scholarly journals COVID-19 vaccine effectiveness against hospitalizations and ICU admissions in the Netherlands, April- August 2021

2021 ◽  
Author(s):  
Brechje de Gier ◽  
Marjolein Kooijman ◽  
Jeanet Kemmeren ◽  
Nicolette de Keizer ◽  
Dave Dongelmans ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Incidence Rate Ratio ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Incidence Rates ◽  
Vaccine Effectiveness ◽  
Negative Binomial Regression Model ◽  
Age Group ◽  
Icu Admission ◽  
Binomial Regression

The objective of this study was to estimate vaccine effectiveness (VE) against COVID-19 hospitalization and ICU admission, per period according to dominating SARS-CoV-2 variant (Alpha and Delta), per vaccine, and per time since vaccination. To this end, data from the national COVID-19 vaccination register was added to the national register of COVID-19 hospitalizations. For the study period 4 April- 29 August 2021, 15,571 hospitalized people with COVID-19 were included in the analysis, of whom 887 (5.7%) were fully vaccinated. Incidence rates of hospitalizations and ICU admissions per age group and vaccination status were calculated, and VE was estimated as 1-incidence rate ratio, adjusted for calendar date and age group in a negative binomial regression model. VE against hospitalization for full vaccination was 94% (95%CI 93-95%) in the Alpha period and 95% (95%CI 94-95%) in the Delta period. The VE for full vaccination against ICU admission was 93% (95%CI 87-96%) in the Alpha period and 97% (95%CI 97-98%) in the Delta period. VE was high in all age groups and did not show waning with time since vaccination up to 20 weeks after full vaccination.

scholarly journals THE US MIDLIFE MORTALITY CRISIS CONTINUES: INCREASED DEATH RATES FROM CAUSES OTHER THAN COVID-19 DURING 2020

2021 ◽  
Author(s):  
Dana A Glei
Keyword(s):  
Indirect Effect ◽  
Causes Of Death ◽  
Excess Mortality ◽  
Negative Binomial ◽  
National Level ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Age Group ◽  
External Causes

COVID-19 has prematurely ended many lives, particularly among the oldest Americans, but the pandemic has also had an indirect effect on health and non-COVID mortality among the working-age population, who have suffered the brunt of the economic consequences. This analysis quantifies the changes in mortality for selected causes of death during the COVID 19 pandemic up to December 31, 2020, and investigates whether the levels of excess mortality varied by age group. The data comprise national-level monthly death counts by age group and selected causes of death from January 1999 to December 2020 combined with annual mid-year population estimates over the same period. A negative binomial regression model was used to estimate monthly cause-specific excess mortality during 2020 controlling for the pre-pandemic mortality patterns by age, calendar year, and season. To determine whether excess mortality varied by age, we tested interactions between broad age groups and dichotomous indicators for the pre-pandemic (January-February) and the pandemic (March-December) portions of 2020. In relative terms, excess all cause mortality (including COVID-19) peaked in December at ages 25-44 (RR=1.58 relative to 2019, 95% CI=1.50-1.68). Excluding COVID-19, all of the excess mortality occurred between ages 15 and 64, peaking in July among those aged 25-44 (RR=1.45, 95% CI 1.37-1.53). We find notable excess mortality during March-December 2020 for many causes (i.e., influenza/pneumonia, other respiratory diseases, diabetes, heart disease, cerebrovascular disease, kidney disease, and external causes), but almost exclusively among young and midlife (aged 25-74) Americans. For those aged 75 and older, there was little excess mortality from causes other than COVID-19 except from Alzheimer's disease. Excess non-COVID mortality may have resulted, at least partly, from incorrectly classified COVID-19 deaths, but neither misclassification nor an atypical flu season that disproportionately affected younger people is likely to explain the increase in mortality from external causes, which was evident even during January-February 2020. Exploratory analyses suggest that drug-related mortality may be driving the early rise in external mortality. The growth in drug overdoses well before there was any hint of a pandemic suggests it is probably not solely an indirect effect of COVID-19, although the pandemic may have exacerbated the problem.

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

2022 ◽  
Author(s):  
Jing Lian Suah ◽  
Masliyana Husin ◽  
Peter Seah Keng Tok ◽  
Boon Hwa Tng ◽  
Thevesh Thevananthan ◽  
...  
Keyword(s):  
Observational Study ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Vaccine Effectiveness ◽  
Negative Binomial Regression Model ◽  
Early Group ◽  
Icu Admission ◽  
Nationally Representative ◽  
Late Group ◽  
Over Time

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.

scholarly journals The campylobacteriosis conundrum – examining the incidence of infection with Campylobacter sp. in Australia, 1998–2013

2016 ◽  
Vol 145 (4) ◽  
pp. 839-847 ◽  
Author(s):  
C. R. M. MOFFATT ◽  
K. GLASS ◽  
R. STAFFORD ◽  
C. D'ESTE ◽  
M. D. KIRK
Keyword(s):  
Incidence Rate ◽  
Negative Binomial ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Incidence Rates ◽  
Age Group ◽  
Disease Notification ◽  
Significant Public Health ◽  
Rate Ratios ◽  
Over Time

SUMMARYCampylobacter sp. are a globally significant cause of gastroenteritis. Although rates of infection in Australia are among the highest in the industrialized world, studies describing campylobacteriosis incidence in Australia are lacking. Using national disease notification data between 1998 and 2013 we examined Campylobacter infections by gender, age group, season and state and territory. Negative binomial regression was used to estimate incidence rate ratios (IRRs), including trends by age group over time, with post-estimation commands used to obtain adjusted incidence rates. The incidence rate for males was significantly higher than for females [IRR 1·20, 95% confidence interval (CI) 1·18–1·21], while a distinct seasonality was demonstrated with higher rates in both spring (IRR 1·18, 95% CI 1·16–1·20) and summer (IRR 1·17, 95% CI 1·16–1·19). Examination of trends in age-specific incidence over time showed declines in incidence in those aged <40 years combined with contemporaneous increases in older age groups, notably those aged 70–79 years (IRR 1998–2013: 1·75, 95% CI 1·63–1·88). While crude rates continue to be highest in children, our findings suggest the age structure for campylobacteriosis in Australia is changing, carrying significant public health implications for older Australians.

scholarly journals Relationship between socioeconomic status and incidence of out-of-hospital cardiac arrest is dependent on age

2020 ◽  
pp. jech-2019-213296
Author(s):  
Martin Jonsson ◽  
Petter Ljungman ◽  
Juho Härkönen ◽  
Ben Van Nieuwenhuizen ◽  
Sidsel Møller ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Cardiac Arrest ◽  
Negative Binomial ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Incidence Rates ◽  
Age Group ◽  
Cross Sectional ◽  
Neighbourhood Base ◽  
Hospital Cardiac Arrest

BackgroundThe association between socioeconomic status (SES) and incidence of out-of-hospital cardiac arrest (OHCA) is not fully understood. The aim of this study was to see if area-level socioeconomic differences, measured in terms of area-level income and education, are associated with the incidence of OHCA, and if this relationship is dependent on age.MethodsWe included OHCAs that occurred in Stockholm County between the 1st of January 2006 and the 31st of December 2017, the victims being confirmed residents (n=10 574). We linked the home address to a matching neighbourhood (base unit) via available socioeconomic and demographic information. Socioeconomic variables and incidence rates were assessed by using cross-sectional values at the end of each year. We used zero-inflated negative binomial regression to calculate incidence rate ratios (IRRs).ResultsAmong 1349 areas with complete SES information, 10 503 OHCAs occurred between 2006 and 2017. The IRR in the highest versus the lowest SES area was 0.61 (0.50–0.75) among persons in the 0–44 age group. Among patients in the 45–64 age group, the corresponding IRR was 0.55 (0.47–0.65). The highest SES areas versus the lowest showed an IRR of 0.59 (0.50–0.70) in the 65–74 age group. In the two highest age groups, no significant association was seen (75–84 age group: 0.93 (0.80–1.08); 85+ age group: 1.05 (0.84–1.23)). Similar crude patterns were seen among both men and women.ConclusionsAreas characterised by high SES showed a significantly lower incidence of OHCA. This relationship was seen up to the age of 75, after which the relationship disappeared, suggesting a levelling effect.

scholarly journals Evolving Epidemiology of Reported Giardiasis Cases in the United States, 1995–2016

2020 ◽  
Author(s):  
Cushla M Coffey ◽  
Sarah A Collier ◽  
Michelle E Gleason ◽  
Jonathan S Yoder ◽  
Martyn D Kirk ◽  
...  
Keyword(s):  
United States ◽  
Negative Binomial ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
The United States ◽  
Incidence Rates ◽  
Age Group ◽  
Case Definitions ◽  
Reporting Practices ◽  
System Data

Abstract Background Giardiasis is the most common intestinal parasitic disease of humans identified in the United States (US) and an important waterborne disease. In the United States, giardiasis has been variably reportable since 1992 and was made a nationally notifiable disease in 2002. Our objective was to describe the epidemiology of US giardiasis cases from 1995 through 2016 using National Notifiable Diseases Surveillance System data. Methods Negative binomial regression models were used to compare incidence rates by age group (0–4, 5–9, 10–19, 20–29, 30–39, 40–49, 50–64, and ≥ 65 years) during 3 time periods (1995–2001, 2002–2010, and 2011–2016). Results During 1995–2016, the average number of reported cases was 19 781 per year (range, 14 623–27 778 cases). The annual incidence of reported giardiasis in the United States decreased across all age groups. This decrease differs by age group and sex and may reflect either changes in surveillance methods (eg, changes to case definitions or reporting practices) or changes in exposure. Incidence rates in males and older age groups did not decrease to the same extent as rates in females and children. Conclusions Trends suggest that differences in exposures by sex and age group are important to the epidemiology of giardiasis. Further investigation into the risk factors of populations with higher rates of giardiasis will support prevention and control efforts.

scholarly journals Analyzing Overdispersed Antenatal Care Visits of Pregnant Women in Bangladesh: Negative Binomial Regression Model

2017 ◽  
Vol 65 (2) ◽  
pp. 133-137
Author(s):  
Nasrin Sultana ◽  
Wasimul Bari
Keyword(s):  
Antenatal Care ◽  
Regression Model ◽  
Negative Binomial ◽  
Incidence Rate Ratio ◽  
Negative Binomial Regression ◽  
Demographic Variables ◽  
Negative Binomial Regression Model ◽  
Data Set ◽  
Care Visit ◽  
Binomial Regression

The main aim of this paper is to find out the potential determinants of antenatal care visits of women in Bangladesh during their pregnancy. The data set was extracted from Bangladesh Demographic and Health Survey, 2014 and overdispersion is found to be present in the data set. To take the overdispersion into account, negative binomial regression model has been used. A number of socioeconomic and demographic variables were observed to have significant impact on the antenatal care visit. Results are explained using incidence rate ratio. Dhaka Univ. J. Sci. 65(2): 133-137, 2017 (July)

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins
Keyword(s):  
Length Of Stay ◽  
Regression Model ◽  
Random Effects ◽  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Comprehensive Approach ◽  
Negative Binomial Regression Model ◽  
Hiv Patients ◽  
Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

Evaluation of Strategies to Mitigate Culvert-Involved Crashes

2021 ◽  
pp. 036119812199207
Author(s):  
Hitesh Chawla ◽  
Megat-Usamah Megat-Johari ◽  
Peter T. Savolainen ◽  
Christopher M. Day
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Cost Effective ◽  
Negative Binomial Regression Model ◽  
Promising Alternative ◽  
Roadside Safety ◽  
Adverse Conditions ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
Binomial Regression

The objectives of this study were to assess the in-service safety performance of roadside culverts and evaluate the potential impacts of installing various safety treatments to mitigate the severity of culvert-involved crashes. Such crashes were identified using standard fields on police crash report forms, as well as through a review of pertinent keywords from the narrative section of these forms. These crashes were then linked to the nearest cross-drainage culvert, which was associated with the nearest road segment. A negative binomial regression model was then estimated to discern how the risk of culvert-involved crashes varied as a function of annual average daily traffic, speed limit, number of travel lanes, and culvert size and offset. The second stage of the analysis involved the use of the Roadside Safety Analysis Program to estimate the expected crash costs associated with various design contexts. A series of scenarios were evaluated, culminating in guidance as to the most cost-effective treatments for different combinations of roadway geometric and traffic characteristics. The results of this study provide an empirical model that can be used to predict the risk of culvert-involved crashes under various scenarios. The findings also suggest that the installation of safety grates on culvert openings provides a promising alternative for most of the cases where the culvert is located within the clear zone. In general, a guardrail is recommended when adverse conditions are present or when other treatments are not feasible at a specific location.

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