Waning COVID-19 Vaccine Effectiveness for BNT162b2 and CoronaVac in Malaysia: An Observational Study

Evaluation of vaccine effectiveness over time against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or coronavirus disease 2019 (COVID-19) is important. Evidence on effectiveness over time for the CoronaVac vaccine is lacking despite its widespread use globally. In Malaysia, a diverse set-up of COVID-19 vaccines was rolled out nationwide, and the waning of vaccine protection is a concern. We aimed to investigate and compare waning vaccine effectiveness against COVID-19 infections, COVID-19 related ICU admission and COVID-19 related deaths for BNT162b2 and CoronaVac vaccines. In this observational study, we consolidated nationally representative data on COVID-19 vaccination and patients′ outcomes. Data on all confirmed COVID-19 cases from 1 to 30 September 2021 were used to compare vaccine effectiveness between the ′early′ group (fully vaccinated in April to June 2021) and the ′late′ group (fully vaccinated in Jul to Aug 2021). We used a negative binomial regression model to estimate vaccine effectiveness against COVID-19 infections for both ′early′ and ′late′ groups, by comparing the rates of infection for individuals vaccinated in the two different periods relative to the unvaccinated. Among confirmed COVID-19 cases, we used logistic regression to estimate and compare vaccine effectiveness against ICU admission and deaths between the two different periods. For BNT162b2, vaccine effectiveness against COVID-19 infections declined from 90.8% (95% CI 89.4, 92.0) in the late group to 79.1% (95% CI 75.8, 81.9) in the late group. Vaccine effectiveness for BNT162b2 against ICU admission and deaths were comparable between the two different periods. For CoronaVac, vaccine effectiveness waned against COVID-19 infections from 74.4% in the late group (95% CI 209 70.4, 77.8) to 30.0% (95% CI 18.4, 39.9) in the early group. It also declined significantly against ICU admission, dropping from 56.1% (95% CI 51.4, 60.2) to 29.9% (95% CI 13.9, 43.0). For deaths, however, CoronaVac′s effectiveness did not wane after three to five months of full vaccination. Vaccine effectiveness against COVID-19 infections waned after three to five months of full vaccination for both BNT162b2 and CoronaVac in Malaysia. Additionally, for CoronaVac, protection against ICU admission declined as well. Evidence on vaccine effectiveness over time informs evolving policy decisions on vaccination.

Consumption of Sugar-Sweetened or Artificially Sweetened Beverages and Semen Quality in Young Men: A Cross-Sectional Study

Background: Existing literature suggests that frequent consumption of sugar-sweetened drinks may be associated with lower semen quality. Studies performed in mice suggest a dose-response relationship between intake of saccharin or aspartame, two artificial sweeteners, and sperm and testis function. Methods: A cross-sectional study based on data from The Fetal Programming of Semen Quality (FEPOS) Cohort, including 1047 young men (mean age = 19 years) was performed. Each male participant completed an online questionnaire on health, health behavior and diet, and provided a semen sample. The associations between consumption of sugar-sweetened or artificially sweetened beverages (moderate ≥ 3 days/week; infrequent < 3 days/week) and semen quality were analyzed using a multivariable, negative, binomial regression model. Results: Sugar-sweetened or artificially sweetened beverage consumption was not strongly associated with either semen volume, sperm concentration, total sperm count or total motility in young men. The proportion of morphologically normal sperm was 11% lower (0.89 (95% CI 0.76, 1.04)) for moderate (≥3 days/week) consumption of artificially sweetened beverages relative to infrequent (<3 days/week). Conclusion: Consumption of sugar-sweetened or artificially sweetened beverages, at the levels present in this study had limited effect on the measured markers of semen quality in young men.

Network Position and Crowdsourcing Innovation Contribution Behavior: The Moderating Role of Knowledge Absorption Capacity

Purpose. The purpose of this study is to examine the relationship between network position and crowdsourcing innovation contribution behavior and the moderating effects of knowledge absorption capacity on the aforementioned relationship. Design/Methodology/Approach. Focusing on the Chinese context, the study conducts empirical research with the user’s knowledge-sharing network of the MIUI community to test the research model. The negative binomial regression model which is suitable for processing discrete data is used to examine the main effects of the network position, knowledge absorption capacity, and crowdsourcing innovation contribution behavior. Findings. The findings reveal that the closer the user gets to the center of the network, the more likely they will contribute. The users’ knowledge absorption capacity can help stimulate the users’ crowdsourcing innovation contribution behavior, and the users with stronger knowledge absorption capacity are more likely to transform their network position advantages into innovative contribution behaviors. Practical Implications. The study provides evidence that network position has a positive impact on their crowdsourcing innovation contribution behavior, and knowledge absorption capacity promotes the crowdsourcing innovation behavior of users. Managers should encourage users to occupy a favorable network position and increase knowledge exchange with other users, while at the same time continuously improving their own knowledge absorption capacity. Originality/Value. This study combines social network theory and the individual mindset to introduce knowledge absorptive capacity into the relationship model of the user’s network position and crowdsourcing innovation contribution behavior, thereby constructing a complete path of “knowledge supply-knowledge acquisition-knowledge application-knowledge output.” The study contributes to provide a theoretical basis for an in-depth understanding of the influence relationship between network position and crowdsourcing innovation contribution behavior. Also, it provides a reference for enterprises to carry out practical crowdsourcing innovation community governance and improve innovation performance.

Importance of respiratory syncytial virus as a predictor of hospital length of stay in bronchiolitis

IIntroduction : Bronchiolitis is the leading cause of hospitalization in children. Estimate potentially preventable variables that impact the length of hospital stay are a priority to reduce the costs associated with this disease. This study aims to identify clinical variables associated with length of hospital stay of bronchiolitis in children in a tropical middle-income country Methods: We conducted a retrospective cohort study in 417 infants with bronchiolitis in tertiary centers in Colombia. All medical records of all patients admitted throughto the emergency department were reviewed. To identify factors independently associated we use negative binomial regression model, to estimate incidence rate ratios (IRR) and adjust for potential confounding variables Results : The median of the length of hospital stay was 3.68 days, with a range of 0.774 days to 29 days, 138 (33.117%) of patients have a hospital stay of 5 or more days. After modeling and controlling for potential confounders age <6 months, comorbidities (CHD or neurological), BPD, chest indrawing, Detection of RSV isolation, and C-reactive protein were independent predictors of LOS Conclusions : Our results show that in infants with bronchiolitis, Detection of RSV isolation, age <6 months, comorbidities (CHD or neurological), BPD, chest indrawing, and C-reactive protein were independent predictors of LOS. As a potentially modifiable risk factor, efforts to reduce the probability of RSV infection can reduce the high medical cost associates with prolonged LOS in bronchiolitis.

Managing Threats on the High Seas: The Role of Naval Bases on Reducing Maritime Piracy

Weak coastal states often lack an adequate, sustained naval presence to monitor and police their territorial waters. Unpatrolled waters, both territorial and otherwise, may provide pirates with substantial financial opportunities that go far beyond any single country. Maritime piracy costs the global economy on average USD 24 billion per year. This research explores the impact of naval bases on acts of piracy to determine if naval presence can decrease the likelihood of piracy. To examine this important economic and national security issue, our research employs a zero-inflated negative binomial regression model. We also rely upon a newly constructed time-series dataset for the years 1992–2018. Our study shows that the presence of naval bases is essential in helping maritime forces combat piracy. Policymakers searching for options to combat piracy should find the results of this study especially useful in creating prescriptive approaches that aid in solving offshore problems.

ANALISIS REGRESI COUNT DATA UNTUK PEMODELAN JUMLAH KASUS PENYAKIT TUBERKULOSIS DI KABUPATEN BANYUMAS

Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. Banyumas Regency is one of the districts with quite high Tuberculosis cases in Central Java. This study aims to analyze the factors that affect the number of tuberculosis cases in Banyumas Regency using regression analysis of count data. Poisson regression is the simplest count data regression model that has the assumption of equidispersion, that is, the mean value equal to the variance. However, in its application, these assumption is often not fulfilled, for example, there are cases of overdispersion (variance value is greater than the mean). In this study, to overcome the case of overdispersion, an approach was used using Generalized Poisson Regression (GPR) and negative binomial regression. The results showed that the data on the number of tuberculosis cases in Banyumas Regency in 2019 was overdispersion. The data modeling of the number of tuberculosis cases in Banyumas Regency with the negative binomial regression model is better than the GPR model. Meanwhile, the only predictor variable that affects the number of tuberculosis cases in Banyumas Regency is the sex ratio of productive age (15-49 years).

Testing Saudi State Capacity: A Study to Investigate How the Government Responded to the covid-19 Pandemic

This study aimed at testing Saudi state capacity in its response to the covid-19 pandemic. The model investigated the significant impact of different curfew levels (a measure of state capacity) on covid-19 cases across five main cities. We used a Negative Binomial regression model to study the association between the covid-19 cases and other independent variables that include curfew levels. Our regression results have tested Saudi state capacity in four different curfew levels, revealing that the Saudi government exhibited its ability to implement one curfew level that decreased covid-19 cases. This curfew level (four) was the most effective policy implementation of all levels that assessed state capacity but required more resources and manpower. Hence, the Saudi state has the capacity to implement its desired policies, however, it needs an increased number of resources and manpower to do that. These findings render comparative implications to gcc monarchies and other Arab countries.

Effect of complete adherence to antenatal care guideline during first visit on maternal and neonatal complications during the intrapartum and postpartum periods: a prospective cohort study in Northwest Ethiopia

ObjectivesTo examine the relationship between complete of providers’ adherence to antenatal care (ANC) guideline during first visit and maternal and neonatal complications during intrapartum and postpartum periods.DesignProspective cohort study.SettingGondar town public health facilities in Northwest, Ethiopia.ParticipantsA total of 832 pregnant women with gestational age <28 weeks who came for first ANC visit were enrolled and followed up to the first 6 hours of the postpartum periods.ExposureProviders’ adherence to ANC guideline during first visit was the exposure variable. An 18-point checklist was used to record the level of providers’ adherence. Clients who received care from providers who adhered completely to the guideline constituted the ‘exposed group’, and those who did not receive such care constituted the ‘unexposed group’.Main outcomesMaternal and neonatal complications occurred during the intrapartum and postpartum periods.Data analysisNegative binomial regression model was used to analyse the data. The adjusted incidence risk ratio (AIRR) with 95% CI was reported in the final model.ResultsA total of 782 pregnant women were followed up and included in the final analysis (254 in the exposed group and 528 non-exposed). Complete adherence to the guidelines during first visit reduced the risk of neonatal complications (AIRR 0.56; 95% CI 0.39 to 0.79). However, complete adherence to the guidelines was not found to have a statistically significant effect on maternal complications (AIRR 0.84; 95% CI 0.67 to 1.05) during the intrapartum and the postpartum periods.ConclusionsThe group that received care from providers who completely adhered to the ANC guidelines during the first antenatal visit showed significantly improved neonatal outcomes. However, it did not show a significant improvement in maternal outcomes. Hence, focusing on safe motherhood programmes like training that gears provider’s conformity to ANC guideline is quite crucial to improve neonatal outcomes.

Race/Ethnicity Moderation on the Relationship Between Neighborhood Minority Composition and Depressive Symptoms

Research showed neighborhood of residence is an important determinant of depressive symptoms. However, the complex effects of neighborhood racial/ethnic composition and individuals’ race/ethnicity on depressive symptoms were not fully explored in previous studies. This study tested whether individuals’ own race/ethnicity moderates the relationship between neighborhood racial/ethnic composition and depressive symptoms. Applying social disorganization theory, this study investigates the relationships between neighborhood racial/ethnic composition (proportion of racial and ethnic minorities), individual race/ethnicity, and depressive symptoms. This study used a merged data from Health and Retirement Study 2016 and the American Community Survey 2014-2018 (N=5,241; all age 50 or older). This study applied a mixed-effects negative binomial regression model. It has four statistical models by race/ethnicity: (a) non-Hispanic Blacks only, (b) Hispanics only, (c) non-Hispanic Whites only, and (d) combined model. Covariates were included two individual-level variables (age and gender) and three census tract-level variables (the proportions of (a) population of income below the poverty level; (b) population of unemployed; (c) population of aged 65 and over). The results showed none of the neighborhood racial/ethnic minority composition was associated with depressive symptoms for the final combined model. The moderation effects of individuals’ race/ethnicity were not significant. Not as a moderator but as the main effect, both non-Hispanic Blacks and Hispanics had higher depressive symptoms, compared to non-Hispanic Whites. Living in neighborhoods with higher poverty rates and females were also related to higher depressive symptoms. This study contributes to explore the subtle nature of depressive symptomatology and race both at individual-level and neighborhood-level.