Sexual transmission chains of Ebola virus (EBOV) have been verified and linked to EBOV RNA persistence in semen, post-recovery. The rate of semen persistence over time, including the average duration of persistence among Ebola virus disease (EVD) survivors, is not well known. This cohort study aimed to analyze population estimates of EBOV RNA persistence rates in semen over time, and associated risk factors in a population of survivors from Sierra Leone.
 
  In this cohort study from May 2015 to April 2017 in Sierra Leone, recruitment was conducted in 2 phases; the first enrolled 100 male participants from the Western Area District in the capital of Freetown, and the second enrolled 120 men from the Western Area District and from Lungi, Port Loko District. Mean age of participants was 31 years. The men provided semen for testing, analyzed by quantitative reverse transcription PCR (qRT-PCR) for the presence of EBOV RNA. Follow-up occurred every 2 weeks until the endpoint, defined as 2 consecutive negative qRT-results will enable planning of the magnitude of testing and targeted counseling needs over time.
 In this study we observed that EBOV RNA persistence in semen was a frequent phenomenon, with high population rates over time. This finding will inform forthcoming updated recommendations on risk reduction strategies relating to sexual transmission of EBOV. Our findings support implementation of a semen testing program as part of epidemic preparedness and response. Further, the results will enable planning of the magnitude of testing and targeted counseling needs over time.Campylobacter jejuni and Campylobacter coli are globally recognized as a major cause of bacterial foodborne gastroenteritis. A cross-sectional study was conducted from October 2015 to May 2016 in Mekelle city to isolate, identify, and estimate the prevalence of C.  https://www.selleckchem.com/products/ro-3306.html  jejuni and C. coli in raw meat samples and to determine their antibiotic susceptibility pattern. A total of 384 raw meat samples were randomly collected from bovine (n = 210), goat (n = 108), and chicken (n = 66), and isolation and identification of Campylobacter spp. were performed using standard bacteriological techniques and PCR. Antibiotic susceptibility test was performed using disc diffusion method. Of the total 384 raw meat samples, 64 (16.67%) were found positive for Campylobacter spp. The highest prevalence of Campylobacter spp. was found in chicken meat (43.93%) followed by bovine meat (11.90%) and goat meat (9.25%). The most prevalent Campylobacter spp. isolated from meat samples was C. jejuni (81.25%). The overall prevalence of Campylobacter in restaurants, butcher shops, and abattoir was 43.93%, 18.30%, and 9.30%, respectively. 96.8%, 81.25%, 75%, and 71% of the Campylobacter spp. isolates were sensitive to norfloxacin, erythromycin, chloramphenicol, and sulphamethoxazole-trimethoprim, respectively. However, 96.9%, 85.9%, and 50% of the isolates were resistant to ampicillin, amoxicillin, and streptomycin, respectively. Strains that developed multi-drug resistant were 68.7%. The result of this study revealed the occurrence of Campylobacter in bovine, goat, and chicken meats. Hence, there is a chance of acquiring infection via consumption of raw or undercooked meat. Thus, implementation of hygienic practices from a slaughterhouse to the retailers, proper handling and cooking of foods of meat are very important in preventing Campylobacter infection.The estimation of the vertical components of built-up areas from free Digital Elevation Model (DEM) global data filtered by multi-scale convolutional, morphological and textural transforms are generalized at the spatial resolution of 250 meters using linear least-squares regression techniques. Six test cases were selected Hong Kong, London, New York, San Francisco, Sao Paulo, and Toronto. Five global DEM and two DEM composites are evaluated in terms of 60 combinations of linear, morphological and textural filtering and different generalization techniques. Four generalized vertical components estimates of built-up areas are introduced the Average Gross Building Height (AGBH), the Average Net Building Height (ANBH), the Standard Deviation of Gross Building Height (SGBH), and the Standard Deviation of Net Building Height (SNBH). The study shows that the best estimation of the net GVC of built-up areas given by the ANBH and SNBH, always contains a greater error than their corresponding gross GVC estimation given s to a sampling size that is larger than the expected average horizontal size of built-up structures as detected from nadir-angle Earth Observation (EO) data, producing more reliable estimates for gross vertical components than for net vertical component of built-up areas. Second, post-production processing targeting Digital Terrain Model specifications may purposely filter out the information on the vertical component of built-up areas that are contained in the global DEMs. Under the limitations of the study presented here, these results show a potential for using global DEM sources in order to derive statistically generalized parameters describing the vertical characteristics of built-up areas, at the scale of 250x250 meters. However, estimates need to be evaluated in terms of the specific requirements of target applications such as spatial population modelling, urban morphology, climate studies and so on.
  The World Health Organization has declared that infection with SARS-CoV-2 is a pandemic. Experiences with SARS in 2003 and SARS-CoV-2 have shown that health professionals are at higher risk of contracting COVID-19. Hence, it has been recommended that aperiodic wide-scale assessment of the knowledge and preparedness of health professionals regarding the current COVID-19 pandemic is critical.
 
  This study aimed to assess the knowledge and preparedness of health professionals regarding COVID-19 among selected hospitals in Addis Ababa, Ethiopia.
 
  A facility-based cross-sectional study was conducted from the last week of March to early April, 2020. Government (n = 6) and private hospitals (n = 4) were included. The front-line participants with high exposure were proportionally recruited from their departments. The collected data from a self-administered questionnaire were entered using EpiData and analyzed in SPSS software. Both descriptive statistics and inferential statistics (chi-square tests) are presented.