William Wint

BACKGROUND: Advanced outbreak analytics were instrumental in informing governmental decision-making during the COVID-19 pandemic. However, systematic evaluations of how modelling practices, data use and science–policy interactions evolved during this and previous emergencies remain scarce. AIM: This study assessed the evolution of modelling practices, data usage, gaps, and engagement between modellers and decision-makers to inform future global epidemic intelligence. METHODS: We conducted a two-stage semiquantitative survey among modellers in a large European epidemic intelligence consortium. Responses were analysed descriptively across early, mid- and late-pandemic phases. We used policy citations in Overton to assess policy impact. RESULTS: Our sample included 66 modelling contributions from 11 institutions in four European countries. COVID-19 modelling initially prioritised understanding epidemic dynamics; evaluating non-pharmaceutical interventions and vaccination impacts later became equally important. Traditional surveillance data (e.g. case line lists) were widely available in near-real time. Conversely, real-time non-traditional data (notably social contact and behavioural surveys) and serological data were frequently reported as lacking. Gaps included poor stratification and incomplete geographical coverage. Frequent bidirectional engagement with decision-makers shaped modelling scope and recommendations. However, fewer than half of the studies shared open-access code. CONCLUSIONS: We highlight the evolving use and needs of modelling during public health crises. Persistent gaps in the availability of non-traditional data underscore the need to rethink sustainable data collection and sharing practices, including from for-profit providers. Future preparedness should focus on strengthening collaborative platforms, research consortia and modelling networks to foster data and code sharing and effective collaboration between academia, decision-makers and data providers.

As the first chikungunya vaccines become available, estimates of their cost-effectiveness are needed. We developed a modelling framework to project the health-economic burden of chikungunya across 31 countries. We simulated several preventive vaccination campaigns and estimated threshold vaccination costs as the cumulative societal costs averted per vaccine dose. From 2025 to 2050, we projected a cumulative 5.96 million (5.10 million-6.93 million) DALYs and $76.5 billion ($57.4 billion-$95.7 billion) societal costs. A five-year population-wide campaign targeting 50% of individuals aged ≥12 years, followed by a ten-year annual routine adolescent vaccination programme, averted 681,000 (569,000-802,000) DALYs and $11.8 billion ($8.73 billion-$14.9 billion) societal costs. Standalone population-wide campaigns were the most cost-effective, with threshold vaccination costs ranging from $1.11 ($0.77-$1.44) in the Democratic Republic of Congo to $48.1 ($36.0-$60.3) in Panama. Preventive deployment of a chikungunya vaccine with a favourable safety profile could substantially reduce the future burden of chikungunya across endemic settings.

In Europe, Lyme borreliosis is the most common vector-borne human disease, caused mainly by Borrelia afzelii and Borrelia garinii , two species of the Borrelia burgdorferi sensu lato (Bbsl) complex transmitted by the tick Ixodes ricinus . Accurately assessing the spatial risk of human exposure to these pathogens is essential for efficient public health surveillance. However conventional monitoring often struggles to produce geographically explicit, large-scale data that capture the heterogeneity of human exposure and its drivers. Focusing on continental France, we leveraged data from the French CiTIQUE citizen science programme to analyse spatial variation of Bbsl infection in georeferenced human-biting I. ricinus ticks and to model the relationship between Bbsl distribution and environmental, ecological, and anthropogenic factors. From 2017–2019, 1,891 ticks were analysed, of which 15% tested positive for Bbsl. The most prevalent genospecies were B. afzelii (7.2%) and B. garinii (4.2%). Infection rates varied spatially, with distinct distribution patterns across pathogen groups. Tick habitat suitability was the most consistent predictor for overall Bbsl infection probability, genospecies-specific models revealed the importance of their respective reservoir hosts: B. afzelii occurrence was positively associated with rodent species richness, whereas B. garinii was associated with Turdidae species and showed potential traces of a dilution effect due to rodents. Our findings demonstrate the value of citizen science for complementing formal surveillance and provide the first geographically explicit, large-scale insights into Bbsl eco-epidemiology in France. This scalable approach offers an adaptable framework for monitoring vector-borne disease risk and guiding public health strategies. Importance: Lyme borreliosis, caused by Borrelia burgdorferi sensu lato, is the most common human vector-borne disease in Europe. Accurate assessment of spatial exposure risk is essential for effective public health surveillance and interventions. Using data from the French CiTIQUE citizen science program, we reveal pathogen-specific spatial patterns and identify the factors shaping them, at a geographic resolution not previously studied. Our findings demonstrate that citizen science can provide a scalable and adaptive framework for long-term surveillance of vector-borne disease risk, offering valuable insights to guide targeted prevention and control measures.

Introduction: Advanced outbreak analytics played a key role in governmental decision-making as the COVID-19 pandemic challenged health systems globally. This study assessed the evolution of European modelling practices, data usage, gaps, and interactions between modellers and decision-makers to inform future investments in epidemic-intelligence globally. Methods: We conducted a two-stage semi-quantitative survey among modellers in a large European epidemic-intelligence consortium. Responses were analysed descriptively across early, mid-, and late-pandemic phases. Policy citations in Overton were used to assess the policy impact of modelling. Findings: Our sample included 66 modelling contributions from 11 institutions in four European countries. COVID-19 modeling initially prioritised understanding epidemic dynamics, while evaluating non-pharmaceutical interventions and vaccination impacts became equally important in later phases. ‘Traditional’ surveillance data (e.g. case linelists) were widely used in near-real time, while real-time non-traditional data (notably social contact and behavioural surveys), and serological data were frequently reported as lacking. Data limitations included insufficient stratification and geographical coverage. Interactions with decision-makers were commonplace and informed modelling scope and, vice versa, supported recommendations. Conversely, fewer than half of the studies shared open-access code. Interpretation: We highlight the evolving use and needs of modelling during public health crises. The reported missing of non-traditional surveillance data, even two years into the pandemic, underscores the need to rethink sustainable data collection and sharing practices, including from for-profit providers. Future preparedness should focus on strengthening collaborative platforms, research consortia and modelling networks to foster data and code sharing and effective collaboration between academia, decision-makers, and data providers.

In the frame of the entomological VectorNet network and its capacity building activities, we collected original mosquito distribution data in southern Poland and bordering areas of the Czech Republic, Germany and Slovakia, in June and September–November 2023. Because of the suspected occurrence of Aedes japonicus or Ae. koreicus in Poland, provided by a photo posted early 2022 on iNaturalist, we targeted the exotic Aedes species in our sampling strategy, but also collected data on other mosquito species. Besides some adult catches, we mainly collected mosquito immature stages from artificial and natural water containers but occasionally from other aquatic habitats. In addition, we collated citizen data and modelled the distribution of Ae. japonicus in Europe incorporating the newly collected data. During this snapshot field study, a total of 162 samples, including 139 yielding mosquitoes, were taken from 111 locations across 47 administrative units, resulting on the detection of 22 mosquito taxa. Our study provides the first substantiated records of Ae. japonicus and Anopheles petragnani in Poland (the second confirmed by molecular identification). While Ae. japonicus is clearly established over a large part of the country, no other exotic mosquito species was detected. The presence of Ae. japonicus was also confirmed at one location by four citizen records submitted to MosquitoAlert in 2023. Regarding native mosquitoes, we identified their presence in 127 species/NUTS3 combinations (113 for Poland, including a single record for An. petragnani). An updated modelling of the distribution of Ae. japonicus suggests higher environment suitability in Central and Eastern Europe than has been previously estimated. Aedes japonicus is probably widespread in the Czech Republic and Slovakia, and might soon colonise the bordering region of Ukraine. Its establishment extends the putative mosquito vector list for West Nile and Rift Valley fever viruses in Central Europe.

Sand flies are vectors of Leishmania spp. protozoa, phleboviruses and Bartonella bacilliformis. In this study we surveyed areas of central-western Europe, encompassing the northern limit of the known sand fly distribution, and investigated the relationship between their presence and environmental variables. In this area, very limited occurrence data exists, none of them recent. Sampling was performed in July and August 2023 using CDC-light traps, sticky traps and human landing captures, at 179 selected sites in 48 municipalities. A total of 55 sand fly specimens were collected at 11% (20/179) of the sites sampled – including 16 sites in France, 2 in Luxembourg and 1 in Germany – comprising the first published records for Luxembourg and the Trier-Saarburg County of Germany. No sand flies were detected in Belgium or in the Netherlands. Two species were captured: Phlebotomus mascittii (37 females, 2 males) and Ph. perniciosus (1 female, 15 males). The latter species was only found in Savoie, the southernmost region sampled in France, while the former species was detected as far north as latitude 50°N. Logistic regression modelling indicated that the probability of sand fly presence gradually decreased with increasing latitude and altitude (P < 0.05), and it was not associated to other analysed landscape features in the proximity of the traps. The study confirms and provides new evidence for the presence of sand flies in areas of Western Europe and highlights the need to be aware of potential autochthonous transmission of sand fly-borne pathogens in these areas.

West Nile virus (WNV) is an emerging mosquito-borne pathogen in Europe where it represents a new public health threat. While climate change has been cited as a potential driver of its spatial expansion on the continent, a formal evaluation of this causal relationship is lacking. Here, we investigate the extent to which WNV spatial expansion in Europe can be attributed to climate change while accounting for other direct human influences such as land-use and human population changes. To this end, we trained ecological niche models to predict the risk of local WNV circulation leading to human cases to then unravel the isolated effect of climate change by comparing factual simulations to a counterfactual based on the same environmental changes but a counterfactual climate where long-term trends have been removed. Our findings demonstrate a notable increase in the area ecologically suitable for WNV circulation during the period 1901–2019, whereas this area remains largely unchanged in a no-climate-change counterfactual. We show that the drastic increase in the human population at risk of exposure is partly due to historical changes in population density, but that climate change has also been a critical driver behind the heightened risk of WNV circulation in Europe.

Crimean–Congo haemorrhagic fever (CCHF) is considered to be spreading across the globe, with many countries reporting new human CCHF cases in recent decades including Georgia, Türkiye, Albania, and, most recently, Spain. We update a human CCHF distribution map produced in 2015 to include global disease occurrence records to June 2022, and we include the recent records for Europe. The predicted distributions are based on long-established spatial modelling methods and are extended to include all European countries and the surrounding areas. The map produced shows the environmental suitability for the disease, taking into account the distribution of the most important known and potential tick vectors Hyalomma marginatum and Hyalomma lusitanicum, without which the disease cannot occur. This limits the disease’s predicted distribution to the Iberian Peninsula, the Mediterranean seaboard, along with Türkiye and the Caucasus, with a more patchy suitability predicted for inland Greece, the southern Balkans, and extending north to north-west France and central Europe. These updated CCHF maps can be used to identify the areas with the highest probability of disease and to therefore target areas where mitigation measures should currently be focused.

Background: Arthropod vectors such as ticks, mosquitoes, sandflies and biting midges are of public and veterinary health significance because of the pathogens they can transmit. Understanding their distributions is a key means of assessing risk. VectorNet maps their distribution in the EU and surrounding areas. Aim: We aim to describe the methodology underlying VectorNet maps, encourage standardisation and evaluate output. Method: s: Vector distribution and surveillance activity data have been collected since 2010 from a combination of literature searches, field-survey data by entomologist volunteers via a network facilitated for each participating country and expert validation. Data were collated by VectorNet members and extensively validated during data entry and mapping processes. Results: As of 2021, the VectorNet archive consisted of ca 475,000 records relating to > 330 species. Maps for 42 species are routinely produced online at subnational administrative unit resolution. On VectorNet maps, there are relatively few areas where surveillance has been recorded but there are no distribution data. Comparison with other continental databases, namely the Global Biodiversity Information Facility and VectorBase show that VectorNet has 5–10 times as many records overall, although three species are better represented in the other databases. In addition, VectorNet maps show where species are absent. VectorNet’s impact as assessed by citations (ca 60 per year) and web statistics (58,000 views) is substantial and its maps are widely used as reference material by professionals and the public. Conclusion: VectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.