An Enhanced Cluster-Based Routing Model for Energy-Efficient Wireless Sensor Networks

Energy efficiency is a crucial consideration in wireless sensor networks since the sensor nodes are resource-constrained, and this limited resource, if not optimally utilized, may disrupt the entire network's operations. The network must ensure that the limited energy resources are used as effectively as possible to allow for longer-term operation. The study designed and simulated an improved Genetic Algorithm-Based Energy-Efficient Routing (GABEER) algorithm to combat the issue of energy depletion in wireless sensor networks. The GABEER algorithm was designed using the Free Space Path Loss Model to determine each node's location in the sensor field according to its proximity to the base station (sink) and the First-Order Radio Energy Model to measure the energy depletion of each node to obtain the residual energy. The GABEER algorithm was coded in the C++ programming language, and the wireless sensor network was simulated using Network Simulator 3 (NS-3). The outcomes of the simulation revealed that the GABEER algorithm has the capability of increasing the performance of sensor network operations with respect to lifetime and stability period

Adverse Events Related to SARS-Cov-2 Vaccination: A Systematic Review and Meta-Analysis

Background: Vaccination has been adopted as a key public health strategy for combating the COVID-19 pandemic. The accelerated SARS-CoV-2 vaccines’ development had limited time for extensive investigation of the adverse events. The study aimed to assess the average adverse events rates in published COVID-19 vaccination studies. Subjects and Method: The study used systematic review and meta-analysis involving studies that reported adverse events following administration of any of the approved COVID-19 vaccines in humans. A highly specific search strategy was developed and implemented in PubMed. The core search string was “(COVID-19 OR COVID OR "coronavirus disease") AND vaccin* AND (side-effects OR "adverse events")”. Titles and abstracts were screened, and full texts of potentially relevant articles were retrieved. Data extracted included general study background, adverse events, and frequency of occurrence. Meta-analyses were conducted for adverse events reported by at least 5 studies. Meta-analysis of proportions was carried out using logit transformation with the generalized linear mixed model estimation method. Results: A total of 108 adverse events were reported in 15 studies observing 735,515 participants from 10 countries. The highest pooled prevalence rates were pain at injection site (67.2%; 95% CI= 46.49 to 82.86; I2= 99.9%, 11 studies, 670,557 participants), weakness/fatigue (41.88%; 95% CI= 26.82 to 58.61, I2= 99.9%, 13 studies, 671,045 participants), muscle/joint pain (28.95%; 95% CI= 16.95 to 44.86, I2= 99.9%, 13 studies, 672,791 participants), and headache (27.78%; 95% CI= 17.59 to 40.95, I2= 99.9%, 14 studies, 672,883 participants). Four cases of death were reported by two papers enrolling 711 patients with cancer or multiple sclerosis, three due to comorbid disease progression, and one case due to COVID-19. Forty-three cases of anaphylaxis were reported in three studies enrolling 68,218 participants. Conclusion: The most prevalent adverse events among recipient of SARS-CoV-2 vaccines were local and general systemic reactions. Keywords: COVID-19, SARS-CoV-2 vaccine, adverse events, meta-analysis, systematic review Correspondence: Segun Bello. Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Nigeria. Email: [email protected]

Adverse Events Related to SARS-Cov-2 Vaccination: A Systematic Review and Meta-Analysis

Background: Vaccination has been adopted as a key public health strategy for combating the COVID-19 pandemic. The accelerated SARS-CoV-2 vaccines’ development had limited time for extensive investigation of the adverse events. The study aimed to assess the average adverse events rates in published COVID-19 vaccination studies. Subjects and Method: The study used systematic review and meta-analysis involving studies that reported adverse events following administration of any of the approved COVID-19 vaccines in humans. A highly specific search strategy was developed and implemented in PubMed. The core search string was “(COVID-19 OR COVID OR "coronavirus disease") AND vaccin* AND (side-effects OR "adverse events")”. Titles and abstracts were screened, and full texts of potentially relevant articles were retrieved. Data extracted included general study background, adverse events, and frequency of occurrence. Meta-analyses were conducted for adverse events reported by at least 5 studies. Meta-analysis of proportions was carried out using logit transformation with the generalized linear mixed model estimation method. Results: A total of 108 adverse events were reported in 15 studies observing 735,515 participants from 10 countries. The highest pooled prevalence rates were pain at injection site (67.2%; 95% CI= 46.49 to 82.86; I2= 99.9%, 11 studies, 670,557 participants), weakness/fatigue (41.88%; 95% CI= 26.82 to 58.61, I2= 99.9%, 13 studies, 671,045 participants), muscle/joint pain (28.95%; 95% CI= 16.95 to 44.86, I2= 99.9%, 13 studies, 672,791 participants), and headache (27.78%; 95% CI= 17.59 to 40.95, I2= 99.9%, 14 studies, 672,883 participants). Four cases of death were reported by two papers enrolling 711 patients with cancer or multiple sclerosis, three due to comorbid disease progression, and one case due to COVID-19. Forty-three cases of anaphylaxis were reported in three studies enrolling 68,218 participants. Conclusion: The most prevalent adverse events among recipient of SARS-CoV-2 vaccines were local and general systemic reactions. Keywords: COVID-19, SARS-CoV-2 vaccine, adverse events, meta-analysis, systematic review Correspondence: Segun Bello. Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Nigeria. Email: [email protected]