The variable prevalence of bovine tuberculosis among dairy herds in Central Ethiopia provides opportunities for targeted intervention.

Bovine tuberculosis (bTB) is an important disease for dairy productivity, as well as having the potential for zoonotic transmission. Previous prevalence studies of bTB in the dairy sector in central Ethiopia have suggested high prevalence, however, they have been limited to relatively small scale surveys, raising concerns about their representativeness. Here we carried out a cross sectional one-stage cluster sampling survey taking the dairy herd as a cluster to estimate the prevalence of bTB in dairy farms in six areas of central Ethiopia. The survey, which to date is by far the largest in the area in terms of the number of dairy farms, study areas and risk factors explored, took place from March 2016 to May 2017. This study combined tuberculin skin testing and the collection of additional herd and animal level data by questionnaire to identify potential risk factors contributing to bTB transmission. We applied the single intradermal cervical comparative tuberculin (SICCT) test using >4mm cut-off for considering an individual animal as positive for bTB; at least one reactor animal was required for a herd to be considered bTB positive. Two hundred ninety-nine dairy herds in the six study areas were randomly selected, from which 5,675 cattle were tested. The overall prevalence of bTB after standardisation for herd-size in the population was 54.4% (95% CI 48.7-60%) at the herd level, and it was 24.5% (95% CI 23.3-25.8) at the individual animal level. A Generalized Linear Mixed Model (GLMM) with herd and area as random effect was used to explore risk factors association with bTB status. We found that herd size, age, bTB history at farm, and breed were significant risk factors for animals to be SICCT positive. Animals from large herds had 8.3 times the odds of being tuberculin reactor (OR: 8.3, p-value:0.008) as compared to animals from small herds. The effect of age was strongest for animals 8-10 years of age (the oldest category) having 8.9 times the odds of being tuberculin reactors (OR: 8.9, p-value:<0.001) compared to the youngest category. The other identified significant risk factors were bTB history at farm (OR: 5.2, p-value:0.003) and cattle breed (OR: 2.5, p-value: 0.032). Our study demonstrates a high prevalence of bTB in central Ethiopia but with a large variation in within-herd prevalence between herds, findings that lays an important foundation for the future development of control strategies.

Introduction

Bovine tuberculosis (bTB) is a chronic disease of cattle primarily caused by Mycobacterium bovis (M. bovis), which has zoonotic potential and can also infect other domestic and wild animals. The disease is prevalent in most of Africa, parts of Asia and the Americas, and in several European countries. Many industrialised countries have managed to reduce or eliminate bTB in their livestock sectors through test-and-slaughter, however significant pockets of infection remain in wildlife [1]. In Africa the disease is endemic due to a lack of control measures. This has economic implications for the growth of the livestock sector, especially the dairy sector, and poses the risk of zoonotic TB transmission which is exacerbated by the existence of concomitant infections such as HIV/AIDS [2]. In Ethiopia, the demand for milk is expanding rapidly due to increased urbanization and population pressure; Ethiopia is the second most populous country in Africa with an estimated population of 110 million people [3]. Since the introduction of intensive dairy farming in central Ethiopia in the 1950s to provide the Emperor and his establishment with milk, the dairy sector has steadily increased. This increase has accelerated during the last 30 years—trying to meet the demand from increased urbanization and the need to supply milk and milk products to the city dwellers [4]. Although the dairy sector is most developed in central Ethiopia, urban centers across the country have more recently seen an increase in dairy farming. This most developed dairy belt in Ethiopia is expected to be challenged with diseases of intensification such as bTB [5, 6]. This is believed to be associated with mainly two factors: Firstly, a shift from dairy herding with existing local zebu cows to crosses of exotic breeds (mainly Holstein Friesian cows), which produce higher milk yields, have established dairy herds that are likely to be more susceptible to bTB [7, 8]. Secondly, an intensified dairy sector with larger herds has likely increased disease transmission as bTB is thriving in an environment with higher density population. bTB animal prevalence recorded in Ethiopia has ranged from around 3% in smallholder production systems (rearing mainly zebu cattle) up to 48% in intensive dairy productions [5, 7, 9–11] and the national average recently estimated to be ~ 5.8% [12].

Tschopp and colleagues [13] estimated (simulated) the cost of bTB for the urban dairy production in central Ethiopia (Addis Ababa) to have ranged from US$500,000–4.9 million over a period of six years (2005–2011). One target for the Ethiopian government in its 2015–2020 Livestock Master Plan is to transform the dairy sector by increasing the number of crossbred cattle by almost eight times the base-year number [14]. Such expansion comes however with a risk since transmission of infectious diseases, such as bTB, is likely to thrive by intensification [12, 15]. This also raises the concern that bTB may spread to the emerging dairies in the regional towns through trading of high milk yield animals from infected farms in the central regions.

Previous bTB prevalence studies in this part of Ethiopia were surveys of smaller scale (significantly fewer farms or fewer study areas) and conducted over different time periods and study areas, leading to concerns about representativeness. Accordingly, there is likely to have been over/under representation of dairy farms in past surveys due to lack of either appropriate stratified sampling or standardisation of the results [10]. A comprehensive review of bTB in Ethiopia by Sibhat et al. [12] showed limitations of previous prevalence studies, central Ethiopia included, including the scope of study objectives, methodology used, target population and geographic coverage. Therefore we carried out a large scale systematically stratified survey to assess the current status of bTB prevalence in the established dairy sector in central Ethiopia and to identify contributing risk factors for the spread of the disease to inform the development of potential control strategies.

Materials and methods

Study areas

Six study areas were purposefully selected in the urban areas of central Ethiopia, including Addis Ababa city, and Sebeta, Holeta, Sululta, Sendafa and Bishoftu towns (Fig 1). Central Ethiopia, which includes the study areas, was a pioneer for the modern dairy development in Ethiopia with the first number of exotic dairy cattle arriving in the early 1950s as a donation from the United Nations [4] and this area has then over decades established itself as the most developed dairy belt in Ethiopia. The study areas are currently the main milk suppliers for people in Addis Ababa and the surrounding peri-urban areas. A free software program called Quantum Geographic Information System (QGIS) version 3.8 [16] was used for compiling the maps. Administrative and road data were extracted and complied from publicly available information of Central Statistical Agency of Ethiopia [17] and Ethiopian Roads Authority [18].

Fig 1

Map of the study areas: Addis Ababa city and Sululta, Sendafa, Holeta, Sebeta, and Bishoftu towns.

Study design

This study was a cross sectional study conducted from March 2016 to May 2017. Lists of herds (the sampling frame) were established at the start of the study in collaboration with district veterinary officers in respective study sites. The term “herd” was used to describe the group of cattle that are housed on a holding at the time of data collection [19]. Herds, with the purpose of producing milk and dairy products, having five or more cattle were included and a list of 1,323 herds was established as a sampling frame. The herds were classified as small [5-20], medium [21-37], and large herds [38-168] (168 being the largest herd size in the studied herds) [5].

Inclusion and exclusion criteria for the study herds: Herd size was the criteria used and herds with less than five animals were excluded.

Sample size and sampling

Sample size was determined using the following formula (that assumes a large population) following one-stage cluster sampling method taking dairy herd as a cluster [20] and every animal in the selected cluster was tested.

Using the assumed parameter values gives an estimated sample size of 383 farms. This was adjusted down using a small population correction (below) to 298.

Hence, we tested 299 herds out of 1323 registered herds in the study sites and selection of each herd was random. All animals in the 299 herds (5,675 animals) were tested excluding animals less than 6 weeks of age and pregnant cattle ≥8 months pregnant.

For herd recruitment and sampling of the 299 herds, proportionate sample was obtained using the formula: (sample size/population size) x stratum size (small, medium or large herd) [20] i.e. 298/1323 = 0.225 x stratum size. In the actual study the fractions for large, medium and small herds were 71% (n = 212), 16% (n = 49) and 13% (n = 38), respectively and those in the overall population were 89%, 7% and 4%. The over-representation of larger farms was due to a greater level of refusal to participate in smaller herds, despite efforts to address this, and numbers were made up in medium and large herds. A direct method of standardization (adjustment) [20] was employed to adjust for the effect of having a higher representation of larger farms in the crude overall bTB prevalence result.

Single Intradermal Cervical Comparative Tuberculin (SICCT) test

The procedure of the SICCT test was adapted from OIE Terrestrial Manual, 2009 (Bovine Tuberculosis) and the supplier of Tuberculin PPD was Prionics, Lelystad, The Netherlands. The injection site used was at the border of the anterior and middle thirds of left side (for consistency) of the neck. Two sites were used, one for bovine PPD (lower site) and the other for avian PPD (upper site). The upper site was 10 cm below the crest and the lower site was 12.5 cm from the upper site, on a line drawn parallel with the line of the shoulder. The selected site of injection was shaved to an adequately sized area for identification of the injection sites and cleansed. Before injection, a fold of skin at each of the intended injection sites and within the clipped area was taken between the forefinger and thumb and measured to the nearest millimeter using the same digital caliper (0-150mm range) throughout the survey. Then 0.1 ml of Bovine Tuberculin PPD and 0.1ml of Avian Tuberculin PPD was injected intradermally in the lower and upper site, respectively. A correct injection was confirmed by palpating a small pea-like swelling at each injection site. The two injection sites were re-measured after 72 hours by the same person who measured the skin thickness before the injection. For the interpretation, the SICCT test was considered positive if the difference was more than 4 mm; inconclusive if between 1 to 4 mm; and negative if the increase in skin thickness at the bovine site of injection was less than 1 mm or equal to the increase in the skin reaction at the avian site of injection.

Farm data collection

Farm data were collected by trained research assistants through face to face interview with pre-tested structured questionnaire to capture animal and herd-level information. General information including herd structure, farm antecedents, farm management/husbandry, housing/ventilation, animal health (veterinary services) and animal bio-security were recorded. Specific information related to potential risk factors for bTB were recorded including animals age, sex, breed, physiology (pregnancy/stages of lactation/body condition), herd size, cattle sourcing (cattle movements in and out of the herd), bTB history on farm, contacts /interactions with neighboring herd/other domestic animals/wild animals etc. (S1 Questionnaire). Global Positioning System(GPS) data was collected for each herd for mapping bTB prevalence in the study areas (S1 Fig).

Statistical analysis

Data from questionnaires and the tuberculin skin test were curated and coded. All the statistical analysis was performed using the R statistical language [22] and RStudio [23]. Based on the SICCT test, the animal level and herd level bTB prevalence for Addis Ababa city and surrounding five study areas was described and 95% confidence interval calculated. The Kruskal–Wallis test was used for comparison of variability in within herd bTB prevalence (%) among studied dairy herds. Our dataset was hierarchal in nature i.e. individual animals were clustered within herds and herds were clustered within study areas. To account for this clustering and deal with variation in prevalence between study areas and in particular between herds, a Generalized Linear Mixed Model (GLMM) [24] was used which allowed us to treat herd and study areas as random effects with a binary response as an outcome variable (bTB reactor or not reactor). Animals with reading difference between 1–4 mm were treated as negatives. We used the glmer() function in the lme4 package [25]. The statistical unit of analysis was the individual animal. We performed a univariable screen to select variables for inclusion in the multivariable model. All variables with a p-value of < 0.20 and those with a high biological relevance were considered as candidate variables for the model building. These candidate explanatory variables were investigated further for collinearity requiring that all selected variables for the multivariable model have a variance inflation factor (VIF) of < 5 [11]. Statistical significance was set at the 5% level.

For binary data a binomial response (more specifically, the Bernoulli distribution) was used [26]. To specify the model, we define the binary response variable:

All screened predictors were initially included in the global model, including biologically plausible two-way interactions. Breed was considered as potential confounder for herd size. As some confounding is invariably present, and the important issue is how large the confounding effect is, not whether or not it is present [24]. We specified a difference of 20% change in the odds ratio as an indication of confounding [24]. The removal of breed from the final model changed the logit of herd size by 13.2% (7.7.-6.8)/6.8) for medium herds and by 19.2% (9.9–8.8)/8.3) for large herds, thus no strong confounding effect was found between the two factors.

For model fitting in addition to the global model, a set of models were proposed (S4 Table) to identify potential risk factors that most affect the outcome variable of interest i.e. bTB status. We used the Akaike information criterion (AIC) for comparing and selecting between models. As described by Burnham and Anderson [27], the AIC approach is first to calculate an AIC value for each model proposed and to examine the differences between the AIC values of competing models to the model with minimum value of AIC (often termed as the best model). To put this mathematically: ΔAIC = AICi−minAIC; where AICi is the competing model and minAIC is the model with the minimum AIC value. We used this ΔAIC value to rank and identify candidate models. A threshold was set for identifying candidate models; where models with ΔAIC < 3 and Akaike weights (w > 0.05) [11] were set as candidate models. A model with highest Akaike weights value (often interpreted as the probability that model is the best model) was used for selecting the best model. In our data we identified that the interaction effect between herd and breed was biasing estimates of other variables (skewing the estimate for the herd size variable) due to the small number of zebu cattle in the medium herd level category. Dropping this interaction–results in the global model having both the lowest AIC and highest Akaike weight and explained the data well and subsequently selected for reporting.

Ethical considerations

This study was approved by AHRI-ALERT Ethics Review Committee (Project Reg.No PO46/14) and Ethiopia’s National Research Ethics Review Committee (NRERC No. 3.10/800/07). Informed consent was obtained verbally from dairy farm owners who were briefed in the presence of a witness (local experts) on the tuberculin skin testing procedure; no known risks to the animal associated with this; their participation in study is voluntary, and that confidentiality on test result will be maintained. When agreed, the witness and the participant’s full addresses including their mobile phone numbers were recorded for filing and in case contact with participant was needed.

Results

Description of the herd demography and characteristics

This study investigated 299 dairy herds (212 small, 49 medium, and 38 large farms) for bTB using the SICCT test in the urban and peri-urban areas of central Ethiopia. In addition, descriptive data on these herds were collected. With regard to ownership of the studied herds, 238 (82.9%) herds were owned privately, 31were cooperatives (10.8%), eight were government herds (2.8%) and ten were share companies (3.5%). Twelve herds had no records about ownership. The majority of herds (77.1%) had loose house type and practice zero grazing (roughage with supplement feeding) (78.5%). Artificial insemination (AI) was the main breeding strategy for 69% of these farmers, 83% vaccinated their cattle against major diseases, while 67% dewormed their cattle on a regular basis. The herd structure of the studied dairy herds is presented in Table 1 and additional herds characteristics is provided in S1 Table.

Table 1

Herd structure of the 299 studied dairy herds.

Characteristics	Levels	Herd size
		Small (n = 212)	Medium (n = 49)	Large (n = 38)	Total (n = 299)
Calf (0-1yr)	Crossbreed	381	257	360	998
	Zebu	34	5	1	40
	Exotic (pure)	0	0	1	1
Heifer	Crossbreed	360	191	413	964
	Zebu	15	4	1	20
	Exotic(pure)	0	0	0	0
Cow	Crossbreed	1116	703	1486	3305
	Zebu	37	15	52	104
	Exotic(pure)	8	2	0	10
Bullock/Steers (1–2 yrs)	Crossbreed	17	27	24	68
	Zebu	6	2	3	11
	Exotic (pure)	0	2	1	3
Bull/Oxen	Crossbreed	32	14	31	77
	Zebu	52	11	6	69
	Exotic(pure)	0	0	5	5
Total cattle	Total	2058	1233	2384	5675
Other animals	Sheep	549	310	500	1359
	Goats	99	56	77	232
	Equine	142	24	34	200
	Dogs	260	87	58	405
	Cats	167	69	18	254
	Swine	6	45	1511	1562
	Poultry	5963	6952	7541	20456

Prevalence of bTB in the study population

In total 5,675 cattle from 299 herds were tested by using the SICCT test. Overall there were1,776 reactors (31.3% crude animal prevalence- not adjusted for herd size; 95% CI: 30–33%) in 180 herds (60.9% crude herd prevalence; 95% CI:55.2–66.2%), with each positive herd having at least one reactor (Table 2). Sebeta had the highest prevalence (42% at animal level with 95% CI: 38–46% and 74%at herd level with 95% CI: 55–87%) among all six regions whereas Holeta had the lowest prevalence(17% at animal level with 95% CI: 14–20% and 27% at herd level with 95% CI: 13–46%). There was significant variation between study areas in prevalence of tuberculin reactors (χ2 = 143.18, df = 5, p-value <0.001). Using GPS data for individual farms, bTB prevalence maps were created for the six study areas, each visualizing the bTB burden for large, medium and small herds (S1 Fig).

Table 2

Animal and herd level bTB prevalence for 299 dairy herds in the six study areas.

Level	Addis Ababa	Sebeta	Holeta	Sululta	Sendafa	Bishoftu	Total
Animal level: % Prev. (95%CI)	32.8(31–35)	42.2(38–46)	16.8 (14–20)	41.9(38–46)	25.5(22–30)	25.5 (23–28)	31.3(30–33)
Positives	797	250	90	257	134	248	1776
Total number tested	2432	593	537	614	525	974	5675
Herd level: % Prev.(95%CI)	63 (55–70)	74 (55–87)	30 (13–46)	60(39–78)	54(33–74)	73.3(50–85)	60.9(54–66)
Positives	100	23	9	15	13	22	182
Total number tested	159	31	30	25	24	30	299

Herd-size specific prevalence of bTB

The bTB prevalence was stratified on herd size based on the study population (Table 3A). The results showed a different prevalence between herd sizes with a significant increase in prevalence with herd size group. As the recruitment of herds into the study had been somewhat over-represented of larger herds as compared to the original sampling strategy, it was relevant to standardise the prevalence estimates in the study population. Therefore, Table 3B presents herd size specific prevalence of bTB for the standard population (a population we aimed to sample) of all study sites. The overall crude bTB prevalence was higher (31.3%: 95% CI: 30–33) compared with herd size adjusted prevalence (24.5%: 95% CI:23.3–25.8) (using direct method of standardization). The same trend was recorded for the herd level bTB prevalence (Table 3).

Table 3

Prevalence of bTB stratified by herd-size for (A) the study population and (B) the standard population of the study areas.

A	Study population
	Herd size group	Herds sampled	Population	bTB positives	Prevalence % (95% CI)
Animal Level	Small herds (>4 to ≤20)	212	2058	373	18.1 (16.5–19.4)
	Medium herds (>20 to ≤37)	49	1233	402	32.6 (30–35.3)
	Large herds (>37 to ≤168)	38	2384	1001	42.0 (40–43.9)
	Total	299	5675	1776	31.3 (30–33)
Herd Level	Small herds (>4 to ≤20)	212	212	108	50.9(44.3–57.6)
	Medium herds (>20 to ≤37)	49	49	41	83.7(71–91.5)
	Large herds (>37 to ≤168)	38	38	33	86.8 (72.7–94.2)
	Total	299	299	182	60.9(55.2–66.2)
B	Standard population
	Herd size group	Expected	Expected	Expected	Expected
		herds sampled	population a	bTB positives b	Prevalence % (95% CI)
Animal Level	Small herds (>4 to ≤20)	266	2926	530	18.1 (16.8–19.6)
	Medium herds (>20 to ≤37)	21	609	199	32.7 (29.1–32.7)
	Large herds (>37 to ≤168)	11	792	333	42 (38.7–45.5)
	Total	298	4327	1062	24.5 (23.3.-25.8)
Herd Level	Small herds (>4 to ≤20	266	266	134	50.4(44.4–56.3)
	Medium herds (>20 to ≤37)	21	21	18	85.7(65.4–95.0)
	Large herds (>37 to ≤168)	11	11	10	90.9(62.3–98.4)
	Total	298	298	162	54.4(48.7–60)

aExpected population = Expected herds sampled * Average population size (for each herd size group)

bExpected bTB positives = Expected population * Prevalence in study population (for each herd size group)

Within herd prevalence of bTB

The average within-herd prevalence is heavily skewed by a relatively small proportion of extremely high prevalence herds (illustrated by Fig 2). Within-herd prevalence is multi-modal with the majority of small and medium herds having a prevalence less than the population average. The population mean 31.5% was higher compared to the median 10%, thus indicating a positive skewedness and that a higher proportion of herds (67.9%) had a within herd prevalence less than the population average. Although the average within-herd prevalence does not demonstrate a strong herd-size dependence, there is a marked difference in the distribution with a markedly higher proportion of herds having a prevalence greater than the population average. A greater proportion of large herds (65.8%) (median: 50%) were having within herd prevalence greater than the population average.

Fig 2

(A) Within-herd bTB prevalence distribution for stratified herds (Visualizing multiple distributions simultaneously) (B) Within-herd bTB prevalence distribution for affected herds (bTB prevalence > 0).

Translating this into numbers: the mean within herd prevalence for all herds was 31.5± 30.7% and a median of 10% (lower quartile0 and 42.5% upper quartile). Stratification on large, medium, and small herds, there was a mean within herd prevalence of 40.6%, 35.1%, and 18.8%, respectively, while the median value for the respective herd size was50%, 33%, and 8.3. In this study, there was a significant difference in within herd prevalence among studied dairy herds (Kruskal–Wallis test: df = 2,χ2 = 33.295, p value < 0.001).

Risk factor analysis

Sixteen potential risk factors, based on knowledge and understanding of the husbandry system and biological relevance were considered and screened by univariable analysis (Table 4). Twelve variables with p-value of < 0.20 and with OR > 1 were selected for multivariable analysis. Contact with other domestic animals, stages of lactation, viral disease outbreak, and regular de-worming did not fulfil the stated criteria and were excluded from analysis. A full description of the measured risk factors is provided in S2 Table. Total number of examined animals (3rd column in Table 4) used for analysis of respective risk factor may differ from the overall number of animals tested (N = 5,675) due to missing values.

Table 4

Univariable analysis of potential risk factors for cattle tuberculin reactors.

Risk factors	Level	Proportion % (bTB positives/total examined)	OR (95% CI)	P value
Herd size	>4 to ≤20	18.1 (373/2058)	ref
	>20 to ≤37	32.6 (402/1233)	2.2 (1.8–2.6)	<0.001
	>37 to ≤168	42 (1001/2384)	3.3 (2.8–3.8)	<0.001
Age (yrs)	>0.1 to ≤2	21.3 (422/1980)	ref
	>2 to ≤4	33.1 (470/ 1420)	1.8 (1.5–2.1)	<0.001
	>4 to ≤6	34.3(376 /1095)	1.9 (1.6–2.3)	<0.001
	>6 to ≤8	39.7(224/564)	2.4 (1.9–3)	<0.001
	>8 to ≤10	41.6 (82/19)	2.6 (1.9–3.6)	<0.001
Source	On farm bred	30 (1431/4757)	ref
	Purchased	37.5 (344/916)	1.4 (1.2–1.6)	<0.001
Breed	Zebu	7.8 (19/244)	ref
	Cross and exotic	32.3 (1757/5431)	5.7 (3.6–9.4)	<0.001
Sex	Male	18 (78/433)	ref
	Female	32.4 (1698/5242)	2.2 (1.7–2.8)	<0.001
Farm age (yrs)	>4to ≤20	25.4 (695/2736)	ref
	>20 to ≤35	36.6 (715/1951)	1.7 (1.4–1.9)	<0.001
	>35 to ≤68	30 (213/708)	1.3 (1–1.5)	0.01
bTB history at farm	No	33.4 (538/1607)	ref
	Yes	40.8 (381/932)	1.4 (1.1–1.6)	<0.001
Contact with other domestic animals	No	31.5 (254 /806)	ref
	Yes	32.5 (702/2161)	1.04 (0.8–1.2)	0.64
Stocking density (no. cattle/m2)	Less	28.6 (1314/4601)	ref
	Satisfactory	35.4 (34/96)	0.7 (0.5–1.1)	0.14
	High	39.8 (300/753)	1.2 (0.8–1.9)	0.4
Ventilation	Very good	28.6 (608/2127)	ref
	Satisfactory	29.7 (506/1706)	1 (0.9–1.2)	0.46
	Poor	34.9 (548/1572)	1.3 (1.2–1.5)	< 0.001
Viral disease outbreak	Yes	30.6 (851/2784)	ref
	No	31.2 (867/2728)	0.9 (0.8–1.1)	0.35
Biosecurity measures	Present	26.4 (384/1457)	ref
	Absent	32.8 (1349/4109)	1.4 (1.1–1.6)	< 0.001
Neighbor herd	No	21.5 (106/494)	ref
	Yes	31.4 (1527/4857)	1.7 (1.3–2.1)	<0.001
House type	Cubicle	21.4 (281/1313)	ref
	Loose	34.5 (1329/3856)	1.9 (1.6–2.2)	<0.001
	Free movement	27.2 (94/345)	1.4 (1–1.8)	0.02
Regular de-worming	No	35.3 (428/1212)	ref
	Yes	29.2 (1239/4247)	0.8 (0.7–9.9)	<0.001
Stages of lactation (months)	>0 to ≤2	34.7 (137/395)	ref
	>2 to ≤4	36.2 (179/494)	1.1(0.8–1.4)	0.63
	>4 to ≤8	39.2 (304/776)	1.2(0.6–1.6)	0.13

Multivariable analysis of potential risk factors for positive cattle reactors using GLMM with herd and area as random effect

Based on their high OR, absence of collinearity and statistical significance (p-value <0.2), twelve variables (Table 4) were considered in the final multivariable model. The final model thus consisted of four variables: herd size, age, bTB history at farm, and breed as significant risk factors for bTB. Animals from large herds had 8.3 times the odds of being a bTB tuberculin reactor compared to animals living in small herds. There was also a strong effect of age, with animals 8–10 years of age having 8.9 times the odds of being reactors compared to the youngest category (Table 5).

Table 5

GLMM multivariable analysis of potential risk factors for bTB positive cattle using herd and area as random effect.

Risk factor	Level	OR (95% CI)	P value
Herd size	>4 to ≤20	ref
	>20 to ≤37	6.8 (2.6–17.9)	0.001
	>37 to ≤168	8.3 (2.2–31.5)	0.008
Age (yrs)	>0.1 to ≤2	ref
	>2 to ≤4	2.7.1 (2.1–3.6)	<0.001
	>4 to≤ 6	3.5 (2.6–4.8)	<0.001
	>6 to ≤8	5 (3.5–7.2)	<0.001
	>8 to ≤10	8.9 (5–15.6)	<0.001
bTB history at farm	No	ref
	Yes	5.2 (2.1–12.9)	0.003
Breed	Zebu	ref
	Crossand exotic	2.5 (1.2–4.5)	0.032

Discussion

In this study we set out to perform the largest bTB prevalence study so far in dairy farms in central Ethiopia (Fig 1) to get a comprehensive understanding of the scope of the burden of the disease and identify potential risk factors contributing to the transmission of bTB within the study area. Previous studies had limitations especially in methodology used. For example two studies in Addis Ababa did not show clearly how sample size was determined (no mention of formula and parameters used) and how different herd categories were proportionally sampled [10, 28]. In these studies there was over representation of farms with herd sizes of 20 and above (>25%) where the proportion of these farms in the overall population was estimated to below 10%. There were similar limitations in scope of study objectives, methodology used, target population and geographic coverage as reviewed by Sibhat et al. [12]. Our study therefore addressed the concerns of previous studies. With an overall crude animal prevalence of 31.3% (n = 1,776) (herd size adjusted: 24.5%) and a 60.9% (n = 180) crude prevalence at herd level (herd size adjusted: 54.4%), we recorded a high level of bTB prevalence. However, there was variation between the six study areas: relatively low prevalence was recorded in Holeta and this could be related to earlier work to control for bTB in selected infected government herds in that area, which at the time were supplying heifers to surrounding farmers [29]. In this survey we also noted significant variation of within-herd bTB prevalence (P-value < 0.05) among the studied dairy herds, which ranged from 0 to 100% and with a mean for all herds of 31.5% ± 30.7 SD. This variability would mean differences in transmission due to husbandry and other risk factors discussed in this paper or as reviewed by Broughan et al. [30]. By herd stratification, large herds recorded the highest within-herd prevalence (mean: 40.6%) and a larger proportion (65.8%) had a within-herd prevalence greater than the population average. Such high herd prevalence could be due to an increased risk of within-herd transmission in farms with larger herd size [31]. This finding is relevant for control measures such as limited test and removal which could be economically viable in the lower prevalence herds.

Risk factors influence transmission and can be categorised at regional, herd, and animal level [32] and vary across regions for several reasons, such as difference in farm management practices [33]. Analysis of this can be useful to develop a strategy for risk-based surveillance and control for bTB. The present study has identified several risk factors for bTB. Animals from large herds had 8.3 times the odds of being tuberculin reactor compared to those from small herds. Herd size is the most frequently reported risk factor for bTB in Ethiopia and elsewhere [5, 10, 11, 34, 35]. The risk of infection in a herd increases with herd size and this could be due to overcrowding which increases probability of contact between animals in larger herds implying that transmission may be density dependent [30]. High density creates favorable environment for bTB as aerosol is one main route of transmission. The postmortem data collected by Firdessa and colleagues [5] support this as most animals had TB lesions in lungs and/or lung associated lymph nodes. Also, larger herds often have a larger grazing area, which may expose them to greater environmental risk factors (e.g. wildlife reservoir though not confirmed in Ethiopia) and may also expose them to more neighboring herds [35]. Although the number of large herds in Ethiopia are few (even in the central part of the country) their impact on bTB transmission is likely to be significant as many of them are highly infected and they are primary suppliers of heifers to smallholder farms as well as of milk to consumers and could therefore be most potential sources of infection. If a future bTB control program in Ethiopia would focus on these farms, such intervention could possibly be financially affordable given their small number and turning them into bTB free herds could potentially have a significant impact on the overall bTB prevalence in the Ethiopian dairy sector.

When looking for other potential risk factors, there was also a strong effect of age. Animals between 8–10 years old were having the highest odds of being bTB reactors (OR: 8.9, 95% CI: 5–15.6) compared to the baseline category, which was the youngest age group. A linear increase between bTB infection and age was reviewed by Broughan et al. [30] and observed in slaughterhouse surveillances in cattle in Northern Ireland and Great Britain [26, 36]. The mean age of reactor cattle was 4.4 years (95% CI: 4.29–4.56). Longevity increases probability of exposure and it also increases the chance for development of visible TB lesions and detection in slaughterhouse surveillances. In addition, purchase of older cattle—particularly from high risk areas—could increase the risk of introducing bTB in a herd. Instead, the adoption of risk-based trading has the potential to reduce the risk of bTB spread [37].

We found also that animals from herds with history of bTB had 5.2 times odds of disease detection compared to herds with no history of bTB. In a tuberculin positive herd which did not remove reactors after skin testing, there could be an increase in infection and hence reactor animals. Even in herds which did cull the reactors, there could be recurrent incidents attributable to persistence of infection in such herds due to failure to detect and remove all infected cattle associated with the performance of the skin test [30].

Exotic and cross bred cattle are known to be more susceptible to bTB [8, 30]. Here we found 2.5 times (95% CI: 1.5–5.8) odds of being bTB reactor in these breeds compared to the indigenous zebu breed. The strategy to meet high milk demand is still geared towards improved dairy cattle as a crossbred dairy cow produces on average at least five times more milk than an indigenous zebu cow [38]. With the Ethiopian Government setting a policy to significantly increase the number of crossbred cattle, intensification is likely to increase and thereby the risk of bTB transmission [12, 15]. The final important risk factor we identified is the introduction of cattle to the herd through purchase. We found that cattle purchased from another farm were more often reactors (37.5%) compared to cattle bred at own farm (30%). Although this difference is not statistically significant, it warrants further investigation.

Overall, when comparing our study with previous surveys of dairy cattle in this established dairy belt of Ethiopia, there was no major difference in bTB animal prevalence but our study showed a slight increase in herd prevalence. Firdessa and colleagues [5] recorded in 2009/2010 a 30% (n = 2,956) animal and 50% (n = 88) herd level bTB prevalence while Tsegaye and colleagues [10] in 2006/2007 recorded 34.1% (n = 1,132) animal and 53.6% (n = 56) herd bTB prevalence, respectively, which is comparable to our corresponding figures. This consistency over time suggests that bTB has reached an endemic equilibrium in these herds. The burden of bTB in the dairy belt in central Ethiopia (31%) is much greater than for emerging dairies in regional states, estimated to range from 0.3% to 12% animal prevalence [6, 11, 13, 34]. At present Ethiopia has no bTB control program but if implemented should consider the central region of the country as a bTB high risk area and this report opens up for a scientific approach for future risk-based surveillance and disease intervention. Cattle trading from this region pose high risk of introducing bTB infection to new herds and underlines the significance of cattle trade regulation with pre-movement testing. The significantly lower bTB prevalence recorded in many emerging dairies in the regional states (which could be considered as low risk regions) presents an opportunity for intervention e.g. by trade restrictions to prevent further disease transmission from high risk areas like central Ethiopia and introduce testing to support farmers to keep their herds free from bTB. A recent survey by Mekonnen and colleagues [6] recorded an average disease rate of 5.2% (95% CI: 4–6%) in three emerging dairies in regional states, including Hawassa (3%), Gondar (1.4%), and Mekelle (12%). An earlier report from 2014 [39] documented also lower prevalence (below 7%) in eight out of twelve emerging dairies, but ranging from 0.8% to 24% with a few hot spots in Kombolcha (24%) and Mekelle (14%), the latter confirmed by Mekonnen et al. [6]. The lower bTB rates in many of these emerging dairy regions could be due to less cattle movement from high risk regions and less intensification, as they may have emerged more recently. However, if these emerging dairy regions will intensify, and without a strategy for bTB disease control in Ethiopia, it is likely that these regions will be more affected by bTB in the future.

As the Ethiopian dairy sector is expanding, especially through emerging new dairies around many other urban centers across the country, the findings from this study add useful epidemiological information critical for the application of targeted evidence-based control measures. Therefore, there is now an opportunity to take steps towards a strategy that can control or significantly reduce the burden of bTB in Ethiopia to improve animal and human health.

As a limitation of this study; in some of the herds, which lacked records-for some risk factors such as age, data was collected through interview. As people may not always recall correct information especially for older animals we tried to compliment such age estimation with parity and dentition data.

Conclusions

The present study reported a high level of bTB prevalence in the large dairy belt around the capital Addis Ababa in central Ethiopia based on the SICCT test. High variability in burden of infection among the tested dairy herds was also an important finding of this study as it can have impact on future disease intervention strategies. In addition, it identified herd size, animal age, cattle breed, and bTB history at farm as important risk factors contributing to the high prevalence of bTB in the central parts of the country.

Map showing the geographical locations and the sizes of bTB-positive and negative herds and within-herd prevalence in central Ethiopia.

(TIF)

Click here for additional data file.

Characteristics of studied farms.

(DOC)

Click here for additional data file.

Description of risk factors.

(DOC)

Click here for additional data file.

Collinearity test of candidate explanatory variables.

(DOC)

Click here for additional data file.

Summary of the global and candidate GLMM models (candidate models in bold).

(DOC)

Click here for additional data file.

Questionnaire for collection of epidemiological data of bovine tuberculosis in central Ethiopia.

(DOC)

Click here for additional data file.

Raw data of this study.

(CSV)

Click here for additional data file.

26 Sep 2020

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

25 Mar 2021

PONE-D-20-28942

High level of bovine tuberculosis in dairy herds of central Ethiopia: a call for intervention

PLOS ONE

Dear Dr. Almaw,

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We look forward to receiving your revised manuscript.

Kind regards,

Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM

Academic Editor

PLOS ONE

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Research Council, the Medical Research Council, the Natural Environment Research Council

and the Defence Science &Technology Laboratory, under the Zoonoses and Emerging Livestock

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Kingdom, ref: TBSE3294"

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: The submitted article addresses the prevalence of bovine tuberculosis which considered as one of the major problems affecting the dairy industry and attract the attention of the dairy producers and public health professionals. The study has been done on large number of herds (299) covering six different geographical areas in Central Ethiopia. The study used comparative intradermal tuberculin test for diagnosis of bovine tuberculosis. The authors provided the raw data and a copy of the survey but there are still some issues that are not clear and need to be addressed before considering publication. The manuscript requires major revision.

1- Title: “High level” Do you mean high prevalence?

2- Abstract:

- Line 23 “have been fragmented” what do you mean by previous studies have been fragmented?

- Line 24 “one-stage cluster” what was your cluster? Please, make it clear in the text.

- Line 25 “The survey, which was by far the largest in the area up to date” it is not clear if the authors mean that the survey was the largest in the number of question or the study was the largest in the area of coverage. Please, clarify.

- Line 26 &28” Tuberculin” and “Single Intradermal Cervical Comparative Tuberculin” you do not have to use capital letters.

- Line 35 “explore risk factors associated with reaction status” what does reaction status mean?

- Line 37 “ten times the odds of bTB detection” what does detection mean? The study did not isolate bTB.

- Line 43” within-herd prevalence between herds” is it within herd or between herds or both?

- Line 43-44 “findings that lays an important foundation for the future development of control strategies” Please clarify how?

-

3- Introduction:

- Line 73-74 “estimated the cost of bTB in Ethiopia for the urban livestock

production to have ranged from US$500,000–4.9 million between 2005 and 2011” is that the cost for the 6 years?

- Line 74 “These figures” which figures?

- Lines 81-83” As previous studies on bTB in this area had been fragmented and limited in coverage, there was a clear need to carry out a comprehensive survey to understand bTB in dairies in central Ethiopia” this is a conclusive statement but there is no mention to these studies and their limitations. It will be more useful for the reader to understand the knowledge gap that the paper will cover if the authors mention these studies and the limitation of each.

4- Material and methods:

- There is no mention of the program and the method used to create the map with the different prevalence’s (Fig 1).

- Statistical analysis:

o In the statistical analysis section, the authors mentioned that they used “Kruskal–Wallis test was used for comparison of variability in within herd bTB prevalence” It is not clear where in the results they mentioned that part. If they mean tables 2 and 3 A&B so where is the p-vales to show if there a significant difference or not?

o The formula for the GLMM is missing the intercept.

o In the formula it appears as the herd and area were crossed random effects. Are the area and herds as random effect crossed or nested? Please clarify.

o Why the authors did not use AIC for evaluation of the model goodness of fit?

o How the authors handled the animals with reading difference between 1-4 mm at the reactor and nonreactor scale for the GLMM?

5- Results:

I would recommend adding a section in the results to add the results of different sections of the survey because some terms are not clear in the manuscript here but has more description in the survey such as ventilation, housing, biosecurity measures.

For example, ventilation in the manuscript the classifications were very good, satisfactory and poor but there is no description for what each of these means while in the survey it is clearly described what each of these categories mean.

- P-value in the tables is mentioned beside the reference group but each level should have its P-value. For example, table 5 there are 3 levels for the herd size and 5 levels for age but only one P-value for the reference category. The model is comparing all the levels to the reference level so each level should have a P-value that could be different than the other levels.

- Data in table 5

� Using of ( ] as exclusive and inclusive criteria is confusing I would recommend using the actual numbers for each group.

� Age categories started at 0.1 but in the testing criteria the authors mentioned that they did not test animals less than 3 months of age. Please clarify.

6- Discussion

Comments are in the attached pdf copy.

7- Other comments are in the attached pdf copy.

8- Supplemented data:

Dataset (S1 Dataset Raw Data):

The authors provided an excel sheet for the dataset. There are some values in the data sheet that looks odd to me and it could be due to incorrect data entry such as:

Column (B2(mm) has values of 2278, 11262, 685.

Column (?A(mm) has value of 794.09

Column (?B(mm) has values of 2275.07, 11254.04

Column (?B-?A(mm) has values of 8.88E-16, 794.09

These measurements cannot be measured by tuberculin caliper. I would recommend the authors to revise their data entry as these values will affect the outcome of the study.

Reviewer #2: The study has relevance due to the fact to demonstrate that large herds is a major risk factor for bTB in the country and due to the fact that large herds are the main suppliers of heifers for small herds.

How is the bTB program in the country? It requires testing and culling? Movement control of the animals? The author should provide a brief of the Ethiopian program to the readers.

Line 75; add space after "[13]"

Line 105: add space after "[15]"

Line 233: correct "Prevalence of"

Line 316; the word becategorisedat must be correct "be categorized at"

Lines 401 to 406 – the comment may be included in discussion but is not a conclusion.

**********

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Reviewer #1: No

Reviewer #2: Yes: Paulo Alex Machado Carneiro

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Submitted filename: PONE-D-20-28942_reviewer.pdf

Click here for additional data file.

8 May 2021

PONE-D-20-28942

High level of bovine tuberculosis in dairy herds of central Ethiopia: a call for intervention

PLOS ONE

Dear Dr. Almaw,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Both expert reviewers have highlighted several concerns that preclude the acceptance of the manuscript as it stands. Please revise the manuscript accordingly making sure to address all reviewers' comments.

Please submit your revised manuscript by May 09 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM

Academic Editor

PLOS ONE

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Response:

We have checked the revised manuscript against the PLOS ONE editorial requirements.

2. Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If the need for consent was waived by the ethics committee, please include this information.

Response:

This study was approved by AHRI-ALERT Ethics Review Committee (Project Reg.No PO46/14) and Ethiopia's National Research Ethics Review Committee (NRERC No. 3.10/800/07). Informed consent was obtained verbally from dairy farm owners who were briefed in the presence of a witness (local experts) on the tuberculin skin testing procedure; no known risks to the animal associated with this; their participation in study is voluntary; and that confidentiality on test result will be maintained. When agreed, the witness and the participant's full addresses including their mobile phone numbers were recorded for filing and in case contact with participant was needed.

3. Thank you for stating the following in the Acknowledgments Section of your manuscript:

"This research was financially supported by the Ethiopia Control of Bovine Tuberculosis

Strategies (ETHICOBOTS) project funded by the Biotechnology and Biological Sciences

Research Council, the Department for International Development, the Economic & Social

Research Council, the Medical Research Council, the Natural Environment Research Council

and the Defence Science &Technology Laboratory, under the Zoonoses and Emerging Livestock

Systems (ZELS) program, ref: BB/L018977/1.Stefan Berg was also funded by Defra, United

Kingdom, ref: TBSE3294"

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

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Response:

Funding-related text has been removed from the revised manuscript. The funding statement is included in the cover letter.

4. One of the noted authors is a group or consortium [ETHICOBOTS consortium]. In addition to naming the author group and listing the individual authors and affiliations within this group in the acknowledgments section of your manuscript, please also indicate clearly a lead author for this group along with a contact email address.

Response:

The lead author: Professor James LN Wood; email: jlnw2@cam.ac.uk has been included

5. We note that you have included the phrase “data not shown” in your manuscript. Unfortunately, this does not meet our data sharing requirements. PLOS does not permit references to inaccessible data. We require that authors provide all relevant data within the paper, Supporting Information files, or in an acceptable, public repository. Please add a citation to support this phrase or upload the data that corresponds with these findings to a stable repository (such as Figshare or Dryad) and provide and URLs, DOIs, or accession numbers that may be used to access these data. Or, if the data are not a core part of the research being presented in your study, we ask that you remove the phrase that refers to these data.

Response:

All references to unpublished data have been removed in the revised manuscript, all raw data tables analysed in the study are provided as supplementary information.

6. We note that Figure 1 and S1Fig in your submission contain map images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

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The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

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Response:

We developed a replacement map which is not copyrighted.

A free software program called Quantum Geographic Information System (QGIS) version 3.8 was used for compiling the maps. Administrative and road data were extracted and complied from publicly available information of Central Statistical Agency of Ethiopia (http://www.csa.gov.et/) and Ethiopian Roads Authority (www.era.gov.et). And a description at the bottom of the map saying: 'the administrative and political boundaries used here are for illustrative purpose and should not be considered authoritative' is included.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The submitted article addresses the prevalence of bovine tuberculosis which considered as one of the major problems affecting the dairy industry and attract the attention of the dairy producers and public health professionals. The study has been done on large number of herds (299) covering six different geographical areas in Central Ethiopia. The study used comparative intradermal tuberculin test for diagnosis of bovine tuberculosis. The authors provided the raw data and a copy of the survey but there are still some issues that are not clear and need to be addressed before considering publication. The manuscript requires major revision.

1- Title: “High level” Do you mean high prevalence?

Response:

Yes, the high level refers to prevalence. We have modified the title to make this point clearer: " The high and variable prevalence of bovine tuberculosis in dairy herds of central Ethiopia provides opportunities for targeted intervention."

2-Abstract:

- Line 23 “have been fragmented” what do you mean by previous studies have been fragmented?

Response:

Thank you for this comment. We have included additional information to make it clearer. By fragmented we meant that previous studies were small scale surveys (few farms/few areas) conducted over different time periods and study areas. So, there were concerns of representativeness. There was over/under representation of farms due to lack of either appropriate stratified sampling or standardization of the result accordingly. We have cited studies in the discussion part to support this. Taking the comment into account we have expanded the section to state: "Previous studies had been limited to few farms/study sites which lead to over/under representation of farms and failed to show the best estimate of bTB prevalence and the associated risk factors for initiating control intervention in central Ethiopia."

- Line 24 “one-stage cluster” what was your cluster? Please, make it clear in the text.

Response:

It was in the text Line 112 "taking dairy herd as a cluster". Now we have included this phrase in the abstract too, to make it clear for abstract readers.

- Line 25 “The survey, which was by far the largest in the area up to date” it is not clear if the authors mean that the survey was the largest in the number of question or the study was the largest in the area of coverage. Please, clarify.

Response:

By this we meant that compared to previous studies we have included a larger number of farms (#299) though this number is determined based on statistics as described in the manuscript. None of the previous surveys sampled more than 100 farms and from fewer study areas. We have also included a significant number of relevant questions as can be seen in the questionnaire format and most of them were used for analysis (# 16 risk factors).

We have modified to “The survey, which was to date by far the largest in the area in terms of number of dairy farms, study areas, and risk factors explored"

- Line 26 & 28” Tuberculin” and “Single Intradermal Cervical Comparative Tuberculin” you do not have to use capital letters.

Response:

Corrected accordingly

- Line 35 “explore risk factors associated with reaction status” what does reaction status mean?

Response:

By "reaction" to mean response to intradermal injection of bovine/avian tuberculin PPD. And reactors are those responding to the test (positive reaction), called reactors and those which did not respond called non-reactors. Common terms in bTB.

We changed to “explore risk factors associated with bTB status” to avoid ambiguity.

- Line 37 “ten times the odds of bTB detection” what does detection mean? The study did not isolate bTB.

Response:

We have changed to: “...the odds of being a tuberculin reactor”. This will clarify the test was tuberculin skin test not isolation of the pathogen.

- Line 43” within-herd prevalence between herds” is it within herd or between herds or both?

Response: It is within herd prevalence.

- Line 43-44 “findings that lays an important foundation for the future development of control strategies” Please clarify how?

Response:

Knowing the within herd prevalence variability, will help to know the extent of transmission in different herds which again is important which herds to target in bTB control strategy. In addition, establishing the best estimate of prevalence and identify potential risk factors is an input for designing a bTB control strategy.

3-Introduction:

- Line 73-74 “estimated the cost of bTB in Ethiopia for the urban livestock

production to have ranged from US$500,000–4.9 million between 2005 and 2011” is that the cost for the 6 years?

Response:

Not. the cost is simulated for each year from 2005 to 2011. For example US$500,000 is the estimated cost for the year 2005. We have clarified the point in the revised manuscript:

Tschopp and colleagues [13] estimated (simulated) the cost of bTB for the urban dairy production in central Ethiopia (Addis Ababa) to have ranged from US$500,000 - 4.9 million over a period of six years (2005-2011).

-Line 74 “These figures” which figures?

Response:

Addressed above in the prior response.

- Lines 81-83” As previous studies on bTB in this area had been fragmented and limited in coverage, there was a clear need to carry out a comprehensive survey to understand bTB in dairies in central Ethiopia” this is a conclusive statement but there is no mention to these studies and their limitations. It will be more useful for the reader to understand the knowledge gap that the paper will cover if the authors mention these studies and the limitation of each.

Response:

Addressed in the preceding section (Abstract section) and limitations of specific studies is mentioned in the discussion part of the revised manuscript Lines 319-325. But for the Introduction section we have modified to:

"Previous bTB prevalence studies in this part of Ethiopia were surveys of smaller scale (significantly fewer farms or fewer study areas) and conducted over different time periods and study areas, leading to concerns about representativeness. Accordingly, there is likely to have been over/under representation of dairy farms in past surveys due to lack of either appropriate stratified sampling or standardisation of the results [10]. A comprehensive review of bTB in Ethiopia by Sibhat et al. [12] showed limitations of previous prevalence studies, central Ethiopia included, including the scope of study objectives, methodology used, target population and geographic coverage.."

4- Material and methods:

- There is no mention of the program and the method used to create the map with the different prevalence’s (Fig 1).

Response:

The paragraph below is included in the revised manuscript (with references):

"A free software program called Quantum Geographic Information System (QGIS) version 3.8 was used for compiling the maps. Administrative and road data were extracted and complied from publicly available information of Central Statistical Agency of Ethiopia and Ethiopian Roads Authority ."

- Statistical analysis:

o In the statistical analysis section, the authors mentioned that they used “Kruskal–Wallis test was used for comparison of variability in within herd bTB prevalence” It is not clear where in the results they mentioned that part. If they mean tables 2 and 3 A&B so where is the p-vales to show if there a significant difference or not?

Response:

It was mentioned Line 271 (Kruskal–Wallis test: df=2,�2=33.295, p value < 0.001) of the previous manuscript. The result is presented in text form not in a table.

o The formula for the GLMM is missing the intercept.

Response:

Thank you. We have revised and βo is now included.

o In the formula it appears as the herd and area were crossed random effects. Are the area and herds as random effect crossed or nested? Please clarify.

Response:

We treated them as crossed. This is because every herd (category) belongs to every study area and we consider this as crossed not nested (to one group or area only).

o Why the authors did not use AIC for evaluation of the model goodness of fit?

Response:

Thank you, for catching this oversight! ROC analysis was used in the previous manuscript to assess the absolute goodness of fit (classification) ability of the estimated models. For model selection AIC, which only provides a relative measure of fit, should have been used for model selection. For the revised manuscript we have repeated the model selection procedure using AIC and clarified the use of AIC for model selection in the revised manuscript.

In the process of carrying out these revisions we identified that the interaction effect between herd and breed was biasing estimates of other variables (skewing the estimate for the herd size variable) due to the small number of zebu cattle in the medium herd level category (# 37 VS 143 for small and 64 for large herds).

Dropping this interaction – which should have been screened out before based on the sparse distribution of breeds between herds – results in the global model having both the lowest AIC and highest Akaike weight. We thank the reviewer again for (indirectly) bringing attention to this error which has greatly improved the robustness of our results.

o How the authors handled the animals with reading difference between 1-4 mm at the reactor and nonreactor scale for the GLMM?

Response:

They were treated as negatives for the binary data (outcome). This clarification is included in the revised manuscript.

5- Results:

I would recommend adding a section in the results to add the results of different sections of the survey because some terms are not clear in the manuscript here but has more description in the survey such as ventilation, housing, biosecurity measures.

For example, ventilation in the manuscript the classifications were very good, satisfactory and poor but there is no description for what each of these means while in the survey it is clearly described what each of these categories mean.

Response:

We can. But we feel major results of the survey is presented in the result section. Additional information is refered in the text as "A full description of the measured risk factors is provided in S2 Table." This table if brought to the result section will increase the number of tables in the manuscript to 6.

- P-value in the tables is mentioned beside the reference group but each level should have its P-value. For example, table 5 there are 3 levels for the herd size and 5 levels for age but only one P-value for the reference category. The model is comparing all the levels to the reference level so each level should have a P-value that could be different than the other levels.

Response:

P values are now included for all levels.

- Data in table 5 Using of ( ] as exclusive and inclusive criteria is confusing I would recommend using the actual numbers for each group.

Response:

We agree and have edited the table as suggested replacing brackets and parenthesis with > or < expression so that it can be easily understood. For example for the age category:

(4,20] >4 to ≤20

(20,37] >20 to ≤37

(37,168] >37 to ≤168

Age categories started at 0.1 but in the testing criteria the authors mentioned that they did not test animals less than 3 months of age. Please clarify.

Response:

Thank you for catching this error. We have corrected the manuscript with respect to excluding animals less than 6 weeks of age.

6-Discussion

Comments are in the attached pdf copy.

Response: Edited as per the comments

7- Other comments are in the attached pdf copy.

Response: Edited as per the comments

8- Supplemented data:

Dataset (S1 Dataset Raw Data):

The authors provided an excel sheet for the dataset. There are some values in the data sheet that looks odd to me and it could be due to incorrect data entry such as:

Column (B2 (mm) has values of 2278, 11262, 685.

Column (?A (mm) has value of 794.09

Column (?B (mm) has values of 2275.07, 11254.04

Column (?B-?A (mm) has values of 8.88E-16, 794.09

These measurements cannot be measured by tuberculin caliper. I would recommend the authors to revise their data entry as these values will affect the outcome of the study.

Response:

Cross-checked with the hard copy and all corrected (shown in brackets below). We have checked them all and these were the only changes (# 4 animals). It was a mistake when entering the decimal point. We have not used the actual measurements for analysis. We used the dichotmous (FALSE coded as "O" for negatives or TRUE coded as 1 for positives) and we found no change in result and not affected. We resubmitted the edited version shown here in brackets.

Column (B2 (mm) has values of 2278 (22.78), 11262 (12.62), 685 (68.5).

Column (?A (mm) has value of 794.09: Due to Column (A2 (mm) 802 (8.02)

Column (?B (mm) has values of 2275.07, 11254.04: associated with value of Column (B2 (mm)

Column (?B-?A (mm) has values of 8.88E-16, 794.09: associated with value of Column (A2 (mm)

Reviewer #2: The study has relevance due to the fact to demonstrate that large herds is a major risk factor for bTB in the country and due to the fact that large herds are the main suppliers of heifers for small herds.

How is the bTB program in the country? It requires testing and culling? Movement control of the animals? The author should provide a brief of the Ethiopian program to the readers.

Response:

A brief comment has been included in the discussion.

Line 75; add space after "[13]"

Response:

corrected.

Line 105: add space after "[15]"

Response: corrected.

Line 233: correct "Prevalence of"

Response:

corrected.

Line 316; the word becategorisedat must be correct "be categorized at"

Response:

corrected.

Lines 401 to 406 – the comment may be included in discussion but is not a conclusion.

Response:

Accepted. This part is removed from the conclusion and moved to the discussion part in the revised manuscript.________________________________________

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Reviewer #1: No

Reviewer #2: Yes: Paulo Alex Machado Carneiro

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PONE-D-20-28942_reviewer.pdf

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Submitted filename: Response to Reviewers.doc

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14 Jun 2021

PONE-D-20-28942R1

The high and variable prevalence of bovine tuberculosis in dairy herds of central Ethiopia provides opportunities for targeted intervention

PLOS ONE

Dear Dr. Almaw,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please make sure that you address all the pending issues highlighted by reviewer #1 in the attached document.

Please submit your revised manuscript by Jul 29 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: There is a significantly improvement of the manuscript after addressing the previous comments. There are few comments in the attached pdf document that has not been addressed from the previous revision, please address them.

I would recommend the title to be modified to "The variable prevalence of bovine tuberculosis among dairy herds in Central Ethiopia provides opportunities for targeted intervention" as variable as aword includes both high and low values.

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Paulo Alex Machado Carneiro

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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Submitted filename: PONE-D-20-28942_reviewer.pdf

Click here for additional data file.

15 Jun 2021

PONE-D-20-28942R1

The high and variable prevalence of bovine tuberculosis in dairy herds of central Ethiopia provides opportunities for targeted intervention

PLOS ONE

Dear Dr. Almaw,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please make sure that you address all the pending issues highlighted by reviewer #1 in the attached document.

Response: All comments highlighted in the PDF file by reviewer # 1 are addressed point by point in the PDF file itself and also in the Revised Clean Manuscript and Revised Manuscript with Track Changes. The PDF file with responses to comments is now uploaded separately as "Response to Reviewers" file. Also we have sent it via email to avoid changes (if any) in the highlighted responses during PDF creation in the online submission system.

Please submit your revised manuscript by Jul 29 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Response: We have checked the reference list and it is complete and correct. We have not cited papers that have been retracted.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

________________________________________

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: There is a significantly improvement of the manuscript after addressing the previous comments. There are few comments in the attached pdf document that has not been addressed from the previous revision, please address them.

Response: Addressed. This time we addressed point by point in the PDF file itself. In the previous revision we addressed these comments only in the Clean Manuscript and Revised Manuscript with Track Changes and we failed to link these responses to the PDF file comments. Now we have included Line numbers, Tables and Pages in the point by point responses in the PDF file for tracking responses easily. The PDF file with responses to comments is now uploaded separately as "Response to Reviewers" file. Also we have sent PDF file with point by point responses via email to the Academic Editor.

I would recommend the title to be modified to "The variable prevalence of bovine tuberculosis among dairy herds in Central Ethiopia provides opportunities for targeted intervention" as variable as a word includes both high and low values.

Response: Thank you! Accepted and title modified as recommended.

Reviewer #2: (No Response)

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Reviewer #1: No

Reviewer #2: Yes: Paulo Alex Machado Carneiro

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Submitted filename: PONE-D-20-28942_reviewer-1.pdf

Click here for additional data file.

21 Jun 2021

The variable prevalence of bovine tuberculosis among dairy herds in Central Ethiopia provides opportunities for targeted intervention

PONE-D-20-28942R2

Dear Dr. Almaw,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

24 Jun 2021

PONE-D-20-28942R2

The variable prevalence of bovine tuberculosis among dairy herds in Central Ethiopia provides opportunities for targeted intervention

Dear Dr. Almaw:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Angel Abuelo

Academic Editor

PLOS ONE