Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of ...view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to - but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a
-test and a genome-wide significance level of
-value < 10
was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to - or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g.,
and
) and genes involved in macrophage recruitment and regulation of inflammations (
and
) were suggested as possible causal genes for susceptibility to - and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to - and recoverability from mastitis.
Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and ...recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable on a (0–1) scale indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 posterior mean of standard deviations (PSD) = 0.03 for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of −0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.
The aim of this study was to develop a new approach for joint genetic evaluation of mastitis and recovery. Two mastitis incidences (0.28 and 0.95) measured via somatic cell count and three between ...traits genetic correlations (0.0, 0.2, and −0.2) were simulated for daughter group sizes of 60 and 240. A transition model was applied to model transitions between healthy and disease state. The RJMC package in DMU was used to estimate (co)variances. Heritabilities were consistent with the simulated value (0.039) for susceptibility and a bit upward biased for recovery. Estimates of genetic correlations were −0.055, 0.205, and −0.192 for the simulated values of 0.0, 0.2, and −0.2, respectively. For daughter group size of 60, accuracies of sire EBV ranged from 0.56 to 0.69 for mastitis and from 0.26 to 0.48 for recovery. The study demonstrated that both traits can be modeled jointly and simulated correlations could be correctly reproduced.
Purpose: COVID-19, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is an emerging global public health problem. The disease is believed to affect older people and is ...accompanied by clinical features such as fever, shortness of breath, and coughing. Currently, there is a lack of information regarding the characteristics of COVID-19 patients in Ethiopia. Thus, this paper aims to evaluate the epidemiological and clinical features of COVID-19 patients in Tigray, Northern Ethiopia. Patients and Methods: A total of 6,637 symptomatic and asymptomatic COVID-19 patients collected from six isolation and treatment centers in Tigray between May 7 and October 28, 2020 were retrospectively analyzed. Chi-square test or Fisher's exact test was used to compare the epidemiological and clinical characteristics of COVID-19 patients as appropriate. A p-value <0.05 was considered statistically significant. Results: The mean age of the patients was 31.3 + or - 12.8. SARS-CoV-2 infects men more than women with a ratio of 1.85:1. About 16% of the patients were symptomatic, of which 13.3% (95% CI=11.3-15.4%) were admitted to intensive care units and 6.1% (95% CI=4.5-7.6%) were non-survivors. The mortality rate was increased up to 40.3% (95% CI=32.1-48.4%) among patients with severe illness. A higher proportion of deaths were observed in men (73.2%) and 55.4% were in the age group of greater than or equal to 50 years. About 4.3% (282 of 6,637) had one or more coexisting comorbidities; the most common being cardiovascular diseases (30.1%) and diabetes mellitus (23.8%). The comorbidity rate in the non-survivor group was significantly higher than in the survivor group (p-value <0.001). Conclusion: The proportion of symptomatic patients was low. Non-survival was linked with old age and the existence of comorbidities. The findings of this study can help in the design of appropriate management strategies for COVID-19 patients, such as giving due emphasis to COVID-19 patients who are old and with comorbidities. Keywords: COVID-19, comorbidity, symptomatic, mortality rate
Background: COVID-19 is one of the leading causes of morbidity and mortality and is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). A patient infected with SARS-CoV-2 is said ...to be recovered from the infection following negative test results and when signs and symptoms disappear. Different studies have shown different median recovery time of patients with COVID-19 and it varies across settings and disease status. This study aimed to assess time to recovery and its predictors among severely ill COVID-19 patients in Tigray. Methods: A total of 139 severely ill COVID-19 patients who were hospitalized between May 7, 2020 and October 28, 2020 were retrospectively analyzed. Cox proportional hazard regression model was fitted to identify the risk factors associated with the time duration to recovery from severe COVID-19 illness. Results: The median age of the patients was 35 years (IQR, 27– 60). Eighty-three (59.7%) patients recovered with a median time of 26 days (95% CI: 23– 27). The results from the multivariable analysis showed that the recovery time was lower for severely ill patients who had no underline comorbidity diseases (AHR=2.48, 95% CI: 1.18– 5.24), shortness of breath (AHR=2.08, 95% CI: 1.07– 3.98) and body weakness (AHR=2.62, 95% CI: 1.20– 5.72). Moreover, COVID-19 patients aged younger than 40 years had lower recovery time compared to patients aged 60 and above (AHR=4.09, 95% CI: 1.58– 10.61). Conclusion: The median recovery time of severely ill COVID-19 patients was long, and older age, comorbidity, shortness of breath, and body weakness were significant factors related with the time to recovery among the severely ill COVID-19 patients. Therefore, we recommended that elders and individuals with at least one comorbidity disease have to get due attention to prevent infection by the virus. Moreover, attention should be given in the treatment practice for individuals who had shortness of breath and body weakness symptoms.
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