Spatial and network aspects of the spread of infectious diseases in livestock populations

In this thesis, I focus on methodological concepts of studying infectious disease transmission between agricultural premises. I used different disease systems as exemplars for spatial and network methods to investigate transmission patterns. Infectious diseases cause tangible economic threat to the farming industry worldwide by damaging livestock populations, reducing farm productivity and causing trade restriction. This implies the importance of veterinary epidemiological studies in control and eradication of pathogens. Recent increase in availability of data and computational power allowed for more opportunities to study mechanisms of pathogenic transmission. Nowadays, the bottleneck is primarily associated with efficient methods that can analyse vast amounts of high-resolution data. Here I address two livestock pathogens that differ in their epidemiology: bacteria Streptococcus agalactiae and foot-and-mouth disease (FMD) virus. Streptococcus agalactiae is a contagious pathogen that causes mastitis in cattle, and thus possesses a substantial economic burden to the dairy industry. Known transmission routes between cattle are restricted to those via milking machines, milkers’ hands and fomites during milking process. Additionally, recent studies suggested potential introductions from other host species: primarily, humans. However, strain typing data showed discrepancies in strain compositions of bacteria isolated from humans and bovines. In this thesis, strain-specific features of between-herd transmission of Streptococcus agalactiae within dairy cattle population in Denmark are investigated. Foot-and-mouth disease (FMD) is a viral infection that affects cloven-hoofed animals and is of big importance mainly because of the trade restrictions against infected regions and countries. Control programmes against FMD usually include vaccination and culling of animals. However, the debate on the optimal control for FMD is still ongoing. In this thesis, I address questions on identification of the routes of infection and on requirements for movement recording systems to be used for efficient contact tracing during an FMD outbreak. This thesis reveals several interesting findings. Firstly, the increased understanding of strain-specific transmission characteristics of Streptococcus agalactiae. One of the observed strains (ST103) showed significant and consistent spatial clustering of its cases among Danish dairy cattle herds in 2009–2011. Secondly, the network analysis of cattle movements and affiliations with veterinary practices showed that veterinary practices were exclusively associated with transmission of ST103 of Streptococcus agalactiae. Contrastingly, movement networks appeared to be important for all the three predominant bacterial strains (ST1, ST23 and ST103). Fourthly, the new extended approach that allows estimation of the whole transmission tree at once was proposed and tested for the Darlington cluster within the 2001 FMD UK epidemic. Finally, in chapter 6, it was shown that mathematical modelling did not suggest any advantages of ensuring smaller delays in the post-silent control of FMD-like pathogens

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

Milk fatty acids as indicators of negative energy balance of dairy cows in early lactation

Most dairy cows experience negative energy balance (NEB) in early lactation because energy demand for milk synthesis is not met by energy intake. Excessive NEB may lead to metabolic disorders and impaired fertility. To optimize herd management, it is useful to detect cows in NEB in early lactation, but direct calculation of NEB is not feasible in commercial herds. Alternative methods rely on fat-to-protein ratio in milk or on concentrations of non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) in blood. Here, we considered methods to assess energy balance (EB) of dairy cows based on the fatty acid (FA) composition in milk. Short- and medium-chain FAs (primarily, C14:0) are typically synthesized de novo in the mammary gland and their proportions in milk fat decrease during NEB. Long-chain FAs C18:0 and C18:1 cis-9 are typically released from body fat depots during NEB, and their proportions increase. In this study, these FAs were routinely determined by Fourier-transform infrared spectroscopy (FTIR) of individual milk samples. We performed an experiment on 85 dairy cows in early lactation, fed the same concentrate ration of up to 5 kg per day and forage ad libitum. Daily milk yield and feed intake were automatically recorded. During lactation weeks 2, 4, and 6 after calving, two milk samples were collected for FTIR spectroscopy, Tuesday evening and Wednesday morning, blood plasma samples were collected Thursday morning. Net energy content in feed and net energy required for maintenance and lactation were estimated to derive EB, which was used to compare alternative indicators of severe NEB. Linear univariate models for EB based on NEFA concentration (deviance explained = 0.13) and other metabolites in blood plasma were outperformed by models based on concentrations of metabolites in milk: fat (0.27), fat-to-protein ratio (0.18), BHB (0.20), and especially C18:0 (0.28) and C18:1 cis-9 (0.39). Analysis of generalized additive models (GAM) revealed that models based on milk variables performed better than those based on blood plasma (deviance explained 0.46 vs. 0.21). C18:0 and C18:1 cis-9 also performed better in severe NEB prediction for EB cut-off values ranging from −50 to 0 MJ NEL/d. Overall, concentrations of C18:0 and C18:1 cis-9 in milk, milk fat, and milk BHB were the best variables for early detection of cows in severe NEB. Thus, milk FA concentrations in whole milk can be useful to identify NEB in early-lactation cows

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

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

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

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

Parity and days in milk affect cubicle occupancy in dairy cows

Modern dairy cattle farms are usually equipped with cubicle systems to provide cows with comfortable conditions for lying down and resting. Cows are free to choose any cubicle they want, but in reality, they do not distribute themselves uniformly throughout the barn. There are many factors that affect where a cow lies down, such as hierarchy of a cow, access to resources, cow traffic nearby, etc. In this study, we used real-time location system data from two commercial farms to examine patterns of cubicle occupancy in relation to parity and lactation stage. We summarized cubicle occupancy over several days and compared different areas of the barn. Our findings suggest that, in general, there was a higher occupancy of cubicles close to the feeding areas. High parity cows lay down more frequently in cubicles close to the milking area as opposed to first lactation cows that tend to occupy less busy areas of the barn. The overall conclusion is that cubicle occupancy is not uniform throughout the barn, and patterns related to parity and DIM are seen. This information can be important for future studies on spread of diseases and for management purposes

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

Crystal structure of 4-[(1R,2S,5R)-2-isopropyl-5-methylcyclohexyl] 2-methyl (2S,4S,5R)-1-[(2S,3R,5R)-5-methoxycarbonyl-2-(2-methylphenyl)pyrrolidine-3-carbonyl]-5-(2-methylphenyl)pyrrolidine-2,4-dicarboxylate

The title compound, C38H50N2O7, represents a chiral β-proline dipeptide. Corresponding stereogenic centres of constituting pyrrolidine units have opposite absolute configurations. The central amide fragment is planar within 0.1 Å and adopts a Z configuration along the N—CO bond. In the crystal, the hydrogen atoms of the methylene groups form several short intermolecular C—H...O contacts with the carbonyl oxygen atoms of an adjacent molecule. The only active amino hydrogen atom is not involved in hydrogen bonding

Crystalline Peroxosolvates: Nature of the Coformer, Hydrogen-Bonded Networks and Clusters, Intermolecular Interactions

Despite the technological importance of urea perhydrate (percarbamide) and sodium percarbonate, and the growing technological attention to solid forms of peroxide, fewer than 45 peroxosolvates were known by 2000. However, recent advances in X-ray diffractometers more than tripled the number of structurally characterized peroxosolvates over the last 20 years, and even more so, allowed energetic interpretation and gleaning deeper insight into peroxosolvate stability. To date, 134 crystalline peroxosolvates have been structurally resolved providing sufficient insight to justify a first review article on the subject. In the first chapter of the review, a comprehensive analysis of the structural databases is carried out revealing the nature of the co-former in crystalline peroxosolvates. In the majority of cases, the coformers can be classified into three groups: (1) salts of inorganic and carboxylic acids; (2) amino acids, peptides, and related zwitterions; and (3) molecular compounds with a lone electron pair on nitrogen and/or oxygen atoms. The second chapter of the review is devoted to H-bonding in peroxosolvates. The database search and energy statistics revealed the importance of intermolecular hydrogen bonds (H-bonds) which play a structure-directing role in the considered crystals. H2O2 always forms two H-bonds as a proton donor, the energy of which is higher than the energy of analogous H-bonds existing in isostructural crystalline hydrates. This phenomenon is due to the higher acidity of H2O2 compared to water and the conformational mobility of H2O2. The dihedral angle H-O-O-H varies from 20 to 180° in crystalline peroxosolvates. As a result, infinite H-bonded 1D chain clusters are formed, consisting of H2O2 molecules, H2O2 and water molecules, and H2O2 and halogen anions. H2O2 can form up to four H-bonds as a proton acceptor. The third chapter of the review is devoted to energetic computations and in particular density functional theory with periodic boundary conditions. The approaches are considered in detail, allowing one to obtain the H-bond energies in crystals. DFT computations provide deeper insight into the stability of peroxosolvates and explain why percarbamide and sodium percarbonate are stable to H2O2/H2O isomorphic transformations. The review ends with a description of the main modern trends in the synthesis of crystalline peroxosolvates, in particular, the production of peroxosolvates of high-energy compounds and mixed pharmaceutical forms with antiseptic and analgesic effects