Life-threatening novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), also known as COVID-19, has engulfed the world and caused health and economic challenges. To control the spread of COVID-19, a mechanism is required to enforce physical distancing between people. This paper proposes a Blockchain-based framework that preserves patients' anonymity while tracing their contacts with the help of Bluetooth-enabled smartphones. We use a smartphone application to interact with the proposed blockchain framework for contact tracing of the general public using Bluetooth and to store the obtained data over the cloud, which is accessible to health departments and government agencies to perform necessary and timely actions (e.g., like quarantine the infected people moving around). Thus, the proposed framework helps people perform their regular business and day-to-day activities with a controlled mechanism that keeps them safe from infected and exposed people. The smartphone application is capable enough to check their COVID status after analyzing the symptoms quickly and observes (based on given symptoms) either this person is infected or not. As a result, the proposed Adaptive Neuro-Fuzzy Interference System (ANFIS) system predicts the COVID status, and K-Nearest Neighbor (KNN) enhances the accuracy rate to 95.9% compared to state-of-the-art results.

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A significant increase in the population in the last few decades in Pakistan has made controlling vehicular traffic an extremely challenging duty for traffic police personnel. Consequently, traffic police personnel are at risk of work-related musculoskeletal disorders (WRMSDs). Therefore, the need to determine this risk is important. This study aimed to determine the prevalence of WRMSDs among traffic police officers. It was a cross-sectional survey conducted within the premises of Rawalpindi and Islamabad. A questionnaire was distributed to 320 traffic police personnel. Active service traffic police having job experience of more than a year were included. Pregnant women and individuals with certain pathologies were excluded from the study to make the study bias-free. Data were collected using the convenient sampling technique. Nordic Musculoskeletal Questionnaire was incorporated in the survey to determine the prevalence of WRMSDs among traffic police in Rawalpindi and Islamabad, while questions related to occupation and demographic data were collected using a self-structured questionnaire. Most of the participants (70%) reported pain. This study reported low back (43%) as the most common region for pain, followed by the neck (31%), upper back (26%), shoulder(21%), knee(18%), ankle(13%), and wrist(7%). Traffic police have a high prevalence of WRMSDs. This study supports the need for ergonomic intervention at job sites and modifications in the fitness training of traffic police.

Low back pain (LBP) related disability is a big concern among the general population, especially undergraduate medical students. This study aimed to evaluate LBP-related disability in undergraduate medical students. It was a cross-sectional survey conducted within the premises of Islamabad and Rawalpindi. The data was collected using an online Oswestry LBP disability questionnaire. A sample of 300 students took part from the following colleges; Riphah University Islamabad and Margalla Institute of Health and Sciences Rawalpindi, Pakistan. There were 150 medicine students (MBBS) and 150 dental students (BDS). The disability index was calculated, and results showed that 205 students had a minimum disability, 79 had a moderate disability, 16 had a severe disability, and no participants fell into the crippled or bed-bound disability category. The results of the study demonstrate that the prevalence of mild LBP-related disability is high in undergraduate students of MBBS and BDS, which might affect the activities of daily life.

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