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Background Modern transportation plays a key role in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and new variants. However, little is known about the exact transmission risk of the virus on airplanes. Methods Using the itinerary and epidemiological data of coronavirus disease 2019 (COVID-19) cases and close contacts on domestic airplanes departing from Wuhan city in China before the lockdown on 23 January 2020, we estimated the upper and lower bounds of overall transmission risk of COVID-19 among travelers. Results In total, 175 index cases were identified among 5797 passengers on 177 airplanes. The upper and lower attack rates (ARs) of a seat were 0.60% (34/5622, 95% confidence interval [CI].43–.84%) and 0.33% (18/5400, 95% CI.21–.53%), respectively. In the upper- and lower-bound risk estimates, each index case infected 0.19 (SD 0.45) and 0.10 (SD 0.32) cases, respectively. The seats immediately adjacent to the index cases had an AR of 9.2% (95% CI 5.7–14.4%), with a relative risk 27.8 (95% CI 14.4–53.7) compared to other seats in the upper limit estimation. The middle seat had the highest AR (0.7%, 95% CI.4%–1.2%). The upper-bound AR increased from 0.7% (95% CI 0.5%–1.0%) to 1.2% (95% CI.4–3.3%) when the co-travel time increased from 2.0 hours to 3.3 hours. Conclusions The ARs among travelers varied by seat distance from the index case and joint travel time, but the variation was not significant between the types of aircraft. The overall risk of SARS-CoV-2 transmission during domestic travel on planes was relatively low. These findings can improve our understanding of COVID-19 spread during travel and inform response efforts in the pandemic. [ABSTRACT FROM AUTHOR]

Two new kinds of integrated superluminescent diodes (SLD) are described and discussed.

Background Identifying young individuals living with human immunodeficiency virus (HIV) who are unaware of their status is a major challenge for HIV control in China. To address this, an innovative, anonymous vending machine–based urine self-collection for HIV testing (USCT) program was implemented in 2016 in colleges across China. Methods From June 2016 to December 2019, 146 vending machines stocked with urine self-collection kits were distributed on 73 college campuses across 11 provinces of China. Urine samples were collected, delivered, and tested in an anonymous manner. We analyzed the returned rate, reactive rate (likelihood of HIV screening positive), testing effectiveness (the annual number of college students living with HIV screened by USCT or other testing methods), and the spatiotemporal relationship between USCT usage and student activity per college generated from the usage of a social networking application. Results Among the 5178 kits sold, 3109 (60%) samples were returned; of these, 2933 (94%) were eligible for testing. The HIV reactive rate was 2.3% (66 of 2933). The average effectiveness ratio among the 34 participating Beijing colleges was 0.39 (12:31) between USCT and conventional testing methods. A strong spatiotemporal correlation between USCT numbers and online student activity was observed during school semesters in Beijing. Conclusions USCT is a powerful complement to current interventions that target at-risk students and promote HIV testing. The social networking–based evaluation framework can be a guide in prioritizing at-risk target populations. [ABSTRACT FROM AUTHOR]

In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotemporal mapping purposes, is proposed in a spatiotemporal disease mapping context. The proposed BME-Kalman synthesis allows BME to use information from both parametric regression modeling and KF estimation leading to enhanced knowledge bases. The BME-Kalman synthetic approach is used to study the space-time incidence mapping of the hand, foot and mouth disease (HFMD) in Shandong province (China) during the period May 1st, 2008 to March 19th, 2009. The results showed that the BME-Kalman approach exhibited very good regressive and predictive accuracies, maintained a very good performance even during low-incidence and extremely low-incidence periods, offered an improved description of hierarchical disease characteristics compared to traditional mapping techniques, and provided a clear explanation of the spatial stratified incidence heterogeneity at unsampled locations. The BME-Kalman approach is versatile and flexible so that it can be modified and adjusted according to the needs of the application. [ABSTRACT FROM AUTHOR]

Background Train travel is a common mode of public transport across the globe; however, the risk of coronavirus disease 2019 (COVID-19) transmission among individual train passengers remains unclear. Methods We quantified the transmission risk of COVID-19 on high-speed train passengers using data from 2334 index patients and 72 093 close contacts who had co-travel times of 0–8 hours from 19 December 2019 through 6 March 2020 in China. We analyzed the spatial and temporal distribution of COVID-19 transmission among train passengers to elucidate the associations between infection, spatial distance, and co-travel time. Results The attack rate in train passengers on seats within a distance of 3 rows and 5 columns of the index patient varied from 0 to 10.3% (95% confidence interval [CI], 5.3%–19.0%), with a mean of 0.32% (95% CI,.29%–.37%). Passengers in seats on the same row (including the adjacent passengers to the index patient) as the index patient had an average attack rate of 1.5% (95% CI, 1.3%–1.8%), higher than that in other rows (0.14% [95% CI,.11%–.17%]), with a relative risk (RR) of 11.2 (95% CI, 8.6–14.6). Travelers adjacent to the index patient had the highest attack rate (3.5% [95% CI, 2.9%–4.3%]) of COVID-19 infection (RR, 18.0 [95% CI, 13.9–23.4]) among all seats. The attack rate decreased with increasing distance, but increased with increasing co-travel time. The attack rate increased on average by 0.15% (P =.005) per hour of co-travel; for passengers in adjacent seats, this increase was 1.3% (P =.008), the highest among all seats considered. Conclusions COVID-19 has a high transmission risk among train passengers, but this risk shows significant differences with co-travel time and seat location. During disease outbreaks, when traveling on public transportation in confined spaces such as trains, measures should be taken to reduce the risk of transmission, including increasing seat distance, reducing passenger density, and use of personal hygiene protection. [ABSTRACT FROM AUTHOR]

When a marine study area is large, the environmental variables often present spatially stratified non-homogeneity, violating the spatial second-order stationary assumption. The stratified non-homogeneous surface can be divided into several stationary strata with different means or variances, but still with close relationships between neighboring strata. To give the best linear-unbiased estimator for those environmental variables, an interpolated version of the mean of the surface with stratified non-homogeneity (MSN) method called point mean of the surface with stratified non-homogeneity (P-MSN) was derived. P-MSN distinguishes the spatial mean and variogram in different strata and borrows information from neighboring strata to improve the interpolation precision near the strata boundary. This paper also introduces the implementation of this method, and its performance is demonstrated in two case studies, one using ocean color remote sensing data, and the other using marine environment monitoring data. The predictions of P-MSN were compared with ordinary kriging, stratified kriging, kriging with an external drift, and empirical Bayesian kriging, the most frequently used methods that can handle some extent of spatial non-homogeneity. The results illustrated that for spatially stratified non-homogeneous environmental variables, P-MSN outperforms other methods by simultaneously improving interpolation precision and avoiding artificially abrupt changes along the strata boundaries. [ABSTRACT FROM AUTHOR]