Impact of short-term aircraft noise on cardiovascular disease risk in the area surrounding London Heathrow airport: the RISTANCO epidemiological study.

Background: Long-term exposure to aircraft noise has been associated with small increases in cardiovascular disease risk, but there are almost no short-term exposure studies.

Objectives: Research questions were: Is there an association between short-term changes in exposure to aircraft noise and cardiovascular morbidity and mortality? What are the key effect modifiers? Is there variability in risk estimates between areas with consistent versus changing patterns of noise exposure? Do risk estimates differ when using different noise metrics?

Design: Descriptive analyses of noise levels and variability at different times of day, analyses of inequalities in noise exposure and case-crossover analyses of cardiovascular events in relation to aircraft noise exposure.

Setting: Area surrounding London Heathrow airport.

Pesticides and risk of pancreatic adenocarcinoma in France: a nationwide spatiotemporal ecological study between 2011 and 2021.

While pancreatic adenocarcinoma (PA) incidence is increasing, especially in France, the association between pesticides and PA remains unclear. The aims of this study were to assess the spatiotemporal distribution of the incidence of PA in France between 2011 and 2021 and to determine whether pesticide exposure was associated with higher risk of PA. We employed a disease-mapping and ecological regression approach with medicoadministrative data covering 99% of the French population.

Associations between Aircraft Noise, Sleep, and Sleep-Wake Cycle: Actimetric Data from the UK Biobank Cohort near Four Major Airports.

Background: Nighttime aircraft noise may affect people's sleep, yet large-scale evidence using objective and subjective measures remains limited.

Objective: Our aim was to investigate associations between nighttime aircraft noise exposure and objectively measured sleep disturbance using a large UK cohort.

Methods: We used data from 105,770 UK Biobank cohort participants exposed and unexposed to aircraft noise who lived in 44 local authority districts near 4 international airports in England.

Effects of the El Niño-Southern Oscillation and seasonal weather conditions on Aedes aegypti infestation in the State of São Paulo (Brazil): A Bayesian spatio-temporal study.

Background: Seasonal fluctuations in weather are recognized as factors that affect both Aedes (Ae.) aegypti mosquitoes and the diseases they carry, such as dengue fever. The El Niño-Southern Oscillation (ENSO) is widely regarded as one of the most impactful atmospheric phenomena on Earth, characterized by the interplay of shifting ocean temperatures, trade wind intensity, and atmospheric pressure, resulting in extensive alterations in climate conditions.

A Bayesian Interrupted Time Series framework for evaluating policy change on mental well-being: An application to England's welfare reform.

Factors contributing to social inequalities are associated with negative mental health outcomes and disparities in mental well-being. We propose a Bayesian hierarchical controlled interrupted time series to evaluate the impact of policies on population well-being whilst accounting for spatial and temporal patterns. Using data from the UKs Household Longitudinal Study, we apply this framework to evaluate the impact of the UKs welfare reform implemented in the 2010s on the mental health of the participants, measured using the GHQ-12 index.

Integrating wastewater and randomised prevalence survey data for national COVID surveillance.

During the COVID-19 pandemic, studies in a number of countries have shown how wastewater can be used as an efficient surveillance tool to detect outbreaks at much lower cost than traditional prevalence surveys. In this study, we consider the utilisation of wastewater data in the post-pandemic setting, in which collection of health data via national randomised prevalence surveys will likely be run at a reduced scale; hence an affordable ongoing surveillance system will need to combine sparse prevalence data with non-traditional disease metrics such as wastewater measurements in order to estimate disease progression in a cost-effective manner. Here, we use data collected during the pandemic to model the dynamic relationship between spatially granular wastewater viral load and disease prevalence.

The effect of immigration policy reform on mental health in people from minoritised ethnic groups in England: an interrupted time series analysis of longitudinal data from the UK Household Longitudinal Study cohort.

Background: In 2012, the UK Government announced a series of immigration policy reforms known as the hostile environment policy, culminating in the Windrush scandal. We aimed to investigate the effect of the hostile environment policy on mental health for people from minoritised ethnic backgrounds. We hypothesised that people from Black Caribbean backgrounds would have worse mental health relative to people from White ethnic backgrounds after the Immigration Act 2014 and the Windrush scandal media coverage in 2017, since they were particularly targeted.

Wastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models.

The evident shedding of the SARS-CoV-2 RNA particles from infected individuals into the wastewater opened up a tantalizing array of possibilities for prediction of COVID-19 prevalence prior to symptomatic case identification through community testing. Many countries have therefore explored the use of wastewater metrics as a surveillance tool, replacing traditional direct measurement of prevalence with cost-effective approaches based on SARS-CoV-2 RNA concentrations in wastewater samples. Two important aspects in building prediction models are: time over which the prediction occurs and space for which the predicted case numbers is shown.

Spatiotemporal bayesian modelling of scorpionism and its risk factors in the state of São Paulo, Brazil.

Background: Scorpion stings in Brazil represent a major public health problem due to their incidence and their potential ability to lead to severe and often fatal clinical outcomes. A better understanding of scorpionism determinants is essential for a precise comprehension of accident dynamics and to guide public policy. Our study is the first to model the spatio-temporal variability of scorpionism across municipalities in São Paulo (SP) and to investigate its relationship with demographic, socioeconomic, environmental, and climatic variables.

Aircraft noise and cardiovascular morbidity and mortality near Heathrow Airport: A case-crossover study.

Aircraft noise causes annoyance and sleep disturbance and there is some evidence of associations between long-term exposures and cardiovascular disease (CVD). We investigated short-term associations between previous day aircraft noise and cardiovascular events in a population of 6.3 million residing near Heathrow Airport using a case-crossover design and exposure data for different times of day and night.

Community factors and excess mortality in the COVID-19 pandemic in England, Italy and Sweden.

Background: Analyses of coronavirus disease 19 suggest specific risk factors make communities more or less vulnerable to pandemic-related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics.

Asthma hospitalisations and heat exposure in England: a case-crossover study during 2002-2019.

Background: Previous studies have reported an association between warm temperature and asthma hospitalisation. They have reported different sex-related and age-related vulnerabilities; nevertheless, little is known about how this effect has changed over time and how it varies in space. This study aims to evaluate the association between asthma hospitalisation and warm temperature and investigate vulnerabilities by age, sex, time and space.

A dependent Bayesian Dirichlet process model for source apportionment of particle number size distribution.

The relationship between particle exposure and health risks has been well established in recent years. Particulate matter (PM) is made up of different components coming from several sources, which might have different level of toxicity. Hence, identifying these sources is an important task in order to implement effective policies to improve air quality and population health.

A decade of child pedestrian safety in England: a bayesian spatio-temporal analysis.

Background: Child pedestrian injury is a public health and health equality challenge worldwide, including in high-income countries. However, child pedestrian safety is less-understood, especially over long time spans. The intent of this study is to understand factors affecting child pedestrian safety in England over the period 2011-2020.

A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic.

The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks.

Community-level characteristics of COVID-19 vaccine hesitancy in England: A nationwide cross-sectional study.

One year after the start of the COVID-19 vaccination programme in England, more than 43 million people older than 12 years old had received at least a first dose. Nevertheless, geographical differences persist, and vaccine hesitancy is still a major public health concern; understanding its determinants is crucial to managing the COVID-19 pandemic and preparing for future ones. In this cross-sectional population-based study we used cumulative data on the first dose of vaccine received by 01-01-2022 at Middle Super Output Area level in England.

Interoperability of statistical models in pandemic preparedness: principles and reality.

We present as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving pandemic response. Interoperability provides an important set of principles for future pandemic preparedness, through the joint design and deployment of adaptable systems of statistical models for disease surveillance using probabilistic reasoning. We illustrate this through case studies for inferring and characterising spatial-temporal prevalence and reproduction numbers of SARS-CoV-2 infections in England.

Towards healthy school neighbourhoods: A baseline analysis in Greater London.

Creating healthy environments around schools is important to promote healthy childhood development and is a critical component of public health. In this paper we present a tool to characterize exposure to multiple urban environment features within 400 m (5-10 min walking distance) of schools in Greater London. We modelled joint exposure to air pollution (NO and PM), access to public greenspace, food environment, and road safety for 2,929 schools, employing a Bayesian non-parametric approach based on the Dirichlet Process Mixture modelling.

Ambient heat exposure and COPD hospitalisations in England: a nationwide case-crossover study during 2007-2018.

Background: There is emerging evidence suggesting a link between ambient heat exposure and chronic obstructive pulmonary disease (COPD) hospitalisations. Individual and contextual characteristics can affect population vulnerabilities to COPD hospitalisation due to heat exposure. This study quantifies the effect of ambient heat on COPD hospitalisations and examines population vulnerabilities by age, sex and contextual characteristics.

Community-level characteristics of COVID-19 vaccine hesitancy in England: A nationwide cross-sectional study.

One year after the start of the COVID-19 vaccination programme in England, more than 43 million people older than 12 years old had received at least a first dose. Nevertheless, geographical differences persist, and vaccine hesitancy is still a major public health concern; understanding its determinants is crucial to managing the COVID-19 pandemic and preparing for future ones. In this cross-sectional population-based study we used cumulative data on the first dose of vaccine received by 01-01-2022 at Middle Super Output Area level in England.

Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England: A population-based ecological study.

Background: Ethnically diverse and socio-economically deprived communities have been differentially affected by the COVID-19 pandemic in the UK.

Method: Using a multilevel regression model we assessed the time-varying association between SARS-CoV-2 infections and areal level deprivation and ethnicity from 1st of June 2020 to the 19th of September 2021. We separately considered weekly test positivity rate and estimated debiased prevalence at the Lower Tier Local Authority (LTLA) level, adjusting for confounders and spatio-temporal correlation structure.

Differential impact of government lockdown policies on reducing air pollution levels and related mortality in Europe.

Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO, O, PM, and PM levels across 47 European cities.

Regional excess mortality during the 2020 COVID-19 pandemic in five European countries.

The impact of the COVID-19 pandemic on excess mortality from all causes in 2020 varied across and within European countries. Using data for 2015-2019, we applied Bayesian spatio-temporal models to quantify the expected weekly deaths at the regional level had the pandemic not occurred in England, Greece, Italy, Spain, and Switzerland. With around 30%, Madrid, Castile-La Mancha, Castile-Leon (Spain) and Lombardia (Italy) were the regions with the highest excess mortality.

A framework for estimating and visualising excess mortality during the COVID-19 pandemic.

COVID-19 related deaths underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it compares observed with expected deaths based on the assumption that the pandemic did not occur. Expected deaths had the pandemic not occurred depend on population trends, temperature, and spatio-temporal patterns.