Knowledge, attitudes, and practices towards seasonal influenza vaccination among pregnant women and healthcare workers: A cross-sectional survey in Afghanistan.

Background: Despite recommendation by the World Health Organization (WHO), influenza vaccination coverage among high-risk groups remains suboptimal in Afghanistan. This study aims to document the knowledge, attitudes, and practices of seasonal influenza vaccine uptake among two priority groups, pregnant women (PWs) and healthcare workers (HCWs). Methods: This cross-sectional study enrolled PWs and HCWs in Kabul, Afghanistan, from September to December 2021. Data on vaccine intention and uptake, knowledge, and attitudes towards vaccination were collected. Simple linear regression was used to predict the impact of sociodemographic characteristics on the KAP score. Results: A total of 420 PWs were enrolled in Afghanistan. The majority (89%) of these women had never heard of the influenza vaccine but 76% intended to receive the vaccine. Of the 220 HCWs enrolled, 88% were unvaccinated. Accessibility and cost were factors which encouraged vaccination among HCWs. Fear of side effects and affordability were identified as key barriers. HCWs reported high level of vaccine intention (93%). PWs aged under 18 years (ß: 6.5, P = 0.004), between 18 and 24 years (ß: 2.9, P = 0.014), currently employed (ß: 5.8, P = 0.004), and vaccinated against COVID-19 (ß: 2.8, P = 0.01) were likely to have a higher attitude score. Among HCWs, being female was a predictor for poor vaccination practice (ß: -1.33, P < 0.001) whereas being vaccinated against COVID-19 was a predictor for higher practice score (ß: 2.4, P < 0.001). Conclusion: To increase influenza vaccination coverage among priority groups, efforts should be made to address issues such as lack of knowledge, limited availability, and cost barriers.

A review of policies and coverage of seasonal influenza vaccination programs in the WHO Eastern Mediterranean Region.

Background: Although there has been an effective seasonal influenza vaccine available for more than 60 years, influenza continues to circulate and cause illness. The Eastern Mediterranean Region (EMR) is very diverse in health systems capacities, capabilities, and efficiencies, which affect the performance of services, especially vaccination, including seasonal influenza vaccination. Aims: The aim of this study is to provide a comprehensive overview on country-specific influenza vaccination policies, vaccine delivery, and coverage in EMR. Materials and Methods: We have analyzed data from a regional seasonal influenza survey conducted in 2022, Joint Reporting Form (JRF), and verified their validity by the focal points. We also compared our results with those of the regional seasonal influenza survey conducted in 2016. Results: Fourteen countries (64%) had reported having a national seasonal influenza vaccine policy. About (44%) countries recommended influenza vaccine for all SAGE recommended target groups. Up to 69% of countries reported that COVID-19 had an impact on influenza vaccine supply in the country, with most of them (82%) reporting increases in procurement due to COVID-19. Discussion: The situation of seasonal influenza vaccination in EMR is varied, with some countries having well established programs while others having no policy or program; these variances may be due to resources inequity, political, and socioeconomic dissimilarities. Few countries have reported wide vaccination coverage over time with no clear trend of improvement. Conclusion: We suggest supporting countries to develop a roadmap for influenza vaccine uptake and utilization, assessment of barriers, and burden of influenza, including measuring the economic burden to enhance vaccine acceptance.

COVID-19 Vaccination and Mental Stress within Diverse Sociodemographic Groups.

In this study, we surveyed 635 participants to determine: (a) major causes of mental stress during the pandemic and its future impacts, and (b) diversity in public perception of the COVID-19 vaccination and its acceptance (specifically for children). Statistical results and intelligent clustering outcomes indicate significant associations between sociodemographic diversity, mental stress causes, and vaccination perception. For instance, statistical results indicate significant dependence between gender (we will use term 'sex' in the rest of the manuscript) and mental stress due to COVID-19 infection (p = 1.7 × 10-5). Over 25% of males indicated work-related stress compared to 35% in females, however, females indicated that they were more stressed (17%) due to relationships compared to males (12%). Around 30% of Asian/Arabic participants do not feel that the vaccination is safe as compared to 8% of white British and 22% of white Europeans, indicating significant dependence (p = 1.8 × 10-8) with ethnicity. More specifically, vaccination acceptance for children is significantly dependent with ethnicity (p = 3.7 × 10-5) where only 47% participants show willingness towards children's vaccination. The primary dataset in this study along with experimental outcomes identifying sociodemographic information diversity with respect to public perception and acceptance of vaccination in children and potential stress factors might be useful for the public and policymakers to help them be better prepared for future epidemics, as well as working globally to combat mental health issues.

Development of a road map to scale up the uptake and utilization of influenza vaccine in 22 countries of Eastern Mediterranean Region.

BACKGROUND: The aim of this project was to develop a road map to support countries in Eastern Mediterranean Region in developing and implementing evidence-based seasonal influenza vaccination policy, strengthen influenza vaccination delivery program and address vaccine misperceptions and hesitancy. METHODS: The road map was developed through consultative meetings with countries' focal points, review of relevant literature and policy documents and analysis of WHO/UNICEF Joint Reporting Form on immunization ((JRF 2015-2020) data. Countries were categorised into three groups, based on the existence of influenza vaccination policy and national regulatory authority, availability of influenza vaccine in the country and number of influenza vaccine doses distributed/ 1000 population. The final road map was shared with representatives of all countries in Eastern Mediterranean Region and other stakeholders during a meeting in September 2021. RESULT: The goal for next 5 years is to increase access to and use of utilization of seasonal influenza vaccine in Eastern Mediterranean Region to reduce influenza-associated morbidity and mortality among priority groups for vaccination. Countries in the Eastern Mediterranean Region are at different stages of implementation of the influenza vaccination program, so activities are planned under four strategic priority areas based on current situations in countries. The consultative body recommended that some countries should establish a new seasonal influenza vaccination programme and ensure the availability of vaccines, while other countries need to reduce vaccine hesitancy and enhance current seasonal influenza vaccination coverage, particularly in all high-risk groups. Countries are also encouraged to leverage COVID-19 adult vaccination programs to improve seasonal influenza vaccine uptake. CONCLUSION: This road map was developed through a consultative process to scale up the uptake and utilization of influenza vaccine in all countries of Eastern Mediterranean Region. The road map proposes activities that should be adopted in the local context to develop/ update national policies and programs.

Usefulness of Vaccine Adverse Event Reporting System for Machine-Learning Based Vaccine Research: A Case Study for COVID-19 Vaccines.

Usefulness of Vaccine-Adverse Event-Reporting System (VAERS) data and protocols required for statistical analyses were pinpointed with a set of recommendations for the application of machine learning modeling or exploratory analyses on VAERS data with a case study of COVID-19 vaccines (Pfizer-BioNTech, Moderna, Janssen). A total of 262,454 duplicate reports (29%) from 905,976 reports were identified, which were merged into a total of 643,522 distinct reports. A customized online survey was also conducted providing 211 reports. A total of 20 highest reported adverse events were first identified. Differences in results after applying various machine learning algorithms (association rule mining, self-organizing maps, hierarchical clustering, bipartite graphs) on VAERS data were noticed. Moderna reports showed injection-site-related AEs of higher frequencies by 15.2%, consistent with the online survey (12% higher reporting rate for pain in the muscle for Moderna compared to Pfizer-BioNTech). AEs {headache, pyrexia, fatigue, chills, pain, dizziness} constituted >50% of the total reports. Chest pain in male children reports was 295% higher than in female children reports. Penicillin and sulfa were of the highest frequencies (22%, and 19%, respectively). Analysis of uncleaned VAERS data demonstrated major differences from the above (7% variations). Spelling/grammatical mistakes in allergies were discovered (e.g., ~14% reports with incorrect spellings for penicillin).

Influenza activity in the Eastern Mediterranean Region (EMR) in 2020-2021 amidst the COVID-19 pandemic.

INTRODUCTION: A global reduction in influenza virus activity during the COVID-19 pandemic has been observed, including in the Eastern Mediterranean Region (EMR). However, these changes have not been thoroughly evaluated scientifically in the EMR. OBJECTIVE: We aim to present data on seasonal influenza activity during the pre-pandemic period (2016-2019) and compare it to the pandemic period (2020-2021) in EM countries. METHODS: Epidemiological and virological influenza surveillance data were retrieved from both WHO FluNet and EMFLU networks. Four pre-pandemic analytical periods were used in the comparative analysis. We compiled and calculated weekly aggregated epidemiological data on the number of enrolled patients, number of tested specimens and number of positive influenza specimens. RESULTS: 19 out of the 22 countries of the EMR have functioning sentinel influenza surveillance systems, and these countries report the influenza data to WHO through FluNet and EMFLU. The number of enrolled patients and tested specimens increased gradually from 51 384 and 50 672, respectively, in 2016-2017 analytical period to 194 049 enrolled patients and 124 697 tested specimens in 2019-2020. A decrease has been witnessed in both enrolled patients and tested specimens in 2020-2021 'pandemic period' (166 576 and 44 764, respectively). By comparing influenza activity of analytical period 2020-2021 with that of 2016-2019 analytical periods, we found that there has been a decrease in influenza positivity rate in the EMR by 89%. CONCLUSION: The implementation of non-pharmaceutical interventions to control the COVID-19 pandemic may have also impacted the spread of influenza viruses. The low circulation of influenza viruses during 2020-2021 and the associated potential immunity gap may result in increased transmission and severity of post-pandemic influenza seasons. This necessitates high vigilance to continuous data and virus sharing to monitor circulating viruses in a timely fashion to reduce the intensity and severity of future influenza epidemics.

Transmission of SARS-CoV-2 in standardised first few X cases and household transmission investigations: A systematic review and meta-analysis.

We aimed to estimate the household secondary infection attack rate (hSAR) of SARS-CoV-2 in investigations aligned with the WHO Unity Studies Household Transmission Investigations (HHTI) protocol. We conducted a systematic review and meta-analysis according to PRISMA 2020 guidelines. We searched Medline, Embase, Web of Science, Scopus and medRxiv/bioRxiv for "Unity-aligned" First Few X cases (FFX) and HHTIs published 1 December 2019 to 26 July 2021. Standardised early results were shared by WHO Unity Studies collaborators (to 1 October 2021). We used a bespoke tool to assess investigation methodological quality. Values for hSAR and 95% confidence intervals (CIs) were extracted or calculated from crude data. Heterogeneity was assessed by visually inspecting overlap of CIs on forest plots and quantified in meta-analyses. Of 9988 records retrieved, 80 articles (64 from databases; 16 provided by Unity Studies collaborators) were retained in the systematic review; 62 were included in the primary meta-analysis. hSAR point estimates ranged from 2% to 90% (95% prediction interval: 3%-71%; I 2 = 99.7%); I 2 values remained >99% in subgroup analyses, indicating high, unexplained heterogeneity and leading to a decision not to report pooled hSAR estimates. FFX and HHTI remain critical epidemiological tools for early and ongoing characterisation of novel infectious pathogens. The large, unexplained variance in hSAR estimates emphasises the need to further support standardisation in planning, conduct and analysis, and for clear and comprehensive reporting of FFX and HHTIs in time and place, to guide evidence-based pandemic preparedness and response efforts for SARS-CoV-2, influenza and future novel respiratory viruses.

A death, infection, and recovery (DIR) model to forecast the COVID-19 spread.

BACKGROUND: The SARS-Cov-2 virus (commonly known as COVID-19) has resulted in substantial casualties in many countries. The first case of COVID-19 was reported in China towards the end of 2019. Cases started to appear in several other countries (including Pakistan) by February 2020. To analyze the spreading pattern of the disease, several researchers used the Susceptible-Infectious-Recovered (SIR) model. However, the classical SIR model cannot predict the death rate. OBJECTIVE: In this article, we present a Death-Infection-Recovery (DIR) model to forecast the virus spread over a window of one (minimum) to fourteen (maximum) days. Our model captures the dynamic behavior of the virus and can assist authorities in making decisions on non-pharmaceutical interventions (NPI), like travel restrictions, lockdowns, etc. METHOD: The size of training dataset used was 134 days. The Auto Regressive Integrated Moving Average (ARIMA) model was implemented using XLSTAT (add-in for Microsoft Excel), whereas the SIR and the proposed DIR model was implemented using python programming language. We compared the performance of DIR model with the SIR model and the ARIMA model by computing the Percentage Error and Mean Absolute Percentage Error (MAPE). RESULTS: Experimental results demonstrate that the maximum% error in predicting the number of deaths, infections, and recoveries for a period of fourteen days using the DIR model is only 2.33%, using ARIMA model is 10.03% and using SIR model is 53.07%. CONCLUSION: This percentage of error obtained in forecasting using DIR model is significantly less than the% error of the compared models. Moreover, the MAPE of the DIR model is sufficiently below the two compared models that indicates its effectiveness.

Fuzzy Logical Algebra and Study of the Effectiveness of Medications for COVID-19

A fuzzy logical algebra has diverse applications in various domains such as engineering, economics, environment, medicine, and so on. However, the existing techniques in algebra do not apply to delta-algebra. Therefore, the purpose of this paper was to investigate new types of cubic soft algebras and study their applications, the representation of cubic soft sets with δ-algebras, and new types of cubic soft algebras, such as cubic soft δ-subalgebra based on the parameter λ (λ-CSδ-SA) and cubic soft δ-subalgebra (CSδ-SA) over η. This study explains why the P-union is not really a soft cubic δ-subalgebra of two soft cubic δ-subalgebras. We also reveal that any R/P-cubic soft subsets of (CSδ-SA) is not necessarily (CSδ-SA). Furthermore, we present the required conditions to prove that the R-union of two members is (CSδ-SA) if each one of them is (CSδ-SA). To illustrate our assumptions, the proposed (CSδ-SA) is applied to study the effectiveness of medications for COVID-19 using the python program.

COVID-19 pandemic: a unique opportunity to 'build back fairer' and reduce health inequities in the Eastern Mediterranean Region.

Evidence has shown that some of the major causes of health inequities arise from the conditions in which people are born, grow, live, work and age, in addition to a wider set of forces and systems shaping individuals' and societies' health and well-being. Such conditions are known as the 'social determinants of health'. However, efforts to address these determinants have remained challenging and unsatisfactory in many parts of the world, including in the Eastern Mediterranean Region. Policies to contain the ongoing COVID-19 pandemic have further exposed and amplified the existing and even created new dimensions in social and health inequities, as we elaborate further below. Meanwhile, the pandemic offers a unique opportunity to tackle inequities and build back fairer.

Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching.

Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 202012/01) such as potential symptoms and predictive tools. However, limited work has been performed towards the modelling of complex associations between the combined demographic attributes and varying nature of the COVID-19 infections across the globe. This study presents an intelligent approach to investigate the multi-dimensional associations between demographic attributes and COVID-19 global variations. We gather multiple demographic attributes and COVID-19 infection data (by 8 January 2021) from reliable sources, which are then processed by intelligent algorithms to identify the significant associations and patterns within the data. Statistical results and experts' reports indicate strong associations between COVID-19 severity levels across the globe and certain demographic attributes, e.g. female smokers, when combined together with other attributes. The outcomes will aid the understanding of the dynamics of disease spread and its progression, which in turn may support policy makers, medical specialists and society, in better understanding and effective management of the disease.