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A point-of-care, microfluidic platform detects antibodies against three SARS-CoV-2 antigens from blood in less than an hour., Highly sensitive, specific, and point-of-care (POC) serological assays are an essential tool to manage coronavirus disease 2019 (COVID-19). Here, we report on a microfluidic POC test that can profile the antibody response against multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens—spike S1 (S1), nucleocapsid (N), and the receptor binding domain (RBD)—simultaneously from 60 μl of blood, plasma, or serum. We assessed the levels of antibodies in plasma samples from 31 individuals (with longitudinal sampling) with severe COVID-19, 41 healthy individuals, and 18 individuals with seasonal coronavirus infections. This POC assay achieved high sensitivity and specificity, tracked seroconversion, and showed good concordance with a live virus microneutralization assay. We can also detect a prognostic biomarker of severity, IP-10 (interferon-γ–induced protein 10), on the same chip. Because our test requires minimal user intervention and is read by a handheld detector, it can be globally deployed to combat COVID-19.

Objective\ud This study was to demonstrate the efficacy of an intervention model involving on-going skills enhancement of users, Biomedical Engineers and Technicians (BMETs) in enhancing the utilization of medical laboratory equipment in low resource settings.\ud \ud Methods\ud In an action research study, the condition of 202 pieces of medical equipment in seven regional blood banks in the Uganda Blood Transfusion Service (UBTS) were studied prospectively from January 2018 to December 2018. Of these, 160 pieces were included in the intervention group where users and BMETs were mentored and trained in the use and preventive maintenance for all equipment types. A second group of 42 pieces of medical equipment which were not involved in the intervention program, were assessed for comparison. Twenty-one participants were interviewed to obtain detailed information about their experiences and the impact of the training interventions.\ud \ud Results\ud The percentage of equipment in good working condition and in use in the intervention group improved from 60% to 74%, while the improvement recorded in the second group was slower (48% to 55%) over the one-year period. Equipment in the intervention group were three times more likely to be in good working condition and in use at the end of the study period with an odds ratio of 3.2 (95% CI: 1.49 to 6.83) and P value < 0.001.\ud \ud Conclusion\ud The model applied by Knowledge for Change (K4C) that involves co-learning and mentorship of users and BMETs was successful and should be implemented in other health facilities in Low- and Middle-Income Countries.

Background With many medical equipment in hospitals coming in direct contact with healthcare workers, patients, technicians, cleaners and sometimes care givers, it is important to pay close attention to their capacity in harboring potentially harmful pathogens. The goal of this study was to assess the role that medical equipment may potentially play in hospital acquired infections in four public health facilities in Uganda. Methods A cross-sectional study was conducted from December 2017 to January 2018 in four public health facilities in Uganda. Each piece of equipment from the neonatal department, imaging department or operating theatre were swabbed at three distinct points: a location in contact with the patient, a location in contact with the user, and a remote location unlikely to be contacted by either the patient or the user. The swabs were analyzed for bacterial growth using standard microbiological methods. Seventeen bacterial isolates were randomly selected and tested for susceptibility/resistance to common antibiotics. The data collected analyzed in STATA version 14. Results A total of 192 locations on 65 equipment were swabbed, with 60.4% of these locations testing positive (116/192). Nearly nine of ten equipment (57/65) tested positive for contamination in at least one location, and two out of three equipment (67.7%) tested positive in two or more locations. Of the 116 contaminated locations 52.6% were positive for Bacillus Species, 14.7% were positive for coagulase negative staphylococcus, 12.9% (15/116) were positive for E. coli, while all other bacterial species had a pooled prevalence of 19.8%. Interestingly, 55% of the remote locations were contaminated compared to 66% of the user contacted locations and 60% of the patient contacted locations. Further, 5/17 samples were resistant to at least three of the classes of antibiotics tested including penicillin, glycylcycline, tetracycline, trimethoprim sulfamethoxazole and urinary anti-infectives. Conclusion These results provides strong support for strengthening overall disinfection/sterilization practices around medical equipment use in public health facilities in Uganda. There’s also need for further research to make a direct link to the bacterial isolates identified and cases of infections recorded among patients in similar settings.