ABSTRACT
Introduction. To successfully manage COVID-19 and to meet the target of vaccinating 22.9 million people in Ghana, the government has adopted community engagement as one of the strategies. Yet, the Volta Region continues to record the lowest rate of vaccine acceptance in Ghana. This study explored how government institutions engaged communities on COVID-19 vaccine preparedness and acceptance in two administrative municipalities in Ghana. Methods. This qualitative study employed face-to-face in-depth interviews among thirty-six respondents comprising of government officials and community leaders and ten focus group discussions among 87 people made up of men and women most of whom were natives and some migrants in two administrative municipalities in Ghana. Data were collected from June to September 2021. Audio interviews were transcribed and uploaded to Nvivo 12 to support triangulation, coding, and thematic analysis. Ethical approval was obtained from the requisite authority, and all COVID-19 restrictions were observed. Results. Government institutions focused on informing communities of vaccines and vaccination with little input from the communities. The Ghana Health Service carried out the most extensive engagement because they had more decentralized institutions. Successful engagement activities resulted in vaccine acceptance among some community members. Challenges in community engagement included insufficient logistics and myths and misconceptions about vaccines, which accounted for some community members' lack of trust in vaccines, resulting in their unwillingness to vaccinate. Government officials used innovative approaches such as comparing the safety of COVID-19 vaccines to vaccines designed for children under the age of five years to deal with misinformation. Conclusion. Government needs to provide more resources to institutions that are mandated to carry out engagement activities to enable them carry out their tasks. It is further recommended that government institutions should intensify community engagement in distant communities to support the country to meet the target.
ABSTRACT
Introduction: COVID-19 pandemic had a significant impact on the pediatric and neonatal surgery. The COVID-19 infection in children present either with mild symptoms or with atypical clinical features mimicking other infectious diseases. This study was conducted to assess the impact of COVID-19 pandemic and lockdown on the pediatric surgical cases admitted and managed at our Institute. Materials and Methods: Clinical characteristics and management & its outcome were noted down. Clinical characteristics included age, weight, gender, residence, nature of disease, any past history of surgery, history of contact with COVID patient, any recent COVID infection. These variables were compared with the patients managed during pre-COVID-19 era of same duration. All the babies admitted for routine and some emergency cases where tested for COVID-19 using RT-PCR method. COVID tests were done post-operatively in emergency cases. Results: During the study 630 patients were admitted and managed in our department, which included 200 elective, 150 semi emergencies, and 280 emergency cases. The average age was 19.53 ± 23 months. The study included 190 surgical neonates also. There were 400 male and 230 female patients. A total of 20 patients were tested positive during the study period. Among these 20 patients, 12 were tested positive on preoperative screening, while as eight cases were positive on post-operative COVID testing. Operation theatre days were reduced from 6 days to 4 days per week. The several measures undertaken in the outpatient clinic, operation theatre, pre and post-operative period to minimize the spread of COVID-19 virus from child to caregiver and surgical staff were highly effective. During these 9 months five doctors in our department got infected, with mild to moderate symptoms of COVID 19. They resumed their duties after an average of 2 to 3 weeks. Our academic activities got significantly hampered, although bedside teaching and case discussions continued in wards and operation theatres. Conclusion: COVID -19 pandemic effects pediatric population also, surgeries and the concern for its transmission. We continue to perform routine neonatal and pediatric surgical cases, while adapting the standard safety protocols. We believe that health professionals who use the appropriate personal protective equipment may continue to work in outpatient and operating rooms.
ABSTRACT
The global threat of the COVID-19 pandemic has exceeded the limits of logic, province, concept, and spirituality. The COVID-19 has, along with its high rate of infection and mortality, induced the psychosocial effect of mass hysteria, economic burden and financial losses in universal terms. It has not only taken the lives of millions of people but has tipped billions into poverty by taking away their livelihoods. Fortunately, the time of this pandemic collided with the Internet of Things (IoT) revolution. By having the ability to blend the aspects of technology, economy and people's requirements together, IoT can help in cushioning the drastic impact of Covid-19 on peoples' psyche. This paper has been written to identify this impact. It also proposes an IoT based solution to stabilize the patients suffering from covid-19-induced post-traumatic stress disorder (PTSD) and anxiety. © 2021 IEEE.
ABSTRACT
Identification of spatial outlier is essential in revealing hidden useful knowledge in different fields of statistical applications for big data. The Score Statistic (SCi) has been used as a diagnostic tool for the identification of spatial outliers in big data. Nonetheless, the SCi method suffers from masking and swamping effects. In order to reduce the swamping effect, we propose two methods denoted as tMDR and tEW. The tMDR and tEW methods adopt location adjacency to construct spatial weights, namely metric distance reciprocal (MDR) weight and exponential weight (EW), respectively, to detect outliers in spatial autoregressiveregressive model (SAR), spatial autoregressive error model (SEM) and general spatial autoregressive-regressive model (GSM). Difference between spatial residuals are calibrated to incorporate adjacency effect into spatial outlier residual. The results of the simulation study and real example show that the performances of the three methods are equally good for SAR model. The tMDR and tEW are comparable and both outperform the SCi for SEM and GSM models with less swamping effects and less computational running times.