Background Health care workers at the frontline are facing a substantial risk of infection during the coronavirus disease 2019 (COVID-19) outbreak. Methods We acquired information and data on the general information, infection and death status of health care workers in Wuhan during the COVID-19 outbreak and completed statistical analyses. Results We have obtained the data on 2,457 infected cases among health care workers in Wuhan, China. More than half of the infected individuals were nurses (52.06%), while 33.62% of infected cases were doctors and 14.33% of cases were medical staff. In particular, the case infection rate of nurses (2.22%) was remarkably higher than that of doctors (1.92%). Most infected cases among health care workers were female (72.28%). A majority of the infected health care workers (89.26%) came from general hospitals, followed by specialized hospitals (5.70%) and community hospitals (5.05%). The case infection rate of health care workers (2.10%) was dramatically higher than that of non-health care workers (0.43%). The case fatality rate of health care workers (0.69%) was significantly lower than that of non-health care workers (5.30%). Conclusions The infection risk of HCWs is clearly higher than that of non-HCWs. HCWs play an essential role in fighting the pandemic. The analysis of the infection status of HCWs is essential to attract enough attention from the public, provide effective suggestions for government agencies and improve protective measures for HCWs.
[1] The Suomi National Polar-Orbiting Partnership (NPP) satellite was launched on 28 October 2011 and carries the Advanced Technology Microwave Sounder (ATMS) on board. ATMS is a cross-track scanning instrument observing in 22 channels at frequencies ranging from 23 to 183 GHz, permitting the measurements of the atmospheric temperature and moisture under most weather conditions. In this study, the ATMS radiometric calibration algorithm used in the operational system is first evaluated through independent analyses of prelaunch thermal vacuum data. It is found that the ATMS peak nonlinearity for all the channels is less than 0.5 K, which is well within the specification. For the characterization of the ATMS instrument sensitivity or noise equivalent differential temperatures (NEDT), both standard deviation and Allan variance of warm counts are computed and compared. It is shown that NEDT derived from the standard deviation is about three to five times larger than that from the Allan variance. The difference results from a nonstationary component in the standard deviation of warm counts. The Allan variance is better suited than the standard deviation for describing NEDT. In the ATMS sensor brightness temperature data record (SDR) processing algorithm, the antenna gain efficiencies of main beam, cross-polarization beam, and side lobes must be derived accurately from the antenna gain distribution function. However, uncertainties remain in computing the efficiencies at ATMS high frequencies. Thus, ATMS antenna brightness temperature data records (TDR) at channels 1 to 15 are converted to SDR with the actual beam efficiencies whereas those for channels 16 to 22 are only corrected for the near-field sidelobe contributions. The biases of ATMS SDR measurements to the simulations are consistent between GPS RO and NWP data and are generally less than 0.5 K for those temperature-sounding channels where both the forward model and input atmospheric profiles are reliable.
Nonisothermal austenite grain growth kinetics under the influence of several combinations of Nb, Ti, and Mo containing complex precipitates has been studied in a microalloyed linepipe steel. The goal of this study is the development of a grain growth model to predict the austenite grain size in the weld heat affected zone (HAZ). Electron microscopy investigations of the as-received steel proved the presence of Ti-rich, Nb-rich, and Mo-rich precipitates. The steel has then been subjected to austenitizing heat treatments to selected peak temperatures at various heating rates that are typical for thermal cycles in the HAZ. Thermal cycles have a strong effect on the final austenite grain size. Using a mean field approach, a model is proposed for the dissolution of Nb-rich precipitates. This model has been coupled to a Zener-type austenite grain growth model in the presence of pinning particles. This coupling leads to accurate prediction of the austenite grain size along the nonisothermal heating path simulating selected thermal profiles of the HAZ.
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