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.

Beyond Reassurance: The Reputational Effect of Cultural Reforms in Peace Agreements

We explore whether including cultural reforms in an intra-state peace accord facilitates its success. We distinguish between accommodationist and integrationist cultural provisions and employ a mixed research method combining negative binomial regression on a data set of all intra-state political agreements concluded between 1989 and 2017, and an in-depth analysis of the 1998 Good Friday Agreement for Northern Ireland. We recognize the important reassuring effect of accommodationist cultural reforms in separatist conflicts. However, we also find that they have an important and hitherto overlooked reputational effect across all conflict types. By enhancing the reputation of negotiating leaders, accommodationist cultural provisions contribute to ending violence by preventing leadership challenges, rebel fragmentation and remobilization across all civil conflicts. By the same logic, and despite the overwhelming emphasis of peace agreements on integrationist cultural initiatives, integrationist cultural reforms problematize leaders' ability to commit to pacts and to ensure compliance among their rank and file.

Disease-Modifying Drug Uptake and Health Service Use in the Ageing MS Population

BackgroundEvidence regarding the efficacy or effectiveness of the disease-modifying drugs (DMDs) in the older multiple sclerosis (MS) population is scarce. This has contributed to a lack of evidence-based treatment recommendations for the ageing MS population in practice guidelines. We examined the relationship between age (<55 and ≥55 years), DMD exposure and health service use in the MS population.MethodsWe conducted a population-based observational study using linked administrative health data from British Columbia, Canada. We selected all persons with MS and followed from the most recent of their first MS or demyelinating event, 18th birthday or 01-January-1996 (index date) until the earliest of emigration, death or 31-December-2017 (study end). We assessed DMD exposure status over time, initially as any versus no DMD, then by generation (first or second) and finally by each individual DMD. Age-specific analyses were conducted with all-cause hospitalizations and number of physician visits assessed using proportional means model and negative binomial regression with generalized estimating equations.ResultsWe included 19,360 persons with MS (72% were women); 10,741/19,360 (56%) had ever reached their 55th birthday. Person-years of follow-up whilst aged <55 was 132,283, and 93,594 whilst aged ≥55. Any DMD, versus no DMD in the <55-year-olds was associated with a 23% lower hazard of hospitalization (adjusted hazard ratio, aHR0.77; 95%CI 0.72-0.82), but not in the ≥55-year-olds (aHR0.95; 95%CI 0.87-1.04). Similar patterns were observed for the first and second generation DMDs. Exposure to any (versus no) DMD was not associated with rates of physician visits in either age group (<55 years: adjusted rate ratio, aRR1.02; 95%CI 1.00-1.04 and ≥55 years: aRR1.00; 95%CI 0.96-1.03), but variation in aRR was observed across the individual DMDs.ConclusionOur study showed beneficial effects of the DMDs used to treat MS on hospitalizations for those aged <55 at the time of exposure. In contrast, for individuals ≥55 years of age exposed to a DMD, the hazard of hospitalization was not significantly lowered. Our study contributes to the broader understanding of the potential benefits and risks of DMD use in the ageing MS population.

Pedestrian Safety in Compact and Mixed-Use Urban Environments: Evaluation of 5D Measures on Pedestrian Crashes

This study examined the impact of density, diversity, design, distance to transit, and destination accessibility, five measures, known as the 5Ds, that characterize the built environment, on pedestrian–vehicle crashes in Seoul, Korea. Using spatial analysis based on 500-m grid cells, this study employed negative binomial regression models on the frequencies of three specific types of pedestrian–vehicle crashes: crashes causing death, major injury, and minor injury to pedestrians. Analysis shows that compact and mixed-use urban environments represented by 5D measures have mixed effects on pedestrian safety. Trade-off effects are found between a higher risk for all types of pedestrian crashes, and a lower risk for fatal pedestrian crashes in 5D urban environments. As a design variable, a higher number of intersections is more likely to increase some types of pedestrian crashes, including fatal crashes, a finding which warrants policy attention to promote pedestrian safety near intersection areas. This study also confirms an urgent need to secure the travel safety of pedestrians near public transit stations due to the higher risk of pedestrian crashes near such facilities. Various destinations, such as retail stores, traditional markets, and hospitals, are associated with pedestrian crashes. Pedestrian safety measures should be implemented to reduce the likelihood of pedestrian crashes near major destination facilities.

Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model

Background/aims This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression. Methods Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective. Results The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression. Conclusion Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare.

Trends of limb amputation considering type, level, sex and age in Saskatchewan, Canada 2006–2019: an in-depth assessment

Background Most epidemiologic reports focus on lower extremity amputation (LEA) caused specifically by diabetes mellitus. However, narrowing scope disregards the impact of other causes and types of limb amputation (LA) diminishing the true incidence and societal burden. We explored the rates of LEA and upper extremity amputation (UEA) by level of amputation, sex and age over 14 years in Saskatchewan, Canada. Methods We calculated the differential impact of amputation type (LEA or UEA) and level (major or minor) of LA using retrospective linked hospital discharge data and demographic characteristics of all LA performed in Saskatchewan and resident population between 2006 and 2019. Rates were calculated from total yearly cases per yearly Saskatchewan resident population. Joinpoint regression was employed to quantify annual percentage change (APC) and average annual percent change (AAPC). Negative binomial regression was performed to determine if LA rates differed over time based on sex and age. Results Incidence of LEA (31.86 ± 2.85 per 100,000) predominated over UEA (5.84 ± 0.49 per 100,000) over the 14-year study period. The overall LEA rate did not change over the study period (AAPC -0.5 [95% CI − 3.8 to 3.0]) but fluctuations were identified. From 2008 to 2017 LEA rates increased (APC 3.15 [95% CI 1.1 to 5.2]) countered by two statistically insignificant periods of decline (2006–2008 and 2017–2019). From 2006 to 2019 the rate of minor LEA steadily increased (AAPC 3.9 [95% CI 2.4 to 5.4]) while major LEA decreased (AAPC -0.6 [95% CI − 2.1 to 5.4]). Fluctuations in the overall LEA rate nearly corresponded with fluctuations in major LEA with one period of rising rates from 2010 to 2017 (APC 4.2 [95% CI 0.9 to 7.6]) countered by two periods of decline 2006–2010 (APC -11.14 [95% CI − 16.4 to − 5.6]) and 2017–2019 (APC -19.49 [95% CI − 33.5 to − 2.5]). Overall UEA and minor UEA rates remained stable from 2006 to 2019 with too few major UEA performed for in-depth analysis. Males were twice as likely to undergo LA than females (RR = 2.2 [95% CI 1.99–2.51]) with no change in rate over the study period. Persons aged 50–74 years and 75+ years were respectively 5.9 (RR = 5.92 [95% Cl 5.39–6.51]) and 10.6 (RR = 10.58 [95% Cl 9.26–12.08]) times more likely to undergo LA than those aged 0–49 years. LA rate increased with increasing age over the study period. Conclusion The rise in the rate of minor LEA with simultaneous decline in the rate of major LEA concomitant with the rise in age of patients experiencing LA may reflect a paradigm shift in the management of diseases that lead to LEA. Further, this shift may alter demand for orthotic versus prosthetic intervention. A more granular look into the data is warranted to determine if performing minor LA diminishes the need for major LA.

The Impact of Drug Interactions in Patients with Community-Acquired Pneumonia on Hospital Length of Stay

(1) Background: An aging society is frequently affected by multimorbidity and polypharmacy, which, in turn, leads to an increased risk for drug interaction. The aim of this study was to evaluate the influence of drug interactions on the length of stay (LOS) in hospitals. (2) Methods: This retrospective, single-centre study is based on patients treated for community-acquired pneumonia in the hospital. Negative binomial regression was used to analyse the association between drug interactions and the LOS in the hospital. (3) Results: The total cohort contained 503 patients, yet 46 inpatients (9%) that died were not included in the analyses. The mean age was 74 (±15.3) years, 35% of patients older than 65 years were found to have more than two drug interactions, and 55% had a moderate, severe, or contraindicated adverse drug reaction. The regression model revealed a significant association between the number of drug interactions (rate ratio (RR) 1.02; 95%-CI 1.01–1.04) and the severity of drug interactions (RR 1.22; 95%-CI 1.09–1.37) on the LOS for the overall cohort as well as for the subgroup of patients aged 80 years and older. (4) Conclusion: Drug interactions are an independent risk factor for prolonged hospitalisation. Standardised assessment tools to avoid drug interactions should be implemented in clinical routines.