Public discourse and sentiment during Mpox outbreak: an analysis using natural language processing.

OBJECTIVES: Mpox has been declared a Public Health Emergency of International Concern by the World Health Organization on July 23, 2022. Since early May 2022, Mpox has been continuously reported in several endemic countries with alarming death rates. This led to several discussions and deliberations on the Mpox virus among the general public through social media and platforms such as health forums. This study proposes natural language processing techniques such as topic modeling to unearth the general public's perspectives and sentiments on growing Mpox cases worldwide. STUDY DESIGN: This was a detailed qualitative study using natural language processing on the user-generated comments from social media. METHODS: A detailed analysis using topic modeling and sentiment analysis on Reddit comments (n = 289,073) that were posted between June 1 and August 5, 2022, was conducted. While the topic modeling was used to infer major themes related to the health emergency and user concerns, the sentiment analysis was conducted to see how the general public responded to different aspects of the outbreak. RESULTS: The results revealed several interesting and useful themes, such as Mpox symptoms, Mpox transmission, international travel, government interventions, and homophobia from the user-generated contents. The results further confirm that there are many stigmas and fear of the unknown nature of the Mpox virus, which is prevalent in almost all topics and themes unearthed. CONCLUSIONS: Analyzing public discourse and sentiments toward health emergencies and disease outbreaks is highly important. The insights that could be leveraged from the user-generated comments from public forums such as social media may be important for community health intervention programs and infodemiology researchers. The findings from this study effectively analyzed the public perceptions that may enable quantifying the effectiveness of measures imposed by governmental administrations. The themes unearthed may also benefit health policy researchers and decision-makers to make informed and data-driven decisions.

Ingenious Methodology to Detect Disguised Human Faces with Masks using Deep Neural Network

Face recognition is now ubiquitous as an efficient and non-invasive method to verify identity. A facial recognition system works by comparison of a digital image or video frame showing a person's face with a database storing face images. Face masks are considered a required biosafety measure during this COVID-19 pandemic. Use of masks led to various issues to emerge and impact the functioning of earlier facial recognition algorithms and that has motivated our research. The construction of a real-time face recognition system that recognizes faces with and without masks is described in this paper. ResNet10 is used to perform the feature extraction. Then, to perform face detection and recognition, it is paired with a machine learning algorithm such as SVM. Without a mask, the maximum recognition accuracy is 99.40%, while with a mask, it is 98.30%. © 2022 IEEE.

A study on histopathological changes in placentas of COVID-19 positive mothers.

IoT Based Contactless Body Temperature Measurement and Data Collection for Covid 19 (preprint)

As a part of the COVID 19 pandemic, people in public places and any premises are passing through a thermal screening procedure for safety purposes, and also each premise collecting personal information of every person coming into that premise. So, everyone has to check the body temperature before entering any premises. The person who monitors the temperature of the people need to spend more time and it also takes more effort. So, in order to avoid this time-consuming process, we have an IOT based temperature monitoring and data collection system. During thermal scan, if the temperature of the person too high i.e., above the normal temperature range the system denies the entry of that particular person. And it will instantly give a notification to the person to take the covid-19 test. If the measured temperature of the person is in the normal range, then it is fine and the entry is possible after proper sanitization. After screening the system asked for the name and phone number of the person and it is recorded using voice to text converter. In our system, we have a provision to send the data into the health care center, of the person who has a higher temperature during screening. Nowadays we know that only a limited number of persons are allotted in most of the premises, to reduce the contact of persons and thereby reducing the spread of the virus. In this system, we are providing a counter so that we can limit the number of persons entering the building. When the number of persons in the building exceeds a certain limit then the entry of a person is denied.