001 introYear2019 × RegionFlandres -0.018 0.0222 -0.8 0.4235 introYear2020 × RegionFlandres -0.018 0.0221 -0.83 0.4048 introYear2021 × RegionFlandres 0.03 0.0221 1.36 0.1740 introYear2019 × RegionWallonia 0.102 0.0221 4.6 < 0.0001 introYear2020 × RegionWallonia 0.04 0.022 1.79 0.0728 introYear2021 × RegionWallonia 0.032 0.022 1.46 0.1445 Discussion and Conclusions Our findings suggest that Ae. albopictus is likely to become successfully established in Belgium, particularly in the Flanders region and Brussels, under conditions of early and multiple introductions. The GLM analysis of the percentage of successful introductions (Eq. 1), obtained using the dynamAedes models informed with downscaled ERA5Land air temperatures, supports the claim that interannual climatic variability is the dominant factor influencing overwintering success. The northern part of the country appeared more favourable for establishment than the southern part, likely due to warmer climatic conditions. Moreover, both earlier summer introductions and multiple introduction events revealed a positive effect on the probability of successful introduction. However, these scenarios also introduce an additional layer of stochasticity, as the timing and location of the three supplementary introductions are randomly assigned within defined temporal and spatial bounds. Our results align with those of other studies using different modelling techniques, all indicating that the suitability for Ae. albopictus establishment will increase for Belgium in a warming world, becoming significantly higher compared to pre-industrial conditions by the mid-21st century 14 – 19 . The continuous influx of propagules, i.e., multiple introductions, from neighbouring countries where the species is already established, such as Germany and France, is likely facilitating its establishment in an area at the margins of its current invasive range, as currently observed in Belgium. This dynamic aligns with the source-sink framework described by Pulliam (1988) 20 , which distinguishes between source habitats, where local reproduction exceeds mortality, and sink habitats, where populations rely on immigration from source areas to persist. In this case, ongoing immigration appears to play a key role in supporting populations of Ae. albopictus in regions where the current local conditions may not otherwise support or favour its persistence. These results, combined with the fieldwork and citizen science findings, raise the question of whether the eradication of Ae. albopictus in Belgium is still feasible, or should efforts shift toward maintaining populations at low densities through control measures to lower nuisance and the risk for local arbovirus transmission upon introduction of viruses. Once populations overwinter in the same locations over multiple years, eradication becomes far more difficult, if not impossible. Given the current situation, immediate, scalable, and sustainable interventions are essential. While innovative methods such as sterile insect techniques or Wolbachia-based suppression hold promise, they require substantial resources and infrastructure, making them less viable in the short term for Belgium. Instead, integrated vector management approaches are underway, combining active surveillance, citizen science initiatives, such as the MosquitoSurveillance app 21 , with targeted larval site inspections and longitudinal ovitrap monitoring in areas where overwintering has been documented. Public awareness campaigns to encourage the elimination of breeding sites 23 , alongside targeted larviciding using Bacillus thuringiensis israelensis (Bti) in non-removable water containers, represent practical, immediately deployable strategies. Additionally, the potential of mass trapping of adult mosquitoes as a complementary, non-insecticidal control method warrants further investigation in this context 22 . Looking ahead, the development of scalable and operational modelling tools, co-designed with vector control and surveillance stakeholders and public health authorities, will be essential to ensure that model predictions truly address field needs 24 . Models capable of forecasting key seasonal dynamics, such as the onset, peak, and offset of Ae. albopictus activity could significantly enhance the timing and efficiency of control efforts 25 . However, to be effective, these tools must go beyond replicating what field scientists already anticipate through prior knowledge and experience. Instead, they should provide actionable insights that complement on-the-ground expertise, offering early warnings, identifying unexpected risk periods, and supporting adaptive management strategies 25 . Beyond its ecological, societal and public health implications, the establishment of Ae. albopictus in Belgium marks a shift to a new epidemiological reality: one where mosquito-borne viruses not previously transmitted by native species could find a foothold. While the current climate may only support transmission during short temporal windows, such as particularly warm summers, a ‘perfect storm’ scenario - where an infected traveller arrives in an area with active mosquito populations during favourable conditions - remains a concern. Further establishment of this vector, coupled with climate change, will likely extend these transmission windows, increasing the probability of local outbreaks. However, these windows will likely remain narrower in Belgium compared to Mediterranean regions. Yet, proactive surveillance and targeted control efforts are critical to limiting future risks and protecting public health. Declarations Ethics and Consent to Participate declarations Not applicable. Competing interests The authors declare no competing interests. Funding Declaration Wim Van Bortel is an Institute of Tropical Medicine Outbreak Research Team member. This team is financially supported by the Department of Economy, Science and Innovation of the Flemish government. Author Contribution Wim Van Bortel and Daniele Da Re conceived the ideas and designed the methodology. Daniele Da Re, Emma Kern and Wim Van Bortel analysed the data. Daniele Da Re and Wim Van Bortel led the writing of the manuscript, with relevant contributions from all the other co-authors. All authors contributed critically to the manuscript and gave final approval for publication. Data Availability Observational data of Aedes albopictus collected in Belgium were obtained from the MEMO and MEMO+ projects. Temperature data were obtained from the ERA5Land dataset and downloaded from the Climate Data Store (https://cds.climate.copernicus.eu/#!/home). 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Supplementary Files DaRealbopictusInBelgium2suppl20250706.docx Cite Share Download PDF Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Parasites & Vectors → Version 1 posted Editorial decision: Revision requested 29 Sep, 2025 Reviews received at journal 20 Aug, 2025 Reviewers agreed at journal 24 Jul, 2025 Reviewers invited by journal 24 Jul, 2025 Editor assigned by journal 10 Jul, 2025 Submission checks completed at journal 10 Jul, 2025 First submitted to journal 06 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7057895","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":508008575,"identity":"f28faf6a-bffc-4919-ab8b-20809f632c78","order_by":0,"name":"Daniele Da Re","email":"","orcid":"","institution":"Fondazione Edmund Mach","correspondingAuthor":false,"prefix":"","firstName":"Daniele","middleName":"Da","lastName":"Re","suffix":""},{"id":508008577,"identity":"517e2174-97ea-4fca-bc8e-0cb066a88672","order_by":1,"name":"Isra Deblauwe","email":"","orcid":"","institution":"Institute of Tropical Medicine 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Environnement","correspondingAuthor":false,"prefix":"","firstName":"Olivier","middleName":"","lastName":"Beck","suffix":""},{"id":508008587,"identity":"a4d7a498-4174-4850-ba24-c4580ce2b363","order_by":11,"name":"Wim Van Bortel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYJACZjDJznzgAJBKIFqLBAMzWwJID0laeAwYiNJicCP52eOCint1/Mw8Hw9/+MWQx09YS5q58YwzxRKSzbwbDhzsYyiWbCCgxezMATNp3rYECYPDIC09DIkbDhDUcvwbWIv9YZ4HYC37CWo53gO1hZmH4cCBH0BbCPnF/nhPmfSMMwmSMw6zGRw42yBRLEHIFslm9m3SBRUJ/PztzY8/VPyxyeNvIGQNCmBskyBJPQj8IVnHKBgFo2AUjAAAAPpCQ9Gi4lk7AAAAAElFTkSuQmCC","orcid":"","institution":"Institute of Tropical Medicine Antwerp","correspondingAuthor":true,"prefix":"","firstName":"Wim","middleName":"Van","lastName":"Bortel","suffix":""}],"badges":[],"createdAt":"2025-07-06 12:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7057895/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7057895/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13071-025-07119-w","type":"published","date":"2025-11-26T15:58:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91541579,"identity":"dc73f8b6-9046-42f6-85e1-84d848a4193b","added_by":"auto","created_at":"2025-09-17 13:56:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":448770,"visible":true,"origin":"","legend":"\u003cp\u003eThe introduction locations (blue) and overwintering observations (red) of \u003cem\u003eAedes albopictus\u003c/em\u003e in Belgium over the period 2000-2024. Inset: the year of observed overwintering at the five locations (districts). Country borders: black; Main routes: light grey.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7057895/v1/3f1ed32edfe0694d1370d42e.png"},{"id":91541581,"identity":"0f9414a7-913e-406b-8043-dd093192e1f8","added_by":"auto","created_at":"2025-09-17 13:56:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1283464,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of successful \u003cem\u003eAedes albopictus\u003c/em\u003eintroductions from 2018 to 2021 under scenarios involving single or multiple introduction events, starting with either 500 or 1000 eggs on June 30 or July 15 of each year. Values represent the average percentage of successful introductions over the final 30 days of each simulation. Lines represent the three regions of Belgium: Flanders (North), Wallonia (South) and Brussels (within Flanders).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7057895/v1/5cb5d7faa446806754c71037.png"},{"id":97178744,"identity":"f5ef5d6e-656e-4b12-8177-2edb9b85d732","added_by":"auto","created_at":"2025-12-01 16:13:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1820734,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7057895/v1/f175b12a-72b4-4fdd-ade3-71a2bf75b633.pdf"},{"id":91541842,"identity":"4608eead-40c8-40f7-96f4-beb9a6bffd15","added_by":"auto","created_at":"2025-09-17 14:04:07","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1690315,"visible":true,"origin":"","legend":"","description":"","filename":"DaRealbopictusInBelgium2suppl20250706.docx","url":"https://assets-eu.researchsquare.com/files/rs-7057895/v1/639e63fd77ea2b43ff61a540.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Warming Welcome? Belgium’s Increasing Suitability for Aedes albopictus","fulltext":[{"header":"Background","content":"\u003cp\u003eInvasive mosquito species pose a major threat to global health by transmitting various pathogens to humans. One of the most notable invasive species in Europe is \u003cem\u003eAedes (Stegomyia) albopictus\u003c/em\u003e (Skuse, 1894) (Diptera: Culicidae), also known as the Asian tiger mosquito, which has been steadily spreading across the continent since its initial introduction in the late 1970s\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. This species has already been responsible for arbovirus outbreaks, mostly in Mediterranean Europe, making its establishment a significant public health concern. Native to Southeast Asia, \u003cem\u003eAe. albopictus\u003c/em\u003e has successfully spread to numerous European countries, including Italy, France, and Germany, due to global trade, transportation, and favourable climatic conditions\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eInvasive species follow a characteristic invasion curve, where early introductions are often hard to detect due to low population densities\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Over time, the population grows exponentially if left unchecked, making eradication efforts increasingly difficult and costly. Early intervention, when populations are still small and localised, provides the best opportunity for successful eradication. In Belgium, surveillance efforts such as the MEMO and MEMO\u0026thinsp;+\u0026thinsp;projects have been ongoing over the past decade, with a primary focus on detecting the introduction of \u003cem\u003eAe. albopictus\u003c/em\u003e and other invasive mosquito species\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. These efforts have shown a marked increase in introduction events, particularly in the northern region of Belgium, Flanders. In 2023, overwintering activity was confirmed for the first time in the Flemish municipalities of Wilrijk and Lebbeke, marking a potential turning point in the species' invasion trajectory\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In 2024, overwintering was observed in three additional locations\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Given the continuous influx of propagules in the country and the first evidence of overwintering populations, the key question we now face is whether the increasing frequency of introductions will lead to the widespread establishment of permanent populations in this area situated at the edge of the current species\u0026rsquo; invasive range.\u003c/p\u003e\u003cp\u003eWe used the \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003edynamAedes\u003c/span\u003e \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e model to explore the likelihood of \u003cem\u003eAe. albopictus\u003c/em\u003e establishment in Belgium under different simulation scenarios. We simulated a single introduction event by introducing either 500 or 1000 eggs on June 30 or July 15 for the years 2018, 2019, 2020, and 2021, hence allowing us to consider the interannual variability of climatic conditions (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). We selected the egg introduction sizes based on the stochastic nature of the \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003edynamAedes\u003c/span\u003e model, which limits the viability of establishment from very small founder populations (e.g., 1\u0026ndash;5 adults), as these are highly likely to result in extinction due to demographic stochasticity. By introducing 500 and 1000 eggs as proxies for adult introductions, we aimed to reflect the average fecundity of \u003cem\u003eAe. albopictus\u003c/em\u003e females, which lay approximately 70 eggs per gonotrophic cycle\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. These quantities correspond roughly to the reproductive output of 5\u0026ndash;8 and 15\u0026ndash;20 adult females, respectively, providing more statistically robust starting conditions for simulating potential establishment.\u003c/p\u003e\u003cp\u003eThe introduction event happened in all the pixels of a lattice grid of 2.5x2.5 km spatial resolution extending over the whole country. Being a stochastic model, we repeated each introduction scenario 50 times. For each iteration and introduction scenario, the model was run for one year, after which we evaluated the probability of successful introduction, i.e. overwintering. This was measured as the proportion of \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003edynamAedes\u003c/span\u003e model iterations that resulted in a viable population one year after the initial introduction event\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. To reduce the influence of short-term fluctuations and better reflect sustained successful introductions, we averaged the percentage of successful introductions over the final 30 days of each simulation. This smoothing approach reduced the impact of inherent stochastic variability and provided a more stable metric.\u003c/p\u003e\u003cp\u003eIn addition to these single introduction events, we simulated multiple introduction events. These consisted of an initial introduction of 500 or 1000 eggs on June 30 or July 15, followed by three random introductions of approximately 100 eggs each, continuing until September 15 of the same year (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). As with the single introduction events, we assessed the probability of successful introduction over the final 30 days of each simulation.\u003c/p\u003e\u003cp\u003eThe \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003edynamAedes\u003c/span\u003e model was informed using mechanistically downscaled temperature surfaces simulating mean daily air temperatures for 2018\u0026ndash;2022 at high spatial resolution. These climatic surfaces were generated using the \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003emicroclima\u003c/span\u003e R package\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e and derived by downscaling a regional climate model (from ERA5Land\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e at 9 km spatial resolution) with a Digital Elevation Model (DEM) at a 2.5 km spatial resolution. To enhance accuracy in urban environments, we also applied corrections for energy flux exchanges in built-up areas, accounting for the unique thermal dynamics of urban landscapes\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe quantitatively assessed the factors influencing the percentage of successful introductions across the different introduction scenarios using a generalised linear model (GLM) with a beta-binomial error distribution to account for overdispersion in the proportional count data. The model was specified as follows:\u003c/p\u003e\u003cp\u003ePercentage of successful introduction \u0026sim; introEggs\u0026thinsp;+\u0026thinsp;introMonth\u0026thinsp;+\u0026thinsp;introduction\u0026thinsp;+\u0026thinsp;introYear\u0026times;Region (Eq.\u0026nbsp;1)\u003c/p\u003e\u003cp\u003ewhere introEggs represents the number of eggs of the first introduction event, introMonth denotes the month of the first introduction event, introduction refers to the introduction type (single vs. multiple), and the interaction term introYear \u0026times; Region captures spatiotemporal variability across years and regions. The baseline levels for the categorical predictors were set as 2018 for introYear, Brussels for Region, and multiple introductions for introduction. Model selection was based on AIC comparison and likelihood ratio tests, which indicated strong support for the beta-binomial model over a standard binomial model (ΔAIC\u0026thinsp;=\u0026thinsp;23485). Model diagnostics using the \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eDHARMa \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/span\u003e package showed no inflation of residual outliers, slight underdispersion (dispersion\u0026thinsp;=\u0026thinsp;0.96), and minimal deviation from uniformity, supporting the adequacy of the final model (Eq.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003eAdditionally, we investigated the factors influencing the simulated egg abundance across the different introduction scenarios. Each simulation produced a stack of rasters representing daily counts of the various life stages per pixel, from the date of introduction through the assessment period in the following year. Since not all introductions led to viable populations, we first calculated the daily egg abundance at the 95th percentile of simulated values. This approach filtered out low-abundance cases, allowing us to focus on scenarios indicative of successful introductions. The resulting daily values were then aggregated weekly to generate a smoothed and temporally consistent measure of egg abundance for each pixel. For each pixel, the total number of eggs observed over the assessment period was used as the response variable. To account for broad-scale spatial and temporal variability, we specified a GLM with the same structure and predictors described in Eq.\u0026nbsp;1:\u003c/p\u003e\u003cp\u003eTotal weekly egg abundance \u0026sim; introEggs\u0026thinsp;+\u0026thinsp;introMonth\u0026thinsp;+\u0026thinsp;introduction\u0026thinsp;+\u0026thinsp;introYear\u0026times;Region (Eq.\u0026nbsp;2)\u003c/p\u003e\u003cp\u003eGiven the count nature of the response variable, we initially fitted the model using a Poisson distribution, but diagnostic checks indicated overdispersion. Therefore, we opted for a Negative Binomial GLM to better account for variability in the data.\u003c/p\u003e\u003cp\u003eSimulations using the \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003edynamAedes\u003c/span\u003e model revealed that the success of \u003cem\u003eAe. albopictus\u003c/em\u003e introduction in Belgium is strongly influenced by both introduction dynamics, namely the timing and number of eggs, and spatiotemporal variability in climatic conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Single introduction events led to successful introductions in some cases, but success was generally limited and highly dependent on early-season introductions (e.g., by June 30), which allowed more time for population growth and egg accumulation before winter. Higher introduction sizes (e.g., 1000 vs. 500 eggs) also improved the successful introduction probability. In contrast, scenarios with multiple introductions showed a slightly higher likelihood of overwintering, particularly when initial introductions occurred earlier and total egg input was greater.\u003c/p\u003e\u003cp\u003eThese simulation findings were supported by the beta-binomial generalised linear model (GLM), which identified significant positive effects of the number of eggs (β\u0026thinsp;=\u0026thinsp;0.574, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and negative effects of later introduction months (β = -1.678, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and single introductions (β = -0.049, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) on the probability of successful introduction. Spatial variation also played a role: Wallonia showed a significantly lower probability of successful introduction compared to the baseline region (Brussels), while Flanders did not differ significantly. Importantly, the interaction terms of the GLM model highlighted that the effects of time and space were not uniform, as the interactions were not always statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe GLM model on the simulated egg abundance dynamics also supported this interpretation, showing a positive and significant estimate for the introduction of 1000 eggs to the baseline of 500 eggs, and a negative and significant estimate for the later introduction date (15th of July vs. 30th of June; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Single introductions also resulted in a negative and significant effect with respect to the baseline (Multiple).\u003c/p\u003e\u003cp\u003eTo complement the analysis of overwintering success, we investigated the spatial and temporal variability in air temperatures across the same pixels and time period. An ANOVA revealed significant effects of season, year, region, and their interaction on temperature (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all factors; Table S2), confirming pronounced spatiotemporal heterogeneity. Post-hoc Tukey comparisons further demonstrated consistent temperature differences between regions, seasons, and years, with significant pairwise differences detected within each season and across regions (Table S3).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParameter estimates from the Beta-Binomial Generalised Linear Model (GLM) assessing factors influencing the proportion of successful introductions of \u003cem\u003eAedes albopictus\u003c/em\u003e. The model includes the number of eggs in the first introduction event (\u003cem\u003eintroEggs\u003c/em\u003e), month of the first introduction (\u003cem\u003eintroMonth\u003c/em\u003e), type of introduction (\u003cem\u003eintroduction\u003c/em\u003e, single vs. multiple), and the interaction between year and region (\u003cem\u003eintroYear \u0026times; Region\u003c/em\u003e) to capture spatiotemporal variability. Baseline levels for categorical variables are set to 2018 (\u003cem\u003eintroYear\u003c/em\u003e), Brussels (\u003cem\u003eRegion\u003c/em\u003e), and multiple introductions (\u003cem\u003eintroduction\u003c/em\u003e). Estimates are presented on the log-odds scale with associated standard errors (SE), z-values, and p-values. The model was fitted using a beta-binomial distribution to account for overdispersion in the proportional response.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ez value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Intercept)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-2.63605\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.049094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-53.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEggs1000 eggs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.574443\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.003956\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e145.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonthNum7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-1.677836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.004758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-352.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle introduction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.049376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.003907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-12.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-4.467238\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.3814\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-11.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.251585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.058313\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.053492\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.195284\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-15.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegionFlandres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.037207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.049231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4498\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.918129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.049431\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-18.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2019 \u0026times; RegionFlandres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.972428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.382158\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0109\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2020 \u0026times; RegionFlandres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.013368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.058602\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.8195\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2021 \u0026times; RegionFlandres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.415163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.195968\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0341\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2019 \u0026times; RegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.223655\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.386191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5625\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2020 \u0026times; RegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.462309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.058776\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2021 \u0026times; RegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.164771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.196959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4028\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParameter estimates from the Negative Binomial Generalised Linear Model (GLM) assessing factors influencing total weekly \u003cem\u003eAedes albopictus\u003c/em\u003e egg abundance. The model includes the number of eggs in the first introduction event (introEggs), month of first introduction (introMonth), type of introduction (introduction, single vs. multiple), and the interaction between year and region (introYear \u0026times; Region) to capture spatiotemporal variability. Baseline levels for categorical variables are set to 2018 (\u003cem\u003eintroYear\u003c/em\u003e), Brussels (\u003cem\u003eRegion\u003c/em\u003e), and multiple introductions (\u003cem\u003eintroduction\u003c/em\u003e). Estimates are presented on the log scale with associated standard errors (SE), z-values, and p-values. The model was fitted using a Negative Binomial distribution due to overdispersion detected in initial Poisson models.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ez value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Intercept)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.504\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e740.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroEggs1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e475.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroMonth7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-326.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle introduction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-97.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-1.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-60.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-20.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-149.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegionFlandres\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.235\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" 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colname=\"c3\"\u003e\u003cp\u003e0.0221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1740\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2019 \u0026times; RegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2020 \u0026times; RegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0728\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eintroYear2021 \u0026times; RegionWallonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1445\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion and Conclusions","content":"\u003cp\u003eOur findings suggest that \u003cem\u003eAe. albopictus\u003c/em\u003e is likely to become successfully established in Belgium, particularly in the Flanders region and Brussels, under conditions of early and multiple introductions. The GLM analysis of the percentage of successful introductions (Eq.\u0026nbsp;1), obtained using the \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003edynamAedes\u003c/span\u003e models informed with downscaled ERA5Land air temperatures, supports the claim that interannual climatic variability is the dominant factor influencing overwintering success. The northern part of the country appeared more favourable for establishment than the southern part, likely due to warmer climatic conditions. Moreover, both earlier summer introductions and multiple introduction events revealed a positive effect on the probability of successful introduction. However, these scenarios also introduce an additional layer of stochasticity, as the timing and location of the three supplementary introductions are randomly assigned within defined temporal and spatial bounds.\u003c/p\u003e\u003cp\u003eOur results align with those of other studies using different modelling techniques, all indicating that the suitability for \u003cem\u003eAe. albopictus\u003c/em\u003e establishment will increase for Belgium in a warming world, becoming significantly higher compared to pre-industrial conditions by the mid-21st century\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. The continuous influx of propagules, i.e., multiple introductions, from neighbouring countries where the species is already established, such as Germany and France, is likely facilitating its establishment in an area at the margins of its current invasive range, as currently observed in Belgium. This dynamic aligns with the source-sink framework described by Pulliam (1988)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, which distinguishes between source habitats, where local reproduction exceeds mortality, and sink habitats, where populations rely on immigration from source areas to persist. In this case, ongoing immigration appears to play a key role in supporting populations of \u003cem\u003eAe. albopictus\u003c/em\u003e in regions where the current local conditions may not otherwise support or favour its persistence.\u003c/p\u003e\u003cp\u003eThese results, combined with the fieldwork and citizen science findings, raise the question of whether the eradication of \u003cem\u003eAe. albopictus\u003c/em\u003e in Belgium is still feasible, or should efforts shift toward maintaining populations at low densities through control measures to lower nuisance and the risk for local arbovirus transmission upon introduction of viruses. Once populations overwinter in the same locations over multiple years, eradication becomes far more difficult, if not impossible.\u003c/p\u003e\u003cp\u003eGiven the current situation, immediate, scalable, and sustainable interventions are essential. While innovative methods such as sterile insect techniques or Wolbachia-based suppression hold promise, they require substantial resources and infrastructure, making them less viable in the short term for Belgium. Instead, integrated vector management approaches are underway, combining active surveillance, citizen science initiatives, such as the MosquitoSurveillance app\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, with targeted larval site inspections and longitudinal ovitrap monitoring in areas where overwintering has been documented. Public awareness campaigns to encourage the elimination of breeding sites\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, alongside targeted larviciding using \u003cem\u003eBacillus thuringiensis israelensis\u003c/em\u003e (Bti) in non-removable water containers, represent practical, immediately deployable strategies. Additionally, the potential of mass trapping of adult mosquitoes as a complementary, non-insecticidal control method warrants further investigation in this context\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eLooking ahead, the development of scalable and operational modelling tools, co-designed with vector control and surveillance stakeholders and public health authorities, will be essential to ensure that model predictions truly address field needs\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Models capable of forecasting key seasonal dynamics, such as the onset, peak, and offset of \u003cem\u003eAe. albopictus\u003c/em\u003e activity could significantly enhance the timing and efficiency of control efforts\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. However, to be effective, these tools must go beyond replicating what field scientists already anticipate through prior knowledge and experience. Instead, they should provide actionable insights that complement on-the-ground expertise, offering early warnings, identifying unexpected risk periods, and supporting adaptive management strategies\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBeyond its ecological, societal and public health implications, the establishment of \u003cem\u003eAe. albopictus\u003c/em\u003e in Belgium marks a shift to a new epidemiological reality: one where mosquito-borne viruses not previously transmitted by native species could find a foothold. While the current climate may only support transmission during short temporal windows, such as particularly warm summers, a \u0026lsquo;perfect storm\u0026rsquo; scenario - where an infected traveller arrives in an area with active mosquito populations during favourable conditions - remains a concern. Further establishment of this vector, coupled with climate change, will likely extend these transmission windows, increasing the probability of local outbreaks. However, these windows will likely remain narrower in Belgium compared to Mediterranean regions. Yet, proactive surveillance and targeted control efforts are critical to limiting future risks and protecting public health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eEthics and Consent to Participate declarations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eDeclaration\u003c/p\u003e\u003cp\u003eWim Van Bortel is an Institute of Tropical Medicine Outbreak Research Team member. This team is financially supported by the Department of Economy, Science and Innovation of the Flemish government.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWim Van Bortel and Daniele Da Re conceived the ideas and designed the methodology. Daniele Da Re, Emma Kern and Wim Van Bortel analysed the data. Daniele Da Re and Wim Van Bortel led the writing of the manuscript, with relevant contributions from all the other co-authors. All authors contributed critically to the manuscript and gave final approval for publication.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eObservational data of Aedes albopictus collected in Belgium were obtained from the MEMO and MEMO+ projects. Temperature data were obtained from the ERA5Land dataset and downloaded from the Climate Data Store (https://cds.climate.copernicus.eu/#!/home). All the analyses were performed in R 4.3.3, the codes used are available on GitHub at https://github.com/danddr/alboBelgium#.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMedlock JM, Hansford KM, Versteirt V, Cull B, Kampen H, Fontenille D, et al. An entomological review of invasive mosquitoes in Europe. 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(2025). + \u003cem\u003eParasites \u0026amp; Vectors\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e, 143.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDa Re, D., Marini, G., Bonannella, C., Laurini, F., Manica, M., Anicic, N., \u0026hellip; Ros\u0026agrave;,R. (2025). Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model. \u0026lt;background-color:;i\u0026gt;Scientific Reports\u0026lt;/background-color:;i\u0026gt;, \u0026lt;background-color:;i\u0026gt;15\u0026lt;/background-color:;i\u0026gt;(1), 3750.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Aedes albopictus, Europe, mechanistic model dynamAedes","lastPublishedDoi":"10.21203/rs.3.rs-7057895/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7057895/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eAedes albopictus\u003c/em\u003e, commonly known as the Asian tiger mosquito, is an invasive species of significant public health concern due to its ability to transmit dengue, chikungunya, and Zika viruses. Since arriving in Europe in the late 1970s, this mosquito species has progressively expanded its range, with Belgium marking an important step in its northward spread. The increasing frequency of its introduction raises the urgent question of whether \u003cem\u003eAe. albopictus\u003c/em\u003e could become permanently present in the country. This study investigates the potential for the establishment of \u003cem\u003eAe. albopictus\u003c/em\u003e populations in Belgium using a mechanistic model and assessing the likelihood of successful establishment based on simulated introduction events. Our results indicate that the probability of establishment is highest in Flanders, particularly under scenarios of early and multiple introductions during the summer months, even though the interannual climatic variability still plays a major role in contributing to the establishment success. The establishment of \u003cem\u003eAe. albopictus\u003c/em\u003e in Belgium would introduce new epidemiological risks, as the species could facilitate the transmission of non-native viruses during particularly warm summers. While the transmission windows may remain limited compared to Mediterranean regions, continued introductions and climate change could expand these periods, increasing the likelihood of local outbreaks.\u003c/p\u003e","manuscriptTitle":"A Warming Welcome? Belgium’s Increasing Suitability for Aedes albopictus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 13:56:03","doi":"10.21203/rs.3.rs-7057895/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-29T16:34:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-20T10:48:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46585006859997446793389705644521250722","date":"2025-07-24T14:37:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-24T10:04:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-10T14:40:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-10T10:47:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Parasites \u0026 Vectors","date":"2025-07-06T12:46:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"da5fb1d2-bf41-4d9b-a113-379157605b0b","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:06:59+00:00","versionOfRecord":{"articleIdentity":"rs-7057895","link":"https://doi.org/10.1186/s13071-025-07119-w","journal":{"identity":"parasites-and-vectors","isVorOnly":false,"title":"Parasites \u0026 Vectors"},"publishedOn":"2025-11-26 15:58:07","publishedOnDateReadable":"November 26th, 2025"},"versionCreatedAt":"2025-09-17 13:56:03","video":"","vorDoi":"10.1186/s13071-025-07119-w","vorDoiUrl":"https://doi.org/10.1186/s13071-025-07119-w","workflowStages":[]},"version":"v1","identity":"rs-7057895","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7057895","identity":"rs-7057895","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}