An Updated Review on Monkeypox Viral Disease: Emphasis on Genomic Diversity

Monkeypox virus has remained the most virulent poxvirus since the elimination of smallpox approximately 41 years ago, with distribution mostly in Central and West Africa. Monkeypox (Mpox) in humans is a zoonotically transferred disease that results in a smallpox-like disease. It was first diagnosed in 1970 in the Democratic Republic of the Congo (DRC), and the disease has spread over West and Central Africa. The purpose of this review was to give an up-to-date, thorough, and timely overview on the genomic diversity and evolution of a re-emerging infectious disease. The genetic profile of Mpox may also be helpful in targeting new therapeutic options based on genes, mutations, and phylogeny. Mpox has become a major threat to global health security, necessitating a quick response by virologists, veterinarians, public health professionals, doctors, and researchers to create high-efficiency diagnostic tests, vaccinations, antivirals, and other infection control techniques. The emergence of epidemics outside of Africa emphasizes the disease's global significance. Increased monitoring and identification of Mpox cases are critical tools for obtaining a better knowledge of the ever-changing epidemiology of this disease.

External validation of the parental attitude about childhood vaccination scale

Introduction

Internal validation techniques alone do not guarantee the value of a model. This study aims to investigate the external validity of the Parental Attitude toward Childhood Vaccination (PACV) scale for assessing parents' attitude toward seasonal influenza vaccination.

Methods

Using a snowball sampling approach, an anonymous online questionnaire was distributed in two languages (English and Arabic) across seven countries. To assess the internal validity of the model, the machine learning technique of "resampling methods" was used to repeatedly select various samples collected from Egypt and refit the model for each sample. The binary logistic regression model was used to identify the main determinants of parental intention to vaccinate their children against seasonal influenza. We adopted the original model developed and used its predictors to determine parents' intention to vaccinate their children in Libya, Lebanon, Syria, Iraq, Palestine, and Sudan. The area under the curve (AUC) indicated the model's ability to distinguish events from non-events. We visually compared the observed and predicted probabilities of parents' intention to vaccinate their children using a calibration plot.

Results

A total of 430 parents were recruited from Egypt to internally validate the model, and responses from 2095 parents in the other six countries were used to externally validate the model. Multivariate regression analysis showed that the PACV score, child age (adolescence), and Coronavirus disease 2019 (COVID-19) vaccination in children were significantly associated with the intention to receive the vaccination. The AUC of the developed model was 0.845. Most of the predicted points were close to the diagonal line, demonstrating better calibration (the prediction error was 16.82%). The sensitivity and specificity of the externally validated model were 89.64 and 37.89%, respectively (AUC = 0.769).

Conclusion

The PACV showed similar calibration and discrimination across the six countries. It is transportable and can be used to assess attitudes towards influenza vaccination among parents in different countries using either the Arabic or English version of the scale.

Impact of virtual continued medical education on carbon footprint and awareness of digital sobriety: A retrospective cross-sectional study among public health professionals in India

Background

Due to the COVID-19 pandemic, physical meetings and continuing medical education (CMEs) are being conducted in virtual mode. Digital sobriety has been advocated as a strategy for controlling the environmental emission from online events. The present study was undertaken to assess the impact of virtual CMEs on the environment and the participants' perception, knowledge, attitude, and practices of digital sobriety during the CMEs.

Methods

A retrospective cross-sectional Google form-based online study was conducted among the 1,311 registrants of 23 virtual CMEs hosted in India. A pre-tested English questionnaire was used to collect the data. The potential carbon footprint of the significant physical CME activities and the carbon emission (CE) of the virtual CMEs were estimated. Among the registrants contacted, 251 consented and participated in the study.

Results

The CE of the virtual CMEs was 0.787 metric tons of carbon dioxide equivalent (MT CO2 Eq). If the CMEs were conducted physically, the potential CE was estimated to be 290.094 MT CO2 Eq. The awareness rate of digital sobriety was 35%. Most of the participants (58.7%) from the current study preferred the hybrid mode of CMEs.

Conclusions

Virtual, digitally sober CMEs have reduced the potential CE by 99.7% compared to physical CMEs in India. The awareness and knowledge about digital sobriety is low in India. Knowledge, networking, social interactions, and overall satisfaction were relatively lower in the virtual mode of CMEs than in the physical mode.

Parents' expectation of antibiotic prescriptions for respiratory infections in children: a systematic review and meta-analysis

Objectives

Despite most childhood infections being self-limiting, children are among the leading consumers of antibiotics. Little is known about parental expectations of antibiotics for childhood infections. A comprehensive systematic review and meta-analysis was conducted to explore the nature and extent of parental expectations of antibiotic prescriptions for children with respiratory infections.

Design

Systematic review and meta-analysis.

Methods

An extensive literature search using six major scientific databases was conducted for all published articles until 7 December 2022. Primary studies reporting parents' expectations of antibiotics for children with upper respiratory tract infections were included after assessment for quality. Heterogeneity between the studies was assessed using the I² statistic and publication bias was analyzed using funnel plots and Egger regression tests. The primary outcome was a summary estimate of the percentage of parents who expect antibiotics from their physicians when their child presents with an upper respiratory tract infection.

Results

From a total of 4510 studies found in the initial searches, a final pool of 19 eligible studies with 15,664 individuals was included in this meta-analysis. Nine of the 19 studies were from the United States or Saudi Arabia. The pooled prevalence of parental expectations of antibiotics in the population reviewed was 55.78% (95% CI = 44.60-66.41). There was significant heterogeneity between the studies, but funnel plot and meta-regression did not detect any publication bias.

Conclusion

More than half of parents expect antibiotics for their children during consultation for upper respiratory tract infections. Such practices may cause undue side effects among children, contribute to the growing burden of antibiotic resistance, and lead to treatment failure for many common infections in the future. To optimize efforts to tackle antimicrobial resistance, shared decision-making and education emphasizing the proper and judicious use of antibiotics are much needed in pediatric healthcare settings. This can also help to manage parents' expectations when seeking antibiotics for their children. Despite pressure from parents, pediatric healthcare providers should continue to advocate for antibiotic use only when warranted and help improve knowledge and awareness amongst parents.

Registration

The protocol has been registered with PROSPERO (CRD42022364198).

The emergence of SARS-CoV-2 Omicron subvariants: current situation and future trends

The SARS-CoV-2 Omicron variant (B.1.1.529) has been the most recent variant of concern (VOC) established by the World Health Organization (WHO). Because of its greater infectivity and immune evasion, this variant quickly became the dominant type of circulating SARS-CoV-2 worldwide. Our literature review thoroughly explains the current state of Omicron emergence, particularly by comparing different omicron subvariants, including BA.2, BA.1, and BA.3. Such elaboration would be based on structural variations, mutations, clinical manifestation, transmissibility, pathogenicity, and vaccination effectiveness. The most notable difference between the three subvariants is the insufficiency of deletion (Δ69-70) in the spike protein, which results in a lower detection rate of the spike (S) gene target known as (S) gene target failure (SGTF). Furthermore, BA.2 had a stronger affinity to the human Angiotensin-converting Enzyme (hACE2) receptor than other Omicron sub-lineages. Regarding the number of mutations, BA.1.1 has the most (40), followed by BA.1, BA.3, and BA.3 with 39, 34, and 31 mutations, respectively. In addition, BA.2 and BA.3 have greater transmissibility than other sub-lineages (BA.1 and BA.1.1). These characteristics are primarily responsible for Omicron's vast geographical spread and high contagiousness rates, particularly BA.2 sub-lineages.

Effectiveness of early warning systems in the detection of infectious diseases outbreaks: a systematic review

Background

Global pandemics have occurred with increasing frequency over the past decade reflecting the sub-optimum operationalization of surveillance systems handling human health data. Despite the wide array of current surveillance methods, their effectiveness varies with multiple factors. Here, we perform a systematic review of the effectiveness of alternative infectious diseases Early Warning Systems (EWSs) with a focus on the surveillance data collection methods, and taking into consideration feasibility in different settings.

Methods

We searched PubMed and Scopus databases on 21 October 2022. Articles were included if they covered the implementation of an early warning system and evaluated infectious diseases outbreaks that had potential to become pandemics. Of 1669 studies screened, 68 were included in the final sample. We performed quality assessment using an adapted CASP Checklist.

Results

Of the 68 articles included, 42 articles found EWSs successfully functioned independently as surveillance systems for pandemic-wide infectious diseases outbreaks, and 16 studies reported EWSs to have contributing surveillance features through complementary roles. Chief complaints from emergency departments’ data is an effective EWS but it requires standardized formats across hospitals. Centralized Public Health records-based EWSs facilitate information sharing; however, they rely on clinicians’ reporting of cases. Facilitated reporting by remote health settings and rapid alarm transmission are key advantages of Web-based EWSs. Pharmaceutical sales and laboratory results did not prove solo effectiveness. The EWS design combining surveillance data from both health records and staff was very successful. Also, daily surveillance data notification was the most successful and accepted enhancement strategy especially during mass gathering events. Eventually, in Low Middle Income Countries, working to improve and enhance existing systems was more critical than implementing new Syndromic Surveillance approaches.

Conclusions

Our study was able to evaluate the effectiveness of Early Warning Systems in different contexts and resource settings based on the EWSs’ method of data collection. There is consistent evidence that EWSs compiling pre-diagnosis data are more proactive to detect outbreaks. However, the fact that Syndromic Surveillance Systems (SSS) are more proactive than diagnostic disease surveillance should not be taken as an effective clue for outbreaks detection.