Publications
23 results found
Konstantinoudis G, Minelli C, Lam HCY, et al., 2023, Asthma hospitalisations and heat exposure in England: a case-crossover study during 2002-2019, Thorax, Vol: 78, Pages: 875-881, ISSN: 0040-6376
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. METHODS: We retrieved individual-level data on summer asthma hospitalisation at high temporal (daily) and spatial (postcodes) resolutions during 2002-2019 in England from the NHS Digital. Daily mean temperature at 1 km×1 km resolution was retrieved from the UK Met Office. We focused on lag 0-3 days. We employed a case-crossover study design and fitted Bayesian hierarchical Poisson models accounting for possible confounders (rainfall, relative humidity, wind speed and national holidays). RESULTS: After accounting for confounding, we found an increase of 1.11% (95% credible interval: 0.88% to 1.34%) in the asthma hospitalisation risk for every 1°C increase in the ambient summer temperature. The effect was highest for males aged 16-64 (2.10%, 1.59% to 2.61%) and during the early years of our analysis. We also found evidence of a decreasing linear trend of the effect over time. Populations in Yorkshire and the Humber and East and West Midlands were the most vulnerable. CONCLUSION: This study provides evidence of an association between warm temperature and hospital admission for asthma. The effect has decreased over time with potential explanations including temporal differences in patterns of heat exposure, adaptive mechanisms, asthma management, lifestyle, comorbidities and occupation.
Itzkowitz N, Gong X, Atilola G, et al., 2023, Aircraft noise and cardiovascular morbidity and mortality near Heathrow Airport: a case-crossover study, Environment International, Vol: 177, Pages: 1-9, ISSN: 0160-4120
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. We included all recorded hospitalisations (n=442,442) and deaths (n=49,443) in 2014-2018 due to CVD. Conditional logistic regression was used to estimate the ORs and adjusted for NO2 concentration, temperature, and holidays. We estimated an increase in risk for 10dB increment in noise during the previous evening (Leve OR = 1.007, 95% CI 0.999-1.015), particularly from 22:00-23:00h (OR= 1.007, 95% CI 1.000-1.013), and the early morning hours 04:30-06:00h (OR= 1.012, 95% CI 1.002-1.021) for all CVD admissions, but no significant associations with day-time noise. There was effect modification by age-sex, ethnicity, deprivation, and season, and some suggestion that high noise variability at night was associated with higher risks. Our findings are consistent with proposed mechanisms for short-term impacts of aircraft noise at night on CVD from experimental studies, including sleep disturbance, increases in blood pressure and stress hormone levels and impaired endothelial function.
Konstantinoudis G, Gómez-Rubio V, Cameletti M, et al., 2023, A workflow for estimating and visualising excess mortality during the COVID-19 pandemic, The R Journal, Vol: 15, Pages: 89-104, ISSN: 2073-4859
COVID-19 related deaths estimates underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it compares the observed number of deaths versus the number that would be expected if the pandemic did not occur. The expected number of deaths depends on population trends, temperature, and spatio-temporal patterns. In addition to this, high geographical resolution is required to examine within country trends and the effectiveness of the different public health policies. In this tutorial, we propose a workflow using R for estimating and visualising excess mortality at high geographical resolution. We show a case study estimating excess deaths during 2020 in Italy. The proposed workflow is fast to implement and allows for combining different models and presenting aggregated results based on factors such as age, sex, and spatial location. This makes it a particularly powerful and appealing workflow for online monitoring of the pandemic burden and timely policy making.
Riou J, Hauser A, Althaus C, et al., 2023, Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland, Nature Communications, Vol: 14, ISSN: 2041-1723
The direct and indirect impact of the COVID-19 pandemic on population-level mortality is of concern to public health but challenging to quantify. Using data for 2011–2019, we applied Bayesian models to predict the expected number of deaths in Switzerland and compared them with laboratory-confirmed COVID-19 deaths from February 2020 to April 2022 (study period). We estimated that COVID-19-related mortality was underestimated by a factor of 0.72 (95% credible interval [CrI]: 0.46–0.78). After accounting for COVID-19 deaths, the observed mortality was −4% (95% CrI: −8 to 0) lower than expected. The deficit in mortality was concentrated in age groups 40–59 (−12%, 95%CrI: −19 to −5) and 60–69 (−8%, 95%CrI: −15 to −2). Although COVID-19 control measures may have negative effects, after subtracting COVID-19 deaths, there were fewer deaths in Switzerland during the pandemic than expected, suggesting that any negative effects of control measures were offset by the positive effects. These results have important implications for the ongoing debate about the appropriateness of COVID-19 control measures.
Konstantinoudis G, Cosetta M, Vicedo Cabrera AM, et al., 2022, Ambient heat exposure and COPD hospitalisations in England: a nationwide case-crossover study during 2007-2018, Thorax, Vol: 77, Pages: 1098-1104, ISSN: 0040-6376
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.Methods: Individual data on COPD hospitalisation at high geographical resolution (postcodes) during 2007–2018 in England was retrieved from the small area health statistics unit. Maximum temperature at 1 km ×1 km resolution was available from the UK Met Office. We employed a case-crossover study design and fitted Bayesian conditional Poisson regression models. We adjusted for relative humidity and national holidays, and examined effect modification by age, sex, green space, average temperature, deprivation and urbanicity.Results: After accounting for confounding, we found 1.47% (95% Credible Interval (CrI) 1.19% to 1.73%) increase in the hospitalisation risk for every 1°C increase in temperatures above 23.2°C (lags 0–2 days). We reported weak evidence of an effect modification by sex and age. We found a strong spatial determinant of the COPD hospitalisation risk due to heat exposure, which was alleviated when we accounted for contextual characteristics. 1851 (95% CrI 1 576 to 2 079) COPD hospitalisations were associated with temperatures above 23.2°C annually.Conclusion: Our study suggests that resources should be allocated to support the public health systems, for instance, through developing or expanding heat-health alerts, to challenge the increasing future heat-related COPD hospitalisation burden.
Bucyibaruta G, Blangiardo M, Konstantinoudis G, 2022, Community-level characteristics of COVID-19 vaccine hesitancy in England: A nationwide cross-sectional study, European Journal of Epidemiology, Vol: 37, Pages: 1071-1081, ISSN: 0393-2990
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. We used Bayesian hierarchical spatial models and investigated if the geographical differences in vaccination uptake can be explained by a range of community-level characteristics covering socio-demographics, political view, COVID-19 health risk awareness and targeting of high risk groups and accessibility. Deprivation is the covariate most strongly associated with vaccine uptake (Odds Ratio 0.55, 95%CI 0.54-0.57; most versus least deprived areas). The most ethnically diverse areas have a 38% (95%CI 36-40%) lower odds of vaccine uptake compared with those least diverse. Areas with the highest proportion of population between 12 and 24 years old had lower odds of vaccination (0.87, 95%CI 0.85-0.89). Finally increase in vaccine accessibility is associated with COVID-19 vaccine coverage (OR 1.07, 95%CI 1.03-1.12). Our results suggest that one year after the start of the vaccination programme, there is still evidence of inequalities in uptake, affecting particularly minorities and marginalised groups. Strategies including prioritising active outreach across communities and removing practical barriers and factors that make vaccines less accessible are needed to level up the differences.
Mazzei A, Konstantinoudis G, Kreis C, et al., 2022, Childhood cancer and residential proximity to petrol stations: a nationwide registry-based case-control study in Switzerland and an updated meta-analysis, INTERNATIONAL ARCHIVES OF OCCUPATIONAL AND ENVIRONMENTAL HEALTH, Vol: 95, Pages: 927-938, ISSN: 0340-0131
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- Citations: 2
Konstantinoudis G, Cameletti M, Gómez-Rubio V, et al., 2022, Regional excess mortality during the 2020 COVID-19 pandemic in five European countries, Nature Communications, Vol: 13, Pages: 1-11, ISSN: 2041-1723
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. In England, Greece and Switzerland, the regions most affected were Outer London and the West Midlands (England), Eastern, Western and Central Macedonia (Greece), and Ticino (Switzerland), with 15-20% excess mortality in 2020. Our study highlights the importance of the large transportation hubs for establishing community transmission in thefirst stages of the pandemic. Here, we show that acting promptly to limit transmission around these hubs is essential to prevent spread to other regions and countries.
Konstantinoudis G, Gómez-Rubio V, Cameletti M, et al., 2022, A framework for estimating and visualising excess mortality during the COVID-19 pandemic., Publisher: arXiv
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. In addition to this, high geographical resolution is required to examine within country trends and the effectiveness of the different public health policies. In this tutorial, we propose a framework using R to estimate and visualise excess mortality at high geographical resolution. We show a case study estimating excess deaths during 2020 in Italy. The proposed framework is fast to implement and allows combining different models and presenting the results in any age, sex, spatial and temporal aggregation desired. This makes it particularly powerful and appealing for online monitoring of the pandemic burden and timely policy making.
Heydari S, Konstantinoudis G, Behsoodi AW, 2021, Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London, PLOS ONE, Vol: 16, ISSN: 1932-6203
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- Citations: 22
Folly CL, Konstantinoudis G, Mazzei-Abba A, et al., 2021, Bayesian spatial modelling of terrestrial radiation in Switzerland, JOURNAL OF ENVIRONMENTAL RADIOACTIVITY, Vol: 233, ISSN: 0265-931X
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- Citations: 5
Lupatsch JE, Kreis C, Konstantinoudis G, et al., 2021, Birth characteristics and childhood leukemia in Switzerland: a register-based case-control study, CANCER CAUSES & CONTROL, Vol: 32, Pages: 713-723, ISSN: 0957-5243
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- Citations: 6
Dhokotera T, Bartels L, Rohrer E, et al., 2021, Spatiotemporal modelling and mapping of cervical cancer incidence among HIV positive women in South Africa: a nationwide study, International Journal of Health Geographics, Vol: 20, Pages: 1-12, ISSN: 1476-072X
BackgroundDisparities in invasive cervical cancer (ICC) incidence exist globally, particularly in HIV positive women who are at elevated risk compared to HIV negative women. We aimed to determine the spatial, temporal, and spatiotemporal incidence of ICC and the potential risk factors among HIV positive women in South Africa.MethodsWe included ICC cases in women diagnosed with HIV from the South African HIV cancer match study during 2004–2014. We used the Thembisa model, a mathematical model of the South African HIV epidemic to estimate women diagnosed with HIV per municipality, age group and calendar year. We fitted Bayesian hierarchical models, using a reparameterization of the Besag-York-Mollié to capture spatial autocorrelation, to estimate the spatiotemporal distribution of ICC incidence among women diagnosed with HIV. We also examined the association of deprivation, access to health (using the number of health facilities per municipality) and urbanicity with ICC incidence. We corrected our estimates to account for ICC case underascertainment, missing data and data errors.ResultsWe included 17,821 ICC cases and demonstrated a decreasing trend in ICC incidence, from 306 to 312 in 2004 and from 160 to 191 in 2014 per 100,000 person-years across all municipalities and corrections. The spatial relative rate (RR) ranged from 0.27 to 4.43 in the model without any covariates. In the model adjusting for covariates, the most affluent municipalities had a RR of 3.18 (95% Credible Interval 1.82, 5.57) compared to the least affluent ones, and municipalities with better access to health care had a RR of 1.52 (1.03, 2.27) compared to municipalities with worse access to health.ConclusionsThe results show an increased incidence of cervical cancer in affluent municipalities and in those with more health facilities. This is likely driven by better access to health care in more affluent areas. More efforts should be made to ensure equitable access to health services
Konstantinoudis G, Padellini T, Bennett J, et al., 2021, Response to "re: long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis", Environment International, Vol: 150, ISSN: 0160-4120
Konstantinoudis G, Padellini T, Bennett J, et al., 2021, Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis, Environment International, Vol: 146, ISSN: 0160-4120
Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 mortality in England using high geographical resolution. In this nationwide cross-sectional study in England, we included 38,573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level (n = 32,844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014–2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. We find a 0.5% (95% credible interval: −0.2%, 1.2%) and 1.4% (95% CrI: −2.1%, 5.1%) increase in COVID-19 mortality risk for every 1 μg/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect equal to 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain.
Konstantinoudis G, Padellini T, Bennett J, et al., 2020, Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis, Publisher: MedRxiv
Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 deaths up to June 30, 2020 in England using high geographical resolution. In this nationwide cross-sectional study in England, we included 38,573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level (n=32,844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. We find a 0.5% (95% credible interval: -0.2%, 1.2%) and 1.4% (95% CrI: -2.1%, 5.1%) increase in COVID-19 mortality risk for every 1μg/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect equal to 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain.
Hauser A, Counotte MJ, Margossian CC, et al., 2020, Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: A modeling study in Hubei, China, and six regions in Europe, PLOS MEDICINE, Vol: 17, ISSN: 1549-1277
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- Citations: 80
Konstantinoudis G, Schuhmacher D, Ammann RA, et al., 2020, Bayesian spatial modelling of childhood cancer incidence in Switzerland using exact point data: a nationwide study during 1985-2015, INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS, Vol: 19, ISSN: 1476-072X
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- Citations: 5
Konstantinoudis G, Schuhmacher D, Rue H, et al., 2020, Discrete versus continuous domain models for disease mapping, Publisher: ELSEVIER SCI LTD
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- Citations: 10
Chasapis CT, Konstantinoudis G, 2020, Protein isoelectric point distribution in the interactomes across the domains of life, BIOPHYSICAL CHEMISTRY, Vol: 256, ISSN: 0301-4622
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- Citations: 7
Riesen M, Konstantinoudis G, Lang P, et al., 2018, Exploring variation in human papillomavirus vaccination uptake in Switzerland: a multilevel spatial analysis of a national vaccination coverage survey, BMJ Open, Vol: 8, Pages: 1-9, ISSN: 2044-6055
Objective Understanding the factors that influence human papillomavirus (HPV) vaccination uptake is critically important to the design of effective vaccination programmes. In Switzerland, HPV vaccination uptake (≥1 dose) by age 16 years among women ranges from 31% to 80% across 26 cantons (states). Our objective was to identify factors that are associated with the spatial variation in HPV vaccination uptake.Methods We used cross-sectional data from the Swiss National Vaccination Coverage Survey 2009–2016 on HPV vaccination status (≥1 dose) of 14–17-year-old girls, their municipality of residence and their nationality for 21 of 26 cantons (n=8965). We examined covariates at municipality level: language, degree of urbanisation, socioeconomic position, religious denomination, results of a vote about vaccination laws as a proxy for vaccine scepticism and, at cantonal level, availability of school-based vaccination and survey period. We used a series of conditional autoregressive models to assess the effects of covariates while accounting for variability between cantons and municipal-level spatial autocorrelation.Results In the best-fit model, living in cantons that have school-based vaccination (adjusted OR 2.51; 95% credible interval 1.77 to 3.56) was associated with increased uptake, while living in municipalities with lower acceptance of vaccination laws was associated with lower HPV vaccination uptake (OR 0.61; 95% credible interval 0.50 to 0.73). Overall, the covariates explained 88% of the municipal-level variation in uptake.Conclusions In Switzerland, both cantons and community opinion about vaccination play a prominent role in the variation in HPV vaccination uptake. To increase uptake, efforts should be made to mitigate vaccination scepticism and to encourage school-based vaccination.
Riesen M, Konstantinoudis G, Lang P, et al., 2017, Exploring variation in human papillomavirus vaccination uptake: multi-level spatial analysis
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Understanding the factors that influence human papillomavirus (HPV) vaccination uptake is critically important to design effective vaccination programmes. In Switzerland, completed HPV vaccination by age 16 years among women ranges from 30 to 79% across 26 cantons (states). Our objective was to identify factors that are associated with the spatial variation in HPV vaccination uptake.</jats:p></jats:sec><jats:sec><jats:title>Methods and findings</jats:title><jats:p>We used data from the Swiss National Vaccination Coverage Survey 2009-2016 on HPV vaccination status (≥1 dose) of 14-17 year old girls, their municipality of residence and their nationality for 21 of 26 cantons (N=8,965). We examined covariates at municipality level: language, degree of urbanisation, socio-economic position, religious denomination, results of a vote about vaccination laws; and, at cantonal level, availability of school-based vaccination and survey period. We used a series of conditional auto regressive (CAR) models to assess the effects of covariates while accounting for variability between cantons and municipal-level spatial autocorrelation. In the best-fit model, school-based vaccination (adjusted odds ratio, OR: 2.51, 95% credible interval, CI: 1.77-3.56) was associated with increased uptake, while lower acceptance of vaccination laws was associated with lower HPV vaccination uptake (OR 0.61, 95% CI: 0.50-0.73). Overall, the covariates explained 88% of the municipal-level variation in uptake.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>In Switzerland, cantons play a prominent role in the variation in HPV vaccination uptake, especially through the provision of school-based vaccination delivery. HPV vaccination uptake is also strongly associated with inhabitants&rsqu
Konstantinoudis G, Kreis C, Ammann RA, et al., 2017, Spatial clustering of childhood leukaemia in Switzerland: A nationwide study, INTERNATIONAL JOURNAL OF CANCER, Vol: 141, Pages: 1324-1332, ISSN: 0020-7136
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- Citations: 11
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