Multivariate and Epidemiological Analysis of a Complex Problem: Bovine Abortion

Abstract

Bovine abortion generates economic losses in herds. When finding its causes, only infectious elements are usually analysed, and a diagnosis is obtained for nearly half of the cases. It is necessary to handle the problem in its multicausality by considering both infectious and non-infectious elements and to identify the causal patterns that affect each herd. This is the only way to achieve a significant reduction of the problem. There are epidemiological tools to suitably characterise the problem and identify the different factors that may be involved. This multivariate approach can serve as a model of analysis for other problems with compound causes.

1. Introduction

One of the challenges that the dairy industry faces is the occurrence of bovine abortion, which reduces the amount of milk that can be obtained and the number of possible replacements for the herd. This serious problem affects the productivity and profitability of dairy farms [1], as it reduces the potential number of heifers for replacement and milk production and increases the costs associated with feeding, treatments, insemination and premature culling of animals. It also constitutes a challenge for the veterinary profession [1, 2].

The studies that examine bovine abortion vary in many aspects, such as the epidemiological indicators and definitions they use. They also differ in how they present their results, how they calculate risk factors, and especially how they define important events. It is necessary to clearly distinguish between factors at the animal and herd levels, which may be associated with different production systems [3].

The most commonly used methodologies for quantifying abortions in epidemiological studies on the subject are characterisation using the proportion of abortions and crude and specific abortion density rates, while survival analysis is used to identify periods of greatest risk and describe the abortion risk function. Modifications have been made to this method to consider abortions that are repeated from one period to another [3].

2. Bovine abortion as a syndrome

A syndrome is understood as a set of phenomena that characterise a specific situation. In the context of bovine abortion, a combination of several factors is required for foetal death to occur, which implies different types of causal mechanisms, which can act independently or interact with each other [4]. In addition, there may be a long interval between exposure to the cause of the abortion and its observation [3].

There are several published studies that report different aetiologies of abortion, especially those of an infectious nature. However, there is not enough information that addresses the bovine abortion syndrome in an integral manner, despite numerous studies demonstrating its multifactorial aetiology [5]. Infectious agents can be responsible for decreased ovulation rates, fertilisation, embryonic survival, foetal and perinatal survival; however, some signs of reproductive diseases may be similar to genetic abnormalities, the effect of toxins or physical trauma [2].

Depending on the predominant aetiology or combinations thereof in a herd or geographic region, the foetal survival curve will have different patterns. When analysing foetal survival curves—for example, if a peak is obtained in the curve at a stage of gestation—a predominant abortion mechanism can be suspected; bi- or trimodal curves may indicate more than one aetiology or their combination [6]. In addition, the foetal survival curve for cows with different characteristics (age and history of previous abortions) may vary within the same farm by showing a similar shape but at a different level [7]; however, very good quality data is needed to estimate these effects.

In general, research addressing the issue of bovine abortion at the national level focuses on the study of a particular pathology and does not analyse the presentation of these diseases in relation to herd or animal factors. It is necessary for study designs to allow inferences to be made to the general population, or to specific strata thereof; it is also important that they allow for the joint analysis of factors and infer causal relationships rather than statistical associations, for which prospective studies with adequate comparison groups are required [8].

3. Epidemiological tools for bovine abortion quantification

To clearly explain the abortion indicators used in a study, it is necessary to have the following aspects defined as precisely as possible [1]: definition of an abortion case, period at risk of aborting, technique used to diagnose pregnancy and the cow’s status at each control check, identification of cows and date of service or artificial inseminations and their repetitions, identification of cows that have been diagnosed pregnant, date of previous delivery, date of termination of the risk period or follow-up of each cow.

It is necessary to resort to the inspection and interpretation of reproductive records in order to detect unnoticed abortions and thus ensure that the numerator of abortion epidemiological indicators reflects the reality of the herd. It is useful to perform an analysis of intervals between artificial insemination or heat repetitions, as there could have been a foetal death if heat or insemination is repeated more than 42 days after the last insemination/heat, since repetitions close to 21 days may correspond to no conception or embryonic death before the maternal recognition period [9]. Repetitions between 21 and 42 days would correspond to embryonic and not foetal mortalities, provided that heat detection is perfect. The interpartum interval less than 260 days or short lactations, that is, less than 8 months, may be indicators that the cow dried up earlier than due, among other causes, due to cessation of gestation. It is also important to review the gestation status of cows that have already been diagnosed as pregnant and that present heat, since the presentation of heat behaviour can be normal in approximately 5% of pregnant cows [10].

Studies analysing the occurrence of SAB agree that there is little accuracy in the gestational age assigned to abortions because the occurrence of the event can be much earlier than the physical manifestation in the cow: return to cyclicity or expulsion of the foetus [11]. This means that most early abortions are not observed, and late ones are observed. In addition, the lack of etiological diagnosis is a problem in most of the cases that are analysed. There are biases from when abortion samples are sent to diagnostic laboratories, to the fact that most of the causes sought as diagnosis are infectious [9]. In designing studies that quantify this syndrome or identify risk factors, the population at risk, event definitions and analytical procedures to be used should be clearly established, since the main inconsistencies when making comparisons between studies are given by these inaccuracies. In addition, clarity should be given to possible associated biases that may exist, for example, to the selection pressure exerted on herds by eliminating cows that have aborted. On the other hand, studies should take into account that the risk of abortion is higher in early gestation [12] and that only considering those abortions that are visually detected underestimates the actual amount produced.

Descriptive epidemiology provides useful tools for defining and quantifying a situation and understanding the nature of a problem. The most commonly used indicators for quantifying abortions in a herd are the proportion of abortions, the incidence of abortions and, for quantitative analysis, survival analysis.

3.1 Proportional abortions rate (PAR)

This is the indicator that requires more general information and is the one that is most frequently used. This should be calculated considering in the numerator the abortions that occurred and in the denominator, the total number of pregnancies in a given period, for example, during 1 year. It can be used in crude form (based on all females) or stratified by age, breed, production level, etc. [13]. Although this measure is objective and provides information about the subgroup of animals where the problem is concentrated, it says nothing about its dynamics. It can be very useful for characterising the herd in a general way or for making evaluations after some intervention; however, it is not the appropriate tool for detecting causal associations in problem herds. This indicator has no bias with respect to the distribution of risk in gestation; it can be determined for a cohort or in a contemporary life table, where it is quantified for each interval of the risk period. The PA should be calculated according to the conditional probability that a cow will not abort before 260 days of gestation [1].

3.2 Abortion incidence rates (TIA)

This is the most appropriate morbidity indicator for characterising the dynamics of an event occurrence since it indicates the number of new events in defined populations and periods. In the numerator are counted new cases of abortion that occur within a given period within a group of animals that are at risk of this happening. The incidence rate can have a bias regarding the representation of risk in periods that are overrepresented by cows in gestational states not normally associated with any risk of abortion [1].

The choice of statistical model for studying a disease is directly related to the assumptions that must be met in them according to the biology of the problem. The results of statistical analysis are a function of the data and assumptions used; therefore, it is necessary to analyse whether the assumptions of the chosen model make sense with the true population structure of the variable studied since if different assumptions are made about the data, the results will be different [14]. The distribution of abortion occurrence time is not symmetrical and is commonly bi- or trimodal [15], so it is not appropriate to analyse it with linear regression [16].

Survival models are appropriate for analysing this type of data, which allow the characterisation of abortion events as a function of the time at which they occur by estimating the foetal survival function and the risk function of a foetus dying. It is a very useful tool for studying the association between different factors and the risk of an event occurring, in this case, abortion, adjusting the different times at risk in which different animals contribute during the observation time [8]. Logistic regression models can be used to analyse the probability of a cow aborting. It is possible to form a multivariable model to jointly analyse the effect of different factors [8]. The indicators of survival models and logistic regression models can be interpreted as risk indicators; however, if information on the timing of abortion is available, survival models use a more adjusted denominator in risk indicators [17].

Given the possible lack of a temporal relationship between abortion and the cause that produced it, it is difficult to obtain precise data on the occurrence of abortions to find a causal association. This leads to the need to try to maintain farm records of possible abortion risk factors so that a thorough retrospective farm analysis can be performed when an abortion occurs. To implement an effective disease surveillance system, at least the following is needed: to have an adequate monitoring method that allows the rapid detection of events of interest, to define and evaluate results in relation to time, to establish a criterion that allows concluding that the indicators obtained in a herd or area are higher than expected. It is usual for monitoring the risk of abortion in a calendar period to be done through PA and/or TIA [11]. A traditional alternative is to establish the Endemic Curve and the Endemic Index of abortion presentation with retrospective data [13].

4. Frequency and risk factors of bovine abortion, the case of central south of Chile

Bovine abortion is an important topic in herd management. There are several determinants that give rise to a loss of gestation. Quantifying abortion occurrence using means of observed abortions underestimates the real situation since observed foetal losses are approximately 20% of the total foetal losses. Frequency estimations of cumulative foetal loss after pregnancy diagnosis in dairy cattle that includes observed and unobserved losses vary from 3.6% to 10.6% [3].

The authors used historical data from 77 dairy farms in southern Chile (Bio-Bio, Los Lagos and Los Ríos regions) that were collected over a period of 5 years (2001–2005) [3]; the data consisted of 44,959 lactations from 20,977 cows. Moreover, the authors evaluated the farm management practices by administering a questionnaire to 127 farms. The farms were chosen based on the owners’ consent and the availability of high-quality electronic records verified by practitioners who advised the farms.

To calculate the observed, inferred and total abortions, we used two measures: the Proportional Abortion Rate (PAR) and the Density Incidence Rate (DIR). These measures show the frequency distribution of abortions in different populations and time periods [3]. The association between the DIR and individual lactation characteristics (number of lactations, year of beginning lactation and trimester of gestation in which the abortion occurred) was assessed using a conditional logistic regression model. A forward approach was used for including variables in model building, and the likelihood ratio test was used for assessing the goodness of fit of the models. One-way interactions and confounding variables were also tested. To investigate the association between herd management and lactation factors and the occurrence of abortion events [3], the authors applied a hierarchical logistic regression model with a random intercept. This model allowed us to account for the clustering of cows within herds and to estimate the variability in the abortion risk across herds.

A common problem in the study of abortion rates in livestock is the reliance on farmers’ own records, which often underestimate the actual number of cases. This can lead to inaccurate estimates of the prevalence and impact of abortion on animal health and productivity. A considerable number of possible cases of abortion might be recovered by analysing the reproductive records in more detail. If we had analysed observed abortions only, we would have detected just 17.8% of total cases. We found a PAR for general abortion of 11.6% and a DIR of 1.7% per cow-month. General abortions were highest in first parity cows (PAR: 14.6%, and DIR: 1.9% per cow-month). The frequency of non-observed abortions decreased as the gestation period progressed, while the frequency of observed abortions increased with the gestation time. The foetal period around 40 days (corresponding to 82 gestation days) was the most critical for the risk of abortion [3]. These results suggest that different factors may affect the occurrence and detection of abortions at different stages of pregnancy. Such patterns of occurrence are different from those found in other production systems worldwide. The PAR in studies that included both observed and unobserved foetal losses varies widely, from 3.6% to 10.6% [1] and 10.2% [18]; our findings (11.6%) are at the upper limit of that report [3].

For parity and trimesters of gestation, we found different patterns of occurrence than in other production systems around the world and some evidence suggesting some potential factors associated. A previous abortion in the same lactation was observed in 9.2% of the cows that aborted, lower than the value for the general population (12.6%). A lower proportion of aborted cows was observed for cows with a history of abortion in the same lactation by parity 1, 2, 3, ≥4: 9.9%, 9.6%, 9.0% and 7.7%, respectively, compared with cows without a history of abortion by parity: 12.3%, 11.6%, 11.3% and 10.9%, respectively. Furthermore, for observed abortion cases, we found an increased trend across gestation that could nonetheless be associated with the fact that it is easier to observe an aborted foetus or signs of the cow in late gestation [12].

We observed that the probability of finding any type of abortion was lower during the second and third trimesters, with respect to the first gestational trimester. Previous studies showed that the highest risk of abortion for cows occurred during the first trimester, and it was related to the rate of twins and damage due to palpation [10]. In contrast, others reported a peak in incidence during the second trimester [19]. These differences may reflect variations in the detection time between studies.

A cow with an unobserved abortion would likely be detected sooner in herds with better oestrus detection; therefore, it might be a reflection of better management practices as well [12]. In addition, depressed progesterone secretion during the early foetal period and cows carrying twins [18] could influence abortions in this period, as well as excessive loss of body condition during early lactation related to metabolic and infectious diseases [19].

Other reports [7, 11] found a higher proportion of abortions than our study in cows with a history of previous occurrence of abortions. Our findings can be interpreted as a consequence of immunity protection for some infectious components. Protection against the recurrence of abortion would be expected in some infectious diseases like brucellosis, Campylobacter fetus, leptospirosis, BVDV infection and IBR infection [19, 20]. Although the studied herds were brucellosis-free, the other agents are prevalent abortion causes in southern Chile [21]. Vaccines against common infectious diseases do not seem to be a solution for reducing the incidence of abortions in a herd, except for the use of the Leptospira vaccine in special conditions of the herd. The above suggests an infectious and non-infectious component in the causal network [5].

The results from studies based on reported cases of abortion should be approached with care due to potential biases such as only analysing the cases of abortion submitted to the lab or searching mainly for a limited number of infectious agents. A definitive diagnosis is not always possible in veterinary diagnostic laboratories. In fact, only 30–55% of submissions result in a clear diagnosis [22]. This could imply a bias if the diagnosed causes of abortions (which occur in late gestation and are then observed) are extended to all gestational losses (early and late). Serological studies have been complemented with other analyses which were not totally successful in identifying an etiologic cause.

The role of common infections causing abortion in a region, as investigated by serology, was inconclusive, while additional etiological diagnoses were made in 31% of foetuses analysed by pathology and microbiology. When associations were found between the serologic results of the dams and the histologic lesions in the foetus, the results of the laboratory tests and the epidemiological investigation suggested that multiple pathogens were involved in the bovine abortion cases. Therefore, the hypothesis of a single etiological agent could not be confirmed. However, histologic lesions were found in only 62% of the analysed foetuses [22].

Based on the information regarding infectious causes and considering the above bias, the principal infectious agents reported as causing abortion in countries with a pasture-based system for milk production have been the following: In Argentina: brucellosis, C. fetus, Escherichia coli, bovine herpes virus, BVDV, neosporosis (NEO) [23, 24].

There are management measures in herds related to the level of abortions that could be grouped as factors associated with infectious diseases, production system intensity and nutritional aspects [3]. A tap drinking system for cows was found to reduce the likelihood of abortion in herds (OR: 0.74) compared to a herd that does not have a tap drinking water system for cows. The presence of some contaminants, such as nitrites, has been reported in southern Chile, which can reach groundwater through leaching and thus contaminate drinking water. On the other hand, a possible cause could be related to the transmission of some infectious diseases, like leptospirosis (serovars of Leptospira interrogans and Leptospira borgpepetseni), which is endemic in the area [25]. We adjusted the effect of vaccination against leptospirosis with the interaction term, and our findings support the idea that leptospirosis participates in the network of factors related to Bovine Abortion Syndrome (BAS). Also, we found a positive association between the practice of rodent control in food storage and the proportion of abortion in herds (OR: 1.61). However, one should not conclude that vaccination decreases the risk of abortion, but rather it is a consequence of high-level abortions in the herd. Another interesting finding [26] was the absence of a protective effect against abortion by using vaccines against other common diseases that cause abortion, such as BVDV, IBR and Neospora caninum. Although these agents are prevalent in the south of Chile and other neighbouring countries [21], the results contradict the common belief that vaccination programmes are effective for controlling abortion problems in herds [27, 28]. This highlights the complexity of the issue and the need for further research to understand the underlying factors and develop effective prevention strategies.

It is interesting to note that certain management practices were found to be associated with a decreased risk of abortions in herds. For example, the use of a bull versus artificial insemination only was associated with a lower risk of abortion (OR: 0.73). This may be related to improved reproductive efficiency, such as oestrous detection [29]. The results of [22] showed that abortion did not have a significant effect (p > 0.05) on the total amount of milk produced by the cows until 120 days after giving birth. This is consistent with previous research that reported a positive relationship between abortion and milk production around the time of artificial insemination for single pregnancies [26]. A potential reason for the discrepancy between the results is that one of the investigations only accounted for the mortality of embryos and foetuses, whereas the others also considered the foetal stage. This implies that the former study had a narrower scope and a different definition of pregnancy loss than the latter ones, which could affect the comparison and interpretation of the findings. Moreover, higher milk production has been reported as a significant factor for the rise in the twinning rate, and twin-bearing cows have a higher chance of losing their pregnancy [26].

It is interesting to note that the exclusive use of pasture for cows was associated with an increased risk of abortion (OR: 1.87) [26]. This could be related to mineral supplementation in cows (OR: 0.56). Although dairy farms in the area studied still adopt relatively extensive production systems, those not using any supplement may be related to low-yielding herds, which have the worst reproductive performance and nutritional problems. Cows with better body conditions have better reproductive performance than those with poor body condition [30]. Additionally, vitamin and mineral deficiencies have been described as being related to reproductive diseases, and cows fed with an adequate grass supply show better reproductive performance [31]. The β-carotene plasma level affects the corpus luteum function, and plasma levels of β-carotene in cows are affected by their feed [32].

Fresh plants have more carotene than preserved ones. Carotenoids in feedstuffs like hay, straw, fodder, etc., lose a lot of their content during the preservation and storage process [33]. For this reason, it would be very interesting to analyse the carotenoid plasma level and the metabolic, energy and protein balance at the cow level and its relation to abortion to elucidate the possible role of nutritional aspects in the incidence of abortion.

According to the results of [26], the problem of Bovine Abortion Syndrome (BAS) in the stratum studied, which includes medium to large dairy herds from southern Chile, is significant. The study also revealed that there is a large underestimation of abortion rates caused by only analysing farmers’ records of abortion. This highlights the importance of using multiple sources of information to accurately assess the incidence of abortion in dairy herds.

5. Different causal patterns of bovine abortion

To test whether cows that are more metabolically demanding could suffer from an imbalance during gestation and whether this could explain abortions that are not attributable to an infectious cause, a prospective observational study was conducted on two farms, one with a history of low (farm A) and another with a history of high lactational incidence of abortions (farm B), both in the southern region of Chile [26]. The gestation of the participating cows and their biochemical parameters were monitored. It was found that farm A had poor adaptation of energy and protein balance and a higher frequency and magnitude in the decrease of body condition score (BCS), while farm B had altered adaptation of protein metabolism. During the first and second third of gestation, cows that aborted had less loss of BCS than those that did not abort (p < 0.05), and then they improved their body condition between samplings (p < 0.05). A decline in body condition can affect pregnancy outcomes between 40 and 90 days of gestation, as it can reduce the production of progesterone by the corpus luteum; progesterone is essential for maintaining pregnancy and preventing embryonic loss. Therefore, body condition should be monitored and managed carefully during this critical period [34]. It is possible that the loss of body condition in this study did not affect the critical period of the corpus luteum or that the magnitude of the BCS loss was not strong enough to affect it. It is clear that the loss of BCS did not affect the presentation of abortions, since both on farm A and on farm B, cows that were aborted improved their body condition between samplings, which can be explained by the decrease in nutritional requirements when gestation is suspended [35]. There was a relationship between high levels of total protein (Pt), possibly due to plasma globulins (Glob), and the presentation of abortions, in relation to joint cases of mastitis or lameness. Pt is mainly influenced by serum globulins [34]. It has been shown that a case of mastitis or a febrile condition increases the risk of abortion due to an increase in prostaglandin (PGF2), which can cause the loss of gestation by luteolysis and contraction of the myometrium [36, 37]. Due to the seroconversion values for N. caninum, it cannot be ruled out that two of the eight abortions may have been favoured by this condition, although in the control group, 21% also had seroconversion without presenting abortion in the studied period and finally gave birth to a live calf.

A cross-sectional study was performed on 40 farms and 400 dairy cows in the central south of Chile to analyse abortigenic diseases in dairy farms [5]. The study used a two-stage sampling method and collected information about the management of the dairy farms using a personal questionnaire. To assess the exposure to four infectious diseases in dairy cattle, blood samples were collected and tested for brucellosis, bovine viral diarrhoea virus (BVD), neosporosis and leptospirosis. The results showed that BVD had the highest farm-level prevalence (97.5%), followed by neosporosis (87.4%) and leptospirosis (52.1%). At the individual level, the same pattern was observed, with BVD having the highest proportion (62.1%), neosporosis (22.4%) and leptospirosis (12.2%). Larger herds had a higher risk of BVD and neosporosis at the farm level. No evidence of brucellosis was detected. The factors associated with each disease were related to biosafety and the intensity of production, despite the control measures implemented [5].

The aim of the study [23] was to investigate the possible associations between bovine abortion syndrome and various factors, such as metabolic disorders and infectious diseases. The study design was a prospective observational cohort, in which cows that experienced abortion were compared with cows that did not. The study measured several parameters, such as blood biochemistry, serology and microbiology, to identify potential causes and risk factors for BAS. We conducted an analysis of how both infectious and non-infectious factors affect the risk of abortion in dairy cows. This study involved selected dairy cows from the Ñuble province of Chile (n = 148) that were 42 days pregnant. The aim was to investigate the effects of different factors on their reproductive performance and health status. Monthly blood samples were taken until abortion or delivery. Biochemical and serological disease indicators were determined. Cows were monitored and sampled monthly during pregnancy by rectal palpation and/or ultrasound. A multivariable logistic regression model and proportional hazard regression were used. In that study, it was found that Neospora caninum and Leptospira interrogans infections were significantly associated with BAS (P < 0.05), with an odds ratio (OR) of 4.27 and a hazard ratio (HR) of 94.35, respectively. We also observed that low cholesterol (Chol) levels (P < 0.05) in the fourth month of gestation (OR = 0.61) and a decline in body condition score from month three to four (OR = 0.32) increased the risk of BAS. These results suggest that BAS is related to the negative energy balance shown with beta-hydroxy-butyrate (BHB), the protective role of high cholesterol concentration in the first trimester, and the prevalence of Neospora caninum, Leptospira interrogans or both.

The results of the analysis for metabolic disorders and infectious diseases [23] indicated different potential aetiologies based on the data collected from the farms under investigation. In farm A, non-infectious factors (energy deficits, protein liver damage, inflammation) were more dominant, except for one abortion case due to neosporosis seropositivity. In farm B, infectious factors associated with leptospirosis (serovars Grippotyphosa and Harjo) and neosporosis were more frequent. These factors are important for the reproductive performance and health of dairy cows. This metabolite, jointly measured with a BCS evaluation, is useful for monitoring energy disorders in dairy herds. The correlation between plasma retinol and BVD titres was negative and moderate (r = −0.42, p < 0.05).

The study [23] that analysed 18 abortion cases due to different disorders and infections is summarised in Table 1. Table 1 also shows the abortion month for each case. The results indicated that the cows had different metabolic challenges in each trimester of pregnancy. In the first trimester, they had low energy and protein levels, signs of liver damage and increased inflammation markers. In the second trimester, they had low energy and protein levels, increased inflammation markers and positive serology for Neospora caninum and Leptospira interrogans (serovars Grippotyphosa and Harjo). In the third trimester, they had low energy and protein levels, signs of liver damage, increased inflammation markers and positive serology for Neospora caninum.

Case	Month	Chol	BHB	Pt	Alb	Glob	Fib	Urea	AST	NEO	Lepto	Possible causal pattern of abortion
1	3	↓	↑				↑					Energy imbalance, inflammation
2	3		↑			↑						Energy imbalance, inflammation
3	3	↓		↓			↑	↑				Protein imbalance, inflammation
4	3				↑				↑			Hepatocellular damage, inflammation
5	3			↓			↑					Inflammation
6	4	↓	↑								Gr	Energy imbalance, leptospirosis
7	4										Ha	Leptospirosis
8	4						↑			+		Inflammation, neosporosis
9	4			↓			↑					Inflammation
10	4						↑					Inflammation
11	4						↑					Inflammation
12	4						↑					Inflammation
13	7		↑						↑	+		Energy imbalance, hepatocellular damage, neosporosis
14	7			↓	↑					+		Inflammation, neosporosis
15	7		↑				↑					Energy imbalance, inflammation
16	8									+		Neosporosis
17	8		↑		↑							Energy imbalance, inflammation
18	8								↑			Hepatocellular damage

Table 1.

Detailed analysis of each abortion case presented in the southern Chile study [23] according to possible causal patterns.

↓ = plasmatic concentration under the reference interval (RI) for the species, ↑ = plasmatic concentration over the IR for the species, +: neosporosis positive serology, Gr: L. interrogans Serovar, Grippotyphosa, Ha: L. int. Serovar Hardjo.

To reduce reproductive losses in dairy cattle, which are often caused by infectious diseases [38] but not detected by routine tests [39, 40], we need to use epidemiological surveillance tools. These tools can help us improve management practices, disease control and nutritional management, as non-infectious factors may also play a role in the syndrome [22].

These tools can help farmers and veterinarians to identify potential risks and take appropriate actions to prevent or mitigate reproductive losses in their herds. By implementing effective management measures, controlling infectious diseases and ensuring proper nutritional management, farmers can improve the reproductive performance of their herds and reduce the incidence of bovine abortion syndrome.

6. Possible biomarkers for abortion risk

Acute phase proteins have been analysed and studied in association with infectious and inflammatory diseases in certain livestock populations. These proteins help to restore homeostasis, reduce microbial growth and have been used as biomarkers for inflammation, infection and trauma. Acute phase proteins are a group of proteins that are produced by the liver in response to inflammation, infection or trauma. Some examples of acute phase proteins include C-reactive protein (CRP), serum amyloid A (SAA) and haptoglobin (Hp). These proteins can be measured in blood samples to assess the presence and severity of inflammation, infection or trauma in livestock populations [41, 42].

The authors evaluated how the biochemical profile and acute phase proteins were related in cows that had abortions [40]. That study aimed to identify the multivariate associations of acute phase proteins and biochemical profiles in cows that were aborted. The results suggest that serum amyloid A (SAA) and haptoglobin (Hp), which are acute phase proteins in dairy cows, show different correlations with metabolic indicators of energy, oxidative, protein or organ dysfunction at the time of abortion. These findings indicate that the levels of these proteins and metabolic indicators in the blood could serve as potential biomarkers for assessing the likelihood of abortion in dairy cows. We collected blood samples monthly from 140 dairy cows during their pregnancy and monitored their health status. Out of these, 18 cows were aborted and were classified as ‘cases’. We also selected 29 ‘control’ cows that did not abort and matched their samples with the ‘cases’ by sampling time. We used multivariate analysis to compare the differences between the two groups and to assess the factors associated with abortion. We categorised abortion as either infectious (caused by DVB, leptospirosis or neosporosis) or non-infectious (related to protein or energy imbalances as shown in the metabolic profile). Among the 18 cows that were aborted, six had positive or seroconverted results for the diseases tested, 13 had signs of protein metabolic imbalances, seven had signs of energy imbalances and ten had both situations [40].

The Principal Component Analysis (PCA) showed significant differences (p < 0.05) between case and control cows, suggesting that they have distinct multivariate patterns. A cluster of variables related to protein metabolism, such as fibrinogen, serum amyloid A, haptoglobin and antibodies for neosporosis and bovine viral diarrhoea virus, was found in aborted cows. These variables were different from others related to energy and protein imbalance, such as high beta-hydroxy-butyrate, low cholesterol and low total protein.

Serum amyloid A and haptoglobin did not increase in cows that had abortions and were infected with pathogens such as bovine viral diarrhoea virus, leptospirosis or neosporosis. This suggests that these diseases do not cause significant systemic inflammation in aborting cows [40].

Cows that evidenced energy imbalances in their metabolic profiles had higher Hp plasma concentration (0.28 mg/ml) before abortion (p < 0.05). Fat mobilisation and negative energetic balance affected liver integrity more in cows that were aborted. Aborted cows also had different multivariate relationships between biochemical variables and serum amyloid A (SAA) and haptoglobin (Hp). We identified a group of variables related to protein metabolism, such as high levels of fibrinogen (Fib), SAA, Hp and antibodies for neosporosis (NEO) and bovine viral diarrhoea virus (BVD). These variables could be biomarkers of infection or inflammation, in addition to the usual indicators of biochemical profiles [40]. Acute phase proteins (APPs) are potential indicators of infection or inflammation in animal health. They are produced by the liver when local defences are overwhelmed by pathogens or tissue damage [41].

Were measured Hp and SAA, two acute phase proteins, in the blood of cows that aborted due to infection or other causes. We found that Hp was higher in cows with infectious abortion and SAA was higher in cows with non-infectious abortion. This means that these proteins can help us to quickly identify the cause of abortion in cows. However, studies also noticed that Hp was higher in cows that had energy imbalances before abortion [40]. These proteins are useful for checking the health and detecting diseases in animals that produce milk or meat [41, 42]. In the study [40], a strong link was found between BVD and NEO, two infectious agents for abortion in cows. The cows that were aborted had lower levels of antibodies for BVD than the cows that did not abort, and some of the cows that were aborted had high levels of antibodies for NEO.

It is important to consider both infectious and non-infectious causes when studying the causality of abortions in a herd. Non-infectious causes can occur in parallel with infectious diseases and can also contribute to the incidence of abortion. Serum amyloid A (SAA) has been suggested as a potential biomarker to differentiate between infectious and non-infectious abortions [40].

7. Economic losses due to bovine abortion syndrome

The losses on production caused by bovine abortion syndrome (BAS) must be comprehensively identified, as they not only correspond to the potential loss of the calf but also to all the actions that had to be carried out to achieve gestation in the cow, such as semen expenses, personnel, feeding, space occupied in infrastructure, etc. In addition, productive losses from the future milk production peak not achieved as a result of the lengthening of the calving interval and sequelae such as infertility or early embryonic losses post-abortion and lengthening of the generational interval must be considered. Bovine abortion problems can be a major cause of cow elimination, reaching 30 or 40% of total replacements [39], being more negative when applied to animals with good genetics and lifespan in the herd [5]. Numerous studies have been carried out using different techniques to estimate the economic losses produced by abortions in dairy production systems. There are reports for dairies in California in the 1980s, where it was estimated that if a cow aborts a 100-day foetus, it means a loss of US$ 640 [1].

The analysis carried out in Chile [38] on the losses caused by bovine abortion syndrome (BAS) according to the conditions of milk production in southern Chile indicates that the economic losses calculated per abortion for the dairy sector studied in one lactation are significant, although they are lower than those reported by studies in other countries [39]. The occurrence of abortion in one lactation was related to longer calving intervals, decreased annual milk production and early elimination of cows, which is consistent with other reports [19]. The main determinants of the cost of abortion were the level of milk production and the age of elimination of cows that had an abortion in their last lactation. Considering the population of cows in the southern zone (Araucanía, Los Ríos, Los Lagos regions), the distribution of the abortion occurrence rate and the distribution of losses due to abortion per year results in an average annual loss of Ch$-8.411 billion (bill), although with a wide variation (p2.5 $-22.247; p97.5 $5.903) and an 87.7% probability that the result of the abortion will be a loss for the producer. Under these conditions, an abortion is more harmful to a producer in a young cow with lower production than in an older cow with better milk production [38].

8. Conclusions

Bovine abortion is an important topic in herd management. Quantifying abortion occurrence using means of observed abortions underestimates the real situation since observed foetal losses are approximately 20% of the total foetal losses. Given the possible lack of a temporal relationship between abortion and the cause that produced it, it is difficult to obtain precise data on the occurrence of abortions to find a causal association. This leads to the need to try to maintain farm records of possible abortion risk factors so that a thorough retrospective farm analysis can be performed when an abortion occurs.

That highlights the importance of using multiple sources of information to accurately assess the incidence of abortion in dairy herds. To prevent the negative impact of reproductive disorders on herd productivity and profitability, it is essential to have epidemiological surveillance tools that enable early detection and intervention of potential problems. These tools include management measures, infectious disease control and proper nutritional management, which can help reduce the risk of reproductive losses and improve herd health and welfare. These tools can help farmers and veterinarians to identify potential risks and take appropriate actions to prevent or mitigate reproductive losses in their herds. By measuring the levels of SAA in blood samples from cows, it may be possible to quickly identify whether an abortion was caused by an infectious or non-infectious factor. By implementing effective management measures, controlling infectious diseases and ensuring proper nutritional management, farmers can improve the reproductive performance of their herds and reduce the incidence of bovine abortion syndrome.

Acknowledgments

I am grateful to my family, the University of Concepción, the Austral University of Chile, the National Commission for Science and Technology for the Doctoral scholarship, the Fondecyt initiation and the Faculty of Veterinary Sciences for allowing me to develop this area of study.