Proposed methods for estimating loss of saleable milk in a cow-calf contact system with automatic milking.

Cow-calf contact (CCC) systems, although beneficial in many respects, introduce additional challenges to collect reliable data on milk production, which is important to assess individual cow efficiency and dairy farm profitability. Apart from weighing calves before and after each feeding, the amount of saleable milk lost due to calf suckling is practically impossible to measure. Here, we assess 2 indirect methods for estimating loss of saleable milk when housing cows and calves together in a robotic milking unit. In our study, treatment (CCC) cows and calves were kept together full time until the calves were 127 ± 6.6 d old (mean ± SD). Control cows were separated from their calves within 12 h of birth and then kept in the same unit as the treatment cows but with no access to either their own or treatment calves. Milk yield recording of both groups was performed from calving until pasture release at 233 ± 20 d in milk. The first estimation method relied on observed postseparation milk yield data, which were fed into a modified Wilmink regression model to determine the best-fitting lactation curve for the preseparation period. The second method was based on the cows' daily energy intake postseparation, calculated by measuring the daily feed intake and analyzing the energy content of the ration. The calculated energy intake was used to determine the average ratio between energy intake and the observed milk yield the following day for each individual cow, assuming constant rates of mobilization and deposition of body fat. The obtained ratio was then used to calculate the expected daily milk yield based on daily energy intake data during the preseparation period. In this paper, we analyzed data from 17 CCC cows kept together with their calves and 16 control cows; both groups calved from September to October 2020 and were followed up until release to pasture in May 2021. Saleable milk yield was lower in CCC cows than in control cows, both before and after separation. The 2 methods were used on data for control cows and showed milk yield loss using the lactation curve method (average of -3.4 ± 2.8 kg/d) and almost no loss using energy intake data (average of -1.4 ± 2.7 kg/d). Milk yield loss for CCC cows was estimated at average 11.3 ± 4.8 and 7.3 ± 6.6 kg milk/d, respectively. The proposed lactation curve estimation method tends to overestimate milk yield loss, whereas the method based on energy intake is more accurate. However, collecting detailed energy intake data per individual cow requires additional effort and equipment, which is not always feasible on commercial farms. Further research is needed to improve milk loss estimation and to better understand trade-offs in CCC systems.

Assessing potential routes of Streptococcus agalactiae transmission between dairy herds using national surveillance, animal movement data and molecular typing.

Streptococcus agalactiae, also known as group B Streptococcus (GBS), is a pathogen of humans and animals. It is an important cause of mastitis in dairy cattle, causing decreased milk quality and quantity. Denmark is the only country to have implemented a national surveillance and control campaign for GBS in dairy cattle. After a significant decline in the 20th century, prevalence has increased in the 21st century. Using a unique combination of national surveillance, cattle movement data and molecular typing, we tested the hypothesis that transmission mechanisms differ between GBS strains that are almost exclusive to cattle and those that affect humans as well as cattle, which would have implications for control recommendations. Three types of S. agalactiae, sequence type (ST) 1, ST23 and ST103 were consistently the most frequent strains among isolates obtained through the national surveillance programme from 2009 to 2011. Herds infected with ST103, which is common in cattle but rarely found in people in Europe, were spatially clustered throughout the study period and across spatial scales. By contrast, strains that are also commonly found in humans, ST1 and ST23, showed no spatial clustering in most or any years of the study, respectively. Introduction of cattle from a positive herd was associated with increased risk of infection by S. agalactiae in the next year (risk ratio of 2.9 and 4.7 for 2009-2010 and 2010-2011, respectively). Moreover, mean exposure to infection was significantly higher for newly infected herds and significantly lower for persistently susceptible herds, as compared to random simulated networks with the same properties, which suggests strong association between the cattle movement network and new infections. At strain-level, new infections with ST1 between 2009 and 2010 were significantly associated with cattle movements, while other strains showed only some degree of association. Sharing of veterinary services, which may serve as proxy for local or regional contacts at a range of scales, was not significantly associated with increased risk of introduction of S. agalactiae or one of the three predominant strains on a farm. Our findings support the reinstatement of restrictions on cattle movements from S. agalactiae positive herds, which came into effect in 2018, but provide insufficient evidence to support strain-specific control recommendations.

Risk factors and dynamics of verotoxigenic Escherichia coli O157:H7 on cattle farms: An observational study combining information from questionnaires, spatial data and molecular analyses.

The increasing number of human cases infected with a highly virulent type of verotoxigenic Escherichia coli (VTEC) O157:H7 in Sweden is the result of domestic transmission originating in regional clusters of infected cattle farms. To control the spread of the bacteria a comprehensive picture of infection dynamics, routes of transmission between farms and risk factors for persistence is urgently needed. The aim of the study was to investigate different aspects of the epidemiology of VTEC O157:H7 on the Swedish island of Öland by combining information from environmental sampling of VTEC O157:H7 from 80 farms with information from farmer questionnaires, spatial and molecular analyses. The farms were sampled in the spring and fall of 2014 and on four of them additional samples were collected during summer and winter. The results show a high prevalence of VTEC O157:H7 and a high proportion of strains belonging to the virulent clade 8. Farms that became infected between samplings were all located in an area with high cattle density. The most important risk factors identified are generally associated with biosecurity and indicate that visitors travelling between farms may be important for transmission. In addition, whole genome sequencing of a subset of isolates from the four farms where additional sampling was performed revealed ongoing local transmission that cannot be observed with a lower resolution typing method. Our observations also show that VTEC O157:H7 may persist in the farm environment for extended periods of time, suggesting that specific on-farm measures to reduce environmental prevalence and spread between groups of animals may be required in these cases.

Spatio-temporal dynamics of dengue in Brazil: Seasonal travelling waves and determinants of regional synchrony.

Dengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years. Here, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterise the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondônia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapá) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period. We also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence. This study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.

Manipulation of contact network structure and the impact on foot-and-mouth disease transmission.

The movements of livestock between premises and markets can be characterised as a dynamic network where the structure of the network itself can critically impact the transmission dynamics of many infectious diseases. As evidenced by the 2001 foot-and-mouth disease (FMD) epidemic in the UK, this can involve transmission over large geographical distances and can result in major economic loss. One consequence of the FMD epidemic was the introduction of mandatory livestock movement restrictions: a 13-day standstill in Scotland for cattle and sheep after moving livestock onto a farm (allowing many exemptions) and a 6-day standstill for cattle and sheep in England and Wales (with minor exemptions, e.g. direct movements to slaughter). Such standstills are known to be effective but commercial considerations result in pressures to relax them. When contemplating legislative changes such as a change in length of movement restrictions we need to consider the consequent effect these could have on the emergent properties of the system, i.e. the network structure itself. In this study, we investigate how disease dynamics change when the local contact structure of the recorded livestock movement network in Scotland is altered through rewiring movements between premises. The network rewiring used here changes the structure of the recorded trade network through a combination of altered movement restrictions and redirection of movements between holdings and markets to avoid nonsensical activity (e.g. movements to markets on days when they are inactive) while conserving other characteristics (e.g. movement date as closely as possible and market sales of the correct animal production type). Rewiring results in networks with higher clustering coefficients and lower network density. The impact of rewiring on a hypothetical foot-and-mouth disease outbreak in Scotland was assessed by stochastic simulation, considering scenarios with and without exemptions to the standstill rules. As expected, rewiring leads to a decrease in outbreak size and - if standstill exemptions are prohibited - higher probability of smaller outbreaks. Without exemptions, a shorter movement standstill is almost as effective as a longer standstill period, indicating that a simpler biosecurity system would offer minimal additional risk for FMD. These results suggest that explicitly manipulating the contact network structure in a sensible way has the potential to significantly impact disease control.