Biology subjects

Choisy, M.

Publications and source records attributed to Choisy, M..

7 recordsLinked to original sources

bioRxiv2025

denim: an R package for deterministic compartmental models with flexible dwell time distributions

O_LICompartmental models are widely used for dynamical systems where states are discrete such as in infectious diseases epidemiology with the so-called SIR or Susceptible-Infectious-Recovered framework. For mathematical simplicity, rates of transition between compartments are generally assumed to be independent of the dwell time (or secondary time scale in survival analysis): they are either constant or dependent on the epidemiological time (or primary time scale in survival analysis) only, either directly (e.g. environmental or behavioral forcings in epidemiological models) or indirectly through dependence on other variables of the system (e.g. the force of infection in epidemiological models). In some domains of application, this memoryless assumption leads to distributions of dwelling times that are incompatible with those observed on data which can lead to serious problems since the model predictions are highly sensitive on the exact shape of these distributions. C_LIO_LIHere we propose a deterministic, continuous-variable, numerical modelling approach that allows full flexibility on the dwell time distributions. The accompanying denim package provides a user-friendly interface to implement our proposed method through a dedicated language for model definition. C_LIO_LIThe package is open-source and available on CRAN. With more detailed data on the clinical process of infections becoming available, the denim package will be extremely useful for building more realistic epidemiological models providing more accurate projections. C_LI The denim package is publicly available for download on CRAN (https://cran.r-project.org/web/packages/denim/index.html) and GitHub (https://github.com/thinhong/denim). Additional documentation can be found on the denim webpage (https://drthinhong.com/denim/). Bug reports can be submitted via Github Issue.

bioinformatics↗

bioRxiv2024

Climate and predation drive variation of diel activity patterns in chacma baboons (Papio ursinus) across southern Africa

Understanding how animals adjust daily activity to environmental gradients reveals key drivers of behavioral plasticity. While diel activity is theorized to reflect trade-offs among thermoregulation, energy balance, and predation risk, few studies test these interactions at broad spatial scales within species. We investigated this in chacma baboons (Papio ursinus) using over a million camera-trap detections across 29 sites in six biomes (2016-2022) in South Africa and Zimbabwe. Activity declined by about 3% with latitude, consistent with lower resource predictability and increased with thermal stress, while sleep and wake times were similar across sites. Baboons avoided midday heat but increased dawn and night activity under predator pressure. These findings show how abiotic and biotic pressures shape diel schedules and highlight temporal flexibility as an adaptive strategy for generalist mammals in a changing world.

animal behavior and cognition↗

bioRxiv2024

Evolution of Virulence in Emerging Epidemics: From Theory to Experimental Evolution and Back

The experimental validation of theoretical predictions is a crucial step in demonstrating the predictive power of a model. While quantitative validations are common in infectious diseases epidemiology, experimental microbiology primarily focuses on the evaluation of a qualitative match between model predictions and experiments. In this study, we develop a method to deepen the quantitative validation process with a polymorphic viral population. We analyse the data from an experiment carried out to monitor the evolution of the temperate bacteriophage {lambda} spreading in continuous cultures of Escherichia coli. This experimental work confirmed the influence of the epidemiological dynamics on the evolution of transmission and virulence of the virus. A variant with larger propensity to lyse bacterial cells was favoured in emerging epidemics (when the density of susceptible cells was large), but counter-selected when most cells were infected. Although this approach qualitatively validated an important theoretical prediction, no attempt was made to fit the model to the data nor to further develop the model to improve the goodness of fit. Here, we show how theoretical analysis - including calculations of the selection gradients - and model fitting can be used to estimate key parameters of the phage life cycle and yield new insights on the evolutionary epidemiology of the phage {lambda}. First, we show that modelling explicitly the infected bacterial cells which will eventually be lysed improves the fit of the transient dynamics of the model to the data. Second, we carry out a theoretical analysis that yields useful approximations that capture at the onset and at the end of an epidemic the effects of epidemiological dynamics on selection and differentiation across distinct life stages of the virus. Finally, we estimate key phenotypic traits characterizing the two strains of the virus used in our experiment such as the rates of prophage reactivation or the probabilities of lysogenization. This study illustrates the synergy between experimental, theoretical and statistical approaches; and especially how interpreting the temporal variation in the selection gradient and the differentiation across distinct life stages of a novel variant is a powerful tool to elucidate the evolutionary epidemiology of emerging infectious diseases.

evolutionary biology↗

bioRxiv2023

Mosquito aging modulates the development, virulence and transmission potential of pathogens

Host age variation is a striking source of heterogeneity that can shape the evolution and transmission dynamic of pathogens. Compared to vertebrate systems, our understanding of the impact of host age on invertebrate-pathogen interactions remains limited. We examined the influence of mosquito age on key life-history traits driving human malaria transmission. Females of Anopheles coluzzii, a major malaria vector, belonging to three age classes (4, 8, and 12 day-old), were experimentally infected with Plasmodium falciparum field isolates. Our findings revealed reduced competence in 12-day-old mosquitoes, characterized by lower oocyst/sporozoite rates and intensities compared to younger mosquitoes. Despite shorter median longevities in older age classes, infected 12-day-old mosquitoes exhibited improved survival, suggesting that the infection might act as a fountain of youth for older mosquitoes specifically. The timing of sporozoite appearance in the salivary glands remained consistent across mosquito age classes, with an extrinsic incubation period of approximately 13 days. Integrating these results into an epidemiological model revealed a lower vectorial capacity for older mosquitoes compared to younger ones, albeit still substantial due to extended longevity in the presence of infection. Considering age heterogeneity provides valuable insights for ecological and epidemiological studies, informing targeted control strategies to mitigate pathogen transmission.

ecology↗

bioRxiv2020

Simulating trajectories and phylogenies from population dynamics models with TiPS

We introduce TiPS, an R package to generate trajectories and phylogenetic trees associated with a compartmental model. Trajectories are simulated using Gillespies exact or approximate stochastic simulation algorithm, or a newly-proposed mixed version of the two. Phylogenetic trees are simulated from a trajectory under a backwards-in-time approach (i.e. coalescent). TiPS is based on the Rcpp package, allowing to combine the flexibility of R for model definition and the speed of C++ for simulations execution. The model is defined in R with a set of reactions, which allow capturing heterogeneity in life cycles or any sort of population structure. TiPS converts the model into C++ code and compiles it into a simulator that is interfaced in R via a function. Furthermore, the package allows defining time periods in which the models parameters can take different values. This package is particularly well suited for population genetics and phylodynamics studies that need to generate a large number of phylogenies used for population dynamics studies. This package is available on the CRAN at https://cran.r-project.org/package=TiPS.

bioinformatics↗

bioRxiv2020

Evolution of virulence in emerging epidemics: inference from an evolution experiment

Inference using mathematical models of infectious disease dynamics is a powerful tool to analyse epidemiological data and elucidate pathogen life cycles. Key epidemiological parameters can be estimated from demographic time series by computing the likelihood of alternative models of pathogen transmission. Here we use this inference approach to analyze data from an evolution experiment in which we monitored both the epidemiology and the evolution of the temperate bacteriophage{lambda} during an epidemic. We estimate parameter values for all the life-history traits of two distinct strains of the virus. In particular, we estimate the ability of the two virus strains to modulate plastically the rate of lysogenization with the multiplicity of infection. Our work illustrates how inference from experimental evolution data can feedback on the development of models aiming to predict the epidemiology and evolution of infectious diseases.

evolutionary biology↗

bioRxiv2020

Effects of prophylactic and therapeutic antimicrobial uses in small-scale chicken flocks

SynopsisO_ST_ABSBackgroundC_ST_ABSAntimicrobials are extensively used both prophylactically and therapeutically in poultry production. Despite this, there are little data on the effect of antimicrobial use (AMU) on disease incidence and mortality rate. ObjectiveWe investigated the relationships between AMU and disease and between AMU and mortality using data from a large (n=322 flocks) cohort of small-scale chicken flocks in the Mekong Delta, Vietnam, that were followed longitudinally from day-old to slaughter (5,566 observation weeks). MethodsWe developed a parameterized algorithm to categorize the observation weeks into non-AMU, prophylactic AMU and therapeutic AMU. To evaluate the prophylactic AMU effect, we compared the frequencies of clinical signs in non-AMU and prophylactic AMU periods. To analyse therapeutic AMU, we compared mortality rates between the weeks of disease episodes before and after AMU. Analyses were stratified by clinical signs (4) and antimicrobial classes (13). ResultsProphylactic AMU never reduced the probability of disease, some antimicrobial classes such as lincosamides, amphenicols and penicillins increased the risk. The risk of diarrhoea consistently increased with prophylactic AMU. Therapeutic AMU often had an effect on mortality but the pattern was inconsistent across the combinations of antimicrobial classes and clinical signs with 14/29 decreasing and 11/29 increasing the mortality rate. Lincosamides, methenamines and cephalosporins were the only three antimicrobial classes that always decreased the mortality rate when used therapeutically. Results were robust respective to the parameters values of the weeks categorization algorithm. ConclusionThis information should help support policy efforts and interventions aiming at reducing AMU in animal production.

pharmacology and toxicology↗