Biology subjects

Tildesley, M. J.

Publications and source records attributed to Tildesley, M. J..

11 recordsLinked to original sources

bioRxiv2026

A spatial transmission model for evaluating interventions during highly pathogenic avian influenza outbreaks

During infectious disease outbreaks, epidemiological models can be used to project future outbreak dynamics and to explore scenarios under different control measures. Here, we present the spatially explicit avian influenza transmission model that we developed during the 2026 WiLiMan-ID consortium Highly Pathogenic Avian Influenza Modelling Challenge, which involved evaluating control measures (preventive and reactive culling, confinement and restocking bans) during a hypothetical avian influenza outbreak. We show that the control measures that were expected to reduce transmission effectively varied between different outbreak stages. For example, policy-makers could choose whether to focus culling efforts on: i) faster reactive culling and no preventive culling; or ii) slower reactive culling and preventive culling. Relatively early in the outbreak, when the number of available culling teams was limited, our results indicate that the two culling strategies were projected to lead to similar numbers of premises with notified infections over the following 28 days. Later in the outbreak, with more culling teams available, the second strategy was projected to lead to substantially fewer notified premises than the first strategy. In addition, we demonstrate that whether a strategy is beneficial or detrimental depends on policy-makers' objectives. For example, preventive culling may reduce transmission, but at the cost of culling poultry on premises without infections, illustrating a trade-off between limiting transmission and the cost of interventions. Our results highlight the importance of choosing policy objectives carefully and reassessing interventions at different outbreak stages to ensure that control policies remain appropriate for the current epidemiological situation.

ecology↗

bioRxiv2025

Impacts of disease surveillance frequency on understanding and controlling Rift Valley fever virus

Effective livestock disease surveillance faces numerous socio-economic and disease-specific challenges, particularly within resource-limited settings. Rift Valley fever (RVF), a zoonotic vector-borne disease which is of growing threat to human and veterinary health, exemplifies these challenges, consequently leading to irregular or infrequent surveillance. While mathematical models frequently utilise these surveillance data to understand disease dynamics and assess the effectiveness of disease control measures, the impact of surveillance frequency on these model-based assessments is not clear. To address this, we used a livestock RVF virus infection model, which incorporates spatial and age structures, livestock movement, and environmental factors. We then generated synthetic cross-sectional seroprevalence surveys with varying frequencies from outbreak scenarios inferred from empirical serological data from the Comoros archipelago. By refitting the model to these synthetic data, we found that lower surveillance frequency was associated with increased uncertainties in understanding disease biology, inferring past outbreak timing, predicting future outbreak size, and recommending optimal control measures. In particular, once serological surveillance was less frequent than annually, the ability to distinguish spatio-temporal patterns of disease transmission and forecast trends diminished. These findings emphasise the need for adequately frequent surveillance data to ensure robust model-based analyses which inform effective preparedness and control strategies for livestock diseases within resource-limited settings. Author summaryDisease surveillance underpins mathematical models that are used to understand the emergence, spread and persistence of disease, and assess and compare the impacts of disease control measures. However, regular surveillance is a particular challenge for livestock diseases in resource-limited settings, such as those affected by Rift Valley fever. Here, our work provides an illustrative example of how surveillance frequency impacts our ability to understand disease outbreaks and to decide which control measures are most effective at combatting disease, using outbreak scenarios for Rift Valley fever in the Comoros archipelago. By simulating from a mathematical model informed by different surveillance frequencies, we found that less frequent surveillance was associated with greater uncertainty in model predictions, and demonstrated that this may distort epidemiological understanding and future control recommendations of a disease. Our work has crucial implications for animal health decision-making, highlighting the importance of consistent and frequent surveillance to improve disease management and prioritise disease control measures.

ecology↗

bioRxiv2025

The role of ducks in detecting Highly Pathogenic Avian Influenza in small-scale backyard poultry farms

Previous research efforts on highly pathogenic H5N1 avian influenza (HPAI) suggest that different avian species exhibit a varied severity of clinical signs after infection. Waterfowl, such as ducks or geese, can be asymptomatic and act as silent carriers of H5N1, making detection harder and increasing the risk of further transmission, potentially leading to significant economic losses. For backyard hobby farmers, passive reporting is a common HPAI detection strategy. We aim to quantify the effectiveness of this strategy by simulating the spread of H5N1 in a mixed-species, small-population backyard flock. Quantities such as detection time and undetected burden of infection in various scenarios are compared. Our results indicate that the presence of ducks can lead to a higher risk of an outbreak and a higher burden of infection. If most ducks within a flock are resistant to H5N1, detection can be significantly delayed. We find that within-flock infection dynamics can heavily depend on the species composition in backyard farms. Ducks, in particular, can pose a higher risk of transmission within a flock or between flocks. Our findings can help inform surveillance and intervention strategies at the flock and local levels. Author summaryWe addressed the gap in our understanding of within-flock transmission dynamics of H5N1, particularly for small-scale, backyard farms, where it is reasonably realistic for multiple species of birds to be housed together. These smaller flocks may differ from their larger, industrialised counterparts in their structure and management, and may play a key role in the persistence and spread of H5N1. Notably, we know from the literature that waterfowl, such as ducks, can be asymptomatic after contracting H5N1 and thus act as silent carriers of the virus, which could amplify the risk posed to other species of birds, mammals, and humans. We used a stochastic mechanistic model that accounted for such possibilities and simulated the possible outcomes of an outbreak. We found that while the presence of chickens is more likely to lead to high mortality upon infection, ducks can make H5N1 harder to detect within a flock, and thus cause a greater burden of infection, which increases the risk of potential between-flock and between-site transmissions. Our findings are consistent with the current literature and can help inform surveillance and control strategies.

zoology↗

bioRxiv2025

A modelling assessment for the impact of control measures on highly pathogenic avian influenza transmission in poultry in Great Britain

Since 2020, large-scale outbreaks of highly pathogenic avian influenza (HPAI) H5N1 in Great Britain have resulted in substantial poultry mortality and economic losses. Alongside the costs, the risk of circulation leading to a viral reassortment that causes zoonotic spillover raises additional concerns. However, the precise mechanisms driving transmission between poultry premises and the impact of potential control measures in Great Britain, such as vaccination, are not fully understood. We have developed a spatial transmission model for the spread of HPAI in poultry premises calibrated to infected premises data for the 2022-23 season using Markov chain Monte Carlo. Our results indicate that enhanced biosecurity measures and/or vaccination of the premises surrounding an identified infected premises can substantially reduce the overall number of infected premises. Our findings highlight that enhanced control measures could limit the future impact of HPAI on the poultry industry and reduce the risk of broader health threats.

systems biology↗

bioRxiv2024

A systematic review quantifying host feeding patterns of Culicoides species responsible for pathogen transmission

Culicoides biting midges are significant vectors of various pathogens, impacting both human and animal health globally. Understanding their host feeding patterns is crucial for deepening our understanding of disease transmission dynamics and developing effective control strategies. While several studies have identified the sources of blood meals in Culicoides, a quantitative synthesis of their host preferences and the factors influencing these behaviours is lacking. A systematic literature search focused on gathering data on (1) host selection and (2) host preference. For reviewing host selection we focused on studies reporting the identification of blood meal sources in individual Culicoides. When reviewing host preference we focused on studies comparing the number of Culicoides caught on or nearby different host species at the same location. Analysis revealed that some Culicoides species exhibit fixed host preferences, consistently feeding on specific hosts such as cattle and horses, while others display more opportunistic feeding behaviours. Notable variations were observed across different geographic regions. The findings indicate that host availability significantly influences Culicoides feeding patterns. This study highlights the complexity of host selection in Culicoides biting midges, which has implications for disease transmission. The variability in feeding behaviours underscores the need for regional assessments to inform targeted vector control strategies.

pathology↗

bioRxiv2024

Effectiveness and equity of vaccination strategies against Rift Valley fever in a heterogeneous landscape

Spatio-temporal variations in environment and socio-agricultural factors create heterogeneity in livestock disease transmission risk, raising challenges in identifying populations most at risk and how this risk changes over time. Consequently, prioritising control strategies, such as vaccination, to achieve optimal or equitable outcomes across regions impedes the design of an effective vaccination strategy. We developed a metapopulation model for Rift Valley fever transmission in livestock across the Comoros archipelago which incorporates livestock vaccination in addition to heterogeneity in viral transmission rates and animal movements. We used the model to evaluate three vaccine allocation strategies-proportional allocation, optimal allocation for maximising total infections averted across the archipelago, and optimal allocation for more equitable outcomes across islands--under different vaccination coverage levels and animal identification scenarios. We report that (i) both archipelago-wide and island-specific strategy effectiveness were impacted by vaccination rate, allocation strategy, and animal identification approach, (ii) optimally allocating vaccines improved strategy effectiveness compared with proportional allocation but resulted in inequitable outcomes between islands, and (iii) tagging animals post-vaccination boosted overall strategy effectiveness for all vaccination rates.

ecology↗

bioRxiv2024

Modelling the influence of climate and vector control interventions on arbovirus transmission

Most mathematical models that assess the vectorial capacity of disease-transmitting insects typically focus on the influence of climatic factors to predict variations across different times and locations, or examine the impact of vector control interventions to forecast their potential effectiveness. We combine features of existing models to develop a novel model for vectorial capacity that considers both climate and vector control. This model considers how vector control tools affect vectors at each stage of their feeding cycle and incorporates host availability and preference. Applying this model to arboviruses of veterinary importance in Europe, we show that African horse sickness virus (AHSV) has a higher peak predicted vectorial capacity than bluetongue virus (BTV), Schmallenberg virus (SBV) and epizootic haemorrhagic disease virus (EHDV). However, AHSV has a shorter average infectious period, due to high mortality, therefore AHSVs overall basic reproduction number is similar to BTV. A comparable relationship exists between SBV and EHDV, with both viruses showing similar basic reproduction numbers. Focusing on AHSV transmission in the UK, insecticide-treated stable netting is shown to significantly reduce vectorial capacity of Culicoides even at low coverage levels. However, untreated stable netting is likely to have limited impact. Overall, this model can be used to consider both climate and vector control interventions either currently utilised or for potential use in an outbreakand could help guide policy makers seeking to mitigate the impact of climate change on disease control. Author summaryIn our study, we developed an advanced mathematical model that integrates the influences of climate and vector control strategies to predict the transmission of arboviruses. This is then used to highlight the increase in vectorial capacity African horse sickness, bluetongue, epizootic haemorrhagic disease and Schmallenberg virus, which are transmitted by the Culi-coides species, in a European climate over the last 50 years. Our research provides valuable insights into how strategic use of insecticide-treated netting, even at low coverage levels, can substantially reduce the transmission potential of African horse sickness virus. This model offers a powerful tool for policymakers and health professionals, aiding in the formulation of more effective vector management strategies that could mitigate the impact of these diseases, especially in the context of changing global climates. This approach not only enhances our understanding of vector-borne disease dynamics but also supports the development of targeted interventions and prevent outbreaks.

ecology↗

bioRxiv2023

Identification of dynamical changes of rabies transmission under quarantine: community-based measures towards rabies elimination

Quarantine has been long used as a public health response to emerging infectious diseases, particularly at the onset of an epidemic when the infected proportion of a population remains identifiable and logistically tractable. In theory, the same logic should apply to low-incidence infections; however, the application and impact of quarantine in low prevalence settings appears less common and lacks a formal analysis. Here, we present a quantitative framework using a series of progressively more biologically realistic models of canine rabies in domestic dogs and from dogs to humans, a suitable example system to characterize dynamical changes under varying levels of dog quarantine. We explicitly incorporate health-seeking behaviour data to inform the modelling of contact-tracing and exclusion of rabies suspect and probable dogs that can be identified through bite-histories of patients presenting at anti-rabies clinics. We find that a temporary quarantine of rabies suspect and probable dogs provides a powerful tool to curtail rabies transmission, especially in settings where optimal vaccination coverage is yet to be achieved, providing a critical stopgap to reduce the number of human and animal deaths due to rabid bites. We conclude that whilst comprehensive measures including sensitive surveillance and large-scale vaccination of dogs will be required to achieve disease elimination and sustained freedom given the persistent risk of rabies re-introductions, quarantine offers a low-cost community driven solution to intersectoral health burden. Author summaryCanine rabies remains a human health risk in many countries around the world, particularly in lower and middle income settings where many dogs are free roaming and able to interact more easily with other dogs and humans. In this paper, we present results from a mathematical model that simulates the spread of rabies both between dogs and from dogs to humans and investigate the impact of quarantine and vaccination at reducing transmission. Our work demonstrates the effectiveness of quarantining both infected and exposed dogs - we observe that quarantine can have a substantial effect on reducing the number of new animals subsequently infected and thereby lowering the risk of humans being exposed to infection. Such a policy can have significant benefits, particularly in settings where access to vaccinations is challenging and resources are limited. Our research can therefore help to inform policy makers in countries where canine rabies is circulating to develop appropriate strategies to reduce the human health risks associated with canine rabies in the future.

ecology↗

bioRxiv2021

Drivers of Rift Valley fever virus persistence and the impact of control measures in a spatially heterogeneous landscape: the case of the Comoros archipelago, 2004-2015

Rift Valley fever (RVF) is one of the many zoonotic arboviral haemorrhagic fevers present in Africa. The ability of the pathogen to persist in multiple geographically distinct regions has raised concerns about its potential for spread to and persistence within currently disease-free areas. However, the mechanisms for which RVF virus persistence occurs at both local and broader geographical scales have yet to be fully understood and rigorously quantified. Here, we developed a mathematical metapopulation model describing RVF virus transmission in livestock across the four islands of the Comoros archipelago and fitted this model in a Bayesian framework to surveillance data conducted in livestock across those islands between 2004 and 2015. In doing so, we estimated the importance of island-specific environmental factors and animal movements between those islands on the persistence of RVF virus in the archipelago, and we further tested the impact of different control scenarios on reducing disease burden. We demonstrated that the archipelago network was able to sustain viral transmission over 10 years after assuming only one introduction event during early 2007. Movement restrictions were only useful to control the disease in Anjouan and Mayotte, as Grande Comore and Moheli were able to self-sustain RVF viral persistence, probably due to local environmental conditions that are more favourable for vectors. We also evidenced that repeated outbreaks during 2004-2020 may have gone under-detected by local surveillance in Grande Comore and Moheli. Strengthened longterm and coordinated surveillance would enable the detection of viral re-emergence and evaluation of different relevant vaccination programmes.

ecology↗

bioRxiv2018

Robustness of local control strategies under modelling uncertainties: the 2004 avian infuenza H5N1 outbreak in Thailand

The Highly Pathogenic Avian Influenza (HPAI) subtype H5N1 virus persists in many countries and has been circulating in poultry, wild birds. In addition, the virus has emerged in other species and frequent zoonotic spillover events indicate that there remains a significant risk to human health. It is crucial to understand the dynamics of the disease in the poultry industry to develop a more comprehensive knowledge of the risks of transmission and to establish a better distribution of resources when implementing control. In this paper, we develop a set of mathematical models that simulate the spread of HPAI H5N1 in the poultry industry in Thailand, utilising data from the 2004 epidemic. The model that incorporates the intensity of duck farming when assessing transmision risk provides the best fit to the spatiotemporal characteristics of the observed outbreak, implying that intensive duck farming drives transmission of HPAI in Thailand. We also extend our models using a sequential model fitting approach to explore the ability of the models to be used in \"real time\" during novel disease outbreaks. We conclude that, whilst predictions of epidemic size are estimated poorly in the early stages of disease outbreaks, the model accurately predicts the preferred control policy that should be deployed to minimise the impact of the disease.

epidemiology↗

bioRxiv2017

The impact of surveillance and control on highly pathogenic avian influenza outbreaks in poultry in Dhaka division, Bangladesh

In Bangladesh, the poultry industry is an economically and socially important sector, but it is persistently threatened by the effects of H5N1 highly pathogenic avian influenza. Thus, identifying the optimal control policy in response to an emerging disease outbreak is a key challenge for policy-makers. To inform this aim, a common approach is to carry out simulation studies comparing plausible strategies, while accounting for known capacity restrictions. In this study we perform simulations of a previously developed H5N1 influenza transmission model framework, fitted to two separate historical outbreaks, to assess specific control objectives related to the burden or duration of H5N1 outbreaks among poultry farms in the Dhaka division of Bangladesh. In particular, we explore the optimal implementation of ring culling, ring vaccination and active surveillance measures when presuming disease transmission predominately occurs from premises-to-premises, versus a setting requiring the inclusion of external factors. Additionally, we determine the sensitivity of the management actions under consideration to differing levels of capacity constraints and outbreaks with disparate transmission dynamics. While we find that reactive culling and vaccination policies should pay close attention to these factors to ensure intervention targeting is optimised, across multiple settings the top performing control action amongst those under consideration were targeted proactive surveillance schemes. Our findings may advise the type of control measure, plus its intensity, that could potentially be applied in the event of a developing outbreak of H5N1 amongst originally H5N1 virus-free commercially-reared poultry in the Dhaka division of Bangladesh.

epidemiology↗