Annoyance in Response to Vibrations from Railways.

Rail transport is a key stepping stone in the EU's transport policy and is pinpointed for investment and growth over the coming decades. This expanding infrastructure implies increased exposure to environmental stressors, such as noise and ground-borne vibrations. Little is known about the health impacts of exposure to these vibrations. The aim of this paper is to examine the association between annoyance from rail vibrations and the distance of residential dwelling from the railway. It reports the first results of a large epidemiological study, EpiVib, which was designed to investigate the long-term health effects of exposure to rail vibrations. The first part of this study examines a self-reported questionnaire. In total, 6894 individuals aged between 18 and 80 living within 1 km of a railway in west Sweden participated. Results presented here examine the association between distance to the railway and annoyance from vibrations and are stratified by train type. A positive association between closer distance and increased annoyance is seen. After adjustment for important modifiers, results showed that vibrations from freight trains and maintenance operations are reported to be moderately and highly annoying at distances of up to 400 m from the railway and diesel up to 300 m. Vibration from passenger and fast trains are significantly annoying up to 200 m from the track. Vibration from freight trains and maintenance operations were considered highly annoying up to 300 m from the track, diesel up to 400 m. Vibration from passenger and fast trains are not reported to be highly annoying after adjustment. Heavier, slower moving locomotives, in the form of diesel and freight trains, appear to be the source of annoyance at distances further from the railway compared to passenger and fast trains. This has implications in terms of property, transport, and infrastructure planning

Enabling countries to manage outbreaks: statistical, operational, and contextual analysis of the early warning and response system (EWARS-csd) for dengue outbreaks

IntroductionDengue is currently the fastest-spreading mosquito-borne viral illness in the world, with over half of the world's population living in areas at risk of dengue. As dengue continues to spread and become more of a health burden, it is essential to have tools that can predict when and where outbreaks might occur to better prepare vector control operations and communities' responses. One such predictive tool, the Early Warning and Response System for climate-sensitive diseases (EWARS-csd), primarily uses climatic data to alert health systems of outbreaks weeks before they occur. EWARS-csd uses the robust Distribution Lag Non-linear Model in combination with the INLA Bayesian regression framework to predict outbreaks, utilizing historical data. This study seeks to validate the tool's performance in two states of Colombia, evaluating how well the tool performed in 11 municipalities of varying dengue endemicity levels.MethodsThe validation study used retrospective data with alarm indicators (mean temperature and rain sum) and an outbreak indicator (weekly hospitalizations) from 11 municipalities spanning two states in Colombia from 2015 to 2020. Calibrations of different variables were performed to find the optimal sensitivity and positive predictive value for each municipality.ResultsThe study demonstrated that the tool produced overall reliable early outbreak alarms. The median of the most optimal calibration for each municipality was very high: sensitivity (97%), specificity (94%), positive predictive value (75%), and negative predictive value (99%; 95% CI).DiscussionThe tool worked well across all population sizes and all endemicity levels but had slightly poorer results in the highly endemic municipality at predicting non-outbreak weeks. Migration and/or socioeconomic status are factors that might impact predictive performance and should be further evaluated. Overall EWARS-csd performed very well, providing evidence that it should continue to be implemented in Colombia and other countries for outbreak prediction

A laboratory study on the effects of wind turbine noise on sleep: Results of the polysomnographic WiTNES study

Study Objectives: Assess the physiologic and self-reported effects of wind turbine noise (WTN) on sleep. Methods: Laboratory sleep study (n = 50 participants: n = 24 living close to wind turbines and n = 26 as a reference group) using polysomnography, electrocardiography, salivary cortisol, and questionnaire endpoints. Three consecutive nights (23:00-07:00): one habituation followed by a randomized quiet Control and an intervention night with synthesized 32 dB LAEq WTN. Noise in WTN nights simulated closed and ajar windows and low and high amplitude modulation depth. Results: There was a longer rapid eye movement (REM) sleep latency (+16.8 min) and lower amount of REM sleep (-11.1 min, -2.2%) in WTN nights. Other measures of objective sleep did not differ significantly between nights, including key indicators of sleep disturbance (sleep efficiency: Control 86.6%, WTN 84.2%; wakefulness after sleep onset: Control 45.2 min, WTN 52.3 min; awakenings: Control n = 11.4, WTN n = 11.5) or the cortisol awakening response. Self-reported sleep was consistently rated as worse following WTN nights, and individuals living close to wind turbines had worse self-reported sleep in both the Control and WTN nights than the reference group. Conclusions: Amplitude-modulated continuous WTN may impact on self-assessed and some aspects of physiologic sleep. Future studies are needed to generalize these findings outside of the laboratory and should include more exposure nights and further examine possible habituation or sensitization

Enhancing the value of mortality data for health systems : adding Circumstances Of Mortality CATegories (COMCATs) to deaths investigated by verbal autopsy

The authors thank the MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt) management team for their support of this project. Analyses are based on data collected by the Unit. Support for the Agincourt HDSS site comes from the School of Public Health and Faculty of Health Sciences, University of the Witwatersrand, and the Medical Research Council, South Africa, with core funding from the Wellcome Trust, UK (Grants 058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z) and contributions from the National Institute on Aging (NIA) of the NIH, William and Flora Hewlett Foundation, and Andrew W Mellon Foundation, USA. Conceptualisation of COMCAT was supported through a parent study funded by the Joint Health Systems Research Initiative from Department for International Development (DFID)/Medical Research Council (MRC)/Wellcome Trust/Economic and Social Research Council (ESRC) (MR/N005597/1 and MR/P014844/1).Peer reviewedPublisher PD

An integrated approach to processing WHO-2016 verbal autopsy data : the InterVA-5 model

Acknowledgements We are grateful for technical discussions with Dr. Erin K. Nichols. Funding There was no specific funding, other than authors’ time at their institutions, for this work. Publication costs were funded by the Health Systems Research Initiative from the Department for International Development (DFID)/ Medical Research Council (MRC)/Wellcome Trust/Economic and Social Research Council (ESRC) (MR/P014844/1). Availability of data and materials The software, demonstration material, datasets and code supporting the conclusions of this article are freely available in the GitHub repository https://github.com/peterbyass/InterVA-5Peer reviewedPublisher PD

Study protocol for WHO and UNICEF estimates of global, regional, and national preterm birth rates for 2010 to 2019.

BACKGROUND: Preterm birth is a leading cause of death among children under five years. Previous estimates indicated global preterm birth rate of 10.6% (14.8 million neonates) in 2014. We aim to update preterm birth estimates at global, regional, and national levels for the period 2010 to 2019. METHODS: Preterm birth is defined as a live birth occurring before 37 completed gestational weeks, or <259 days since a woman's last menstrual period. National administrative data sources for WHO Member States with facility birth rates of ≥80% in the most recent year for which data is available will be searched. Administrative data identified for these countries will be considered if ≥80% of UN estimated live births include gestational age information to define preterm birth. For countries without eligible administrative data, a systematic review of studies will be conducted. Research studies will be eligible if the reported outcome is derived from an observational or intervention study conducted at national or sub-national level in population- or facility-based settings. Risk of bias assessments will focus on gestational age measurement method and coverage, and inclusion of special subgroups in published estimates. Covariates for inclusion will be selected a priori based on a conceptual framework of plausible associations with preterm birth, data availability, and quality of covariate data across many countries and years. Global, regional and national preterm birth rates will be estimated using a Bayesian multilevel-mixed regression model. DISCUSSION: Accurate measurement of preterm birth is challenging in many countries given incomplete or unavailable data from national administrative sources, compounded by limited gestational age assessment during pregnancy to define preterm birth. Up-to-date modelled estimates will be an important resource to measure the global burden of preterm birth and to inform policies and programs especially in settings with a high burden of neonatal mortality. TRIAL REGISTRATION: PROSPERO registration: CRD42021237861

EWARS

Early Warning and Response System for Dengue Outbreak

Local perceptions of causes of death in rural South Africa: a comparison of perceived and verbal autopsy causes of death

Background: Understanding how lay people perceive the causes of mortality and their associated risk factors is important for public health. In resource-limited settings, where verbal autopsy (VA) is used as the most expedient method of determining cause of death, it is important to understand how pre-existing concepts of cause of death among VA-informants may influence their VA-responses and the consequential impact on cause of death assessment. This study describes the agreement between VA-derived causes of death and informant-perceived causes and associated influential factors, which also reflects lay health literacy in this setting. Method: Using 20 years of VA data (n=11,228) from the Agincourt Health and Demographic Surveillance System (HDSS) site in rural South Africa, we explored the agreement between the causes of death perceived by the VA-informants and those assigned by the automated Inter-VA tool. Kappa statistics and concordance correlation coefficients were applied to measure agreement at individual and population levels, respectively. Multivariable regression models were used to explore factors associated with recognised lay perceptions of causes of mortality. Results: Agreement between informant-perceived and VA-derived causes of death at the individual level was limited, but varied substantially by cause of death. However, agreement at the population level, comparing cause-specific mortality fractions was higher, with the notable exception of bewitchment as a cause. More recent deaths, those in adults aged 15–49 years, deaths outside the home, and those associated with external causes showed higher concordance with InterVA. Conclusion: Overall, informant perception of causes of death was limited, but depended on informant characteristics and causes of death, and to some extent involved non-biomedical constructs. Understanding discordance between perceived and recognised causes of death is important for public health planning; low community understanding of causes of death may be detrimental to public health. These findings also illustrate the importance of using rigorous and standardised VA methods rather than relying on informants’ reported causes of death

Effects of recall time on cause-of-death findings using verbal autopsy: empirical evidence from rural South Africa

Abstract Background Verbal autopsy (VA) is a widely used technique for assigning causes to non-medically certified deaths using information gathered from a close caregiver. Both operational and cultural factors may cause delays in follow-up of deaths. The resulting time lag—from death to VA interview—can influence ways in which terminal events are remembered, and thus affect cause-of-death assignment. This study investigates the impact of recall period on causes of death determined by VA. Methods A total of 10,882 deaths from the Agincourt Health and Demographic Surveillance System (HDSS) with complete VAs, including recall period, were incorporated in this study. To measure seasonal effect, cause specific mortality fractions (CSMFs) were calculated and compared by every cause for VAs undertaken within six months of death and those undertaken from six to 12 months of death. All causes were classified into eight broad categories and entered in a multiple logistic regression to explore outcome by recall period in relation to covariates. Results The majority of deaths (83 %) had VAs completed within 12 months. There was a tendency towards longer recall periods for deaths of those under one year or over 65 years of age. Only the acute respiratory, diarrhoeal and other unspecified non-communicable disease groups showed a CSMF ratio significantly different from unity at the 99 % confidence level between the two recall periods. Only neonatal deaths showed significantly different OR for recall exceeding 12 months (OR 1.69; p value = 0.004) and this increased when adjusting for background factors (OR 2.58; p value = 0.000). Conclusion A recall period of up to one year between death and VA interview did not have any consequential effects on the cause-of-death patterns derived, with the exception of neonatal causes. This is an important operational consideration given the planned widespread use of the VA approach in civil registration, HDSS sites and occasional surveys

Swedish intrauterine growth reference ranges of biometric measurements of fetal head, abdomen and femur

Ultrasonic assessment of fetal growth is an important part of obstetric care to prevent adverse pregnancy outcome. However, lack of reliable reference ranges is a major barrier for accurate interpretation of the examinations. The aim of this study was to create updated Swedish national reference ranges for intrauterine size and growth of the fetal head, abdomen and femur from gestational week 12 to 42. This prospective longitudinal multicentre study included 583 healthy pregnant women with low risk of aberrant fetal growth. Each woman was examined up to five times with ultrasound from gestational week 12+3 to 41+6. The assessed intrauterine fetal biometric measurements were biparietal diameter (outer-inner), head circumference, mean abdominal diameter, abdominal circumference and femur length. A two-level hierarchical regression model was employed to account for the individual measurements of the fetus and the number of repeated visits for measurements while accounting for the random effect of the identified parameterization of gestational age. The expected median and variance, expressed in both standard deviations and percentiles, for each individual biometric measurement was calculated.  The presented national reference ranges can be used for assessment of intrauterine size and growth of the fetal head, abdomen and femur in the second and third trimester of pregnancy