Biology subjects

Hobbs, N. P.

Publications and source records attributed to Hobbs, N. P..

7 recordsLinked to original sources

bioRxiv2025

GLOWORM-META: Modelling gastrointestinal nematode metapopulation dynamics to inform cattle biosecurity research

Gastrointestinal nematode (GIN) parasite infections in grazing livestock cause significant disease, and are responsible for estimated annual losses of over {euro}1.8 billion in Europe alone. The management of GINs in cattle is threatened by anthelmintic drug resistance (AR). Immediate action is needed to slow the progression of AR in cattle GINs and avoid the increasingly common scenario of multiple drug resistance seen in sheep. Although AR can arise independently on multiple farms, it may also be spread between holdings via purchased cattle. Therefore, effective biosecurity measures on cattle enterprises could help to reduce the risk of establishment of AR populations. A metapopulation model was developed and validated for two GIN species infecting cattle, Ostertagia ostertagi and Cooperia oncophora, incorporating the full parasite life cycle, weather- and immunity-dependent parasite life history traits and multiple pasture sub-populations. This allowed for complex grazing management strategies and weather influences to be simulated. The models successfully replicated the seasonal patterns and intensity of infections reported in multiple published longitudinal datasets. Global sensitivity analysis against four Quantities of Interest (QoIs) related to factors affecting the safety of the resident herd and of the purchased animals was used to quantify the influence of candidate biosecurity measures. The duration of quarantine, the date of purchase (weather/seasonal influences) and the intensity of infection on the day of purchase strongly influenced the QoIs. The outcomes for the UK were not significantly influenced by the geographic location of the purchasing farm, suggesting that the influence of weather patterns on GIN populations outweighs that of regional climate differences, and thus regional variations to GIN biosecurity recommendations are not warranted without alternative evidence to support this. The model presented here is the first full lifecycle GIN metapopulation model for O. ostertagi and C. oncophora, validated against longitudinal field data, and can be broadly used to evaluate the relative efficacy of a range of cattle GIN management strategies, as demonstrated here. These findings offer valuable insights to focus initial biosecurity recommendations for cattle enterprises, and are being used to direct qualitative and quantitative research to refine recommendations. HighlightsO_LIA metapopulation model for cattle GINs was developed C_LIO_LIThe model includes weather-dependence and complex grazing C_LIO_LIThe model replicated seasonal infection patterns from multiple datasets C_LIO_LISensitivity analysis explored influential biosecurity measures C_LIO_LIThe influence of weather outweighed that of geographic location (climate) C_LIO_LIInitial recommendations for biosecurity and further research are made C_LI

ecology↗

bioRxiv2024

Household level insecticide deployments (micro-mosaics) for insecticide resistance management: Evaluating deliberate and accidental deployments

Mixtures of two insecticides in a single formulation at full-dose are frequently evaluated as the "best" insecticide resistance (IRM) strategy in public health. However, this requires both insecticides to be mixed together in a single formulation which may not be possible or practical. Deploying different insecticides in different households ("micro-mosaics") may allow for mosquitoes to encounter different insecticides in subsequent gonotrophic cycles obtaining a "temporal mixture". We evaluate micro-mosaics considering their deliberate use and their accidental use using a mathematical model assuming polygenic resistance. Deliberate micro-mosaics are evaluated against rotations and mixtures (full-dose or half-dose) over a range of scenarios allowing for cross resistance and insecticide decay on their ability to slow the development of resistance. Accidental micro-mosaics are evaluated to understand the implication of mixture insecticide-treated nets (ITNs) and standard (pyrethroid only) ITNs being deployed alongside one another on the development of resistance across a range of initial resistance scenarios. Deliberate micro-mosaics are found to not differ substantially in their IRM capability from either rotations or half-dose mixtures. When micro-mosaics do outperform rotations or half-dose mixtures the benefit is often small. Micro-mosaics are found to perform worse than full-dose mixtures. Accidental micro-mosaics are found to reduce the ability of mixtures to slow the development of resistance. The deployment of deliberate micro-mosaics was found to not be beneficial versus rotations or mixtures indicating this strategy should not be pursued. Micro-mosaics occurring accidentally due to multiple distribution channels inhibits the effectiveness of mixture ITNs in slowing the development of resistance. Where mixture ITNs are used keep the coverage of the mixture high relative to standard (pyrethroid-only) ITNs is key.

evolutionary biology↗

bioRxiv2024

Combinations of Insecticide-Treated Nets and Indoor Residual Spraying for Insecticide Resistance Management: A Modelling Exploration

Insecticides are heavily used for the control of vectors of disease. Malaria control has been reliant on insecticide treated nets (ITNs) and indoor residual spraying (IRS). There are concerns insecticide resistance will impede malaria control. The use of insecticide resistance management (IRM) strategies is recommended. One proposed IRM strategy is the combination of ITNs and IRS. Using a mathematical model of polygenic insecticide resistance evolution, this combination strategy is evaluated. First, combinations are evaluated against ITNs alone to determine if and when combinations may be beneficial in slowing resistance evolution to the pyrethroid on the ITN. Second combinations where multiple IRS insecticides are available are compared against full-dose mixture ITNs. Results of the simulations indicate the addition of IRS to ITNs may be beneficial, providing coverage of both interventions is high. The greater number IRS insecticides available for rotation the better, however even when combinations rotate three different IRS insecticides this is still a less potent IRM strategy than deploying full-dose mixtures. In conclusion the combination of ITNs and IRS appears to offer limited benefit over full-dose mixture ITNs for an IRM perspective

evolutionary biology↗

bioRxiv2024

Exploring operational requirements of mixtures for insecticide resistance management in public health using a mathematical model assuming polygenic resistance.

Long-lasting insecticide treated nets (LLINs) have been developed which contain two active ingredients. Mixture products for vector control are now an available insecticide resistance management (IRM) strategy. There is a theoretical concern around the use mixtures pertaining to dosing, insecticide decay, initial resistance, and cross resistance. Mixture LLINs all currently have a pyrethroid as one of the partner insecticides. Using previously described mathematical models of polygenic insecticide resistance evolution, which implement selection either by truncation ("polytrucate) or as a probabilistic process ("polysmooth") mixtures are evaluated for their IRM potential. Scenarios are developed to explore the impact of the initial levels of resistance to the pyrethroid insecticide, insecticide decay rates, and insecticide doses, and cross resistance. Results from our simulations indicate that mixtures should be deployed at full doses. As the initial level of resistance to the pyrethroid increases the benefit of mixture decreases. Insecticide decay was found to be less important than might be thought, with other variables having a greater impact. The mechanism of selection demonstrated consistent results, diverging only at very high levels of resistance to the pyrethroid. Our simulations demonstrate that the impact of positive cross resistance is best mitigated using full-dose mixtures. Insecticide decay less important than previously considered, and opens up the opportunity to mix a wider variety of insecticides. However, as mixtures remain a challenge to develop and therefore strategies which could generate an effect of a "temporal" mixture should be evaluated.

evolutionary biology↗

bioRxiv2024

The impact of insecticide decay on the rate of insecticide resistance evolution for monotherapies and mixtures.

The issue of insecticide decay in the public health deployments of insecticides is frequently highlighted as an issue for disease control. There are additional concerns insecticide decay also impacts the selection for insecticide resistance. Despite these concerns insecticide decay is lacking from models evaluating insecticide resistance management strategies. The impact of insecticide decay is modelled using a model which assumes a polygenic basis of insecticide resistance. Single generation selection events covering the insecticide efficacy and insecticide resistance space for both monotherapies and mixtures are conducted. With the outcome being the between generation change in the bioassay survival to the insecticides. The monotherapy sequence strategy and mixture strategy were compared against each other when including insecticide decay, with the outcome being the difference in strategy lifespan. The results demonstrate that as insecticides decay, they can apply a greater selection pressure than newly deployed insecticides, a process which can occur for both monotherapies and mixtures. For mixtures, it is seen that the rate of selection is highest when both insecticides are at reduced efficacies which would occur if reduced dose mixtures were used. Inclusion of insecticide decay in simulations was found to reduce the benefit of mixtures against monotherapy sequences, and this is especially so when reduced-dose mixtures are used. Insecticide decay is often highlighted as an important consideration for mixtures. The inclusion of insecticide decay in models is often lacking, and these results indicate this is absence may be over-inflating the performance of full-dose mixtures. As insecticides decay, they still provide selection pressures with reduced ability to control transmission, replenishing worn-out insecticides more frequently should be considered.

evolutionary biology↗

bioRxiv2024

Mathematical Methodology for Dynamic Models of Insecticide Selection Assuming a Polygenic Basis of Resistance

Mathematical models for evaluating insecticide resistance management (IRM) have primarily assumed insecticide resistance (IR) is monogenic. Modelling using a quantitative genetics framework to model polygenic IR has less frequently been used. We introduce a complex mathematical model for polygenic IR with a focus on public health insecticide deployments for vector control. Conventional polygenic models assume selection differentials are constant over the course of selection. We instead propose calculating the selection differentials dynamically depending on the level of IR and the amount of insecticide encountered. Dynamically calculating the selection differentials increases biological and operational realism, allowing for the evaluation of strategies of policy relevance, including reduced dose mixtures or the deployment of long-lasting insecticide-treated nets and indoor residual spraying in combination. The dynamic calculations of insecticide selection allow for two methods: 1) Truncation ("polytruncate") - where only the most resistant individuals in the population survive, and 2) Probabilistic ("polysmooth") - where an individuals survival probability is dependent on their own level of IR. We describe in detail the calculation and calibration of these models. The models ("polytruncate" and "polysmooth") are compared against a previous polygenic model ("polyres") and the monogenic literature for the IRM strategies of rotations, sequences and full-dose mixtures. We demonstrate consistency in results of full-dose mixtures remaining the best IRM strategy, with sequences and rotations being similar in their efficacy between the two selection processes, and consistency in "global conclusions" with previous models. Consistency between the "polysmooth", "polytruncate" and previous models helps provide confidence in their predictions, as operational interpretations are not overly impacted by model assumptions. This increases confidence in the application of these dynamic models to investigate more complex IRM strategies and scenarios, and their future applications will investigate more scenario specific evaluations of IRM strategies.

evolutionary biology↗

bioRxiv2022

Insecticide resistance management strategies for public health control of mosquitoes exhibiting polygenic resistance: a comparison of sequences, rotations, and mixtures.

Malaria control uses insecticides to kill Anopheles mosquitoes. Recent successes in malaria control are threatened by increasing levels of insecticide resistance (IR), requiring insecticide resistance management (IRM) strategies to mitigate this problem. Field trials of IRM strategies are usually prohibitively expensive with long timeframes, and mathematical modelling is often used to evaluate alternative options. Previous IRM models in the context of malaria control assumed IR to have a simple (monogenic) basis, whereas in natural populations, IR will often be a complex polygenic trait determined by multiple genetic variants. A quantitative genetics model was developed to model IR as a polygenic trait. The model allows insecticides to be deployed as sequences (continuous deployment until a defined withdrawal threshold, termed "insecticide lifespan", as indicated by resistance diagnosis in bioassays), rotations (periodic switching of insecticides), or full-dose mixtures (two insecticides in one formulation). These IRM strategies were compared based on their "strategy lifespan" (capped at 500 generations). Partial rank correlation and generalised linear modelling was used to identify and quantify parameters driving the evolution of resistance. Random forest models were used to identify parameters offering predictive value for decision-making. Deploying single insecticides as sequences or rotations usually made little overall difference to their "strategy lifespan", though rotations displayed lower mean and peak resistances. Deploying two insecticides in a full-dose mixture formulation was found to extend the "strategy lifespan" when compared to deploying each in sequence or rotation. This pattern was observed regardless of the level of cross resistance between the insecticides or the starting level of resistance. Statistical analysis highlighted the importance of insecticide coverage, cross resistance, heritability, and fitness costs for selecting an appropriate IRM strategy. Full-dose mixtures appear the most promising of the strategies evaluated, with the longest "strategy lifespans". These conclusions broadly corroborate previous results from monogenic models. Author SummaryInsecticides impregnated into bed-nets or sprayed on walls are used to kill the Anopheles mosquitoes which transmit malaria. Unfortunately, the usage of insecticides has inevitably led to mosquitoes evolving resistance to the toxic effect of these insecticides. Insecticide resistance management strategies may be used to slow the rate of resistance evolution, however which strategies are effective, and when they are effective, is often unclear. Previous models evaluating insecticide resistance management strategies have assumed resistance is encoded by a single gene (is a monogenic trait). However, in natural populations resistance may be determined by multiple genes (is a polygenic trait). It is unclear whether such increased model complexity may change predictions We modelled resistance as a polygenic trait and found little difference in the benefit between rotating insecticides regularly versus deploying continuously until resistance reaches a critical threshold then switching. In contrast, mixtures combining two insecticides extended the projected lifespan of the insecticides, even when they share resistance mechanisms (cross resistance). Similar findings from previous monogenic models, strengthen support for the use of full-dose mixtures.

evolutionary biology↗