Impact of 7-valent versus 10-valent pneumococcal conjugate vaccines on primary care consultations across various age groups in the Netherlands, 5 years after the switch: A time-series analysis

Abstract Background Seasonality in tuberculosis (TB) has been found in different parts of the world, showing a peak in spring/summer and a trough in autumn/winter. The evidence is less clear which factors drive seasonality. It was our aim to identify and evaluate seasonality in the notifications of TB in Germany, additionally investigating the possible variance of seasonality by disease site, sex and age group. Methods We conducted an integer-valued time series analysis using national surveillance data. We analysed the reported monthly numbers of started treatments between 2004 and 2014 for all notified TB cases and stratified by disease site, sex and age group. Results We detected seasonality in the extra-pulmonary TB cases (N = 11,219), with peaks in late spring/summer and troughs in fall/winter. For all TB notifications together (N = 51,090) and for pulmonary TB only (N = 39,714) we did not find a distinct seasonality. Additional stratified analyses did not reveal any clear differences between age groups, the sexes, or between active and passive case finding. Conclusion We found seasonality in extra-pulmonary TB only, indicating that seasonality of disease onset might be specific to the disease site. This could point towards differences in disease progression between the different clinical disease manifestations. Sex appears not to be an important driver of seasonality, whereas the role of age remains unclear as this could not be sufficiently investigated.

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The Impact of an Inactivated Hepatitis A Vaccine with One Dose in Brazil: A Retrospective Time-Series

Vaccines ◽

10.3390/vaccines9040407 ◽

2021 ◽

Vol 9 (4) ◽

pp. 407

Author(s):

Ana Luiza Bierrenbach ◽

Yoonyoung Choi ◽

Paula de Mendonça Batista ◽

Fernando Brandão Serra ◽

Cintia Irene Parellada ◽

...

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Hepatitis A ◽

National Level ◽

Age Groups ◽

High Rate ◽

Series Analysis ◽

Annual Reduction ◽

The Impact ◽

Vaccination Period

Background: In 2014, a recommended one-dose of inactivated hepatitis A vaccine was included in the Brazilian National Immunization Program targeting children 12–24 months. This decision addressed the low to intermediate endemicity status of hepatitis A across Brazil and the high rate of infection in children and adolescents between 5 and 19 years old. The aim of the study was to conduct a time-series analysis on hepatitis A incidence across age groups and to assess the hepatitis A distribution throughout Brazilian geographic regions. Methods: An interrupted time-series analysis was performed to assess hepatitis A incidence rates before (2010–2013) and after (2015–2018) hepatitis A vaccine program implementation. The time-series analysis was stratified by age groups while a secondary analysis examined geographic distribution of hepatitis A cases. Results: Overall incidence of hepatitis A decreased from 3.19/100.000 in the pre-vaccine period to 0.87/100.000 (p = 0.022) post-vaccine introduction. Incidence rate reduction was higher among children aged 1-4 years old, with an annual reduction of 67.6% in the post-vaccination period against a 7.7% annual reduction in the pre-vaccination period (p < 0.001). Between 2015 and 2018, the vaccination program prevented 14,468 hepatitis A cases. Conclusion: Our study highlighted the positive impact of a recommended one-dose inactivated hepatitis A vaccine for 1–4-years-old in controlling hepatitis A at national level.

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Functional time series analysis of age-specific fertility rates: visualizing the change in the age-pattern of fertility in India

International Journal of Advanced Statistics and Probability ◽

10.14419/ijasp.v4i2.6182 ◽

2016 ◽

Vol 4 (2) ◽

pp. 79

Author(s):

Mallika Deb ◽

Tapan Kumar Chakrabarty

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Rural Women ◽

Age Groups ◽

Reproductive Age ◽

Data Series ◽

Fertility Rates ◽

Registration System ◽

Series Analysis ◽

Functional Time Series

Functional Time Series Analysis (FTSA) is carried out in this article to uncover the temporal variations in the age pattern of fertility in India. Attempt is made to find whether there is any typical age pattern in the nation’s fertility across the reproductive age groups. If so, how do we characterize the role of changing age pattern of fertility across reproductive age groups in the nation’s fertility transition? We have used region-specific (rural-urban) and country level data series on Age-Specific Fertility Rates (ASFRs) available from Sample Registration System (SRS), India during 1971-2013. Findings of this study are very impressive. It is observed that the youngest age group of women in 15-19 years has contributed to the maximum decline in fertility with a substantially accelerated pace during the period of study. The major changes in fertility rates among Indian women dominated by the rural representation occur at the ages after 30. Further, the study also suggests that the future course of demographic transition in India from third phase to the fourth phase of replacement fertility would depend on the degree and pace of decline among the rural women aged below 30 years.

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Spectrum Parameter Estimation in Time Series Analysis† †Part of this work was supported by the Netherlands Organization for the Advancement of Pure Research (Z.W.O.) under Grant B62-165.

Developments in Statistics ◽

10.1016/b978-0-12-426604-9.50007-0 ◽

1983 ◽

pp. 1-96 ◽

Cited By ~ 7

Author(s):

K.O. DZHAPARIDZE ◽

A.M. YAGLOM

Keyword(s):

Time Series ◽

Parameter Estimation ◽

The Netherlands ◽

Time Series Analysis ◽

Spectrum Parameter ◽

Series Analysis ◽

Pure Research

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A Time-Series Analysis of Contextual-Level Effects on Hate Crime in The Netherlands

Social Forces ◽

10.1093/sf/soaa102 ◽

2020 ◽

Author(s):

Laura Jacobs ◽

Joost van Spanje

Keyword(s):

Time Series ◽

The Netherlands ◽

Time Series Analysis ◽

Hate Crime ◽

Hate Speech ◽

Contextual Factors ◽

Hate Crimes ◽

Party Leader ◽

Terrorist Attacks ◽

Series Analysis

Abstract Nowadays, registered hate crimes are on the rise in many Western societies. What explains temporal variation in the incidence of hate crimes? Combining insights from the grievance model and the opportunity model, we study the role of three types of contextual factors: security (terrorism), media (news about terrorism and immigration), and political factors (speech by anti-immigration actors, hate speech prosecution, and high-profile anti-immigration victories). We apply time-series analysis to our original dataset of registered hate crimes in the Netherlands, 2015–2017 (N = 7,219). Findings indicate that terrorist attacks, (both print and online) news on refugees, immigration, and terrorism boost nonviolent hate crime. Similarly, news of the hate speech prosecution of Freedom Party leader Geert Wilders increases nonviolent crime as well. Tentative evidence points to a contagion effect of speech by anti-immigration actors. With regard to violent hate crime, only terrorist attacks had an effect. This effect was modest and only found in one of our models. Hence, the grievance and the opportunities model each partially explain nonviolent hate crime, although the security and media context seem most influential. Our findings help to identify the contextual factors contributing to a climate for hate and suggest that perceived threats play a key role.

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