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BackgroundLiving kidney donation currently constitutes approximately a quarter of all kidney donations. There exist barriers that preclude prospective donors from donating, such as medical ineligibility and costs associated with donation. A better understanding of perceptions of and barriers to living donation could facilitate the development of effective policies, education opportunities, and outreach strategies and may lead to an increased number of living kidney donations. Prior research focused predominantly on perceptions and barriers among a small subset of individuals who had prior exposure to the donation process. The viewpoints of the general public have rarely been represented in prior research. ObjectiveThe current study designed a web-scraping method and machine learning algorithms for collecting and classifying comments from a variety of online sources. The resultant data set was made available in the public domain to facilitate further investigation of this topic. MethodsWe collected comments using Python-based web-scraping tools from the New York Times, YouTube, Twitter, and Reddit. We developed a set of guidelines for the creation of training data and manual classification of comments as either related to living organ donation or not. We then classified the remaining comments using deep learning. ResultsA total of 203,219 unique comments were collected from the above sources. The deep neural network model had 84% accuracy in testing data. Further validation of predictions found an actual accuracy of 63%. The final database contained 11,027 comments classified as being related to living kidney donation. ConclusionsThe current study lays the groundwork for more comprehensive analyses of perceptions, myths, and feelings about living kidney donation. Web-scraping and machine learning classifiers are effective methods to collect and examine opinions held by the general public on living kidney donation. 

Kanagawa and Hokkaido were affected by COVID-19 in the early stage of the pandemic. Japan’s initial response included contact tracing and PCR analysis on anyone who was suspected of having been exposed to SARS-CoV-2. In this retrospective study, we analyzed publicly available COVID-19 registry data from Kanagawa and Hokkaido (n = 4392). Exponential random graph model (ERGM) network analysis was performed to examine demographic and symptomological homophilies. Age, symptomatic, and asymptomatic status homophilies were seen in both prefectures. Symptom homophilies suggest that nuanced genetic differences in the virus may affect its epithelial cell type range and can result in the diversity of symptoms seen in individuals infected by SARS-CoV-2. Environmental variables such as temperature and humidity may also play a role in the overall pathogenesis of the virus. A higher level of asymptomatic transmission was observed in Kanagawa. Moreover, patients who contracted the virus through secondary or tertiary contacts were shown to be asymptomatic more frequently than those who contracted it from primary cases. Additionally, most of the transmissions stopped at the primary and secondary levels. As expected, significant viral transmission was seen in healthcare settings. 

Introduction Living-donor kidney transplantation is the gold standard treatment for patients with end-stage kidney disease. However, potential donors ubiquitously face financial as well as logistical barriers. To remove these disincentives from living kidney donations, the governments of 23 countries have implemented reimbursement programmes that shift the burdens of non-medical costs from donors to the governments or private entities. However, scientific evidence for the effectiveness of these programmes is scarce. The present study investigates whether these reimbursement programmes designed to ease the financial and logistical barriers succeeded in increasing the number of living kidney donations at the country level. The study examined within-country variations in the timing of such reimbursement programmes. Method The study applied the difference-in-difference (two-way panel fixed-effect) technique on the Poisson distribution to estimate the effects of these reimbursement programmes on a 17 year long (2000–2016) dataset covering 109 countries where living donor kidney transplants were performed. Results The results indicated that reimbursement programmes have a statistically significant positive effect. Overall, the model predicted that reimbursement programmes increased country-level donation numbers by a factor of 1.12–1.16. Conclusion Reimbursement programmes may be an effective approach to alleviate the kidney shortage worldwide. Further analysis is warranted on the type of reimbursement programmes and the ethical dimension of each type of such programmes.