Sero-epidemiology and Molecular Detection of Bluetongue Virus in Goats in Bangladesh

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The incidence of BT in Bangladesh is poorly understood, and there is no molecular evidence of BTV in Bangladesh. Thus, the current study has been designed to estimate the seroprevalence of BTV and associated risk factors and identification of BTV molecularly in Bangladesh. Total 460 goat serum samples were randomly collected from ten goat-rich districts of Bangladesh from July 2023 to June 2024. To determine risk factors, farmers were interviewed with a structured questionnaire. Competitive enzyme-linked immunosorbent assay (cELISA) was utilized for screening serum for anti-BTV antibodies. The logistic regression models were applied to identify potential risk factors. ELISA-positive pooled blood samples were considered for RNA extraction and nested RT-PCR was performed for the molecular detection of BTV by using both VP7 and NS1 gene-specific primers. The overall seroprevalence was 63.04% (95%CI:58.63-67.45). Multivariate logistic regression analysis showed that breed (crossbred; OR:3.4, 95%CI:1.34-8.63), sex (female; OR:1.97, 95% CI:1.15-3.40), age (over 2yrs; OR:6.32, 95%CI:2.42-16.81), biosecurity (poor; OR:26.48, 95%CI:1.72-405.6), farm type (household; OR:33.72, 95%CI:3.02-375.5), flock size (large; OR:30.53, 95% CI:2.91-319.6), and vector control (No; OR:27.56, 95%CI:8.60-88.28) were the major risk factors associated with the occurrence of the BTV infection. The VP7 and NS1 genes were amplified at 770 bp and 101 bp by nested‑PCR for molecular confirmation. In conclusion, the study confirmed both the serological evidence and molecular existence of BTV with potential risk factors for occurring BT in goats of Bangladesh. Veterinary Epidemiology Bluetongue Goat Seroprevalence Risk factors Nested PCR Bangladesh Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Goats play an important role in global livestock systems. Their role is essential in sustaining the nutritional health of a significant population in rural areas, particularly landless small-scale farmers in tropical regions [ 1 ]. Goats also possess a significant importance in the national economy, serving as an important component for both large- and small-scale farmers in their farming practices. The primary sources of protein include milk and meat, while a considerable portion of exports consists of live animals, skins, and carcasses for profit generation [ 2 ]. The raising of goats is increasing in Bangladesh[ 3 ] to satisfy the demand for animal protein; however, various diseases and disorders are hindering the growth of this industry [ 4 ]. The hot and humid climate of Bangladesh fosters diseases that diminish the productivity of animals and increase veterinary costs [ 3 , 5 ]. Goat production is significantly affected by various infectious diseases, with Bluetongue (BT) identified as a serious emerging disease in Bangladesh [ 6 ]. Bluetongue (BT) is a viral disease affecting goats and sheep, characterized as infectious yet non-contagious, and transmitted by arthropods. Its causal agent is the Bluetongue virus (BTV) under Orbivirus genus and Sedoreoviridae family [ 7 , 8 ]. BTV is a virus characterized by the absence of an envelope, featuring ten distinct segments of its double-stranded RNA (dsRNA) genome, which is encircled with an icosahedral triple stack. The BTV genome encodes five non-structural proteins (NS1-NS5) and seven structural proteins (VP1-VP7) [ 9 , 10 ]. The analysis of the genome segment-2 (Seg-2) sequence and its corresponding translated protein VP2 reveals the existence of 28 serotypes of BTV [ 11 ]. Its primary mode of transmission involves blood-feeding insects identified as Culicoides spp., which facilitate the spread of the infection to susceptible hosts. This includes both domestic and wild species such as sheep, goats, cattle, buffaloes, deer, and other members of the Artiodactyla family from infected viremic animals [ 12 , 13 ]. Cattle and goats frequently serve as asymptomatic carriers of the virus, whereas sheep and deer tend to exhibit clinical signs more readily, with certain instances leading to moderate to high fatality rates [ 14 ]. World Organisation for Animal Health has described BT as a notifiable disease due to its significant morbidity and mortality rates [ 11 , 15 ]. The primary manifestations of this disease include fever, serous to bloody discharge from the nose, subsequent mucopurulent discharge, hyperemia, and swelling of the lips, face, ears, and submaxillary region, resulting in a "monkey face" appearance. Additional symptoms include oral erosions and wounds, coronitis, tongue cyanosis, muscular necrosis, and breathing difficulties ultimately resulting in weakness and fatality [ 11 , 16 ]. Restrictions on trade that limit access to valuable markets result in passive losses, whereas direct losses arise from production declines, including mortality, abortion, and reductions in milk and meat production, as well as costs related to vaccines and control measures [ 17 , 18 ]. Worldwide impacts resulting from BT outbreaks were estimated at 3 billion US dollars [ 19 ] and poses a significant risk of economic losses in Bangladesh, since BTV is endemic in India, Myanmar, China, and Pakistan. Many studies indicate the existence of BT in goats, cattle, camels, and buffalo across various states in India adjacent to the Bangladesh border [ 20 , 21 ]. BT has also been reported in Afghanistan, Nepal, Pakistan, India, and Sri Lanka [ 11 ]. Bangladesh has a large bordering area with India to the west, north, and east, and with Myanmar to the south [ 13 ]. The nations have undertaken many steps to assess the prevalence, identify the causal agent, and implement control and prevention measures for this infection [ 22 – 24 ]. Serological existence of bluetongue virus has been identified in sheep within the Chittagong district of Bangladesh near to Myanmar border [ 25 ]. However, in Bangladesh, research on BT incidence is very limited. Additionally, comprehensive epidemiological and molecular data concerning the prevalence and possible risk factors related to BT disease in goats are not available in this country. A comprehensive serological study, along with molecular investigations, is needed to pinpoint the impacted regions and enhance the prediction as well as management of this disease's spread. According to the aforementioned economic impact of this infection and lacking available rational scientific information, the current study aimed to generate large-scale epidemiological data and determine risk factors associated with BT disease, as well as to identify BTV infection by molecular methods for the first time in goats from Bangladesh. The study's findings offer novel viewpoints on the prevalence and state of the infection, which will assist in developing efficient approaches to mitigate BT within this country. 2. Materials and Methods 2.1. Study population, areas, and duration This cross-sectional study aimed to evaluate the seroprevalence and molecular detection of BTV infection in goats in 10 goat-populated districts of Bangladesh between July 2023 and June 2024. A total of 460 blood samples were taken from randomly selected goats living in the study locations (Fig. 1 ). Samples comprising Black Bengal (BBG), Jamunapari (JP), and crossbred goats of both sexes were collected from small (1–10 goats), medium (11–50 goats), and large (> 50 goats) flocks, across three age categories: under 6 months (kids), 6 to 24 months (growing), and over 24 months (adults) were taken for the study. Farmers at the research location practiced semi-intensive and free-range methods for goat rearing. None of the goats included in this study had been vaccinated against BTV. 2.2. Sampling strategy Since there have been relatively few prior reports on BTV from Bangladesh, we estimated the sample size according to the formula by Thrusfield [ 26 ] using the prevalence data from neighboring countries and other sources, the outcome factor's percentage frequency in the overall population (p) is 50% in a 95% confidence interval and 5% desired absolute precision. n = 1.96 2 Pexp (1-Pexp)/d 2 where, n = required sample size, Pexp = expected prevalence and d = desired absolute precision (5%) To achieve the highest level of precision, 460 goats were sampled out of the 384 needed for this investigation. 2.3. Data Collection Information on goat rearing was obtained using structured and pretested questionnaires (Supplementary File 1) during direct interviews to the owners or their representatives. When the interview took place, information about the sex, age, breed, housing, raising method, size of the flock, farm type, biosecurity status, knowledge about BTV, vector control, rearing with other species, vaccination against PPR, body condition score (BCS) of goats were obtained (Supplementary File 2). 2.4. Sample Collection and processing Four hundred and sixty (n = 460) blood samples were collected from selected 10 districts of Bangladesh. For blood collection, animals were restrained gently, the jugular vein area was soaked with povidone-iodine, and approximately 5 mL of blood was drawn using a sterile syringe and needle. The collected blood was divided into two portions, one portion was transferred into a 2 ml EDTA tube for molecular study and another portion was transferred into a vacutainer tube containing clot activator for serum preparation. Then, samples were quickly brought into the Small Ruminant Research Laboratory, Bangladesh Livestock Research Institute, by maintaining proper cool chain conditions for the required laboratory investigations. Blood samples were centrifuged at 3000 rpm for 10 minutes to separate serum. Then serum samples were collected in eppendorf tubes and kept at -20°C and whole blood samples at -80°C before testing in the laboratory. 2.5. Serological analysis All sera were tested for the detection of antibodies against the VP7 protein of BTV in goats by competitive enzyme-linked immunosorbent assay (c-ELISA), using the ID Screen Bluetongue Competition® c-ELISA kit (ID. vet, France, Ref: BTC-5P, Lot: O69), following the manufacturer’s instructions. In brief, the optical density (OD) was measured at 450 nm using an ELISA microplate. For each sample, the percentage OD of sample/ OD of negative control (S/ N percentage) was calculated using the formula provided in the manual: S/N%= (OD sample /OD NC ) ×100. Where OD sample is the optical density of the sample, OD NC is the mean value of the optical density of negative control. Samples showing an S/N% less than 40% were observed as positive while those having S/N% greater than or equal to 40% were observed as negative. 3. Molecular Detection of Bluetongue virus (BTV) 3.1. Preparation of dsRNA and Amplification of BTV Genome Segment using Reverse Transcription Polymerase Chain Reaction (RT-PCR) Total dsRNA was extracted from blood samples, using the PureLink™ RNA Mini kit (Invitrogen, Thermofisher Scientific, USA, Catalog: 12183018A, Lot: 2639227) according to the guidelines provided by the manufacturer. After that extracted RNA was used for PCR or stored at -80°C for further analysis. The following primer sets (Table 1 ) were used to amplify portions of segments VP7 and NS1 by nested PCR of each segment of target genes. Using the One-step RT-PCR kit (ABclonal, USA, Catalog No.: RK20404) following the manufacturer's protocol, the regions of segments VP7 and NS1 were amplified. Configuration for the reaction was: 12.5 µl buffer, 1 µl enzyme mix, l µl of each primer (forward and reverse), 4.5µl nuclease-free water, and 5 µl extracted RNA sample. A PCR tube containing 25µl of the reaction mixture was used for the process. The nestedPCR was done for the second-round amplification of the 770 bp and 101 bp PCR products using BTV VP7 gene-specific primers and BTV NS1 gene-specific primers, respectively. Five µl of the first-round amplified product were used as a template for the second round of PCR amplification. Primer details and different conditions of the RT-PCR method have been described in Table 1 . After the PCR reaction, 5 µl of amplified products were electrophoresed on a 1.5% agarose gel and visualized with ethidium bromide. The generated amplicons were confirmed by their sizes on agarose gel and nested PCR. Table 1 Genes, Primer sequences, and optimal amplification settings for PCR assay Gene Primer sequence (5'-3') PCR Conditions Amplicon size References BTV-Seg-7/VP7 For 1st round, F: GTTAAAAATCTATAGAG R: GTAAGTGTAATCTAAGAG Primary activation at 95°C, 15 min Cycles: 35 Denaturation 95°C, 1 min Annealing 39°C, 1 min Extension 72°C, 2 min Terminal extension 72°C, 7 min 1156 bp [ 27 ] For nested, F: ACAACTGATGCTGCGAATGA R: AACCCACACCCGTGCTAAGTGG All the reaction conditions were the same as for the nested PCR, except the annealing temperature, which was 55°C instead of 39°C. 770 bp BTV-Seg-5/NS1 For 1st round, F: GTTCTCTAGTTGGCAACCACC R: AAGCCAGACTGTTTCCCGAT Primary activation 95°C, 30 min Cycles: 35 Denaturation at 95°C, 30 sec Annealing at 57°C, 30 sec Extension at 72°C, 1 min Terminal extension at 72°C, 10 min 274 bp [ 9 ] For nested, F: GCAGCATTTTGAGAGAGCGA R: CCCGATCATACATTGCTTCCT Primary activation at 94°C, 5 min Cycles: 40 Denaturation at 95°C, 30 sec Annealing at 55°C, 30 sec Extension at 72°C, 1 min Terminal extension at 72°C, 10 min 101 bp 3.2. Statistical analysis The data collected during the survey were entered in Microsoft Excel 2019, checked for quality, and coded the data according to the nature of the variables. Then data were converted to a CSV file for risk factors analysis in the STATA® 14 (StataCorp, Texas, USA). The numerical variables including “age” and “flock size” were tested for multicollinearity and showed a non-linear relationship with each other. Therefore, continuous variables are converted into binary categorical variables by using quantiles especially medians to avoid the error of linearity. Then descriptive statistics were done to calculate the percentage and 95% confidence interval (CI) of each category of individual factor variables. Using chi-square test between variables to find out binary association of BTV in animal levels. Univariable logistic regression analysis was applied to test the association of individual risk factors with the outcome variables of BTV and crude Odds ratios (CORs), their 95% CI and corresponding p-values were estimated by logistic functions in STATA. The farms were considered as a random effect and a backward elimination procedure was followed in the model for multivariable logistic regression analysis to calculate the Adjusted OR (AOR) with CI. The p < 0.05 was considered significant in the chi-square test and both univariable and multivariable analyses. The effectiveness of the multivariate logistic regression model was evaluated using the goodness of fit test and the receiver operating characteristic (ROC) curve. 4. Results 4.1. BTV Sero-prevalence in the study areas The BTV-VP7 antibodies were detected in 290 of 460 sera tested, hence an overall seroprevalence was 63.04% (95% CI: 58.63–67.45). Goats of the Jashore district showed the highest seroprevalence, 84.78% (95% CI: 71.13–93.65) and Dhaka district had the lowest seroprevalence, 35.42% (95% CI: 22.16–50.54). Furthermore, statistical analysis revealed that BTV seroprevalence varied significantly (P < 0.05) among ten study areas (Table 2 ). Table 2 BTV seroprevalence of goats in the study locations by cELISA. Locations Sample tested (Positive) Prevalence (%) 95% CI COR (95% CI) P -value Thakurgaon 48 (27) 56.25 41.18–70.51 2.34 (1.03–5.33) 0.042 Faridpur 41 (22) 53.66 51.96–85.77 2.11 (0.90–4.95 0.086 Chuadanga 49 (39) 79.59 65.66–89.75 7.11 (2.85–17.71) < 0.001 Bandarban 44 (25) 56.82 41.03–71.65 2.39 (1.03–5.56) 0.041 Kustia 42 (32) 76.19 60.54–87.94 5.83 (2.31–14.70) < 0.001 Gaibandha 42 (20) 47.62 32.04–63.58 1.65 (0.71–3.86) 0.242 Rajshahi 50 (29) 58 43.20-71.81 2.51 (1.11–5.69) 0.026 Jashore 46 (39) 84.78 71.13–93.65 10.15 (3.74–27.5) < 0.001 Dhaka 48 (17) 35.42 22.16–50.54 Ref. Sylhet 50 (40) 80 66.28–89.96 7.29 (2.93–18.14) < 0.001 Total 460 63.04% 58.63–67.45 COR- Crude Odds Ratio; CI- Confidence Interval 4.2. Risk Factors associated with BTV 4.2.1. Univariable logistic regression model Table 3 shows the results of an univariable logistic regression study to figure out risk variables for BTV infection. While compared to other goat breeds, cross-bred goats showed the greatest seroprevalence of BTV infection at 76.16% (95% CI: 69.08–82.32, COR: 3.62), which was statistically significant (Table 3 ). Adult goats had a significantly greater prevalence of BTV (83.2%, 95% CI: 76.19–89.86, COR: 5.48) than kids (< 6 months) and young goats (6–24 months). Seropositivity varied significantly between female goats, poor biosecurity measures, no vector control, no knowledge about BTV, and household goat farms, respectively (Table 3 ). Furthermore, goats with poor body condition scores (BCS), medium-sized flocks, free-ranged reared goats, reared with other species, and no PPR vaccination showed higher seropositivity to BTV. But the relationship has not shown any statistical significance. Table 3 Univariable logistic regression analysis of risk factors for BTV seropositivity in goats Variables Group Sample tested (Positive) Prevalence (95% CI) COR (95% CI) P -value Breed BBG 224 (129) 57.59 (50.83–64.14) 1.54 (0.88–2.68) 0.130 JP 64 (30) 46.88 (34.28–59.78) Ref. Cross 172 (131) 76.16 (69.08–82.32) 3.62 (1.98–6.62) < 0.001 Age (month) Below 6 59 (28) 47.46 (34.29–60.88) Ref. 6 to 24 276 (158) 57.25 (50.98–62.94) 1.48 (0.84–2.60) 0.171 over 24 125 (104) 83.2 (76.19–89.86) 5.48 (2.74–10.97) < 0.001 Sex Male 171 (84) 49.12 (41.41–56.86) Ref. Female 289 (206) 71.28 (65.69–76.42) 2.57 (1.73–3.81) < 0.001 Rearing system Semi-intensive 170 (98) 57.65 (49.84–65.17) Ref. Free range 290 (192) 66.21 (60.44.71.63) 1.43 (0.97–2.12) 0.067 Flock size Small 121 (75) 61.98 (52.71–70.65) 1.12 (0.69–1.81) 0.629 Medium 170 (115) 67.65 (60.06–74.61) 1.44 (0.92–2.25) 0.106 Large 169 (100) 59.17 (51.35–66.65) Ref. BCS Good 143 (82) 57.34 (48.80-65.56) Ref. Medium 121 (77) 63.64 (54.40-72.18) 1.30 (0.79–2.13) 0.298 Poor 196 (131) 66.84 (59.77–73.38) 1.49 (0.96–2.34) 0.075 Housing system Floor 243 (168) 69.14 (62.91–74.88) 1.74 (1.19–2.56) 0.004 Slat 217 (122) 56.22 (49.34–62.93) Ref. Biosecurity Good 208 (108) 51.92 (44.91–58.88) Ref. Poor 252 (182) 72.22 (66.25–77.65) 2.40 (1.63–3.54) < 0.001 Farm type Commercial 180 (96) 53.33 (45.76–60.79) Ref. Household 280 (194) 69.29 (63.51–74.63) 1.97 (1.33–2.90) 0.001 Knowledge about BTV Yes 116 (57) 49.14 (39.73–58.58) Ref. No 344 (233) 67.73 (62.50-72.64) 2.17 (1.41–3.33) < 0.001 Vector control Yes 40 (5) 12.5 (4.18–26.80) Ref. No 420 (285) 67.86 (63.15–72.30) 14.78 (5.66–38.5) < 0.001 Rearing with other species Yes 348 (227) 65.23 (59.96–70.22) 1.45 (0.95–2.25) 0.088 No 112 (63) 56.25 (45.56–65.60) Ref. Vaccination against PPR Yes 254 (155) 61.02 (54.72–67.05) Ref. No 206 (135) 65.53 (58.61–72.01) 1.21 (0.83–1.78) 0.319 4.2.2. Multivariable logistic regression model BTV seroprevalence of goats in Bangladesh was predicted to be influenced by seven variables through multivariate logistic regression analysis: breed, age, sex, flock size, biosecurity, farm types, and vector control. The predictive value of these factors has been determined in conjunction with each other. The results of the study found that the likelihood of testing positive for BTV infection was higher in cross-breed goats (AOR: 3.4, 95% CI: 1.34–8.63), adult goats over 24 months (AOR: 6.38, 95% CI: 2.42–16.81), female goats (AOR: 1.97, 95% CI: 1.15–3.40), large flock size (AOR: 30.53, 95% CI: 2.91–319.6), household farms (AOR: 33.72, 95% CI: 3.02–375.5), and farms without vector control (AOR: 27.56, 95% CI: 8.60-88.28) (Table 4 ). Table 4 Potential risk factors for BTV seropositivity in goat farms of different districts of Bangladesh using multivariable logistic regression analysis. Variable Level Estimates SEM Adjusted OR (95% CI) P -value Intercept -8.28 Breed JP Ref. BBG 1.11 0.44 1.7 (0.71–4.05) 0.226 Cross 2.11 0.45 3.4 (1.34–8.63) 0.010 Age (month) Below 6 Ref. 6 to 24 0.38 0.38 1.32 (0.63–2.75) 0.449 over 24 1.82 0.48 6.38 (2.42–16.81) < 0.001 Sex Male Ref. Female 0.60 0.28 1.97 (1.15–3.40) 0.014 Flock size Small Ref. Medium 0.42 0.46 1.69 (0.77–3.67) 0.183 Large 4.75 1.22 30.53 (2.91–319.6) 0.004 Biosecurity Good Ref. Poor 1.60 0.69 26.48 (1.72–405.6) 0.02 Farm type Commercial Ref. Household 3.16 1.08 33.72 (3.02–375.5) < 0.001 Vector control Yes Ref. No 3.45 0.64 27.56 (8.60-88.28) < 0.001 * SEM, standard error of the mean. 4.3. Detection of BTV nucleic acid by RT-PCR The current study employed a nested PCR-based technique utilizing forward and reverse primers specific to both the VP7 and NS1 genes to confirm BTV from ELISA-positive pooled blood samples of goats. By using appropriate primers, PCR products of the predicted sizes were found in the agarose gel electrophoresis at 770 bp for the VP7 gene (Fig. 3 ) and at 273 bp and 101 bp for the NS1 gene (Fig. 4 ), respectively. 5. Discussion BTV is a serious infectious disease on a global basis due to its transmission between international borders via vectors, authorized or unauthorized animal trafficking, or its byproducts [ 28 , 29 ]. Comprehending and observing the epidemiological status of BTV infection within a nation is essential for implementing appropriate actions to mitigate the spreading of the infection and its significant socioeconomic repercussions [ 30 ]. This study encompasses serological and molecular detection of BTV conducted in goats across different goat-rich districts of Bangladesh. The study is the first extensive wide-scale sero-epidemiological investigation on BTV in goats from Bangladesh that covers a broad area of previously untouched goat-prone areas alongside evaluating its related risk factors. The current investigation employed c-ELISA for the detection of BTV antibodies chosen over various serological assays because of a high specificity of 99.96%. This method has been demonstrated as being reliable and ideal for determining BTV antibodies in sheep, goats, and cattle [ 11 , 28 ]. The present study reveals an overall seroprevalence of BTV at 63.04%, indicating as over half of the samples tested positive for BTV infection. There are no vaccinations for BT disease given in Bangladesh. The higher level of BTV antibodies signifies that BTV is prevalent in Bangladeshi goats. The result of the present study is nearly similar to Şevik [ 31 ], who reported 63.3%% of BTV in goats in Turkey, Bakhshesh et al. [ 29 ] reported a 65.65% prevalence of BTV in goats in Iran, and Gizaw et al. [ 32 ] reported a 60.33% prevalence of BTV in goats of Ethiopia. However, Oryan et al. [ 33 ], El-Sebelgy et al. [ 34 ], and Islam et al. [ 13 ] found a higher prevalence of 85.3%, 77.8%, and 78.1% in southern Iran. Egypt and Bangladesh, respectively. The contradiction can be attributed to the lower sample size and study area as well as distinct environmental conditions. High temperatures and tick infestation could be the reasons behind the increasing incidence of BTV, as the virus replicates more effectively above 15ºC [ 28 , 35 ], hence the prevalence of BTV is higher in countries with tropical and subtropical climates. On the other hand, our finding is higher than China’s 28.1% [ 36 ], Morocco’s 37.5% [ 30 ], Pakistan’s 40.75% [ 37 ], Africa’s 47% [ 38 ], India’s 47.58% [ 21 ], and Saudi Arabia’s 53.3% [ 39 ]. Considering these factors were noted in the occurrence of infectious diseases in recent times, the incidence of BTV infection could vary in various countries depending on climate, breed, farming methods, and housing circumstances [ 38 , 40 ]. This difference may also be due to sheep and cattle, which are the main sources of vectors that can spread disease and make goats that are raised with sheep and cattle more likely to get infected [ 28 , 41 ]. The situation became worse because of the absence of clinical manifestation of BTV in goats and the lack of routine serological testing, thus failing to detect the ongoing infection [ 28 ]. The present investigation found a significant association between seroprevalence and breed. Crossbred goats exhibit a significantly higher seroprevalence compared to other breeds (BBG and JP). Small ruminants have been previously reported to have a mild or larger influence on breed susceptibility towards BTV infection [ 42 – 44 ]. Additionally, some researchers found that Indigenous goats are more resistant to various infectious diseases due to their inherent genetic resistance, and exotic and crossbred goats are more susceptible to many infectious diseases [ 45 , 46 ]. Another possible reason for this discrepancy is that the total number of samples analyzed from crossbreeds (n = 172) was lower than that of natives (n = 228), which could have influenced the result. Age was another significant factor for BTV seropositivity observed in the study. Adult goats had significantly higher seroprevalence compared to other groups of goats. This is most likely due to loss of colostral antibodies, becoming more susceptible with age, the raising of previously unnoticed antibody response, increased vector exposure, or a bigger total surface area of the body in adults compared to young goats [ 43 ]. Another factor significantly associated with seroprevalence was the sex of goats where females are more seropositive than males (p > 0.05). Similarly, many studies reported that female goats exhibited significantly higher seroprevalence of BTV [ 36 , 43 , 47 ]. This might be because females are reared for longer periods for reproduction than males as a result they have a higher exposure to Culicoides midges. Additionally, lactating females may release higher levels of volatile organic compounds that attract vectors, hence elevating their risk of being bitten by infected Culicoides midges [ 48 ]. In contrast, Sohail et al. [ 37 ] found higher seroprevalence in male compared to female goats. This might be due to the very low sample collected from male goats (n = 79) than female goats (n = 397). Flock size was another factor that was significantly associated with seroprevalence. Larger flocks exhibited a higher seroprevalence than small and medium-sized flocks. This result is consistent with Gaire et al. [ 47 ] who also found more BTV cases in large flocks. It could be due to larger flocks tend to have higher host densities, providing more opportunities for vectors like Culicoides midges to feed and transmit the virus [ 49 ]. Additionally, managing vector control measures (e.g., insecticides or housing during peak vector activity) is more challenging in large flocks than in small and medium-sized flocks [ 11 ]. The current study revealed significant differences in seroprevalence associated with different farm types and biosecurity measures. There was significantly higher seroprevalence in household farms than in commercial farms and also higher seroprevalence was observed in farms where poor biosecurity measures were maintained by the farmers. This discrepancy might result from the density of the vector population. Previous studies have documented the geographical variation in Culicoides vector densities with BTV seroprevalence [ 47 , 50 , 51 ]. Furthermore, every animal sampled in household farms had no compliance with good farming practices and the farmers did not know BTV infection properly which may also have contributed to this discrepancy. In addition, the vector's sexual and biting activities are facilitated by the poor hygiene of farms, which includes wet soil that is enriched with fresh or decomposed feces [ 21 ]. A significant variation was observed among BTV seroprevalence and the vector control measures implemented by goat farmers. Animals raised without vector control had the highest seroprevalence of BTV. Goat owners lack awareness and knowledge about vector-borne diseases, specifically Bluetongue, which is the main transmission method for BTV [ 13 ]. The complex epidemiological settings of vectors can also influence BTV seroprevalence in the study areas [ 13 , 21 ]. PCR-based methods, including conventional PCR and real-time quantitative PCR (qPCR), are widely used for detecting bluetongue viruses due to their high sensitivity and specificity. These assays target conserved genes like VP7 and NS1 which are critical for reliable diagnosis [ 52 – 54 ]. Here, we first report molecular evidence of BTV in goats in Bangladesh using RT-PCR techniques. This study used the VP7 gene-based nested RT-PCR, a standard gene for BTV detection, to analyze blood samples for the presence of the virus. Conventional PCR targeting the VP7 gene is widely used for detecting Bluetongue Virus (BTV) due to its conserved nature across all serotypes. The VP7 gene encodes a major core protein essential for group-specific diagnosis. Studies have demonstrated its reliability and sensitivity in amplifying BTV RNA from various samples, making it suitable for surveillance and outbreak investigations [ 27 , 55 , 56 ]. Furthermore, this study applied the NS1 gene-based nested PCR of BTV using viral RNA of blood samples. This method produced amplified products of 274 bp and 101 bp, respectively, by using NS1 gene-specific primers. These results align with [ 9 , 57 , 58 ] where they used nested PCR using the NS1 gene for BTV identification. The BTV NS1 gene-based PCR assay serves as a quick, specific, and accurate detection tool for analyzing clinical field blood samples, facilitating the identification of BT disease and the BTV viral epidemiology [ 9 ]. This study provides valuable baseline information on the seroprevalence, associated risk factors, and molecular detection of BTV in goats across different regions of Bangladesh. However, this study also has certain limitations. First, although samples were collected from various farms and districts, flock-level identifiers were not recorded, and the sampling design was based on individual animals rather than a formal multistage cluster approach. Second, the study focused solely on goats and did not include other susceptible ruminants such as sheep, cattle, or buffalo, which may also play a role in BTV transmission. Future studies should incorporate multistage sampling, flock-level data collection, broader species inclusion, and genomic characterization of the circulating BTV serotypes in Bangladesh to support national surveillance and develop effective control programs. 6. Conclusions In this study, serological testing that detects BTV antibodies to determine the nationwide seroprevalence of bluetongue infection and also find out its associated risk factors in Bangladesh. Furthermore, molecular analysis using RT-PCR provides insights into the active circulation of BTV within this country. The findings indicate that BTV is a serious pathogen with economic consequences, and is highly prevalent in goats of Bangladesh, even though the little signs and symptoms are noticed. In addition, the outcomes of this study reveal that goats may pose an imminent threat to other ruminant species within this country. Implementing biosecurity practices in farms and utilizing insect repellents is recommended to decrease infection spread, limit host-vector contact, and reduce financial losses in this country. Declarations Ethical approval The Animal Experimentation Ethics Committee of Bangladesh Livestock Research Institute approved this research project (Reference no: AEEC/BLRI00102/2023). During sample collection, all guidelines for animal care were carefully followed. Funding This study was funded by the Bangladesh Livestock Research Institute, Savar, Dhaka, Bangladesh. Acknowledgments The authors would like to express their sincere gratitude to Md. Abu Haris Miah, Kanis Farzana, Bijay Barua, Md. Munirujjaman, Md. Sohag Talukder and also all the Veterinary Surgeons and Upazilla Livestock Officers in the study areas for their valuable cooperation in facilitating the field samples and data collection. 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Rahman","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYBACAwYehsMQJvMxhgcMEhAmAxthLUClbGkMCcRqYYZo4TEDamEgrMWc/ezBw4V77Or4Z/d8e5C4x4JB3r3HgLmgDLcWy568hMMzniVLSNw5u90g4ZkEg+GZMwbMM87hcdiBHIPDPAeYJRhu5G6TSDgA1DIjLYGZtw2PlvNvQFrqJeRv5DwjUssNsC2HJYAMNrAWeYnkAwS0vAP65cBxyY030swNgFp4DHgOHziM1y/ncw9/LjhQzS93I/nZgw8H6uTk2xsbH+MLMQzAY3CAgeEACRqAQL6BNPWjYBSMglEw/AEADfpUvh+LeEEAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3221-2142","institution":"Bangladesh Livestock Research Institute, Savar, Dhaka","correspondingAuthor":true,"prefix":"","firstName":"Md","middleName":"Habibur","lastName":"Rahman","suffix":""},{"id":488439900,"identity":"220b1837-83f5-4de7-bd1f-91243ad61e10","order_by":1,"name":"Md Nurul Haque","email":"","orcid":"https://orcid.org/0009-0001-1140-3855","institution":"Bangladesh Livestock Research Institute, Savar, 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Research Institute, Savar, Dhaka","correspondingAuthor":false,"prefix":"","firstName":"Md","middleName":"Zakir","lastName":"Hassan","suffix":""},{"id":488447722,"identity":"b0201269-07f4-4269-9519-84536639b205","order_by":5,"name":"Sadek Ahmed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYHACA8YGBoYEIMPwMUMBAw9YjLGBmSgtxsYMBiRqMZMGamEgqEW+/fDGhzMY7PJ025u3VRcY3JNh4F98TIJxhzVuK86kFRtuYEguNjtzrOz2DINiHgaJZ2kSjGfScWthyDGTfMDAnLjtRo7ZbR6DBKCWM8YGjG2HcTus/435zwcM9Ynb7r8xKyZKCwPQcMYNDIeBtvCYMYO18PcYPsCnxeDGs2LJGQbHE7cBPSU9A6iFTYIt8UEiHr/I9ydv/NhTUZ247fjhjZ8LKhLs+fkPHzjwEU+IwQIBAdgkEiDRRALgP0Ca+lEwCkbBKBj2AACxWVQhpZoHQgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-9680-7372","institution":"Bangladesh Livestock Research Institute, Savar, Dhaka","correspondingAuthor":true,"prefix":"","firstName":"Sadek","middleName":"","lastName":"Ahmed","suffix":""}],"badges":[],"createdAt":"2025-07-10 07:22:08","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7090021/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7090021/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1002/vms3.70909","type":"published","date":"2026-03-31T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87279898,"identity":"f867f496-efda-4025-b9d1-883870645479","added_by":"auto","created_at":"2025-07-22 09:31:34","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118521,"visible":true,"origin":"","legend":"\u003cp\u003eStudy areas and collected sample number\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7090021/v1/002da3c3c75d31182397c7e4.jpg"},{"id":87282622,"identity":"3a1d48da-868e-489b-be73-a0af459d5839","added_by":"auto","created_at":"2025-07-22 09:55:34","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55989,"visible":true,"origin":"","legend":"\u003cp\u003eGraph depicting sensitivity against specificity for the receiver operating characteristic (ROC) curve derived from the final multivariable logistic regression analysis of BTV of goats in Bangladesh. The points of the curve indicate the maximum accuracy of the model.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7090021/v1/1a3c31873083ae801b84b38b.jpg"},{"id":87281225,"identity":"213ef8a0-fc6a-4bd8-8a27-e5e6379407ab","added_by":"auto","created_at":"2025-07-22 09:39:34","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33556,"visible":true,"origin":"","legend":"\u003cp\u003eAmplification of BTV VP7 gene as product size 770 bp. PC = positive control and NC = negative control, positive samples = S1, S2, S3, and M = 100 bp DNA ladder.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7090021/v1/95fc4f2bdf032032f8f40566.jpg"},{"id":87281548,"identity":"2594d81e-a8fd-4396-9733-bd306396335a","added_by":"auto","created_at":"2025-07-22 09:47:34","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":61385,"visible":true,"origin":"","legend":"\u003cp\u003eAmplification of BTV NS1 gene as product size 274 bp (left; M = 100 bp DNA ladder) and 101 bp (right; M = 50 bp DNA ladder). PC = positive control and NC = negative control, positive samples = S1 to S8.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7090021/v1/d0e6dfb7683da2f9d705c611.jpg"},{"id":105938690,"identity":"6b1a0a55-c661-46d8-a38e-6c0a9c4d8ffa","added_by":"auto","created_at":"2026-04-01 15:28:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1295741,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7090021/v1/cf235ad3-4fcd-4f2e-a78f-4ff736ff07a7.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSero-epidemiology and Molecular Detection of Bluetongue Virus in Goats in Bangladesh\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGoats play an important role in global livestock systems. Their role is essential in sustaining the nutritional health of a significant population in rural areas, particularly landless small-scale farmers in tropical regions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Goats also possess a significant importance in the national economy, serving as an important component for both large- and small-scale farmers in their farming practices. The primary sources of protein include milk and meat, while a considerable portion of exports consists of live animals, skins, and carcasses for profit generation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The raising of goats is increasing in Bangladesh[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] to satisfy the demand for animal protein; however, various diseases and disorders are hindering the growth of this industry [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The hot and humid climate of Bangladesh fosters diseases that diminish the productivity of animals and increase veterinary costs [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Goat production is significantly affected by various infectious diseases, with Bluetongue (BT) identified as a serious emerging disease in Bangladesh [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Bluetongue (BT) is a viral disease affecting goats and sheep, characterized as infectious yet non-contagious, and transmitted by arthropods. Its causal agent is the Bluetongue virus (BTV) under Orbivirus genus and Sedoreoviridae family [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. BTV is a virus characterized by the absence of an envelope, featuring ten distinct segments of its double-stranded RNA (dsRNA) genome, which is encircled with an icosahedral triple stack. The BTV genome encodes five non-structural proteins (NS1-NS5) and seven structural proteins (VP1-VP7) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The analysis of the genome segment-2 (Seg-2) sequence and its corresponding translated protein VP2 reveals the existence of 28 serotypes of BTV [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Its primary mode of transmission involves blood-feeding insects identified as \u003cem\u003eCulicoides\u003c/em\u003e spp., which facilitate the spread of the infection to susceptible hosts. This includes both domestic and wild species such as sheep, goats, cattle, buffaloes, deer, and other members of the Artiodactyla family from infected viremic animals [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Cattle and goats frequently serve as asymptomatic carriers of the virus, whereas sheep and deer tend to exhibit clinical signs more readily, with certain instances leading to moderate to high fatality rates [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. World Organisation for Animal Health has described BT as a notifiable disease due to its significant morbidity and mortality rates [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe primary manifestations of this disease include fever, serous to bloody discharge from the nose, subsequent mucopurulent discharge, hyperemia, and swelling of the lips, face, ears, and submaxillary region, resulting in a \"monkey face\" appearance. Additional symptoms include oral erosions and wounds, coronitis, tongue cyanosis, muscular necrosis, and breathing difficulties ultimately resulting in weakness and fatality [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Restrictions on trade that limit access to valuable markets result in passive losses, whereas direct losses arise from production declines, including mortality, abortion, and reductions in milk and meat production, as well as costs related to vaccines and control measures [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Worldwide impacts resulting from BT outbreaks were estimated at 3\u0026nbsp;billion US dollars [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and poses a significant risk of economic losses in Bangladesh, since BTV is endemic in India, Myanmar, China, and Pakistan. Many studies indicate the existence of BT in goats, cattle, camels, and buffalo across various states in India adjacent to the Bangladesh border [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. BT has also been reported in Afghanistan, Nepal, Pakistan, India, and Sri Lanka [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Bangladesh has a large bordering area with India to the west, north, and east, and with Myanmar to the south [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The nations have undertaken many steps to assess the prevalence, identify the causal agent, and implement control and prevention measures for this infection [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Serological existence of bluetongue virus has been identified in sheep within the Chittagong district of Bangladesh near to Myanmar border [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, in Bangladesh, research on BT incidence is very limited. Additionally, comprehensive epidemiological and molecular data concerning the prevalence and possible risk factors related to BT disease in goats are not available in this country. A comprehensive serological study, along with molecular investigations, is needed to pinpoint the impacted regions and enhance the prediction as well as management of this disease's spread. According to the aforementioned economic impact of this infection and lacking available rational scientific information, the current study aimed to generate large-scale epidemiological data and determine risk factors associated with BT disease, as well as to identify BTV infection by molecular methods for the first time in goats from Bangladesh. The study's findings offer novel viewpoints on the prevalence and state of the infection, which will assist in developing efficient approaches to mitigate BT within this country.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study population, areas, and duration\u003c/h2\u003e\u003cp\u003eThis cross-sectional study aimed to evaluate the seroprevalence and molecular detection of BTV infection in goats in 10 goat-populated districts of Bangladesh between July 2023 and June 2024. A total of 460 blood samples were taken from randomly selected goats living in the study locations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Samples comprising Black Bengal (BBG), Jamunapari (JP), and crossbred goats of both sexes were collected from small (1\u0026ndash;10 goats), medium (11\u0026ndash;50 goats), and large (\u0026gt;\u0026thinsp;50 goats) flocks, across three age categories: under 6 months (kids), 6 to 24 months (growing), and over 24 months (adults) were taken for the study. Farmers at the research location practiced semi-intensive and free-range methods for goat rearing. None of the goats included in this study had been vaccinated against BTV.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Sampling strategy\u003c/h2\u003e\u003cp\u003eSince there have been relatively few prior reports on BTV from Bangladesh, we estimated the sample size according to the formula by Thrusfield [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] using the prevalence data from neighboring countries and other sources, the outcome factor's percentage frequency in the overall population (p) is 50% in a 95% confidence interval and 5% desired absolute precision.\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;1.96\u003csup\u003e2\u003c/sup\u003ePexp (1-Pexp)/d\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ewhere, n\u0026thinsp;=\u0026thinsp;required sample size, Pexp\u0026thinsp;=\u0026thinsp;expected prevalence and d\u0026thinsp;=\u0026thinsp;desired absolute precision (5%)\u003c/p\u003e\u003cp\u003eTo achieve the highest level of precision, 460 goats were sampled out of the 384 needed for this investigation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Data Collection\u003c/h2\u003e\u003cp\u003eInformation on goat rearing was obtained using structured and pretested questionnaires (Supplementary File 1) during direct interviews to the owners or their representatives. When the interview took place, information about the sex, age, breed, housing, raising method, size of the flock, farm type, biosecurity status, knowledge about BTV, vector control, rearing with other species, vaccination against PPR, body condition score (BCS) of goats were obtained (Supplementary File 2).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Sample Collection and processing\u003c/h2\u003e\u003cp\u003eFour hundred and sixty (n\u0026thinsp;=\u0026thinsp;460) blood samples were collected from selected 10 districts of Bangladesh. For blood collection, animals were restrained gently, the jugular vein area was soaked with povidone-iodine, and approximately 5 mL of blood was drawn using a sterile syringe and needle. The collected blood was divided into two portions, one portion was transferred into a 2 ml EDTA tube for molecular study and another portion was transferred into a vacutainer tube containing clot activator for serum preparation. Then, samples were quickly brought into the Small Ruminant Research Laboratory, Bangladesh Livestock Research Institute, by maintaining proper cool chain conditions for the required laboratory investigations. Blood samples were centrifuged at 3000 rpm for 10 minutes to separate serum. Then serum samples were collected in eppendorf tubes and kept at -20\u0026deg;C and whole blood samples at -80\u0026deg;C before testing in the laboratory.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Serological analysis\u003c/h2\u003e\u003cp\u003eAll sera were tested for the detection of antibodies against the VP7 protein of BTV in goats by competitive enzyme-linked immunosorbent assay (c-ELISA), using the ID Screen Bluetongue Competition\u0026reg; c-ELISA kit (ID. vet, France, Ref: BTC-5P, Lot: O69), following the manufacturer\u0026rsquo;s instructions. In brief, the optical density (OD) was measured at 450 nm using an ELISA microplate. For each sample, the percentage OD of sample/ OD of negative control (S/ N percentage) was calculated using the formula provided in the manual: S/N%= (OD\u003csub\u003esample\u003c/sub\u003e /OD\u003csub\u003eNC\u003c/sub\u003e) \u0026times;100. Where OD \u003csub\u003esample\u003c/sub\u003e is the optical density of the sample, OD\u003csub\u003eNC\u003c/sub\u003e is the mean value of the optical density of negative control. Samples showing an S/N% less than 40% were observed as positive while those having S/N% greater than or equal to 40% were observed as negative.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Molecular Detection of Bluetongue virus (BTV)","content":"\u003cp\u003e\u003cem\u003e3.1. Preparation of dsRNA and Amplification of BTV Genome Segment using Reverse Transcription Polymerase Chain Reaction (RT-PCR)\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTotal dsRNA was extracted from blood samples, using the PureLink\u0026trade; RNA Mini kit (Invitrogen, Thermofisher Scientific, USA, Catalog: 12183018A, Lot: 2639227) according to the guidelines provided by the manufacturer. After that extracted RNA was used for PCR or stored at -80\u0026deg;C for further analysis. The following primer sets (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were used to amplify portions of segments VP7 and NS1 by nested PCR of each segment of target genes. Using the One-step RT-PCR kit (ABclonal, USA, Catalog No.: RK20404) following the manufacturer's protocol, the regions of segments VP7 and NS1 were amplified. Configuration for the reaction was: 12.5 \u0026micro;l buffer, 1 \u0026micro;l enzyme mix, l \u0026micro;l of each primer (forward and reverse), 4.5\u0026micro;l nuclease-free water, and 5 \u0026micro;l extracted RNA sample. A PCR tube containing 25\u0026micro;l of the reaction mixture was used for the process. The nestedPCR was done for the second-round amplification of the 770 bp and 101 bp PCR products using BTV VP7 gene-specific primers and BTV NS1 gene-specific primers, respectively. Five \u0026micro;l of the first-round amplified product were used as a template for the second round of PCR amplification. Primer details and different conditions of the RT-PCR method have been described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. After the PCR reaction, 5 \u0026micro;l of amplified products were electrophoresed on a 1.5% agarose gel and visualized with ethidium bromide. The generated amplicons were confirmed by their sizes on agarose gel and nested PCR.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenes, Primer sequences, and optimal amplification settings for PCR assay\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimer sequence (5'-3')\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePCR Conditions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAmplicon size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eReferences\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eBTV-Seg-7/VP7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFor 1st round,\u003c/p\u003e\u003cp\u003eF: GTTAAAAATCTATAGAG\u003c/p\u003e\u003cp\u003eR: GTAAGTGTAATCTAAGAG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrimary activation at 95\u0026deg;C, 15 min\u003c/p\u003e\u003cp\u003eCycles: 35\u003c/p\u003e\u003cp\u003eDenaturation 95\u0026deg;C, 1 min Annealing 39\u0026deg;C, 1 min\u003c/p\u003e\u003cp\u003eExtension 72\u0026deg;C, 2 min\u003c/p\u003e\u003cp\u003eTerminal extension 72\u0026deg;C, 7 min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1156 bp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFor nested,\u003c/p\u003e\u003cp\u003eF: ACAACTGATGCTGCGAATGA\u003c/p\u003e\u003cp\u003eR: AACCCACACCCGTGCTAAGTGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAll the reaction conditions were the\u0026nbsp;same as for the nested PCR, except the annealing temperature, which was 55\u0026deg;C instead of 39\u0026deg;C.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e770 bp\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eBTV-Seg-5/NS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFor 1st round,\u003c/p\u003e\u003cp\u003eF: GTTCTCTAGTTGGCAACCACC\u003c/p\u003e\u003cp\u003eR: AAGCCAGACTGTTTCCCGAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrimary activation 95\u0026deg;C, 30 min\u003c/p\u003e\u003cp\u003eCycles: 35\u003c/p\u003e\u003cp\u003eDenaturation at 95\u0026deg;C, 30 sec\u003c/p\u003e\u003cp\u003eAnnealing at 57\u0026deg;C, 30 sec\u003c/p\u003e\u003cp\u003eExtension at 72\u0026deg;C, 1 min\u003c/p\u003e\u003cp\u003eTerminal extension at 72\u0026deg;C, 10 min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e274 bp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFor nested,\u003c/p\u003e\u003cp\u003eF: GCAGCATTTTGAGAGAGCGA\u003c/p\u003e\u003cp\u003eR: CCCGATCATACATTGCTTCCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrimary activation at 94\u0026deg;C, 5 min\u003c/p\u003e\u003cp\u003eCycles: 40\u003c/p\u003e\u003cp\u003eDenaturation at 95\u0026deg;C, 30 sec\u003c/p\u003e\u003cp\u003eAnnealing at 55\u0026deg;C, 30 sec\u003c/p\u003e\u003cp\u003eExtension at 72\u0026deg;C, 1 min\u003c/p\u003e\u003cp\u003eTerminal extension at 72\u0026deg;C, 10 min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e101 bp\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Statistical analysis\u003c/h2\u003e\u003cp\u003eThe data collected during the survey were entered in Microsoft Excel 2019, checked for quality, and coded the data according to the nature of the variables. Then data were converted to a CSV file for risk factors analysis in the STATA\u0026reg; 14 (StataCorp, Texas, USA). The numerical variables including \u0026ldquo;age\u0026rdquo; and \u0026ldquo;flock size\u0026rdquo; were tested for multicollinearity and showed a non-linear relationship with each other. Therefore, continuous variables are converted into binary categorical variables by using quantiles especially medians to avoid the error of linearity. Then descriptive statistics were done to calculate the percentage and 95% confidence interval (CI) of each category of individual factor variables. Using chi-square test between variables to find out binary association of BTV in animal levels. Univariable logistic regression analysis was applied to test the association of individual risk factors with the outcome variables of BTV and crude Odds ratios (CORs), their 95% CI and corresponding p-values were estimated by logistic functions in STATA. The farms were considered as a random effect and a backward elimination procedure was followed in the model for multivariable logistic regression analysis to calculate the Adjusted OR (AOR) with CI. The \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant in the chi-square test and both univariable and multivariable analyses. The effectiveness of the multivariate logistic regression model was evaluated using the goodness of fit test and the receiver operating characteristic (ROC) curve.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1. BTV Sero-prevalence in the study areas\u003c/h2\u003e\u003cp\u003eThe BTV-VP7 antibodies were detected in 290 of 460 sera tested, hence an overall seroprevalence was 63.04% (95% CI: 58.63\u0026ndash;67.45). Goats of the Jashore district showed the highest seroprevalence, 84.78% (95% CI: 71.13\u0026ndash;93.65) and Dhaka district had the lowest seroprevalence, 35.42% (95% CI: 22.16\u0026ndash;50.54). Furthermore, statistical analysis revealed that BTV seroprevalence varied significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among ten study areas (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBTV seroprevalence of goats in the study locations by cELISA.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSample tested (Positive)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrevalence\u003c/p\u003e\u003cp\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThakurgaon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48 (27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41.18\u0026ndash;70.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.34 (1.03\u0026ndash;5.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFaridpur\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41 (22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.96\u0026ndash;85.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.11 (0.90\u0026ndash;4.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChuadanga\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49 (39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.66\u0026ndash;89.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.11 (2.85\u0026ndash;17.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBandarban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41.03\u0026ndash;71.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.39 (1.03\u0026ndash;5.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKustia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e60.54\u0026ndash;87.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.83 (2.31\u0026ndash;14.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGaibandha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.04\u0026ndash;63.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.65 (0.71\u0026ndash;3.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRajshahi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50 (29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43.20-71.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.51 (1.11\u0026ndash;5.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJashore\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e71.13\u0026ndash;93.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.15 (3.74\u0026ndash;27.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDhaka\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48 (17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.16\u0026ndash;50.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSylhet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50 (40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66.28\u0026ndash;89.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.29 (2.93\u0026ndash;18.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e460\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e63.04%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e58.63\u0026ndash;67.45\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eCOR- Crude Odds Ratio; CI- Confidence Interval\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Risk Factors associated with BTV\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e4.2.1. Univariable logistic regression model\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results of an univariable logistic regression study to figure out risk variables for BTV infection. While compared to other goat breeds, cross-bred goats showed the greatest seroprevalence of BTV infection at 76.16% (95% CI: 69.08\u0026ndash;82.32, COR: 3.62), which was statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Adult goats had a significantly greater prevalence of BTV (83.2%, 95% CI: 76.19\u0026ndash;89.86, COR: 5.48) than kids (\u0026lt;\u0026thinsp;6 months) and young goats (6\u0026ndash;24 months). Seropositivity varied significantly between female goats, poor biosecurity measures, no vector control, no knowledge about BTV, and household goat farms, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Furthermore, goats with poor body condition scores (BCS), medium-sized flocks, free-ranged reared goats, reared with other species, and no PPR vaccination showed higher seropositivity to BTV. But the relationship has not shown any statistical significance.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariable logistic regression analysis of risk factors for BTV seropositivity in goats\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSample tested (Positive)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePrevalence (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eBreed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBBG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e224 (129)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.59 (50.83\u0026ndash;64.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.54 (0.88\u0026ndash;2.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.130\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 (30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e46.88 (34.28\u0026ndash;59.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCross\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e172 (131)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e76.16 (69.08\u0026ndash;82.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.62 (1.98\u0026ndash;6.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAge (month)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBelow 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59 (28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47.46 (34.29\u0026ndash;60.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 to 24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e276 (158)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.25 (50.98\u0026ndash;62.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.48 (0.84\u0026ndash;2.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eover 24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e125 (104)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e83.2 (76.19\u0026ndash;89.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.48 (2.74\u0026ndash;10.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e171 (84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49.12 (41.41\u0026ndash;56.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e289 (206)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e71.28 (65.69\u0026ndash;76.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.57 (1.73\u0026ndash;3.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRearing system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSemi-intensive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e170 (98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.65 (49.84\u0026ndash;65.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFree range\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e290 (192)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66.21 (60.44.71.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.43 (0.97\u0026ndash;2.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eFlock size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e121 (75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e61.98 (52.71\u0026ndash;70.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.12 (0.69\u0026ndash;1.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.629\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e170 (115)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67.65 (60.06\u0026ndash;74.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.44 (0.92\u0026ndash;2.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e169 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e59.17 (51.35\u0026ndash;66.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eBCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e143 (82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.34 (48.80-65.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e121 (77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e63.64 (54.40-72.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.30 (0.79\u0026ndash;2.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.298\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e196 (131)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66.84 (59.77\u0026ndash;73.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.49 (0.96\u0026ndash;2.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHousing system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFloor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e243 (168)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69.14 (62.91\u0026ndash;74.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.74 (1.19\u0026ndash;2.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e217 (122)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56.22 (49.34\u0026ndash;62.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eBiosecurity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e208 (108)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.92 (44.91\u0026ndash;58.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e252 (182)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e72.22 (66.25\u0026ndash;77.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.40 (1.63\u0026ndash;3.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFarm type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommercial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e180 (96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e53.33 (45.76\u0026ndash;60.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousehold\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e280 (194)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69.29 (63.51\u0026ndash;74.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.97 (1.33\u0026ndash;2.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eKnowledge about BTV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116 (57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49.14 (39.73\u0026ndash;58.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e344 (233)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67.73 (62.50-72.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.17 (1.41\u0026ndash;3.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVector control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.5 (4.18\u0026ndash;26.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e420 (285)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67.86 (63.15\u0026ndash;72.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.78 (5.66\u0026ndash;38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRearing with other species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e348 (227)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.23 (59.96\u0026ndash;70.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.45 (0.95\u0026ndash;2.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.088\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e112 (63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56.25 (45.56\u0026ndash;65.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVaccination against PPR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e254 (155)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e61.02 (54.72\u0026ndash;67.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e206 (135)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.53 (58.61\u0026ndash;72.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.21 (0.83\u0026ndash;1.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.319\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e4.2.2. Multivariable logistic regression model\u003c/h2\u003e\u003cp\u003eBTV seroprevalence of goats in Bangladesh was predicted to be influenced by seven variables through multivariate logistic regression analysis: breed, age, sex, flock size, biosecurity, farm types, and vector control. The predictive value of these factors has been determined in conjunction with each other. The results of the study found that the likelihood of testing positive for BTV infection was higher in cross-breed goats (AOR: 3.4, 95% CI: 1.34\u0026ndash;8.63), adult goats over 24 months (AOR: 6.38, 95% CI: 2.42\u0026ndash;16.81), female goats (AOR: 1.97, 95% CI: 1.15\u0026ndash;3.40), large flock size (AOR: 30.53, 95% CI: 2.91\u0026ndash;319.6), household farms (AOR: 33.72, 95% CI: 3.02\u0026ndash;375.5), and farms without vector control (AOR: 27.56, 95% CI: 8.60-88.28) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePotential risk factors for BTV seropositivity in goat farms of different districts of Bangladesh using multivariable logistic regression analysis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSEM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-8.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eBreed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBBG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.7 (0.71\u0026ndash;4.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.226\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCross\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.4 (1.34\u0026ndash;8.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAge (month)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBelow 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 to 24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.32 (0.63\u0026ndash;2.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.449\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eover 24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.38 (2.42\u0026ndash;16.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.97 (1.15\u0026ndash;3.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eFlock size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.69 (0.77\u0026ndash;3.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.183\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.53 (2.91\u0026ndash;319.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eBiosecurity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26.48 (1.72\u0026ndash;405.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFarm type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommercial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousehold\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.72 (3.02\u0026ndash;375.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVector control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27.56 (8.60-88.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003eSEM, standard error of the mean.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Detection of BTV nucleic acid by RT-PCR\u003c/h2\u003e\u003cp\u003eThe current study employed a nested PCR-based technique utilizing forward and reverse primers specific to both the VP7 and NS1 genes to confirm BTV from ELISA-positive pooled blood samples of goats. By using appropriate primers, PCR products of the predicted sizes were found in the agarose gel electrophoresis at 770 bp for the VP7 gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and at 273 bp and 101 bp for the NS1 gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), respectively.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eBTV is a serious infectious disease on a global basis due to its transmission between international borders via vectors, authorized or unauthorized animal trafficking, or its byproducts [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Comprehending and observing the epidemiological status of BTV infection within a nation is essential for implementing appropriate actions to mitigate the spreading of the infection and its significant socioeconomic repercussions [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This study encompasses serological and molecular detection of BTV conducted in goats across different goat-rich districts of Bangladesh.\u003c/p\u003e\u003cp\u003eThe study is the first extensive wide-scale sero-epidemiological investigation on BTV in goats from Bangladesh that covers a broad area of previously untouched goat-prone areas alongside evaluating its related risk factors. The current investigation employed c-ELISA for the detection of BTV antibodies chosen over various serological assays because of a high specificity of 99.96%. This method has been demonstrated as being reliable and ideal for determining BTV antibodies in sheep, goats, and cattle [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The present study reveals an overall seroprevalence of BTV at 63.04%, indicating as over half of the samples tested positive for BTV infection. There are no vaccinations for BT disease given in Bangladesh. The higher level of BTV antibodies signifies that BTV is prevalent in Bangladeshi goats. The result of the present study is nearly similar to Şevik [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], who reported 63.3%% of BTV in goats in Turkey, Bakhshesh et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] reported a 65.65% prevalence of BTV in goats in Iran, and Gizaw et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] reported a 60.33% prevalence of BTV in goats of Ethiopia. However, Oryan et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], El-Sebelgy et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and Islam et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] found a higher prevalence of 85.3%, 77.8%, and 78.1% in southern Iran. Egypt and Bangladesh, respectively. The contradiction can be attributed to the lower sample size and study area as well as distinct environmental conditions. High temperatures and tick infestation could be the reasons behind the increasing incidence of BTV, as the virus replicates more effectively above 15\u0026ordm;C [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], hence the prevalence of BTV is higher in countries with tropical and subtropical climates. On the other hand, our finding is higher than China\u0026rsquo;s 28.1% [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], Morocco\u0026rsquo;s 37.5% [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], Pakistan\u0026rsquo;s 40.75% [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], Africa\u0026rsquo;s 47% [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], India\u0026rsquo;s 47.58% [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and Saudi Arabia\u0026rsquo;s 53.3% [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Considering these factors were noted in the occurrence of infectious diseases in recent times, the incidence of BTV infection could vary in various countries depending on climate, breed, farming methods, and housing circumstances [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This difference may also be due to sheep and cattle, which are the main sources of vectors that can spread disease and make goats that are raised with sheep and cattle more likely to get infected [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The situation became worse because of the absence of clinical manifestation of BTV in goats and the lack of routine serological testing, thus failing to detect the ongoing infection [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe present investigation found a significant association between seroprevalence and breed. Crossbred goats exhibit a significantly higher seroprevalence compared to other breeds (BBG and JP). Small ruminants have been previously reported to have a mild or larger influence on breed susceptibility towards BTV infection [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Additionally, some researchers found that Indigenous goats are more resistant to various infectious diseases due to their inherent genetic resistance, and exotic and crossbred goats are more susceptible to many infectious diseases [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Another possible reason for this discrepancy is that the total number of samples analyzed from crossbreeds (n\u0026thinsp;=\u0026thinsp;172) was lower than that of natives (n\u0026thinsp;=\u0026thinsp;228), which could have influenced the result.\u003c/p\u003e\u003cp\u003eAge was another significant factor for BTV seropositivity observed in the study. Adult goats had significantly higher seroprevalence compared to other groups of goats. This is most likely due to loss of colostral antibodies, becoming more susceptible with age, the raising of previously unnoticed antibody response, increased vector exposure, or a bigger total surface area of the body in adults compared to young goats [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAnother factor significantly associated with seroprevalence was the sex of goats where females are more seropositive than males (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Similarly, many studies reported that female goats exhibited significantly higher seroprevalence of BTV [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This might be because females are reared for longer periods for reproduction than males as a result they have a higher exposure to \u003cem\u003eCulicoides\u003c/em\u003e midges. Additionally, lactating females may release higher levels of volatile organic compounds that attract vectors, hence elevating their risk of being bitten by infected Culicoides midges [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. In contrast, Sohail et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] found higher seroprevalence in male compared to female goats. This might be due to the very low sample collected from male goats (n\u0026thinsp;=\u0026thinsp;79) than female goats (n\u0026thinsp;=\u0026thinsp;397).\u003c/p\u003e\u003cp\u003eFlock size was another factor that was significantly associated with seroprevalence. Larger flocks exhibited a higher seroprevalence than small and medium-sized flocks. This result is consistent with Gaire et al. [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] who also found more BTV cases in large flocks. It could be due to larger flocks tend to have higher host densities, providing more opportunities for vectors like \u003cem\u003eCulicoides\u003c/em\u003e midges to feed and transmit the virus [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Additionally, managing vector control measures (e.g., insecticides or housing during peak vector activity) is more challenging in large flocks than in small and medium-sized flocks [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe current study revealed significant differences in seroprevalence associated with different farm types and biosecurity measures. There was significantly higher seroprevalence in household farms than in commercial farms and also higher seroprevalence was observed in farms where poor biosecurity measures were maintained by the farmers. This discrepancy might result from the density of the vector population. Previous studies have documented the geographical variation in Culicoides vector densities with BTV seroprevalence [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Furthermore, every animal sampled in household farms had no compliance with good farming practices and the farmers did not know BTV infection properly which may also have contributed to this discrepancy. In addition, the vector's sexual and biting activities are facilitated by the poor hygiene of farms, which includes wet soil that is enriched with fresh or decomposed feces [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA significant variation was observed among BTV seroprevalence and the vector control measures implemented by goat farmers. Animals raised without vector control had the highest seroprevalence of BTV. Goat owners lack awareness and knowledge about vector-borne diseases, specifically Bluetongue, which is the main transmission method for BTV [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The complex epidemiological settings of vectors can also influence BTV seroprevalence in the study areas [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePCR-based methods, including conventional PCR and real-time quantitative PCR (qPCR), are widely used for detecting bluetongue viruses due to their high sensitivity and specificity. These assays target conserved genes like VP7 and NS1 which are critical for reliable diagnosis [\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Here, we first report molecular evidence of BTV in goats in Bangladesh using RT-PCR techniques. This study used the VP7 gene-based nested RT-PCR, a standard gene for BTV detection, to analyze blood samples for the presence of the virus. Conventional PCR targeting the VP7 gene is widely used for detecting Bluetongue Virus (BTV) due to its conserved nature across all serotypes. The VP7 gene encodes a major core protein essential for group-specific diagnosis. Studies have demonstrated its reliability and sensitivity in amplifying BTV RNA from various samples, making it suitable for surveillance and outbreak investigations [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Furthermore, this study applied the NS1 gene-based nested PCR of BTV using viral RNA of blood samples. This method produced amplified products of 274 bp and 101 bp, respectively, by using NS1 gene-specific primers. These results align with [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] where they used nested PCR using the NS1 gene for BTV identification. The BTV NS1 gene-based PCR assay serves as a quick, specific, and accurate detection tool for analyzing clinical field blood samples, facilitating the identification of BT disease and the BTV viral epidemiology [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study provides valuable baseline information on the seroprevalence, associated risk factors, and molecular detection of BTV in goats across different regions of Bangladesh. However, this study also has certain limitations. First, although samples were collected from various farms and districts, flock-level identifiers were not recorded, and the sampling design was based on individual animals rather than a formal multistage cluster approach. Second, the study focused solely on goats and did not include other susceptible ruminants such as sheep, cattle, or buffalo, which may also play a role in BTV transmission. Future studies should incorporate multistage sampling, flock-level data collection, broader species inclusion, and genomic characterization of the circulating BTV serotypes in Bangladesh to support national surveillance and develop effective control programs.\u003c/p\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003eIn this study, serological testing that detects BTV antibodies to determine the nationwide seroprevalence of bluetongue infection and also find out its associated risk factors in Bangladesh. Furthermore, molecular analysis using RT-PCR provides insights into the active circulation of BTV within this country. The findings indicate that BTV is a serious pathogen with economic consequences, and is highly prevalent in goats of Bangladesh, even though the little signs and symptoms are noticed. In addition, the outcomes of this study reveal that goats may pose an imminent threat to other ruminant species within this country. Implementing biosecurity practices in farms and utilizing insect repellents is recommended to decrease infection spread, limit host-vector contact, and reduce financial losses in this country.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Animal Experimentation Ethics Committee of Bangladesh Livestock Research Institute approved this research project (Reference no: AEEC/BLRI00102/2023). During sample collection, all guidelines for animal care were carefully followed.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was funded by the Bangladesh Livestock Research Institute, Savar, Dhaka, Bangladesh.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Md. Abu Haris Miah, Kanis Farzana, Bijay Barua, Md. Munirujjaman, Md. Sohag Talukder and also all the Veterinary Surgeons and Upazilla Livestock Officers in the study areas for their valuable cooperation in facilitating the field samples and data collection. The authors would like to thank all the lab staff of the Small Ruminant Research Laboratory, Goat Production Research Division at Bangladesh Livestock Research Institute, Savar, Dhaka 1341, Bangladesh, for their assistance with this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data that supports the findings of this study are available in the supplementary material of this article\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eM.R.R. Nair, V. Sejian, M. V. Silpa, V.F.C. Fons\u0026ecirc;ca, C.C. de Melo Costa, C. Devaraj, G. Krishnan, M. Bagath, P.O. Nameer, R. 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Bhadaniya, Evaluation of group specific nested PCR for detection of bluetongue virus, Vet. World 2 (2009) 179\u0026ndash;182. https://doi.org/10.5455/vetworld.2009.179-182.\u003c/li\u003e\n\u003cli\u003eA. Bhagat, B. Chandel, A. Dadawala, H. Chauhan, H. Kher, Isolation and identification of bluetongue virus from goat, Indian J. Small Ruminants 21 (2015) 269\u0026ndash;272. https://doi.org/10.5958/0973-9718.2015.00058.6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"Bangladesh Livestock Research Institute","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bluetongue, Goat, Seroprevalence, Risk factors, Nested PCR, Bangladesh","lastPublishedDoi":"10.21203/rs.3.rs-7090021/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7090021/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBluetongue (BT) is an arthropod-transmitted viral non-contagious and infectious disease of domestic ruminants caused by bluetongue virus (BTV). The incidence of BT in Bangladesh is poorly understood, and there is no molecular evidence of BTV in Bangladesh. Thus, the current study has been designed to estimate the seroprevalence of BTV and associated risk factors and identification of BTV molecularly in Bangladesh. Total 460 goat serum samples were randomly collected from ten goat-rich districts of Bangladesh from July 2023 to June 2024. To determine risk factors, farmers were interviewed with a structured questionnaire. Competitive enzyme-linked immunosorbent assay (cELISA) was utilized for screening serum for anti-BTV antibodies. The logistic regression models were applied to identify potential risk factors. ELISA-positive pooled blood samples were considered for RNA extraction and nested RT-PCR was performed for the molecular detection of BTV by using both VP7 and NS1 gene-specific primers. The overall seroprevalence was 63.04% (95%CI:58.63-67.45). Multivariate logistic regression analysis showed that breed (crossbred; OR:3.4, 95%CI:1.34-8.63), sex (female; OR:1.97, 95% CI:1.15-3.40), age (over 2yrs; OR:6.32, 95%CI:2.42-16.81), biosecurity (poor; OR:26.48, 95%CI:1.72-405.6), farm type (household; OR:33.72, 95%CI:3.02-375.5), flock size (large; OR:30.53, 95% CI:2.91-319.6), and vector control (No; OR:27.56, 95%CI:8.60-88.28) were the major risk factors associated with the occurrence of the BTV infection. \u0026nbsp;The VP7 and NS1 genes were amplified at 770 bp and 101 bp by nested‑PCR for molecular confirmation. In conclusion, the study confirmed both the serological evidence and molecular existence of BTV with potential risk factors for occurring BT in goats of Bangladesh.\u003c/p\u003e","manuscriptTitle":"Sero-epidemiology and Molecular Detection of Bluetongue Virus in Goats in Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-22 09:31:30","doi":"10.21203/rs.3.rs-7090021/v1","editorialEvents":[{"type":"communityComments","content":1}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"948cf7f6-5c60-4b95-955f-c524f5b0f577","owner":[],"postedDate":"July 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51321963,"name":"Veterinary Epidemiology"}],"tags":[],"updatedAt":"2026-04-01T15:28:47+00:00","versionOfRecord":{"articleIdentity":"rs-7090021","link":"https://doi.org/10.1002/vms3.70909","journal":{"identity":"veterinary-medicine-and-science","isVorOnly":true,"title":"Veterinary Medicine and Science"},"publishedOn":"2026-03-31 00:00:00","publishedOnDateReadable":"March 31st, 2026"},"versionCreatedAt":"2025-07-22 09:31:30","video":"","vorDoi":"10.1002/vms3.70909","vorDoiUrl":"https://doi.org/10.1002/vms3.70909","workflowStages":[]},"version":"v1","identity":"rs-7090021","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7090021","identity":"rs-7090021","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}