Pauline Ezanno

A Rainfall- and Temperature-Driven Abundance Model for Aedes albopictus Populations

The mosquito Aedes (Stegomyia) albopictus (Skuse) (Diptera: Culicidae) is an invasive species which has colonized Southern Europe in the last two decades. As it is a competent vector for several arboviruses, its spread is of increasing public health concern, and there is a need for appropriate monitoring tools. In this paper, we have developed a modelling approach to predict mosquito abundance over time, and identify the main determinants of mosquito population dynamics. The model is temperature- and rainfall-driven, takes into account egg diapause during unfavourable periods, and was used to model the population dynamics of Ae. albopictus in the French Riviera since 2008. Entomological collections of egg stage from six locations in Nice conurbation were used for model validation. We performed a sensitivity analysis to identify the key parameters of the mosquito population dynamics. Results showed that the model correctly predicted entomological field data (Pearson r correlation coefficient values range from 0.73 to 0.93). The model’s main control points were related to adult’s mortality rates, the carrying capacity in pupae of the environment, and the beginning of the unfavourable period. The proposed model can be efficiently used as a tool to predict Ae. albopictus population dynamics, and to assess the efficiency of different control strategies.

Association of growth, feeding practices and exercise conditions with the prevalence of Developmental Orthopaedic Disease in limbs of French foals at weaning

Developmental Orthopaedic Disease (DOD) in limb joints of horses is frequent and is a common cause of pain and lameness. DOD is a multifactorial disease involving genetics, growth, feeding practices and exercise conditions leading to joint injuries. However, there is no clear understanding of the contribution of each factor. The aim of this cohort study was to assess the adjusted effects of breed and gender, growth, feeding practices and exercise conditions on the prevalence of DOD in the limbs of foals at weaning and on the prevalence restricted to osteochondrosis (OC). Twenty-one farms in Normandy, France, were convenience sampled and enrolled in a cohort study. The study sample consisted of 401 foals from 3 breeds, followed from the 8th month of pregnancy of the mares until weaning period at approximately 6 months of age of the foals. Stud farms were regularly visited to collect growth, feeding practices and exercise conditions data. The carpus, the front and hind digits, the hock and the stifle of the foals were X-rayed at the end of follow-up. Foals were categorised as affected or unaffected by DOD or by OC. Two mixed-effects logistic regression models were used to determine risk factors for DOD or OC, adjusting for clustering by farm. Of the 378 foals with complete data, 47% (95% CI: 42-52) were affected by DOD and 36% (95% CI: 31-41) by OC. Risk was significantly increased for DOD and for OC in Warmblood foals compared to Thoroughbreds (OR 2.8; 95% CI: 1.2-6.5 for DOD, OR 2.9; 95% CI: 1.1-7.5 for OC), in foals with a high wither height at 30 days of age, and in foals with a rapid increase of wither height (for DOD only). Exercise conditions such as large area of pasture, some irregular exercise, or some batch changes were also significant risk factors for DOD or OC. No association was found with quantitative feeding practices; it was likely due to the limited variability of horse regimens and to the partial inclusion of nutritional effects in other factors such as breed and growth. In order to reduce the prevalence of DOD or OC in foals, following the growth and reducing nutritional supply in subjects growing fast, limiting the pasture areas offered and providing a regular exercise to foals seems appropriate. To our knowledge, to date the assessment of adjusted effects of potential risk factors for DOD has never been proposed.

Within-herd contact structure and transmission of Mycobacterium avium subspecies paratuberculosis in a persistently infected dairy cattle herd.

Within-herd transmission of pathogens occurs either by direct or by indirect contact between susceptible and infected animals. In dairy herds that are structured into groups, the way in which animals encounter each other and share an environment can affect pathogen transmission. Dairy cattle are heterogeneous in terms of susceptibility and infectivity with respect to Mycobacterium avium subspecies paratuberculosis (Map) transmission. It is mainly young animals that are susceptible and adults that are infectious. Both vertical and horizontal transmission through the ingestion of Map shed into the environment by adults and transiently infected calves can occur. Our objective was to assess the effect of contact structure on Map transmission in persistently infected dairy herds and to examine the effect of isolating calves from other calves or from adults before weaning. We developed a stochastic compartmental model of Map transmission in a closed dairy herd. The model reflects the Map infection process and herd management characteristics. Indirect transmission via the environment was modelled explicitly. Six infection states (susceptible, resistant, transiently infectious, latently infected, subclinically infected, and clinically affected) and two contaminated farm area environments (whole farm and calf area) were modelled. Calves were housed in hutches, individual indoor pens, or group indoor pens. Two different levels of exposure of calves to a farm environment contaminated by adults were possible: no exposure and indirect exposure through fomites. Three herd sizes were studied. We found that contacts between calves before weaning did not influence Map transmission in a herd, whereas the level of exposure of calves to an environment contaminated by adults and the starting age of exposure of calves to adults were pivotal. Early culling of clinically affected adults led to a lower prevalence of infectious adults over time. The results were independent of herd size. Despite the many transmission routes that are known, the best control approach is to limit the exposure of calves to adult faeces through the systematic separation of adults and calves in combination with hygiene measures. Reducing contact between calves does not appear effective.

A fully coupled, mechanistic model for infectious disease dynamics in a metapopulation: movement and epidemic duration.

The drive to understand the invasion, spread and fade out of infectious disease in structured populations has produced a variety of mathematical models for pathogen dynamics in metapopulations. Very rarely are these models fully coupled, by which we mean that the spread of an infection within a subpopulation affects the transmission between subpopulations and vice versa. It is also rare that these models are accessible to biologists, in the sense that all parameters have a clear biological meaning and the biological assumptions are explained. Here we present an accessible model that is fully coupled without being an individual-based model. We use the model to show that the duration of an epidemic has a highly non-linear relationship with the movement rate between subpopulations, with a peak in epidemic duration appearing at small movement rates and a global maximum at large movement rates. Intuitively, the first peak is due to asynchrony in the dynamics of infection between subpopulations; we confirm this intuition and also show the peak coincides with successful invasion of the infection into most subpopulations. The global maximum at relatively large movement rates occurs because then the infectious agent perceives the metapopulation as if it is a single well-mixed population wherein the effective population size is greater than the critical community size.

Impact of the infection period distribution on the epidemic spread in a metapopulation model.

Epidemic models usually rely on the assumption of exponentially distributed sojourn times in infectious states. This is sometimes an acceptable approximation, but it is generally not realistic and it may influence the epidemic dynamics as it has already been shown in one population. Here, we explore the consequences of choosing constant or gamma-distributed infectious periods in a metapopulation context. For two coupled populations, we show that the probability of generating no secondary infections is the largest for most parameter values if the infectious period follows an exponential distribution, and we identify special cases where, inversely, the infection is more prone to extinction in early phases for constant infection durations. The impact of the infection duration distribution on the epidemic dynamics of many connected populations is studied by simulation and sensitivity analysis, taking into account the potential interactions with other factors. The analysis based on the average nonextinct epidemic trajectories shows that their sensitivity to the assumption on the infectious period distribution mostly depends on , the mean infection duration and the network structure. This study shows that the effect of assuming exponential distribution for infection periods instead of more realistic distributions varies with respect to the output of interest and to other factors. Ultimately it highlights the risk of misleading recommendations based on modelling results when models including exponential infection durations are used for practical purposes.

Modelling the spread of Bovine Viral Diarrhoea Virus (BVDV) in a managed metapopulation of cattle herds.

In numerous epidemiological models developed within a metapopulation framework, it is assumed that a single infected individual introduced into a patch infects the whole patch and that the proportion of infected individuals into infected patches is consistent over time and among patches. If this approach is relevant for rapidly spreading pathogens, it is less appropriate for moderately spreading pathogens, like the Bovine Viral Diarrhoea Virus (BVDV), characterized by a variability in within-patch prevalence. Our objective is to study the respective influence of neighbouring relationships and animal movements on the spread of BVDV in a managed metapopulation of 100 cattle herds. Infection dynamics is represented by two coupled stochastic compartmental models in discrete-time: a within-herd and a between-herd models. Animal movements are mechanistically modelled. They largely influence the BVDV persistence, the prevalence in infected herds and the epidemic size. Neighbouring relationships only influence epidemic size. Whatever the neighbouring relationships, the infection does not persist in the metapopulation without animal movement between herds. The proposed model can be easily adapted for different herd contact structures.

Seasonal spread and control of Bluetongue in cattle

Bluetongue is a seasonal midge-borne disease of ruminants with economic consequences on herd productivity and animal trade. Recently, two new modes of transmission have been demonstrated in cattle for Bluetongue virus serotype 8 (BTV8): vertical and pseudo-vertical transmission. Our objective was to model the seasonal spread of BTV8 over several years in a homogeneous population of cattle, and to evaluate the effectiveness of vaccination strategies. We built a deterministic mathematical model accounting for the seasonality in vector abundance and all the modes of transmission. We proposed a counterpart of the basic reproduction number (R(0)) in a seasonal context (R(S)). Set A(t) is the number of secondary cases produced by a primary case introduced at time t. R(S) is the average of A(t). It is a function of midge abundance and vaccination strategy. We also used A*, the maximum of A(t), as an indicator of the risk of an epidemic. Without vaccination, the model predicted a large first epidemic peak followed by smaller annual peaks if R(S)>1. When R(S)<1, small epidemics could occur if A* >1. Vaccination reduced R(S) and A* to less than one, but almost perfect vaccine efficacy and coverage were required to ensure no epidemics occurred. However, a lower coverage resulting in R(S)>1 could decrease infection prevalence. A further step would be to optimize vaccination strategies by targeting an appropriate period of the year to implement the vaccination.

Modelling of paratuberculosis spread between dairy cattle farms at a regional scale

Mycobacterium avium subsp. paratuberculosis (Map) causes Johne’s disease, with large economic consequences for dairy cattle producers worldwide. Map spread between farms is mainly due to animal movements. Locally, herd size and management are expected to influence infection dynamics. To provide a better understanding of Map spread between dairy cattle farms at a regional scale, we describe the first spatio-temporal model accounting simultaneously for population and infection dynamics and indirect local transmission within dairy farms, and between-farm transmission through animal trade. This model is applied to Brittany, a French region characterized by a high density of dairy cattle, based on data on animal trade, herd size and farm management (birth, death, renewal, and culling) from 2005 to 2013 for 12 857 dairy farms. In all simulated scenarios, Map infection highly persisted at the metapopulation scale. The characteristics of initially infected farms strongly impacted the regional Map spread. Network-related features of incident farms influenced their ability to contaminate disease-free farms. At the herd level, we highlighted a balanced effect of the number of animals purchased: when large, it led to a high probability of farm infection but to a low persistence. This effect was reduced when prevalence in initially infected farms increased. Implications of our findings in the current enzootic situation are that the risk of infection quickly becomes high for farms buying more than three animals per year. Even in regions with a low proportion of infected farms, Map spread will not fade out spontaneously without the use of effective control strategies.

A generic weather-driven model to predict mosquito population dynamics applied to species of Anopheles, Culex and Aedes genera of southern France.

An accurate understanding and prediction of mosquito population dynamics are needed to identify areas where there is a high risk of mosquito-borne disease spread and persistence. Simulation tools are relevant for supporting decision-makers in the surveillance of vector populations, as models of vector population dynamics provide predictions of the greatest risk periods for vector abundance, which can be particularly helpful in areas with a highly variable environment. We present a generic weather-driven model of mosquito population dynamics, which was applied to one species of each of the genera Anopheles, Culex, and Aedes, located in the same area and thus affected by similar weather conditions. The predicted population dynamics of Anopheles hyrcanus, Culex pipiens, and Aedes caspius were not similar. An. hyrcanus was abundant in late summer. Cx. pipiens was less abundant but throughout the summer. The abundance of both species showed a single large peak with few variations between years. The population dynamics of Ae. caspius showed large intra- and inter-annual variations due to pulsed egg hatching. Predictions of the model were compared to longitudinal data on host-seeking adult females. Data were previously obtained using CDC-light traps baited with carbon dioxide dry ice in 2005 at two sites (Marais du Viguerat and Tour Carbonnière) in a favourable temperate wetland of southern France (Camargue). The observed and predicted periods of maximal abundance for An. hyrcanus and Cx. pipiens tallied very well. Pearsons coefficients for these two species were over 75% for both species. The model also reproduced the major trends in the intra-annual fluctuations of Ae. caspius population dynamics, with peaks occurring in early summer and following the autumn rainfall events. Few individuals of this species were trapped so the comparison of predicted and observed dynamics was not relevant. A global sensitivity analysis of the species-specific models enabled us to identify the parameters most influencing the maximal abundance of mosquitoes. These key parameters were almost similar between species, but not with the same contributions. The emergence of adult mosquitoes was identified as a key process in the population dynamics of all of the three species considered here. Parameters associated with adult emergence therefore need to be precisely known to achieve accurate predictions. Our model is a flexible and efficient tool that predicts mosquito abundance based on local environmental factors. It is useful to and already used by a mosquito surveillance manager in France.

A metapopulation model for the spread and persistence of contagious bovine pleuropneumonia (CBPP) in african sedentary mixed crop-livestock systems

Contagious bovine pleuropneumonia (CBPP) is endemic in several developing countries. Our objective is to evaluate the regional CBPP spread and persistence in a mixed crop-livestock system in Africa. A stochastic compartmental model in metapopulation is used, in which between-herd animal movements and the within-herd infection dynamics are explicitly represented. Hundred herds of varying size are modelled, each sending animals to n other herds (network degree). Animals are susceptible, latent, infectious, chronic carrier or resistant. The role of chronic carriers in CBPP spread being still debated, several chronic periods and infectiousness are tested. A sensitivity analysis is performed to evaluate the influence on model outputs of these parameters and of pathogen virulence, between-herd movement rate, network degree, and calves recruitment. Model outputs are the probability that individual- and group-level reproductive numbers R(0) and R(*) are above one, the metapopulation infection duration, the probability of CBPP endemicity (when CBPP persists over 5 years), and the epidemic size in infected herds and infected animals. The most influential parameters are related to chronic carriers (infectiousness and chronic period), pathogen virulence, and recruitment rate. When assuming no CBPP re-introduction in the region, endemicity is only probable if chronic carriers are assumed infectious for at least 1 year and to shed the pathogen in not too low an amount. It becomes highly probable when assuming high pathogen virulence and high recruitment rate.