scholarly journals Risk factors and true prevalence of bovine tuberculosis in Bangladesh

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247838
Author(s):  
Md. Nazimul Islam ◽  
Mohammad Kamruzzaman Khan ◽  
Mohammad Ferdousur Rahman Khan ◽  
Polychronis Kostoulas ◽  
A. K. M. Anisur Rahman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bovine Tuberculosis ◽  
Critical Threshold ◽  
Bayesian Hierarchical ◽  
Herd Level ◽  
Control Programs ◽  
True Prevalence ◽  
Apparent Prevalence ◽  
Risk Factor Data ◽  
Factor Data

Bovine tuberculosis (bTb) is endemic in Bangladesh but the true prevalence has not yet been reported. Our objectives for this study were to determine the true prevalence and identify risk factors for bTb at the animal- and herd-level in Bangladesh. A total of 510 cows were randomly selected during January 2018 to December 2018. Caudal fold (CFT) and comparative cervical tuberculin tests (CCT) were serially interpreted. Animal- and herd-level risk factor data were collected using a pre-tested questionnaire. The hierarchical true prevalence of bTb was estimated within a Bayesian framework. The herd- and animal-level risk factors were identified using mixed effects logistic regression. The apparent prevalence of bTb was 20.6% [95% Confidence Interval (CI): 17.3; 24.3] based on CFT. The animal-level true prevalence of bTb was 21.9 (13.0; 32.4). The herd-level true prevalence in different regions varied from 41.9% to 88.8%. The region-level true prevalence was 49.9 (13.8; 91.2). There is a 100% certainty that herds from Bhaluka and Mymensingh Sadar upazilas are not free from bTb. The odds of bTb were 3.9 times (1.2; 12.6) higher in herds having more than four cows than those with ≤ 4 cows. On the other hand, the risk of bTb was 3.3 times higher (1.0; 10.5) in non-grazing cows than grazing cows. Crossbred cows were 2.9 times (1.5; 5.9) more likely to be infected with bTb than indigenous cows. The risk of bTb in animals with cough was 2.3 times (1.2; 4.3) higher than those without cough. Crossbred, non-grazing cows with cough should be targeted for bTb surveillance. Herds of the Mymensingh, Sadar and Bhaluka regions should be emphasized for bTb control programs. Estimation of Bayesian hierarchical true prevalence facilitates identification of areas with higher prevalence and can be used to indicate regions that where true prevalence exceeds a pre-specified critical threshold.

scholarly journals Using machine learning improves predictions of herd-level bovine tuberculosis breakdowns in Great Britain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
K. Stański ◽  
S. Lycett ◽  
T. Porphyre ◽  
B. M. de C. Bronsvoort
Keyword(s):  
Machine Learning ◽  
Risk Factor ◽  
Great Britain ◽  
Bovine Tuberculosis ◽  
Test Results ◽  
Predictive Capability ◽  
Herd Level ◽  
The United Kingdom ◽  
Risk Factor Data ◽  
Factor Data

AbstractIn the United Kingdom, despite decades of control efforts, bovine tuberculosis (bTB) has not been controlled and currently costs ~ £100 m annually. Critical in the failure of control efforts has been the lack of a sufficiently sensitive diagnostic test. Here we use machine learning (ML) to predict herd-level bTB breakdowns in Great Britain (GB) with the aim of improving herd-level diagnostic sensitivity. The results of routinely-collected herd-level tests were correlated with risk factor data. Four ML methods were independently trained with data from 2012–2014 including ~ 4700 positive herd-level test results annually. The best model’s performance was compared to the observed sensitivity and specificity of the herd-level test calculated on the 2015 data resulting in an increased herd-level sensitivity from 61.3 to 67.6% (95% confidence interval (CI): 66.4–68.8%) and herd-level specificity from 90.5 to 92.3% (95% CI: 91.6–93.1%). This approach can improve predictive capability for herd-level bTB and support disease control.

scholarly journals Prevalence and herd-level risk factors of bovine tuberculosis in the State of Goiás, Brazil

2016 ◽  
Vol 37 (5Supl2) ◽  
pp. 3625 ◽  
Author(s):  
Willian Vilela Rocha ◽  
Valéria De Sá Jayme ◽  
Ana Lourdes Arrais de Alencar Mota ◽  
Wilia Marta Elsner Diederichsen de Brito ◽  
Glauciane Ribeiro de Castro Pires ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bovine Tuberculosis ◽  
Protective Factor ◽  
Management Practices ◽  
Multiple Logistic Regression Analysis ◽  
Livestock Production ◽  
The State ◽  
Economic Losses ◽  
Strong Concentration ◽  
Herd Level

Bovine tuberculosis results in economic losses in livestock production and poses a risk to public health. This study aimed to characterize the epidemiological status of bovine tuberculosis in adult cows in the state of Goiás, Brazil. The state was divided into three sampling strata, corresponding to different livestock production circuits. A total of 18,659 animals were tested with the comparative cervical tuberculin test (CCT), in 300 randomly sampled bovine herds per stratum. An epidemiological questionnaire was used to identify health and management practices that may be associated with the presence of tuberculosis infection in the herd. In Stratum 1, dominated by beef cattle, no animals reacted to the CCT. In Stratum 2, which covers the main dairy regions of the state, the prevalence was estimated at 8.67% [5.73 to 12.74%] for herds and at 0.9% [0.21 to 1.58%] for animals. In Stratum 3, characterized by a mix of dairy, beef and dual-purpose herds, the prevalence was estimated at 1.00% [0.21 to 2.89] for herds and 0.30% [0.10 to 0.49 %] for animals. The overall prevalence in the state of Goiás was 3.43% [2.20 to 4.67%] for herds and 0.30% [0.10 to 0.49%] for animals. The multiple logistic regression analysis revealed that herd-level risk factors associated with the presence of the bovine tuberculosis are: the location of the herd in Stratum 2 (OR = 12.05 [3.52 to 41.28]) and the number of times a cow is milked per day (OR = 6.27 [2.72 to 14.44]). Regular veterinary care was identified as a protective factor (OR = 0.38 [0.15-0.94]). These results indicate that bovine tuberculosis is endemic in the state; its spatial distribution is heterogeneous with a strong concentration in dairy regions. The most intensive dairy farms are those with the highest risk, which is consistent with what other authors’ found elsewhere in Brazil. The epidemiological information generated by this study provides information for planning of risk-based surveillance actions, and justifies the adoption of free-herd certification programs for bovine tuberculosis in the main dairy regions of Goiás.

Herd-level risk factors for bovine tuberculosis in French cattle herds

2016 ◽  
Vol 131 ◽  
pp. 31-40 ◽  
Author(s):  
Maud Marsot ◽  
Marina Béral ◽  
Axelle Scoizec ◽  
Yoann Mathevon ◽  
Benoit Durand ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bovine Tuberculosis ◽  
Herd Level ◽  
Cattle Herds

scholarly journals Herd-level bovine tuberculosis risk factors: assessing the role of low-level badger population disturbance

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
David M. Wright ◽  
Neil Reid ◽  
W. Ian Montgomery ◽  
Adrian R. Allen ◽  
Robin A. Skuce ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bovine Tuberculosis ◽  
Herd Level ◽  
Low Level ◽  
Tuberculosis Risk

scholarly journals Twenty years and counting: epidemiology of an outbreak of isoniazid-resistant tuberculosis in England and Wales, 1995 to 2014

2017 ◽  
Vol 22 (8) ◽  
Author(s):  
Catherine M Smith ◽  
Suzan C M Trienekens ◽  
Charlotte Anderson ◽  
Maeve K Lalor ◽  
Tim Brown ◽  
...  
Keyword(s):  
Risk Factors ◽  
Function Analysis ◽  
Surveillance Systems ◽  
Social Risk ◽  
Social Risk Factors ◽  
Resistant Tuberculosis ◽  
Risk Factor Data ◽  
Social Risk Factor ◽  
Factor Data ◽  
Over Time

An outbreak of isoniazid-resistant tuberculosis first identified in London has now been ongoing for 20 years, making it the largest drug-resistant outbreak of tuberculosis documented to date worldwide. We identified culture-confirmed cases with indistinguishable molecular strain types and extracted demographic, clinical, microbiological and social risk factor data from surveillance systems. We summarised changes over time and used kernel-density estimation and k-function analysis to assess geographic clustering. From 1995 to 2014, 508 cases were reported, with a declining trend in recent years. Overall, 70% were male (n = 360), 60% born in the United Kingdom (n = 306), 39% white (n = 199), and 26% black Caribbean (n = 134). Median age increased from 25 years in the first 5 years to 42 in the last 5. Approximately two thirds of cases reported social risk factors: 45% drug use (n = 227), 37% prison link (n = 189), 25% homelessness (n = 125) and 13% alcohol dependence (n = 64). Treatment was completed at 12 months by 52% of cases (n = 206), and was significantly lower for those with social risk factors (p < 0.05), but increased over time for all patients (p < 0.05). The outbreak remained focused in north London throughout. Control of this outbreak requires continued efforts to prevent and treat further active cases through targeted screening and enhanced case management.

Prevalence and risk factors for Salmonella in veal calves at Danish cattle abattoirs

2010 ◽  
Vol 139 (7) ◽  
pp. 1075-1080 ◽  
Author(s):  
L. R. NIELSEN ◽  
D. L. BAGGESEN ◽  
S. AABO ◽  
M. K. MOOS ◽  
E. RATTENBORG
Keyword(s):  
Risk Factors ◽  
Food Safety ◽  
Dairy Industry ◽  
Low Risk ◽  
Surveillance Programme ◽  
Veal Calves ◽  
True Prevalence ◽  
Apparent Prevalence ◽  
Faecal Samples ◽  
Veal Calf

SUMMARYThe study's objectives were to determine herd- and animal-level prevalence and herd-level risk factors for Salmonella in dairy-bred veal calves at slaughter in Denmark. In total, 1296 faecal samples were collected at five cattle abattoirs in Denmark during 2007–2008. The animals came from 71 randomly selected specialized veal-calf producers that delivered more than 100 animals to slaughter per year. Salmonella Dublin bacteria were isolated from 19 samples from 12 herds and Salmonella Typhimurium was isolated from one sample. The apparent prevalence of herds delivering Salmonella-shedding animals to slaughter was 18% (95% CI 9–27). The overall estimated true prevalence of shedding calves at slaughter was 1·3%. Veal-calf herds that purchased animals from herds not classified as low risk in the Danish Salmonella surveillance programme had significantly (P=0·03) higher risk of delivering Salmonella-shedding calves to slaughter. The results emphasize the importance of efforts in the dairy industry to ensure food safety for consumers.

scholarly journals Improvement of cardiovascular risk prediction by longitudinal risk factor and competing risk data

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
I Roman Degano ◽  
J Marrugat ◽  
R Elosua ◽  
I Subirana
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Risk Factor ◽  
Cardiovascular Risk ◽  
Competing Risks ◽  
Competing Risk ◽  
Cerebrovascular Events ◽  
Risk Factor Data ◽  
Coronary Events ◽  
Factor Data

Abstract Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Spanish Society of Cardiology OnBehalf REGICOR Study Background Cardiovascular risk assessment is the cornerstone of cardiovascular primary prevention. However, most of the recommended or regionally validated risk assessment tools are not updated. Purpose To analyze the effect of including longitudinal information of risk factors as well as competing risks for cardiovascular risk prediction. Methods Data from 10,152 general population individuals from North-Eastern Spain was included. Individuals were recruited in 1995-2000-2005 in three different cohorts of the REGICOR Study. Risk factor data was obtained at baseline and in 2 follow-up visits. Risk factor data included age, sex, education, lipid profile, blood pressure, glucose, smoking, body mass index, and treatment for hypercholesterolemia, hypertension and diabetes. Event data was obtained by cross linkage with healthcare and mortality databases. Cardiovascular events included myocardial infarction, angina and stroke. Cancer mortality and other mortality were included as competing risks. Four cox proportional hazards models developed to model time to coronary/cerebrovascular events with longitudinal or competing risk data. Interactions between age and risk factors were included. Discrimination was assessed with the area under the ROC curve (AUC) and Sommer’s D statistic, and compared with discrimination of Framingham-REGICOR function. Results The variable with the largest effect on coronary/cerebrovascular event incidence was diabetes treatment in the longitudinal models [Hazard ratio -HR- (95% confidence interval -CI-): 3.02 (2.00, 4.58)/2.58 (1.33, 5.00)] as well as in the competing risk models [HR (95% CI): 3.08 (2.09, 4.55)/2.77 (1.48, 5.18)]. In addition to currently used variables, medication for hypertension and diabetes, and interaction between age and diabetes medication were included in all models. Compared to the Framingham-REGICOR function, discrimination improved with the inclusion of longitudinal or competing risk data as shown in the Table. Conclusion Including longitudinal information of cardiovascular risk factors or competing risks improved discrimination of a regionally validated cardiovascular risk function. The availability of these data in healthcare databases would allow its use in primary care cardiovascular risk assessment. Discrimination analysis Models AUC (95% CI) developed models AUC (95% CI) Framingham-REGICORfunction p-value Competing risks - coronary events 0.80 (0.77-0.82) 0.74 (0.71-0.77) &lt; 0.001 Competing risks - cerebrovascular events 0.78 (0.74-0.82) 0.68 (0.63-0.72) &lt; 0.001 Longitudinal data - coronary events 0.79 (0.78-0.81) 0.76 (0.74-0.78) &lt; 0.001 Longitudinal data - cerebrovascular events 0.80 (0.78-0.83) 0.71 (0.69-0.74) &lt; 0.001

Epidemiology of Epilepsy in Nigeria

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012416
Author(s):  
Musa M. Watila ◽  
Salisu A. Balarabe ◽  
Morenikeji A. Komolafe ◽  
Stanley C. Igwe ◽  
Michael B. Fawale ◽  
...  
Keyword(s):  
Risk Factors ◽  
Family History ◽  
Perinatal Care ◽  
Significant Risk ◽  
Febrile Seizures ◽  
Pooled Prevalence ◽  
Risk Factor Data ◽  
Potential Risk Factors ◽  
Factor Data ◽  
Active Epilepsy

BackgroundWe determined the prevalence, incidence, and risk factors for epilepsy in Nigeria.MethodsWe conducted a door-to-door survey to identify cases of epilepsy in 3 regions. We estimated age-standardized prevalence adjusted for nonresponse and sensitivity and the 1-year retrospective incidence for active epilepsy. To assess potential risk factors, we conducted a case-control study by collecting sociodemographic and risk factor data. We estimated odds ratios using logistic regression analysis and corresponding population attributable fractions (PAFs).ResultsWe screened 42,427 persons (age ≥6 years), of whom 254 had confirmed active epilepsy. The pooled prevalence of active epilepsy per 1,000 was 9.8 (95% confidence interval [CI] 8.6–11.1), 17.7 (14.2–20.6) in Gwandu, 4.8 (3.4–6.6) in Afikpo, and 3.3 (2.0–5.1) in Ijebu-Jesa. The pooled incidence per 100,000 was 101.3 (95% CI 57.9–167.6), 201.2 (105.0–358.9) in Gwandu, 27.6 (3.3–128.0) in Afikpo, and 23.9 (3.2–157.0) in Ijebu-Jesa. Children's significant risk factors included febrile seizures, meningitis, poor perinatal care, open defecation, measles, and family history in first-degree relatives. In adults, head injury, poor perinatal care, febrile seizures, family history in second-degree relatives, and consanguinity were significant. Gwandu had more significant risk factors. The PAF for the important factors in children was 74.0% (71.0%–76.0%) and in adults was 79.0% (75.0%–81.0%).ConclusionThis work suggests varied epidemiologic numbers, which may be explained by differences in risk factors and population structure in the different regions. These variations should differentially determine and drive prevention and health care responses.

scholarly journals May Measurement Month 2018: an analysis of blood pressure screening results from Botswana

2020 ◽  
Vol 22 (Supplement_H) ◽  
pp. H23-H25
Author(s):  
Tiny Masupe ◽  
John Thato Tlhakanelo ◽  
Mary Banyana Tiro ◽  
Keneilwe Motlhatlhedi ◽  
Abraham Mamela ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Capital City ◽  
Shopping Malls ◽  
Measure Blood Pressure ◽  
Hypertension Awareness ◽  
Risk Factor Data ◽  
Factor Data ◽  
Study Sites ◽  
And Control

Abstract During the May Measurement Month 2018 (MMM18) campaign, we aimed to raise hypertension awareness and measure blood pressure (BP) across different communities in Botswana. Study sites included four large villages and Gaborone (capital city). Screening sites were shopping malls, train stations, churches, and workplaces. Individuals aged ≥18 years were recruited through fliers, word of mouth, and as volunteer walk-ins at the sites. Demographic and risk factor data were collected through a questionnaire prior to measuring three BP readings per participant. Weight was measured while height was usually estimated. Hypertension was defined as: systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg or taking antihypertensive medication. The mean of readings 2 and 3 was used and was estimated using multiple imputation where missing. Amongst 4599 participants whose BPs were measured, 54.5% were female, while mean age was 35.9 years. A total of 1510 (32.8%) participants were hypertensive and of those, 712 (47.1%) were aware of the hypertension. Only 35.2% of hypertensives were on antihypertensive treatment with 54.4% had controlled BP. Amongst all hypertensives, only 19.1% had controlled BP. Risk factors associated with higher BP included obesity, more than 1 unit of alcohol/week and BP measured on Sunday. Less than half (47.1%) of those identified as having hypertension during MMM18 were aware of their condition, despite the escalating prevalence of hypertension in the country. Regular BP awareness and opportunistic BP measurement campaigns like MMM are recommended to improve detection and control of hypertension and other cardiovascular risk factors.

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