Failure of Passive Immune Transfer in Calves: A Meta-Analysis on the Consequences and Assessment of the Economic Impact
Failure of Passive Immune Transfer in Calves: A Meta-Analysis on the Consequences and Assessment of the Economic Impact
Didier Raboisson 0 1
Pauline Trillat 1
Clélia Cahuzac 0 1
0 Université de Toulouse, Institut National Polytechnique (INP), Ecole Nationale Vétérinaire de Toulouse (ENVT), UMR 1225, Interaction Hôte Agent Pathogène (IHAP) , F-31076 Toulouse, France, 2 INRA, UMR1225, IHAP, F-31076 Toulouse , France , 3 Université de Toulouse, Institut National Polytechnique (INP), Ecole Nationale Vétérinaire de Toulouse (ENVT) , F-31076 Toulouse , France
1 Editor: Dan Weary, University of British Columbia , CANADA
Low colostrum intake at birth results in the failure of passive transfer (FPT) due to the inadequate ingestion of colostral immunoglobulins (Ig). FPT is associated with an increased risk of mortality and decreased health and longevity. Despite the known management practices associated with low FPT, it remains an important issue in the field. Neither a quantitative analysis of FPT consequences nor an assessment of its total cost are available. To address this point, a meta-analysis on the adjusted associations between FPT and its outcomes was first performed. Then, the total costs of FPT in European systems were calculated using a stochastic method with adjusted values as the input parameters. The adjusted risks (and 95% confidence intervals) for mortality, bovine respiratory disease, diarrhoea and overall morbidity in the case of FPT were 2.12 (1.43-3.13), 1.75 (1.50-2.03), 1.51 (1.052.17) and 1.91 (1.63-2.24), respectively. The mean (and 95% prediction interval) total costs per calf with FPT were estimated to be €60 (€10-109) and €80 (€20-139) for dairy and beef, respectively. As a result of the double-step stochastic method, the proposed economic estimation constitutes the first estimate available for FPT. The results are presented in a way that facilitates their use in the field and, with limited effort, combines the cost of each contributor to increase the applicability of the economic assessment to the situations farmadvisors may face. The present economic estimates are also an important tool to evaluate the profitability of measures that aim to improve colostrum intake and FPT prevention.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information files.
Funding: The authors have no support or funding to
Competing Interests: The authors have declared
that no competing interests exist.
The failure of the neonatal calf to absorb adequate colostral immunoglobulins (Ig) within the
first hours of life results in failure of passive transfer (FPT). FPT leads to an increased risk of
mortality and decreased health and longevity. Depending on how FPT and livestock systems
are defined, the prevalence of FPT is reported to reach 20 to 40% of newborn calves [
Mortality linked to FPT has been reported as ranging from 8 to 25%. Ensuring that calves drink
enough colostrum within a few hours of birth is a powerful way to reduce FPT and its
associated disorders. The minimal quantity of Ig that the calf needs to absorb to prevent FPT is
approximately 150 g . Several practical guidelines to prevent FPT have been proposed for
use on farms [
]. Management practices that are risk factors for FPT are also well known
]. However, FPT remains an important issue on dairy and beef farms. Worldwide, FPT
contributes to high and increasing mortality rates of young calves . Because FPT increases
the risk of health disorders (mostly bovine respiratory diseases [BRD] and diarrhoea), it also
contributes to antimicrobial use and, consequently, to antimicrobial resistance [
The consequences of FPT on health are poorly described, and no quantitative overview is
available. Moreover, the total cost of FPT has never been reported. A clear overview of the
consequences of FTP and an assessment of its total costs would be key to helping farm advisors
make decisions. Because FPT is associated with several disorders, even simple economic
calculations made at the farms, such as a partial budget analysis, remain difficult and time
consuming. Good decision-making requires that the total cost of FPT be accurately determined, with
biological and livestock system variability included in the model. The present work aims to
estimate the total costs of FPT in European systems using a stochastic method with adjusted values
as the input parameters. Such an economic assessment cannot be performed without a
preliminary quantification of the adjusted associations between FPT and its outcomes using the
changing definitions of FPT and the co-variables from previously published models.
Materials and Methods
A literature search and screening process were conducted using the PubMed, CAB and Google
Scholar search engines to create a dataset of papers with the key words “passive immunity”,
“IgG”, “immunoglobulins”, “colostrum management”, “colostrum”, and “calf”, separately or in
combination. Additional papers referenced by at least 1 of the papers identified in the search
were also included. To be included in the dataset, the papers must have examined the risks of
various disorders (mortality, all diseases and production changes in calves with or without
FPT) and have been peer-reviewed. No other inclusion criteria were used. Exclusion criteria
were (i) papers with no quantification of the risk of diseases in case of FPT, since they cannot
included in the meta-regression, (ii) definition of PFT that did not fit with the retained one,
since they cannot be included in the related co-variables (Table 1) and (iii) outcomes that are
not mortality, diarrhoea, BRD or average daily gain (ADG), since other outcome only gather
one or two data. Papers published through June 2014 were included (Fig 1).
Fifteen papers evaluating the association between FPT and the above-mentioned outcomes
in calves were identified. The main reasons of exclusion were no quantification of risk and no
clear definition or quantification of FPT (Fig 1). Most of the papers studied several outcomes,
and 68 different models published in the literature were included in the present study. A
template for data extraction was drafted that included the numbers of calves and herds studied; the
breed (beef or dairy); the statistical method used (logistic regression, Poisson regression, or raw
data with contingency table); the expression of risk (relative risk [RR] or odd ratio [OR]); the
prevalence of FPT; the metabolite used to diagnose FPT (total proteins (TP) or Ig); the
threshold of TP or Ig used to diagnose FTP; the nature (univariate [U] or multivariate [M]) of the
reported model; the prevalence of the outcome or of the mean value if relevant; the duration of
the period of outcome inclusion; the value of the risk and its 95% confidence interval (95% CI);
standard error (SE) or standard deviation (SD); and all the covariates included within the
given model. No distinction was made between total Ig and IgG, and only the designation IgG
was used. For diseases, the method of diagnosis (in particular, whether by a veterinarian or a
farmer) was also reported in the dataset. Calves were sampled after 24 hour of life, so as to wait
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the final immunoglobulin absorption. Sampling occurred in a narrow window of time, such as
from 24 to 36 hour of age, in particular when TP where measured. When sampling occurred in
a large window of time, up to 1 week old, Ig and not TP were sampled in most of case. This was
consequently not further considered. All the studied publications had obtained their samples
prior to the onset of disease.
The threshold used to diagnose FPT, the presence of a gap between the thresholds used to
define calves with or without FPT, the duration of observation of the outcomes, and the
diseases analysed in cases of multiple diseases were transformed into categorical moderators for
the meta-analysis (FPTDIAG1; FPTDIAG2; FPTGAP; FPTTHRES; OUTTIME and OUTMORBIDITY)
according to the rules noted in Table 1. The covariates of the models were not considered
further except through the moderators of U/M and OR/RR. These covariates could not be
gathered into moderators because of their diversity. Few multivariate models were available.
Because of varying degree of dependence amongst the models retained for the meta-regression,
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Fig 1. Flowchart on selection of papers. BRD: Bovine Respiratory Diseases; ADG: Average Daily Gain; 1: Some papers included several outcomes at a
glance; 2: Some papers were excluded at the previous stage (literature review) based on its title.
1 extra moderator was created (designated “Group”) for each outcome by grouping the
different models in the same paper into different random classes.
A meta-analysis was conducted on the extracted outcomes using the Metafor package of R
(version 3.0.2; R Foundation for Statistical Computing, Vienna, Austria). The meta-analysis
was performed as previously described [
], and the different steps were recently outlined [
Briefly, fixed-effects and random-effects models were first conducted for each outcome to
estimate the log-effect size, its 95% CI and its statistical significance. The inconsistency of results
among trials was quantified using both Cochran’s Q test and the I2 statistic [
]. An I2 value
greater than 50% was considered to indicate substantial heterogeneity. If evidence of
heterogeneity was found, a meta-regression analysis was subsequently performed to explore the sources
of heterogeneity using the log-individual effect size for each trial as the outcome and a
fixedeffects or mixed-effects model with the random moderator “Group”. The meta-regression was
then conducted by screening for the moderators FTPDIAG1, FTPDIAG2, FTPGAP, FTPTHRES,
OUTTIME_MORT, OUTTIME_RESPI, OUTMORBIDITY, OR/RR, and U/M. The τ2 values of the
models, with or without moderators, were compared to explain the decrease in heterogeneity that
occurred when the moderator was included in the model. All the variables that met the first
screening criteria were entered into a backward stepwise regression model until all the variables
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that remained were significant at P<0.05. Forest plots were used to visually display the
estimated effect size, its 95% CI and the final meta-regression adjustments (in grey). For all the
meta-regressions, the “Reference” classes of the moderators were chosen to allow for the direct
interpretation of the effect size as an adjusted risk of outcome in the case of FPT. Because ORs
or RRs were used in the various analyses, the term “risk” may refer to any of these terms.
Values within parentheses after the risk values refer to 95% CIs. A sensitivity analysis was finally
performed using funnel plots and influential case diagnoses and included the analyses of
externally standardized residuals, DFFITS values, Cook's distances, covariance ratios, estimates of τ2
and test statistics for (residual) heterogeneity when each study is removed in turn, hat values,
and weights for the studies examining the risk of each outcome in the case of FPT.
The economic model was based on the principle of increased risk of disorders (mortality,
diseases and ADG decrease) for calves with FPT compared with those without FPT. The methods
were previously described for subclinical ketosis [
] and are briefly reported here. The
outcome variable of the economic model (Cost) was the total cost of FPT for a herd at a given (=
study) prevalence of FPT compared with the total cost of FPT for a control herd at a reference
prevalence of FPT. The total cost (Cost) was estimated by the sum of the cost (Costi) of each
contributor i (Eq 1)). Contributors design each of the disorders promoted (mortality and each
disease) or performances (ADG losses) modified in the presence of FPT. The calculations were
made for an average herd of 100 calves.
Costi ¼ Costi FPT
For each contributor i, Costi was the difference between the cost of FPT at the study
prevalence (Costi_FPT) and the cost of FPT for the control herd (Costi_CT) (Eq 2).
Costi ¼ Ci
Costi was calculated differently for mortality and diseases than for ADG decreases in
accordance with the ways the impact of FPT were expressed in the literature. For mortality and
diseases, Costi was defined as expressed in Eq 3. Costi for the study herd was the cost for one calf
with disease i (Ci in Eq 3) multiplied by the number of calves suffering from disease i denoted
by Uniti (the second part of Eq 3). Uniti was the difference in the number of calves suffering
from disease i in the study herd (the first bracket of Eq 3) minus those suffering from the same
disease in the control herd (the second bracket of Eq 3). The number of calves suffering from
disease i in the study herd (within the first bracket) was the number of calves without FPT
multiplied by the prevalence of disease i within this population (without FPT) plus the number of
calves with FPT multiplied by the prevalence of disease i within this population (with FPT).
The number of calves suffering from disease i in the control herd (within the second bracket)
was calculated in the same way as for the study herd, but the number of calves with and without
FPT was different for the study and control herds.
PrevHERD_CT = Prevalence of FPT in the control herd
PrevCOMPi_NoFPT = Within-herd prevalence of disease i in calves without FPT
PrevCOMPi_FPT = Within-herd prevalence of disease i in calves with FPT
PrevCOMPi_FPT and PrevCOMPi_NoFPT were linked by RRi (Eq 4).
PrevCOMPi FPT ¼ PrevCOMPi NoFPT
RRi = Relative risk of disease i in calves with FPT compared to calves without FPT
Combining Eq 3 and Eq 4 led to Eq 5.
PrevCOMPi_AllPop = Prevalence of disease i in calves with or without FPT
PrevFPT = Prevalence of FPT from the study reporting RRi and PrevCOMPi_AllPop
The cost related to ADG decreased in the case of FPT calculated using Eq 7 for beef,
considering the decrease in selling price due to reduced growth.
CostADG BEEF ¼ DADG
Duration of breeding
ΔADG = Decrease in ADG due to FPT (Kg/d)
Duration of breeding = Duration between birth and sale for fattening (d.)
Selling price = Selling price (€ / Kg of body weight [BW])
For dairy cattle, cost was calculated for heifers considering the extra day before the first
insemination in case of decreased ADG, according to Eqs 8 and 9. This allowed us to consider
several livestock systems with different values for ADG and age at first calving.
CostADGDAIRY ¼ DDAYS
CDaily Bredding ¼
ðAge in d at calving #1
ΔDAYS = Extra days needed to compensate for decreased ADG
CDaily Breeding = Average daily cost of breeding for a heifer (€ /d)
ΔWeight = Decrease in weight due to decreased ADG (Kg) for the whole breeding period
ADG = Average daily gain for the whole breeding period
ΔADG = Decrease in ADG due to FPT
The unit cost of mortality (CMORTALITY) was defined as either the market value of the dairy
or beef calf at the date of death (denoted CMORTALITY_Replacement) or the lost earnings (denoted
CMORTALITYEarningforgone ) up to the date of sale for beef calves (Eq 10).
CMORTALITYEarningforgone ¼ Selling Price
Selling Weight = Weight of the calf at sale (Kg)
CConc = Cost of concentrate for calves (€ /Kg)
QtyConc = Quantity of concentrate eaten per calf for the whole breeding period (Kg)
The unit cost of morbidity (CMORBDITY) was the sum of 3 components proportional to weight at
treatment (i.e., drugs), fixed per animal (i.e., veterinarian visits) and labour of the farmer (Eq 11).
CMORBIDITY ¼ CMORBIDITY Prop þ CMORBIDITY Fixed þ CMORBIDITY Labour
CMORBIDITY_Prop = Proportional cost of one case of morbidity (€ / Kg BW)
CMORBIDITY_Fixed = Fixed cost of one case of morbidity (€ /case)
CMORBIDITY_Labour = Labour cost of one case of morbidity (€ /case)
In cases of diarrhoea and BRD, the risk of relapse has to be accounted for. Uniti, calculated
in Eq 5, only considers calves that are sick (and treated) at least once. Therefore, the relapse
risk was taken in account through CMORBIDITY, according to Eq 12 and Eq 13.
CDIARRHOEA_relapse and CBRD_relapse were included in Eq 5 instead of CDIARRHOEA and CBRD, respectively.
CDIARRHOEA relapse ¼ CDIARRHOEA ð1 þ Relapse1DIARRHOEA Þ
CBRD relapse ¼ CBRD ð1 þ Relapse1BRD Þ ð1 þ Relapse2BRD Þ
Relapse1DIARRHOEA = Relapse risk of rank 1 for diarrhoea
Relapse1BRD = Relapse risk of rank 1 for BRD
Relapse2BRD = Relapse risk of rank 2 for BRD
To account for more severe disorders for calves with FPT compared to these without FPT
and for supplementary difficulties in managing the herd in cases of high PrevHERD_FPT, 2
conditional coefficients of severity (Eqs 14 and 15) were introduced in Eq 5.
SevFPT for calves with FPT
CMORBIDITY for calves without FPT
SevPRESSURE when PrevHERD FPT
CMORBIDITY when PrevHERD FPT < 40%
Eqs 12, 13, 14 and 15 apply additively in Eq 5.
The economic model was run using Scilab open source software (www.scilab.org) with
10,000 iterations, and 95% prediction intervals (PI) and 95% CIs were calculated. The PI makes
it possible to predict the situation for the next farm with 95% probability, whereas the CI
indicates the situation in 95 of 100 farms visited.
The RRi, the prevalence and the unit costs Ci used in the assessment are presented in
Table 2 and explained in detail. Most of the input parameters were included as a law of
distribution (normal or log-normal) and not as a point estimate. Four scenarios were proposed that
combined different input parameters. The baseline scenario was the most probable. The
alternative scenario included more contributors and different calibrations. The low and high
scenarios used minimum and maximum values for calibration, respectively. For RRi, the
alternative and high scenarios included raw data from the literature review before any correction,
whereas the baseline and low scenarios included the results of the above meta-analysis.
PrevCOMPi_NoFPT was calculated using Eq 6 and applied to studies of the meta-analysis (S1–S3
Tables). Lack of data on omphalitis and septicaemia led to a definition in line with the entity
“morbidity” of the meta-analysis. PrevMortality_NoFPT was defined based on Eq 6, and data from
studies included in the meta-analysis led to a value considered low by the authors (3.2%).
PrevMortality_AllPop is well described for France. On average, it is 6.2% and 10% between birth
and 1 month of age for beef and dairy cattle, respectively (Raboisson, 2014). PrevMortality_NoFPT
is shown in Table 2 with the 2 last values included in Eq 6, and PrevFPT was fixed at 25% and
40% for beef and dairy cattle, respectively.
Unit costs (Ci) were derived from different sources. These have been explained in detail
]. Selling Price, Selling Weight, QtyConc, Age in d at calving #1, CDaily Bredding and
Duration of breeding were adapted from French Livestock Institute publications [
CMORTALITY Remplacement was the market value . CMORBIDITY was defined by the authors
based on health consequences and common medical protocols. Based on the authors’ expertise,
Ci is explained in S1 Table. Medicines were chosen according to the most common protocols
observed in the field, and prices were defined as the sale prices recommended by veterinary
clinics in 2014 (www.centravet.fr).
PrevHERD_CT was defined at 10%. SevFPT and SevPRESSURE were fixed at 1.375, according to
one or two extra days of treatment (mean = 4 days) needed for calves with FPT compared to
these without [
]. Relapse2DIARRHOEA ; Relapse1BRD and Relapse1BRD were 20%, 30% and 20%,
The association between FPT and mortality was reported in 28 models from 10 publications
(S2 Table). The mean (SD) risk of mortality associated with FPT was 4.87 (7.62). The
heterogeneity of the dataset was high (I2 = 68% [95% CI = 46–79] and Q statistics χ2 = 80, df = 27,
P < 0.001). The intercept of the log-effect size in the mixed-effects model with no moderator
was 0.88 (SE = 0.020, P<0.001), which corresponded to an effect size of 2.41 (1.62–3.58).
Including the moderators FTPDIAG1, FTPDIAG2 and FTPGAP reduced the heterogeneity by 23,
29 and 22%, respectively (Table 3). All other moderators were not significant (P>0.05), and
their inclusion in the meta-regression did not decrease the heterogeneity. Similarly, no
multivariate meta-regression allowed us to reduce the heterogeneity. Replacing FTPDIAG1 with
FTPDIAG2 in the meta-regression led to an OR of mortality in the case of FPT of 1.92 (data not
shown) instead of 2.12 (Table 3). The sensitivity analysis showed no outlier for the
metaregression without a moderator, but doubt exists regarding model #4 (S2 Table) when the
moderator FTPDIAG2 was considered based on DIFFTS and cov and τ2 statistics. Excluding these
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1: LN = LogNormal, N = Normal
2: Average daily gain reduction due to FTP and bovine respiratory diseases
3: mean (and SD)
6: formula is selling price * selling weight–CConc * QtyConc; only applies to beef cattle
7: particularly during treatment.
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1: n: number; m: mean; SD: standard deviation; SE: standard error; 95% CI: 95% confidence interval. P values are coded as follow
2: Meta-regression after the sensitivity analysis and exclusion of one model of the data.
data did not lead to significant changes (Table 3). In summary, the present work retains the
risk (95% CI) of mortality in calves with FPT adjusted for the moderator FTPDIAG2 (Fig 2),
which is 2.16 (1.51–3.09).
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Fig 2. Forest graph for mortality. Adjustments were made for the moderator FPTDIAG1. The column on the
left refers to the values of FPTDIAG1. The column on the right refers to the log-scale observed outcomes (OR
or RR) and their relative 95% CIs. The grey squares represent the log-effect size adjusted for FPTDIAG1.
The association between FPT and BRD was reported in 12 models from 5 publications (S3
Table). The mean (SD) risk of BRD associated with FPT was 2.24 (1.20). The heterogeneity of
the dataset was high (I2 = 72% [55–82] and Q statistics χ2 = 61, df = 11, P < 0.001). The
intercept of the log-effect size in the mixed-effects model with no moderator was 0.82 (SE = 0.17,
P<0.001), which corresponded to an effect size of 2.27 (1.62–3.17). No moderators were
significant or allowed a decrease in heterogeneity. The sensitivity analysis showed an outlier (model
#2) based on most of the statistics considered. Excluding these data led to a decrease in the risk
(95% CI) of BRD in calves with FPT (Fig 3 and S1 Fig), which was 1.75 (1.50–2.03). I2 also
The association between FPT and diarrhoea was reported in 5 models from 2 publications
(S1 Table). The mean (SD) risk of BRD associated with FPT was 1.71 (0.70). The heterogeneity
of the dataset was high (I2 = 80%). The intercept of the log-effect size in the mixed-effects
model with no moderator was 0.56 (SE = 0.32, P = 0.07), which corresponded to an effect size
of 1.76 (0.94–3.27). None of the moderators were significant. Excluding the data from model
#2 as suggested by the sensitivity analysis led to a risk (95% CI) of diarrhoea in calves with FPT
of 1.51 (1.05–2.17).
Four publications (8 models) provided data on the risk of at least one disorder (except
mortality) or at least one treatment in cases of FPT (S3 Table). The mean (SD) risk associated with
FPT was 2.72 (1.71). I2 was 51%. The intercept of the log-effect size in the mixed-effects model
with no moderator was 0.58 (SE = 0.17, P<0.05), which corresponded to an effect size of 1.80
(1.28–2.52). None of the moderators were significant. The sensitivity analysis did not reveal
When combining data related to the last 3 outcomes, 25 studies from 10 publications were
available (Table 3). The mean (SD) risk of BRD associated with FPT was 2.34 (1.31). The
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Fig 3. Forest graph for bovine respiratory disease. The column on the right refers to the observed
outcomes (OR or RR) and their relative 95% CIs.
heterogeneity of the dataset was high (I2 = 73% [50–88] and Q statistics χ2 = 107, df = 24,
P < 0.001). The intercept of the log-effect size in the mixed-effects model with no moderator
was 0.64 (SE = 0.08, P<0.001), which corresponded to an effect size of 1.91 (1.63–2.24). The
moderators FTPDIAG1 and OUTMORBIDITY were significant, but their inclusion did not reduce
the heterogeneity and led to slight changes in the log-effect size (Table 2).
The ADG change related to FPT was reported in 12 models from 6 publications (S4 Table).
The mean (SD) ADG decrease for calves with FPT was 81 g/day (76). It was 54 (48) when
redundant data from Robinson, 1998, were excluded (only the ADG for the period of 0 to 180
days was considered). SEs of the models were not provided in most of the results, preventing a
meta-regression for this outcome. The ADG change relative to morbidity was reported in 6
models from 4 publications. No further analysis was provided.
The total cost of one case of FPT in the baseline scenario is €60 [95% PI = €10–109] and €80
[95% PI = €20–139] per dairy and beef calf, respectively. It is €95 [95% PI = €38–151] and €132
[95% PI = €70–200] in cases of high prevalence (Table 4). These costs are nearly twice as high
in the alternative scenario, up to three times as high in the high scenario, and approximately 10–
20% lower in the low scenario. The total cost of each contributor increases linearly up to a
prevalence of 40%, and above 40% the slopes differ in accordance with the SevPRESSURE applied. One
exception is ADG (Fig 4). The relative parts of each contributor (Table 5) for the different
scenarios show the high part related to ADG compared to other parts. This is most commonly observed
in the alternative and high scenarios in accordance with the higher ΔADG (Table 3), and for
dairy compared to beef cattle. This part of the ADG tends to decrease with a high prevalence of
FPT. The total cost of FPT increased by 20% and 40% for dairy heifers that first calved at 2.5 or 3
years old, respectively, compared to those that calved at 2 years old (results not shown); the
difference originated from the component ADG, which was applied to the whole breeding period.
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1: The baseline scenario was the most probable. The alternative scenario was also possible and included higher prices for some contributors. The high
and low scenarios minimized and maximized all input parameters.
The present work used the OR or RR. Differences between OR and RR are negligible when the
probability of the outcome is low and when the baseline risk for each subgroup is relatively
Fig 4. The total cost of the contributors in cases of FPT for beef and dairy in the baseline scenario. BRD: bovine respiratory disease; ADG; average
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1: The sum is not 100% because the contributors omphalitis and diarrhoea are not shown.
]. These criteria were met for mortality in the present work but remained
questionable in terms of morbidity. A scarcity of data led us to consider all available data. Regressions
including the moderator RR/OR were not significant.
The definition of FPT was based on low TP or low IgG. At present, TP and IgG are
commonly and consensually used to evaluate FPT. Both are quantitative indicators of immune
transfer success, although TP may increase due to inflammation and rather than to IgG
pinocytosis. The thresholds for TP and IgG used to define FPT vary, but thresholds used as references
in the present work are those most commonly used. Subclinical disorders associated with
diseases or production changes are defined with a threshold of metabolites or of biochemical
parameters that maximize the sensitivity and specificity of the diagnosis. These studies
simultaneously defined the objective animal-level threshold of interest parameters and the risk linked
to the disease or production change. Similar intensive studies have been conducted for
subclinical ketosis but rarely for FPT. Except for a few examples [
] that only involved small
populations, no multiple regression with different thresholds and associated ROC curves has been
performed for FPT. The threshold to define FPT is consequently often arbitrary and without
justification. This highlights the need to standardize the risk value by the definition of FPT, as
we have done here. This is in accordance with the results of the meta-regression for mortality
and morbidity showing the significance of the moderator FTPDIAG and the decrease in
heterogeneity when this moderator was applied (Table 3). The adjustment of the mean risk by the
threshold used to diagnose FPT allowed us to prevent an overestimated mean risk (2.12 instead
of 2.41) in the present work (Table 2). Similarly, the risk of mortality for FPT comparing two
extreme populations for IgG or PT is overestimated (FPTGAP, Table 2). The duration of
observation of mortality was not reported as a significant bias of the risk value in the present work,
even though the longer the study, the higher the expected mortality.
The absence of any significant moderator for BRD, diarrhoea, or at least one other disorder
is linked to the low statistical power permitted by the size of the dataset. The risk of diarrhoea
in cases of FPT is extremely low. This is in accordance with the high prevalence of diarrhoea in
calves without FPT, which mathematically caps the value of the risk. The risk for BRD in cases
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of FPT is of the same magnitude as the risk of diarrhoea. Improvement of BRD through
colostrum feeding is rarely promoted in the field as opposed to diarrhoea. A recent study has shown
that vaccinating cows against BRD before calving and good colostrum feeding help to control
BRD in calves [
One other significant limitation of the present meta-regression originates from the data
available, particularly (i) the lack of co-variates in many of the raw models included, and (ii)
the lack of data for the other consequences of FPT that were not included here. First, the value
of the risk obtained in the various studies depends on not only the thresholds used but also the
adjustments made by potential biases of co-factors. For example, no model explaining the risk
of diarrhoea in cases of FPT included the presence of BRD (or versa); instead, the interaction
between both is described [
]. The OR of mortality in cases of FPT was adjusted by neither
diarrhoea nor BRD in the studies, preventing any adjustment within the meta-regression.
Second, the disorders and production changes associated with FPT in only a few studies were not
included in the present work. This includes feed efficiency, age at first calving, milk production
at first and second lactation, and risk of culling at first lactation [
]. Some of these factors
are related to ADG. Data on the reduction of ADG in cases of FPT is controversial, with
significant differences between results. Interestingly, most of the high values originate from one
]. Only 3 studies reported ADG calculated using a long duration, but ADG
variability still remains (16, 50 and 134 g/d). Although most of the models involved are
multivariate, they did not include morbidity as a co-variate. This may bias the results and contribute
to the significant heterogeneity of the estimations.
The present meta-regression was performed as previously described [
]. The intercept
obtained in the random-effects model with no moderator was more precise than the raw mean
of risk because the lower the variance of the raw value, the higher the weight in the
metaregression. These changes may be high. For example, the OR for mortality decreased from 4.87
(raw mean) to 2.41 (mixed-effects meta-regression without moderator, Table 3). The final
meta-regression (and relative adjusted risk) that was retained was judged on the reduction of
the heterogeneity relative to the regression without moderators. Only the mixed-effects models
were reported in the present work, in accordance with the structure of the dataset (several lines
of the dataset were from the same publication). The funnel plots did not show any publication
bias. They were not asymmetric, suggesting no studies with a reduced likelihood of inclusion
within the meta-analysis because they were not published due to small or non-significant
A double-step stochastic method for easy application of the results in the
In the cattle industry, many decisions about animal health are made without considering
economics. In particular, estimates of the cost of multiple diseases thought to be occurring
simultaneously -where losses or extra costs are difficult to attribute to one disease or the other- are
rare. The proposed double-step approach has been extensively discussed elsewhere [
allowed the costs of diseases with multiple interactions to be estimated accurately because of (i)
the correction permitted by the meta-analysis that led to a reduced risk of economic
miscalculation due to overestimated or underestimated RR and (ii) the use of the prevalence of diseases
in calves without FPT instead of the prevalence in calves with and without FPT. These two
types of adjustments to the input parameters allowed for the proposed accurate estimation.
The total cost of FPT was considered to be the sum of the costs related to mortality, morbidity
and ADG decrease. Such an approach is accurate because the input parameters are adjusted by
the other components. For example, mortality represents the whole mortality linked to FPT
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regardless of the cause of the mortality, and the cost of morbidity never includes consecutive
deaths from diarrhoea, BRD or other causes. This is why the unit cost of morbidity was based
on extra costs only and did not include losses in production. Another example is ADG, which
included not only the potential direct impact of FPT but also the indirect impact through
morbidity. The choices were made according to the data that were available and have no
connection to biological mechanisms. The way the economic model was constructed has to be kept in
mind when interpreting the weight of the different components in the total cost of FPT.
Because FPT appears around birth and generally has short-term consequences, the static
approach proposed seems adequate. A dynamic model may have been useful but it would have
led to significant difficulties in calibration.
The present results were expressed as the total cost of one case of FPT, but the avoidable
cost linked to FPT can easily be estimated in the field. Our detailed method is explained
]. Briefly, the prevalence of FPT at the initial stage must be estimated first (using TP,
for example). The total avoidable cost for a given farm will then be (i) the unit cost of FPT
multiplied by (ii) the number of calves born (iii) multiplied by the prevalence of FPT at the initial
stage minus a reference (not null) prevalence of FPT. Whether the expected prevalence (based
on practitioner experience) after measures have been adopted is used instead of the reference
prevalence, the comparison of the avoidable cost linked to FPT and the prices of the measures
proposed helps in making a decision. Using the stochastic approach, both the mean and a 95%
PI have been proposed. Because of biological variability, the use of the mean values as well as
the ranges of the 95% PI is recommended to make robust economic-oriented decisions when
end users calculate the herd-level avoidable costs. Farm advisors must use the PI rather than
the CI because the PI predicts the value with 95% probability for the next case (i.e.; the next
herd they have to evaluate), whereas the CI gives the distribution of values for 95 of the next
Calibration and interpretation of the economic model
Despite the significant efforts made in the present study to address double counting and
incorrect estimations, factors such as ADG, septicaemia and omphalitis continued to be difficult to
address. Some assumptions were also adopted when performing the current estimation due to
a lack of data. A good understanding of the calibration of the economic model and the report
on the part of each contributor (Table 5) allow an integrative use of the present results.
First, the model was performed at the herd level to allow for different calibrations of low
and high prevalences of diseases. The importance of the infectious pressure on the
management and control of disease at the herd level cannot be overlooked. The values of SevPRESSURE
and PrevHERD_FPT that may affect the infectious pressure (Eq 15) remain questionable. The
present method may present results at the herd level (mean cost per 100 cows for a given
prevalence) or per cow with FPT, as is the case here. The total cost and marginal cost were the same
up to an FPT prevalence of 40%. This result is consistent with how the total cost was calculated
based on the input parameters and the literature. Above this prevalence, the marginal cost of
FPT increased dramatically. The threshold established at an FPT prevalence of 40% definitely
does not exist in the field, and infectious pressure may be progressive. It is the responsibility of
the user of the present results in the field to decide which results to use (i.e., 60 or 120 for dairy
and 80 or 160 for beef) according to the farm and the current situation.
Second, the clear identification of the relevant part of each contributor allows for the
modulation of the results to various farming systems. Because the different contributors to the total
cost of FTP are additive, the total cost can easily be recalculated to best fit to the user’s
experience and the farming system. The summary of the input parameters (Table 3) and parts of the
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contributors for all key situations (Table 5) can assist in such work. For example, the
contributor ADG may be adapted depending on the user’s goal. ΔADG applies for the whole breeding
period for both dairy and beef calves. For beef calves, ΔADG is likely to apply up to weaning,
and beef calves are mostly sold at this point. Reduced ADG after weaning and selling in case of
FPT was not considered even though it may occur. In other words, the present total cost is
appropriate for breeding activity only and excludes fattening activity. Similarly, ΔADG was not
applied to male dairy calves, which are fattened outside the farm of birth in most cases. By
contrast, the application of ΔADG for the whole breeding period for dairy heifers may be excessive,
and it might only apply for 6 months to one year. This suggests that the cost for calving at 2.5
or 3 years is the same as for a first calving at 2 years. The literature suggests that weight curves
of heifers with FPT are lower than those without FPT, but the curves remain parallel [
would indicate that only-half or one-quarter of the contributor ADG needs to be considered
for dairy cattle. Other possibilities for the integrative use of the present results are the
differentiation of male and female cattle on a dairy farm: deleting the ADG contributor for males and
just considering it for females is a possible way to apply the present total cost. Such an
approach may be appropriate for dairy farms with differentiated habits in colostrum
distribution (and care provided) for males and females. By contrast because of the lack of consistency
on the value of ΔADG, using the alternative or high scenario instead of the baseline or low
scenario is not recommended for the contributor ADG. The total costs for dairy males and females
with FPT are consequently €28.2 [95% PI = 9.1–47.2] and €51.1 [95% PI = 29.4–72.9],
respectively, when applying the present parameters for ADG (only ADG in females, and reduced to
By contrast, questions have arisen on a potential underestimation of diarrhoea and BRD
contributors in the baseline and low scenarios. On one hand, the unit cost of these contributors
is quite low when compared to the real cost, including the intervention of a veterinarian. On
the other hand, only some ill calves are observed by practitioners in most farming systems, and
the definition of the unit cost accounted for that (S1 Table). The inclusion of the contributors
septicaemia and omphalitis should remain at each practitioner’s discretion. A different
approach may be used in the field for these 2 contributors: septicaemia may be related to high
mortality, and omphalitis is often well identified, allowing for a specific evaluation of the
Third, some key parameters are poorly known. Relapse after BRD or diarrhoea and the
value of SevPRESSURE may differ greatly among farming systems, farms, dominant pathogens
involved and years.
The present work proposed an adjusted risk of mortality, diarrhoea, and BRD in cases of FPT.
These results may be used by practitioners and also for the further calibration of epidemiologic
or economic empiric models. The mean total costs related to FPT for farmers were estimated
to be €60 and €80 per dairy and beef calf with FPT, respectively. The 95% PIs were €10–109
and €20–139, respectively. As a result of using a double-step stochastic method, the proposed
economic estimation constitutes a first estimate available for FPT. Nonetheless, a lack of data
for calibration limits confirmation of the accuracy of the present estimation. The way in which
the results are presented facilitates their use in the field and allows, with limited effort, the
combination of the cost of each contributor to increase the appropriateness of the economic
assessment to the situations farm-advisors may face. The present economic estimates are also an
important tool to evaluate the profitability of measures that aim at improving colostrum
17 / 19
S1 Fig. Example of an influential case diagnostics graph for respiratory diseases
S1 Table. Definitions of costs of diseases
S2 Table. Raw data used for the meta-analysis and to calculate the prevalence of mortality
in calves without failure of passive transfer
S3 Table. Raw data used for the meta-analysis and to calculate the prevalence of diseases in
calves without failure of passive transfer
S4 Table. Raw data used for the review of ADG reduction in calves without failure of
Conceived and designed the experiments: DR CC. Performed the experiments: DR PT CC.
Analyzed the data: DR PT CC. Contributed reagents/materials/analysis tools: DR PT CC.
Wrote the paper: DR PT CC.
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1. Beam AL , Lombard JE , Kopral CA , Garber LP , Winter AL , Hicks JA , et al. ( 2009 ) Prevalence of failure of passive transfer of immunity in newborn heifer calves and associated management practices on US dairy operations . J Dairy Sci 92 : 3973 - 3980 . doi: 10 .3168/jds.2009-2225 PMID: 19620681
2. National Animal Health Monotoring Sytem (NAHMS) ( 1993 ) National dairy heifer evaluation projecct. Dairy herd managment practices focusing on preweaned heifers . Ft Collins, CO: USDA-APHIS Veterinary Services .
3. Chigerwe M , Tyler JW , Schultz LG , Middleton JR , Steevens BJ , Spain JN . ( 2008 ) Effect of colostrum administration by use of oroesophageal intubation on serum IgG concentrations in Holstein bull calves . Am J Vet Res 69 : 1158 - 1163 . doi: 10 .2460/ajvr.69.9.1158 PMID: 18764687
4. Chigerwe M , Coons DM , Hagey JV ( 2012 ) Comparison of colostrum feeding by nipple bottle versus oroesophageal tubing in Holstein dairy bull calves . J Am Vet Med Assoc 241 : 104 - 109 . doi: 10 .2460/ javma.241.1.104 PMID: 22720994
5. Chigerwe M , Tyler JW , Summers MK , Middleton JR , Schultz LG , Nagy DW . ( 2009 ) Evaluation of factors affecting serum IgG concentrations in bottle-fed calves . J Am Vet Med Assoc 234 : 785 - 789 . doi: 10 . 2460/javma.234.6.785 PMID: 19284346
6. Pritchett LC , Gay CC , Besser TE , Hancock DD ( 1991 ) Management and production factors influencing immunoglobulin G1 concentration in colostrum from Holstein cows . J Dairy Sci 74 : 2336 - 2341 . PMID: 1894821
7. Godden S ( 2008 ) Colostrum management for dairy calves . Vet Clin North Am Food Anim Pract 24 : 19 - 39 . doi: 10 .1016/j.cvfa. 2007 . 10 .005 PMID: 18299030
8. Quigley JD 3rd, Drewry JJ ( 1998 ) Nutrient and immunity transfer from cow to calf pre- and postcalving . J Dairy Sci 81 : 2779 - 2790 . PMID: 9812284
9. Trotz-Williams LA , Leslie KE , Peregrine AS ( 2008 ) Passive immunity in Ontario dairy calves and investigation of its association with calf management practices . J Dairy Sci 91 : 3840 - 3849 . doi: 10 .3168/jds. 2007-0898 PMID: 18832206
10. Raboisson D , Delor F , Cahuzac E , Gendre C , Sans P , Allaire G. ( 2013 ) Perinatal, neonatal and rearing period mortality of dairy calves and replacement heifers in France . J Dairy Sci 96 : 2913 - 2924 . doi: 10 . 3168/jds.2012-6010 PMID: 23477819
11. Finch R ( 2010 ) Generic antibiotics, antibiotic resistance, and drug licensing . Lancet Infect Dis 10 : 754 . doi: 10 .1016/S1473- 3099 ( 10 ) 70246 - 2 PMID: 21029992
12. Viechtbauer W ( 2010 ) Conducting meta-analyses in R with the meta for package . Journal of Statistical Software 36 : 1 - 48 .
13. Raboisson D , Mounie M , Maigne E ( 2014 ) Diseases, reproductive performance, and changes in milk production associated with subclinical ketosis in dairy cows: a meta-analysis and review . J Dairy Sci 97 : 7547 - 7563 . doi: 10 .3168/jds.2014-8237 PMID: 25306269
14. Higgins JP , Thompson SG , Deeks JJ , Altman DG ( 2003 ) Measuring inconsistency in meta-analyses . BMJ 327 : 557 - 560 . PMID: 12958120
15. Raboisson D , Mounie M , Khenifar E , Maigne E ( 2015 ) The economic impact of subclinical ketosis at the farm level: tackling the challenge of over-estimation due to multiple interactions . Prev Vet Med 122 : 417 - 425 . doi: 10 .1016/j.prevetmed. 2015 . 07 .010 PMID: 26276398
16. Hasler B , Alarcon P , Raboisson D , Waret-Szkuta A , Rushton J ( 2015 ) Integration of production and financial models to analyse the financial impact of livestock diseases: a case study of Schmallenberg virus disease on British and French dairy farms . Vet Rec Open 2 : e000035. doi: 10 .1136/vetreco-2014 - 000035 PMID: 26392883
17. Raboisson D , Waret-Szkuta A , Rushton J , Hasler B , Alarcon P ( 2014 ) Application of integrated production and economic models to estimate the impact of Schmallenberg virus for various beef suckler production systems in France and the United Kingdom . BMC Vet Res 10 : 254 . doi: 10 .1186/s12917-014- 0254-z PMID: 25344772
18. Institut de l'Elevage [French Livestock Institut] ( 2013 ) Résultats 2011 des exploitations bovins lait. Résultats nationaux. Collection résultats annuels. Réseaux d'élevage pour le conseil et la prospective . In: Insitut de l'Elevage [French Livestock Institut], editor. Résultats nationaux Collection résultats annuels Réseaux d'élevage pour le conseil et la prospective : Insitut de l'Elevage [French Livestock Institut]. pp. 52 .
19. Insitut de l'Elevage [French Livestock Institut] ( 2013 ) Résultats 2011 des exploitations bovins viande. Résultats nationaux. Collection résultats annuels. Réseaux d'élevage pour le conseil et la prospective . In: Insitut de l'Elevage [French Livestock Institut], editor. Résultats nationaux Collection résultats annuels Réseaux d'élevage pour le conseil et la prospective : Insitut de l'Elevage [French Livestock Institut]. pp. 40 .
20. France Agricole ( 2012 ) n° 3443 3455 . Available: http://www.lafranceagricole.fr/.
21. Donovan GA , Dohoo IR , Montgomery DM , Bennett FL ( 1998 ) Associations between passive immunity and morbidity and mortality in dairy heifers in Florida, USA . Prev Vet Med 34 : 31 - 46 . PMID: 9541949
22. Zou G ( 2004 ) A modified poisson regression approach to prospective studies with binary data . Am J Epidemiol 159 : 702 - 706 . PMID: 15033648
23. Tyler JW , Hancock DD , Thorne JG , Gay CC , Gay JM ( 1999 ) Partitioning the mortality risk associated with inadequate passive transfer of colostral immunoglobulins in dairy calves . J Vet Intern Med 13 : 335 - 337 . PMID: 10449225
24. Dudek K , Bednarek D , Ayling RD , Szacawa E ( 2014 ) Stimulation and analysis of the immune response in calves from vaccinated pregnant cows . Res Vet Sci 97 : 32 - 37 . doi: 10 .1016/j.rvsc. 2014 . 04 .005 PMID: 24815344
25. Gulliksen SM , Lie KI , Loken T , Osteras O ( 2009 ) Calf mortality in Norwegian dairy herds . J Dairy Sci 92 : 2782 - 2795 . doi: 10 .3168/jds.2008-1807 PMID: 19448012
26. Wells SJ , Dartgatz DA , Ott SL ( 1996 ) Factors associated with mortality to 21 days of life in dairy heifers in the United States . Prev Vet Med 29 : 9 - 19 .
27. DeNise SK , Robison JD , Stott GH , Armstrong DV ( 1989 ) Effects of passive immunity on subsequent production in dairy heifers . J Dairy Sci 72 : 552 - 554 . PMID: 2703576
28. Faber SN , Faber NE , McCauley TC , Ax RL ( 2005 ) Case study: effects of colostrum ingestion on lactational performance . The Professional Animal Scientist 21 : 420 - 425 .
29. Robison JD , Stott GH , DeNise SK ( 1988 ) Effects of passive immunity on growth and survival in the dairy heifer . J Dairy Sci 71 : 1283 - 1287 . PMID: 3135297
30. Kovalchik S ( 2013 ) Tutorial on meta-analysis in R . R useR! Conference 2013 . pp. 204 .