Rewiring cattle trade movements helps to control bovine paratuberculosis at a regional scale.

Paratuberculosis is a worldwide disease mainly introduced through trade. Due to the low sensitivity of diagnostic tests, it is difficult to protect herds from purchasing infected animals. Our objective was to assess if rewiring trade networks to promote risk-based movements could reduce the spread of Mycobacterium avium subsp. paratuberculosis (MAP) between dairy cattle herds at a regional scale. Two levels of control strategies were assessed. At the between-herd scale, trade rewiring aimed to prevent animals from high-risk herds moving into low-risk herds. At the within-herd scale, complementary additional measures were considered based on the herd infection status, aiming to limit the within-herd spread by reducing calf exposure to adult faeces and culling more rapidly after positive test results. We used a stochastic individual-based and between-herd mechanistic epidemiological model adapted to the 12,857 dairy cattle herds located in Brittany, western France. We compared the regional spread of MAP using observed trade movements against a rewiring algorithm rendering trade movements risk-based. All females over two years old were tested. Based on the results, and taking into account the low test sensitivity, herds were annually assigned one of three statuses: A if the estimated true prevalence was below 7%, B if it ranged from 7 to 21 %, C otherwise. We also identified herds with a high probability of being MAP-free (AAA herds that had obtained an A status over three consecutive years) to assess the effect of decreasing their risk of purchasing infected animals on MAP regional spread. We showed that movement rewiring to prevent the sale of animals from high to low-prevalence herds reduces MAP regional spread. Targeting AAA herds made it possible to minimize the control effort to decrease MAP regional spread. However, animals purchased by AAA herds should have a moderate to high probability of being MAP-free, especially if the risk of purchasing animals from herds of unknown status cannot be managed. Improved hygiene and early culling of positive animals were relevant complementary on-farm control options to further decrease MAP spread. Future studies should identify how to define herd statuses to target optimal control measure combinations that could reduce the spread of MAP on a regional scale most effectively.

The effect of risk-based trading and within-herd measures on Mycobacterium avium subspecies paratuberculosis spread within and between Irish dairy herds.

Johne's disease (bovine paratuberculosis) is an endemic disease caused by Mycobacterium avium subspecies paratuberculosis (Map). Map is transmitted between herds primarily through movement of infected but undetected animals. Within infected herds, possible control strategies include improving herd hygiene by reducing calf exposure to faeces from cows, reducing stress in cows resulting in a longer latently infected period where shedding is minimal, or culling highly test-positive cows soon after detection. Risk-based trading can be a strategy to reduce the risk that Map spreads between herds. Our objective was to assess whether within-herd measures combined with risk-based trading could effectively control Map spread within and between dairy cattle herds in Ireland. We used a stochastic individual-based and between-herd mechanistic epidemiological model to simulate Map transmission. Movement and herd demographic data were available from 1st January 2009-31st December 2018. In total, 13,353 herds, with 4,494,768 dairy female animals, and 72,991 bulls were included in our dataset. The movement dataset consisted of 2,304,149 animal movements. For each herd, a weekly indicator was calculated that reflected the probability that the herd was free from infection. The indicator value increased when a herd tested negative, decreased when animals were introduced into a herd, and became 0 when a herd tested positive. Based on this indicator value, four Johne's assurance statuses were distinguished: A) ≥ 0.7 - 1.0, B) ≥ 0.3 - < 0.7, C) > 0.0 - < 0.3, and D) 0.0. A is the highest and D the lowest Johne's assurance status. With risk-based trading some of the observed movements between herds were redirected based on Johne's assurance status with the aim of reducing the risk that a non-infected herd acquired an infected animal. Risk-based trading effectively reduced the increase in herd prevalence over a 10-year-period in Ireland: from 50% without risk-based trading to 42% with risk-based trading in the metapopulation only, and 26% when external purchases were risk-based as well. However, for risk-based trading to be effective, a high percentage of dairy herds had to participate. The most important within-herd measures were improved herd hygiene and early culling of highly infectious cows. These measures reduced both herd and within-herd prevalence compared to the reference scenario. Combining risk-based trading with within-herd measures reduced within-herd prevalence even more effectively.

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. Pearson's 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.