Impact of COVID-19 Pandemic on Antenatal Healthcare in Al-Ramadi city, Iraq

Background:Antenatal care (ANC) is a form of preventive medicine, pregnancy-specific, and general health advice effectively given in the antenatal period. ANC is conducted by healthcare personnel on pregnant women at regular intervals to protect and improve maternal and neonatal health. Objectives: The study aimed to know if the COVID-19 pandemic affects the coverage rate of ANC visits of pregnant women. Materials and methods: This is a retrospective cross-sectional study conducted at Al-Andalus Primary Healthcare Center which is located in the center of Al-Ramadi city, Iraq. We reviewed the records of all ANC first, second, and total visits of the months February, May, and October during the years 2019, 2020, and 2021. Results: The study showed the coverage rate of ANC visits was statistically significantly declined with the restrictions imposed in response to the COVID-19 pandemic. At the end of 2021, there are some elevation in the coverage rate of ANC visits.. Conclusion: The study concluded that the lockdown period in the pandemic state due to COVID-19 led to a significant decline in the coverage rate of ANC visits. © 2022, Al-Anbar Medical Journal.

COVID-19 Fake News and Misinformation Detection using Transformer Learning

As COVID-19 spreads globally and generates an unprecedented pandemic, COVID-19 fake news is born and quickly disseminated on the internet. Misinformation and disinformation of COVID-19 can distort public perception of the virus and have a serious negative influence on society. To increase vaccine coverage rates and achieve herd immunity, eliminating fake news becomes an urgent need worldwide. Our research aims at using the Transformer model to implement COVID-19 fake news detection. We use the dataset of COVID-19 fake news, extract features through the embedding method of one hot representation, and construct the transformer model to implement text classification on the binary problem. Then we analyze results through loss curve and confusion matrix and show performance parameters, including accuracy, AUC score, and F1 score. We conclude that the model can achieve an accuracy of 72% for COVID-19 fake news detection. This research provides insight for transformer learning dealing with fake news detection of COVID-19. © 2022 IEEE.

The vaccination coverage rate in under-5 children in Nasiriyah, Iraq before and during the COVID-19 pandemic.

OBJECTIVES: This study compared the vaccination coverage rate (VCR) in children under 5 years old in Nasiriyah, Iraq before and during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: This cross-sectional study was conducted in the city of Nasiriyah in southeastern Iraq, with data collected from 79 primary healthcare facilities. This study evaluated the VCR in 3 periods (2018, 2019, and 2020) using multi-level random sampling. Pertinent data were extracted from the vaccination records of 598 children for Bacillus Calmette-Guérin (BCG); pentavalent 1, 2, and 3; measles; and activated oral poliovirus vaccine 1 and 2. Missing data were completed by telephone calls to participants' parents. Logistic regression was applied to compare and estimate the odds ratios (ORs) with 95% confidence intervals (CIs) for the association between VCR and related factors. RESULTS: The data showed the greatest decline in the studied vaccines in 2020. Among the vaccines studied, BCG had the highest rate in all 3 periods (100% VCR) and measles had the lowest rate (83.7%), reaching 63.6% in 2020 (p<0.001). The highest OR among all types of vaccine were found for the pentavalent-3 vaccine among city dwellers and those born in 2020 (OR, 2.67; 95% CI, 1.39 to 5.10 and OR, 2.34; 95% CI, 1.28 to 4.28, respectively). CONCLUSIONS: The VCR for children decreased during the COVID-19 pandemic in Iraq, and new health policies are needed to increase the coverage rate. Improving the knowledge and attitudes of parents, as well as removing barriers or risk factors, can also be effective in improving the VCR.

Forest Area, CO2 Emission, and COVID-19 Case-Fatality Rate: A Worldwide Ecological Study Using Spatial Regression Analysis

Spatial analysis is essential to understand the spreading of the COVID-19 pandemic. Due to numerous factors of multi-disciplines involved, the current pandemic is yet fully known. Hence, the current study aimed to expand the knowledge on the pandemic by exploring the roles of forests and CO2 emission in the COVID-19 case-fatality rate (CFR) at the global level. Data were captured on the forest coverage rate and CO2 emission per capita from 237 countries. Meanwhile, extra demographic and socioeconomic variables were also included to adjust for potential confounding. Associations between the forest coverage rate and CO2 emission per capita and the COVID-19 CFR were assessed using spatial regression analysis, and the results were further stratified by country income levels. Although no distinct association between the COVID-19 CFR and forest coverage rate or CO2 emission per capita was found worldwide, we found that a 10% increase in forest coverage rates was associated with a 2.37‰ (95%CI: 3.12, 1.62) decrease in COVID-19 CFRs in low-income countries;and a 10% increase in CO2 emission per capita was associated with a 0.94‰ (95%CI: 1.46, 0.42) decrease in COVID-19 CFRs in low-middle-income countries. Since a strong correlation was observed between the CO2 emission per capita and GDP per capita (r = 0.89), we replaced CO2 emission with GDP and obtained similar results. Our findings suggest a higher forest coverage may be a protective factor in low-income countries, which may be related to their low urbanization levels and high forest accessibilities. On the other hand, CO2 can be a surrogate of GDP, which may be a critical factor likely to decrease the COVID-19 CFR in lower-middle-income countries. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Influenza vaccine uptake among at-risk adults (aged 16-64 years) in the UK: a retrospective database analysis.

BACKGROUND: In the UK, annual influenza vaccination is currently recommended for adults aged 16-64 years who are in a clinical at-risk group. Despite recommendations, rates of vaccine uptake in the UK have historically been low and below national and international targets. This study aims to analyse vaccine uptake among adults in clinical at-risk groups from the 2015-2016 influenza season to the present. METHODS: A retrospective analysis of influenza vaccine coverage in the UK was conducted using data extracted from publicly available sources. Clinically at-risk individuals (as defined by Public Health England), including pregnant women, aged 16-64 years, were included in this study. RESULTS: Influenza vaccination coverage rates across the UK in adults aged 16-64 years in a clinical at-risk group have been consistently low over the past 5 years, with only 48.0, 42.4, 44.1 and 52.4% of eligible patients in England, Scotland, Wales and Northern Ireland receiving their annual influenza vaccination during the 2018-2019 influenza season. Influenza vaccine coverage was lowest in patients with morbid obesity and highest in patients with diabetes in 2018-2019. Coverage rates were below current national ambitions of ≥75% in all clinical risk groups. In these clinical at-risk groups, influenza vaccine coverage decreased between 2015 and 2019, and there was considerable regional variation. CONCLUSIONS: Uptake of the influenza vaccine by adults aged 16-64 years in a clinical at-risk group was substantially below the national ambitions. As a result, many individuals in the UK remain at high risk of developing severe influenza or complications. Given that people who are vulnerable to COVID-19 are also at increased risk of complications from influenza, during the 2020-2021 season, there is a heightened need for healthcare professionals across the UK to address suboptimal vaccine uptake, particularly in at-risk patients. Healthcare professionals and policymakers should consider measures targeted at increasing access to and awareness of the clinical benefits of the influenza vaccine.

Trends and determinants of vaccination among children aged 06-59 months in Bangladesh: country representative survey from 1993 to 2014.

BACKGROUND: Vaccination has important consequences for childhood development, mortality, and inequalities in health and well-being. This research explores the trend of vaccinations coverage from 1993 to 2014 and determines the significant factors for vaccinations coverage in Bangladesh, considering geospatial, socioeconomic, and demographic characteristics. METHODS: This study uses a secondary dataset extracted from the Bangladesh Demographic and Health Survey (BDHS) from 1992 to 93 to 2014. The association between selected independent variables and vaccination coverage of children was examined through the Chi-square test. In addition, unadjusted and adjusted logistic regression approaches were applied to determine the effects of covariates on vaccination status by using the BDHS-2014 dataset. RESULTS: The results reveal that the trend of the vaccination coverage rate has gradually been increased over the study period. The coverage rate of BCG is observed maximum while the lowest for Measles vaccination among all types of vaccinations. The findings revealed that the significantly lower coverage of all vaccination had been observed in the Sylhet region. Children of higher educated mothers (OR 10.21; CI: 4.10-25.37) and father (OR 8.71; CI: 4.03-18.80), born at health facilities (OR 4.53; CI: 2.4-8.55) and whose mother has media exposure (OR 3.20; CI: 2.22-4.60) have more chance of receiving BCG vaccine. For DPT vaccination coverage, there is a significant difference from children whose mothers have primary (OR 1.7; CI: 1.35-2.15), secondary (OR 3.5; CI: 2.75-4.45), and higher (OR 9.6; CI: 5.28-17.42) educational qualification compared to children of illiterate mothers. Findings demonstrated that children born in wealthier households have a higher likelihood of being immunized against DPT, Polio, and Measles vaccination than children born in the poorest households. CONCLUSIONS: The findings reveal that to enhance and make sustainable the overall country's vaccination coverage, we should pay more attention to the mother's education, socioeconomic condition, children's age, birth order number, having media exposure, place of residence, and religion. The authors think that this finding would be helpful to accelerate the achievement target of Sustainable Development Goals (SDGs) for children's health in Bangladesh.

Relationship between Influenza Vaccination Coverage Rate and COVID-19 Outbreak: An Italian Ecological Study.

Background: The lack of specific vaccines or drugs against coronavirus disease 2019 (COVID-19) warrants studies focusing on alternative clinical approaches to reduce the spread of this pandemic disease. In this study, we investigated whether anti-influenza vaccination plays a role in minimizing the diffusion of COVID-19 in the Italian population aged 65 and over. Methods: Four COVID-19 outcomes were used: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence, hospitalizations for COVID-19 symptoms, admissions to intensive care units for reasons related to SARS-CoV-2, and deaths attributable to COVID-19. Results: At univariate analyses, the influenza vaccination coverage rates correlated negatively with all COVID-19 outcomes (Beta ranging from -134 to -0.61; all p < 0.01). At multivariable analyses, influenza vaccination coverage rates correlated independently with SARS-CoV-2 seroprevalence (Beta (95% C.I.): -130 (-198, -62); p = 0.001), hospitalizations for COVID-19 symptoms (Beta (95% C.I.): -4.16 (-6.27, -2.05); p = 0.001), admission to intensive care units for reasons related to SARS-CoV-2 (Beta (95% C.I.): -0.58 (-1.05, -0.12); p = 0.017), and number of deaths attributable to COVID-19 (Beta (95% C.I.): -3.29 (-5.66, -0.93); p = 0.010). The R2 observed in the unadjusted analysis increased from 82% to 159% for all the considered outcomes after multivariable analyses. Conclusions: In the Italian population, the coverage rate of the influenza vaccination in people aged 65 and over is associated with a reduced spread and a less severe clinical expression of COVID-19. This finding warrants ad hoc studies to investigate the role of influenza vaccination in preventing the spread of COVID-19.