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• Journal article
  Tornimbene B, Leiva Rioja ZB, Aderinola O, Cucunubá ZM, González-Uribe C, Mihailov D, Riley S, Tak SW, Morgan Oet al., 2025,

  Pathways to strengthening the epidemic intelligence workforce

  , BMC Proceedings, Vol: 19

  The evolving landscape of public health surveillance demands a proficient and diverse workforce adept in data science and analysis. This report summarises discussions from the third session of the WHO Pandemic and Epidemic Intelligence Innovation Forum, focusing on workforce readiness and technological advancements in epidemic intelligence. The forum emphasizes the necessity of multidisciplinary surveillance teams equipped with advanced data skills. Digital tools play a transformative role in data collection and analysis, enabling real-time tracking, integration, and interpretation of diverse data sources. However, effective surveillance relies on inclusive representation and skill development. Collaborative surveillance and interdisciplinary training programs were emphasized as critical pathways to enhance workforce capacity, decision-making, and equity in public health. Case studies from Nigeria, Korea, the UK, and Colombia showcase the role of digital tools and contextual expertise in addressing surveillance gaps. Sustained institutional support, cross-sector partnerships, and investments in data literacy and workforce development are pivotal for creating resilient and inclusive public health systems.

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• Journal article
  Ahmed AN, Fornace KM, Iwamura T, Murray KAet al., 2025,

  Human animal contact, land use change and zoonotic disease risk: a protocol for systematic review

  , Systematic Reviews, Vol: 14

  Background: Zoonotic diseases pose a significant risk to human health globally. The interrelationship between humans, animals, and the environment plays a key role in the transmission of zoonotic infections. Human-animal contact (HAC) is particularly important in this relationship, where it serves as the pivotal interaction for pathogen spillover to occur from an animal reservoir to a human. In the context of disease emergence linked to land-use change, increased HAC as a result of land changes (e.g., deforestation, agricultural expansion, habitat degradation) is frequently cited as a key mechanism. We propose to conduct a systematic literature review to map and assess the quality of current evidence linking changes in HAC to zoonotic disease emergence as a result of land-use change. Method: We developed a search protocol to be conducted in eight (8) databases: Medline, Embase, Global Health, Web of Science, Scopus, AGRIS, Africa-Wide Info, and Global Index Medicus. The review will follow standard systematic review methods and will be reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. The search will consist of building a search strategy, database search, and a snowballing search of references from retrieved relevant articles. The search strategy will be developed for Medline (through PubMed) and EMBASE databases. The search strategy will then be applied to all eight (8) databases. Retrieved articles will be exported to EndNote 20 where duplicates will be removed and exported to Rayyan®, to screen papers using their title and abstract. Screening will be conducted by two independent reviewers and data extraction will be performed using a data extraction form. Articles retrieved will be assessed using study quality appraisal tools (OHAT-Office for Health Assessment and Technology Risk of Bias Rating Tool for Human and Animal Studies, CCS-Case Control Studies, OCCSS-Observational Cohort and Cross-Sectio

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• Journal article
  De Nardi A, Marini G, Dorigatti I, Rosà R, Tamba M, Gelmini L, Prosperi A, Menegale F, Poletti P, Calzolari M, Pugliese Aet al., 2025,

  Quantifying West Nile virus circulation in the avian host population in Northern Italy.

  , Infect Dis Model, Vol: 10, Pages: 375-386

  West Nile virus (WNV) is one of the most threatening mosquito-borne pathogens in Italy where hundreds of human cases were recorded during the last decade. Here, we estimated the WNV incidence in the avian population in the Emilia-Romagna region through a modelling framework which enabled us to eventually assess the fraction of birds that present anti-WNV antibodies at the end of each epidemiological season. We fitted an SIR model to ornithological data, consisting of 18,989 specimens belonging to Corvidae species collected between 2013 and 2022: every year from May to November birds are captured or shot and tested for WNV genome presence. We found that the incidence peaks between mid-July and late August, infected corvids seem on average 17% more likely to be captured with respect to susceptible ones and seroprevalence was estimated to be larger than other years at the end of 2018, consistent with the anomalous number of recorded human infections. Thanks to our modelling study we quantified WNV infection dynamics in the corvid community, which is still poorly investigated despite its importance for the virus circulation. To the best of our knowledge, this is among the first studies providing quantitative information on infection and immunity in the bird population, yielding new important insights on WNV transmission dynamics.

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• Journal article
  Morgenstern C, Rawson T, Hinsley W, Perez Guzman P, Bhatt S, Ferguson Net al., 2025,

  Socioeconomic and temporal heterogeneity in SARS-CoV-2 exposure and disease in England from May 2020 to February 2023

  , Science Advances, ISSN: 2375-2548
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• Journal article
  Jombart T, 2025,

  Contrasting the impact and cost-effectiveness of successive intervention strategies in response to Ebola in the Democratic Republic of the Congo, 2018-2020

  , BMJ Global Health, ISSN: 2059-7908
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• Journal article
  Lim A, Shearer FM, Sewalk K, Pigott DM, Clarke J, Ghouse A, Judge C, Kang H, Messina JP, Kraemer MUG, Gaythorpe KAM, de Souza WM, Nsoesie EO, Celone M, Faria N, Ryan SJ, Rabe IB, Rojas DP, Hay SI, Brownstein JS, Golding N, Brady OJet al., 2025,

  The overlapping global distribution of dengue, chikungunya, Zika and yellow fever

  , Nature Communications, Vol: 16

  <jats:title>Abstract</jats:title> <jats:p>Arboviruses transmitted mainly by <jats:italic>Aedes</jats:italic> (<jats:italic>Stegomyia</jats:italic>) <jats:italic>aegypti</jats:italic> and <jats:italic>Ae. albopictus</jats:italic>, including dengue, chikungunya, and Zika viruses, and yellow fever virus in urban settings, pose an escalating global threat. Existing risk maps, often hampered by surveillance biases, may underestimate or misrepresent the true distribution of these diseases and do not incorporate epidemiological similarities despite shared vector species. We address this by generating new global environmental suitability maps for <jats:italic>Aedes</jats:italic>-borne arboviruses using a multi-disease ecological niche model with a nested surveillance model fit to a dataset of over 21,000 occurrence points. This reveals a convergence in suitability around a common global distribution with recent spread of chikungunya and Zika closely aligning with areas suitable for dengue. We estimate that 5.66 (95% confidence interval 5.64-5.68) billion people live in areas suitable for dengue, chikungunya and Zika and 1.54 (1.53-1.54) billion people for yellow fever. We find large national and subnational differences in surveillance capabilities with higher income more accessible areas more likely to detect, diagnose and report viral diseases, which may have led to overestimation of risk in the United States and Europe. When combined with estimates of uncertainty, these suitability maps can be used by ministries of health to target limited surveillance and intervention resources in new strategies against these emerging threats.</jats:p>

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• Book chapter
  Kaupp LM, Muchemwa D, Skovdal M, Magoge-Mandizvidza P, Maswera R, Gregson S, Nyamukapa Cet al., 2025,

  How young Zimbabwean men's attitudes towards female PrEP use depend on gender norms

  , Young Masculinities and Sexual Health in Southern Africa, Publisher: Routledge, Pages: 231-245
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• Journal article
  Bhatt S, Coupland H, Scheidwasser N, Katsiferis A, Davies M, Flaxman S, Hulvej Rod N, Mishra S, Unwin HJTet al., 2025,

  Exploring the Potential and Limitations of Deep Learning and Explainable AI for Longitudinal Life Course Analysis

  , BMC Public Health, ISSN: 1471-2458

  Background: Understanding the complex interplay between life course exposures, such as adverse childhood experiences and environmental factors, and disease risk is essential for developing effective public health interventions. Traditional epidemiological methods, such as regression models and risk scoring, are limited in their ability to capture the non-linear and temporally dynamic nature of these relationships. Deep learning (DL) and explainable artificial intelligence (XAI) are increasingly applied within healthcare settings to identify influential risk factors and enable personalised interventions. However, significant gaps remain in understanding their utility and limitations, especially for sparse longitudinal life course data and how the influential patterns identified using explainability are linked to underlying causal mechanisms.Methods: We conducted a controlled simulation study to assess the performance of various state-of-the-art DL architectures including CNNs and (attention-based) RNNs against XGBoost and logistic regression. Input data was simulated to reflect a generic and generalisable scenario with different rules used to generate multiple realistic outcomes based upon epidemiological concepts. Multiple metrics were used to assess model performance in the presence of class imbalance and SHAP values were calculated. Results: We find that DL methods can accurately detect dynamic relationships that baseline linear models and tree-based methods cannot. However, there is no one model that consistently outperforms the others across all scenarios. We further identify the superior performance of DL models in handling sparse feature availability over time compared to traditional machine learning approaches. Additionally, we examine the interpretability provided by SHAP values, demonstrating that these explanations often misalign with causal relationships, despite excellent predictive and calibrative performance.Conclusions: These insights provide a founda

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• Book chapter
  Bagnay S, Skovdal M, Maswera R, Moorhouse L, Magoge-Mandizvidza P, Moyo B, Gregson S, Nyamukapa Cet al., 2025,

  Masculine norms and sexual health implications for young men in Zimbabwe

  , Young Masculinities and Sexual Health in Southern Africa, Publisher: Routledge, Pages: 77-94
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• Journal article
  Stopard I, Sanou A, Suh E, Cator LJC, Thomas MB, Guelbéogo WM, Sagnon N, Lambert B, Churcher TSet al., 2025,

  Modelling the effects of diurnal temperature variation on malaria infection dynamics in mosquitoes

  , Communications Biology, ISSN: 2399-3642
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