Estimate Population Exposure Research Articles

Recent Developments in Satellite Remote Sensing for Air Pollution Surveillance in Support of Sustainable Development Goals

Air pollution is an integral part of climatic, environmental, and socioeconomic current affairs and a cross-cutting component of certain United Nations Sustainable Development Goals (SDGs). Hence, reliable information on air pollution and human exposure is a crucial element in policy recommendations and decisions. At the same time, Earth Observation is steadily gaining confidence as a data input in the calculation of various SDG indicators. The current paper focuses on the usability of modern satellite remote sensing in the context of SDGs relevant to air quality. We introduce the socioeconomic importance of air quality and discuss the current uptake of geospatial information. The latest developments in Earth Observation provide measurements of finer spatial, temporal, and radiometric resolution products with increased global coverage, long-term continuation, and coherence in measurements. Leveraging on the two latest operational satellite technologies available, namely the Sentinel-5P and the Geostationary Environment Monitoring Spectrometer (GEMS) missions, we demonstrate two potential operational applications for quantifying air pollution at city and regional scales. Based on the two examples and by discussing the near-future anticipated geospatial capabilities, we showcase and advocate that the potential of satellite remote sensing as a, complementary to ground station networks, source of air pollution information is gaining confidence. As such, it can be an invaluable tool for quantifying global air pollution and deriving robust population exposure estimates.

Toward cleaner air and better health: Current state, challenges, and priorities.

The most up-to-date estimate of the global burden of disease indicates that ambient air pollution, including fine particulate matter and ozone, contributes to an estimated 5.2 million deaths each year. In this review, we highlight the challenges in estimating population exposure to air pollution and attributable health risks, particularly in low- and middle-income countries and among vulnerable populations. To protect public health, the evidence so far confirms urgent needs to prioritize interdisciplinary research on air pollution exposure and risk assessment and to develop evidence-based intervention policies and risk communication strategies. Here, we synthesize the emerging evidence supporting the monitoring and evaluation of the progress in implementation of the Global Air Quality Guidelines prepared by the World Health Organization.

The Impact of Air Pollution from Industrial Fires in Urban Settings: Monitoring, Modelling, Health, and Environmental Justice Perspectives

Industrial fires at facilities including waste management sites, warehouses, factories, chemical works, and fuel storage depots are relatively frequent occurrences. Often, these fires occur adjacent to urban communities and result in ground-level airborne pollutant concentrations that are well above guideline values. Land, water, livestock, and crops may also be contaminated by the emissions and by firefighting activities. Moreover, impacted communities tend to have a higher proportion of minority ethnic populations as well as individuals with underlying health vulnerabilities and those of lower socio-economic status. Nevertheless, this is an aspect of air quality that is under-researched, and so this review aims to highlight the public health hazards associated with industrial fires and the need for an effective, coordinated, public health response. We also review the range of monitoring techniques that have been utilised in such fires and highlight the role of dispersion modelling in predicting plume trajectories and in estimating population exposure. We recommend establishing 1 h guideline values for particulate matter to facilitate timely public health interventions, and we highlight the need to review regulatory and technical controls for sites prone to fires, particularly in the waste sector.

ImproRisk model, an open access risk assessment tool

Abstract ImproRisk is an open‐access Risk Assessment model, developed in Cyprus, which contributes to the harmonization, standardization and transparency of the Dietary Exposure Assessment methodologies across Europe. It is a simple and transparent tool, built in R, for conducting accurate dietary exposure assessments to chemical substances. Aiming to be established as a standardized Risk Assessment tool at European level, the model has been designed to accept occurrence and consumption data, coded according to the EFSA's food classification and description system version 2 (FoodEx2). ImproRisk users are able to estimate dietary exposure to a chemical substance under study at any level of the EFSA's FoodEx2, considering the FoodEx2 base term and the Process facet (F28). Dietary exposure is estimated at individual level for different population groups and exposure estimates are stratified by different demographic characteristics. ImproRisk is considered as a useful tool both for risk assessors and risk managers, as it facilitates decision making, by providing information regarding the percentage of the population exceeding the relevant health‐based guidance value or reference points for a specific chemical substance.

Projected population exposure to heatwaves in Xinjiang Uygur autonomous region, China.

The intensification of heatwaves dues to climate change is a significant concern, with substantial impacts on ecosystems and human health, particularly in developing countries. This study utilizes NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) and projected population data accounting for China's population policies to project changes in various grades of heatwaves (light, moderate, and severe) and the population exposure to heatwaves (PEH) in Xinjiang under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results show that the number of days and intensity of heatwaves in Xinjiang are projected to increase. Heatwaves occurring in Xinjiang will predominantly be severe heatwaves (SHW) in the long-term under the SSP5-8.5 scenario, and the number of SHW days projected to increase by 62 ± 18.4days compared to the reference period. Changes in heatwaves are anticipated to influence PEH, estimating population exposure to light, moderate, and severe heatwaves (LPEH, MPEH, and SPEH) at 534.6 ± 64 million, 496.2 ± 43.5 million, and 1602.4 ± 562.5 million person-days, respectively, in the long-term under the SSP5-8.5 scenario. The spatial distribution of PEH is projected to be consistent with that of the reference period, with high values persisting in Urumqi, Kashgar and Hotan. Changes in PEH are primarily driven by climate effects, followed by interactive effects, while population effects contribute the least. Therefore, mitigating climate change is crucial to reduce the PEH in Xinjiang.

Current and future rainfall-driven flood risk from hurricanes in Puerto Rico under 1.5 and 2 °C climate change

Abstract. Flooding associated with Hurricane Maria in 2017 had devastating consequences for lives and livelihoods in Puerto Rico. Yet, an understanding of current and future flood risk on small islands like Puerto Rico is limited. Thus, efforts to build resilience to flooding associated with hurricanes remain constrained. Here, we take an event set of hurricane rainfall estimates from a synthetic hurricane rainfall simulator as the input to an event-based rainfall-driven flood inundation model using the hydrodynamic code LISFLOOD-FP. Validation of our model against high-water-mark data for Hurricane Maria demonstrates the suitability of this model for estimating flood hazard in Puerto Rico. We produce event-based flood hazard and population exposure estimates for the present day and the future under the 1.5 and 2 ∘C Paris Agreement goals. Population exposure to flooding from hurricane rainfall in Puerto Rico for the present-day climate is approximately 8 %–10 % of the current population for a 5-year return period, with an increase in population exposure to flooding by 2 %–15 % and 1 %–20 % under 1.5 and 2 ∘C futures (5-year return period). This research demonstrates the significance of the 1.5 ∘C Paris Agreement goal for Small Island Developing States, providing the first event-based estimates of flooding from hurricane rainfall under climate change for a small island.

Quantifying flood risks during monsoon and post-monsoon seasons: An integrated framework for resource-constrained coastal regions

Global coastal regions are transforming into “flooding hot-spots” due to the multi-faceted confluence of several flood-drivers. Unfortunately, these regions are often poorly gauged, hindering comprehensive flood hazard quantification. Besides summer-monsoon floods, post-monsoon rainfalls induced by cyclonic-depressions have escalated the flood risks in the coastal regions. For the first time, the present study captures the seasonal flood hazards by disentangling monsoon (June, July, August, and September) and post-monsoon (October, November, and December) periods of rainfall. An integrated MIKE + 1D-2D coupled model was used to generate flood hazard risks for Jagatsinghpur district (Odisha, India), a resource-constrained multi-hazard catchment in the Lower Mahanadi River Basin. Due to limited data for this coastal region, we investigated the performance of CHIRPS v2.0, a global Satellite Precipitation Product (SPP) with high spatiotemporal characteristics, for capturing extreme rainfall events and deriving flood hazards at the inundation scale. We observed higher magnitude of flood hazards are prominent in the coastal villages, emerging from a complex interaction between rainfall and storm-tide events. Three widely used Archimedean copulas were implemented to capture the rainfall and storm-tide events' joint (bivariate) behavior and their implications on population exposure, which is valuable for mapping flood hazard risks. We observed that univariate analysis (Ua) significantly underestimates the flood hazard over bivariate analysis (Ba) during both periods. Interestingly, the results are more pronounced in the population exposure estimates as ∼47 % (monsoon) and ∼54 % (post-monsoon) of the population are exposed based on univariate analysis against ∼65 % (monsoon) and ∼60 % (post-monsoon) under bivariate analysis. Our study highlights the necessity of disentangling rainfall time-series for foreseeing under-shadowed flood risks, vital for designing flood combating structures, evacuation plans, land use planning, and flood governance. The results further enhance our understanding of monsoon and post-monsoon flood hazards and their associated risks under different return periods.

Five Years of Accurate PM2.5 Measurements Demonstrate the Value of Low-Cost PurpleAir Monitors in Areas Affected by Woodsmoke

Low-cost optical sensors are used in many countries to monitor fine particulate (PM2.5) air pollution, especially in cities and towns with large spatial and temporal variation due to woodsmoke pollution. Previous peer-reviewed research derived calibration equations for PurpleAir (PA) sensors by co-locating PA units at a government regulatory air pollution monitoring site in Armidale, NSW, Australia, a town where woodsmoke is the main source of PM2.5 pollution. The calibrations enabled the PA sensors to provide accurate estimates of PM2.5 that were almost identical to those from the NSW Government reference equipment and allowed the high levels of wintertime PM2.5 pollution and the substantial spatial and temporal variation from wood heaters to be quantified, as well as the estimated costs of premature mortality exceeding $10,000 per wood heater per year. This follow-up study evaluates eight PA sensors co-located at the same government site to check their accuracy over the following four years, using either the original calibrations, the default woodsmoke equation on the PA website for uncalibrated sensors, or the ALT-34 conversion equation (see text). Minimal calibration drift was observed, with year-round correlations, r = 0.98 ± 0.01, and root mean square error (RMSE) = 2.0 μg/m3 for daily average PA PM2.5 vs. reference equipment. The utitilty of the PA sensors without prior calibration at locations affected by woodsmoke was also demonstrated by the year-round correlations of 0.94 and low RMSE between PA (woodsmoke and ALT-34 conversions) and reference PM2.5 at the NSW Government monitoring sites in Orange and Gunnedah. To ensure the reliability of the PA data, basic quality checks are recommended, including the agreement of the two laser sensors in each PA unit and removing any transient spikes affecting only one sensor. In Armidale, from 2019 to 2022, the continuing high spatial variation in the PM2.5 levels observed during the colder months was many times higher than any discrepancies between the PA and reference measurements. Particularly unhealthy PM2.5 levels were noted in southern and eastern central Armidale. The measurements inside two older weatherboard houses in Armidale showed that high outdoor pollution resulted in high pollution inside the houses within 1–2 h. Daily average PM2.5 concentrations available on the PA website allow air pollution at different sites across regions (and countries) to be compared. Such comparisons revealed major elevations in PA PM2.5 at Gunnedah, Orange, Monash (Australian Capital Territory), and Christchurch (New Zealand) during the wood heating season. The data for Gunnedah and Muswellbrook suggest a slight underestimation of PM2.5 at other times of the year when there are proportionately more dust and other larger particles. A network of appropriately calibrated PA sensors can provide valuable information on the spatial and temporal variation in the air pollution that can be used to identify pollution hotspots, improve estimates of population exposure and health costs, and inform public policy.

Uncertainty analysis of potential population exposure within the coastal lowlands of mainland China

With accelerating global sea level rise driven by climate change, accurate estimates of potential population exposure (PPE) within the low-elevation coastal zones (LECZ) are critical for coastal planning and assessing the benefits of climate mitigation. Multiple digital elevation models (DEM) and population grid datasets have been used for the PPE assessment of coastal lowlands. However, the uncertainty arising from differences in data sources and production methods results in poorly guided estimates. In this study, four global DEM and five population datasets were used to estimate the PPE in the LECZ of China and to assess the uncertainty of PPE estimation. Based on the DEM and population grid with the best accuracy, we found that more than 13.82% of China’s residents lived in the LECZ in 2010. Different DEM-population combinations yielded significantly different PPE estimates, ranging between 3.59–24.61 million and 31.56–112.24 million people in the LECZ below 1 m and 4 m elevation, respectively. The satellite Lidar-based DEM improves the estimates of the LECZ and obtains the PPE within LECZ below 4 m elevation that far exceeds those of other DEM datasets. The usage of WorldPop and LandScan population datasets leads to an underestimation of PPE within the LECZ of China. In contrast, integrating more geospatial big data helps generate better population grids, thus reducing the uncertainty of coastal PPE estimates. There is still a need to improve the availability and accuracy of coastal geospatial data and to deepen the understanding of coastal vulnerability.

HEALTH RISK AS A CRITERION TO ESTIMATE POPULATION SAFETY IN AN AIRPORT ZONE

The paper considers and tests methodological approaches to assessing public health risks when establishing and using the sanitary (seventh) subzone in an airport zone. Testing was performed at a large civilian airport in Russia. It involved outlining noise contours in accordance with the ICAO methodology. The aviation noise contours were verified with the results produced by instrumental measurements. Acoustic exposure was calculated through assessing averaged daily equivalent noise level (LDN) that was equal to 65 dBA. Health risk assessment showed that long-term exposure primarily affected the cardiovascular system: moderate risks would occur by 23 years; high, by 55 years; and very high, by 63 years. Identified health disorders may become apparent through elevated blood pressure, heart diseases, myocardial infarctions and others.
 Background. It is quite common to locate certain objects within an AZ that are subject to sanitary-epidemiological standardization. Use of any AZ for location of such objects should be well grounded and this is a significant issue occurring when the sanitary (seventh) subzone is established. In particular, this concerns equivalent outdoor noise levels and equivalent and maximum permissible indoor noise levels.
 Purpose. Our research goal was to test the suggested approach to health risk assessment within the boundaries of an aircraft zone.
 Materials and methods. Our research object was a large civil aviation airport located in the temperate zone with an average daily number of landings and takeoffs being about 200. At the exposure assessment stage, we calculated aircraft noise contours by using a certified software package that was based on «Recommended Method for Computing Noise Contours Around Airports» (ICAO Doc 9911-2018). We took an equivalent averaged noise level (LAday, dBА) as an indicator applied to estimate population exposure to a harmful factor.
 We performed continuous AN measurements on a territory that was planned for development. This AN occurred due to AC takeoffs and landings with more than 600 AC flights detected during the measurement period. This determined effects produced by AN on the examined territory. Assessment of “exposure – response” and “exposure – effect” relationships involved using recurrent risk growth equations built on conventional pair mathematical models. This risk was measured within a range from 0 to 1 and scale was considered when giving its estimates.
 Results. This value was calculated based on maximum noise levels established during a single aircraft flight when it took off or landed along a route that was the most significant for determining exposure to aircraft noise. We also calculated equivalent noise levels at day and at night that corresponded to flight intensities typical for normal airport operations (2019). These levels were LAeq.day = 66,0 dBA (“takeoff”), LAeq.night = 52,0 dBA (“landing”).
 Health risk assessment indicated that long-term (chronic) exposure to average daily noise LАd = 65 dBA primarily produced effects on the cardiovascular system. This created moderate risks by the age of 23 years; high risks, 55 years; and extremely high risks, by 63 years.
 We established that living for more than 15 years in an airport zone with identified noise levels could result in negative health outcomes.
 Conclusion. Overall, we have confirmed that health risk assessment should be considered an important instrument for substantiating boundaries of a zone influenced by an airport. Results produced by such assessment are a key criterion in determining how to use a territory near an airport in future as regards locating capital objects there including residential areas and their exploitation.

Industrial Use of Phosphate Food Additives: A Mechanism Linking Ultra-Processed Food Intake to Cardiorenal Disease Risk?

The consumption of ultra-processed food (UPF) keeps rising, and at the same time, an increasing number of epidemiological studies are linking high rates of consumption of UPF with serious health outcomes, such as cardiovascular disease, in the general population. Many potential mechanisms, either in isolation or in combination, can explain the negative effects of UPF. In this review, we have addressed the potential role of inorganic phosphate additives, commonly added to a wide variety of foods, as factors contributing to the negative effects of UPF on cardiorenal disease. Inorganic phosphates are rapidly and efficiently absorbed, and elevated serum phosphate can lead to negative cardiorenal effects, either directly through tissue/vessel calcification or indirectly through the release of mineral-regulating hormones, parathyroid hormone, and fibroblast growth factor-23. An association between serum phosphate and cardiovascular and bone disease among patients with chronic kidney disease is well-accepted by nephrologists. Epidemiological studies have demonstrated an association between serum phosphate and dietary phosphate intake and mortality, even in the general American population. The magnitude of the role of inorganic phosphate additives in these associations remains to be determined, and the initial step should be to determine precise estimates of population exposure to inorganic phosphate additives in the food supply.

Population, land use and economic exposure estimates for Europe at 100 m resolution from 1870 to 2020

Understanding the influence of climate change on past extreme weather impacts is a vital research task. However, the effects of climate change are obscured in the observed impact data series due to the rapid evolution of the social and economic circumstances in which the events occurred. The HANZE v2.0 (Historical Analysis of Natural HaZards in Europe) dataset presented in this study quantifies the evolution of key socioeconomic drivers in Europe since 1870, namely land use, population, economic activity and assets. It consists of algorithms to reallocate baseline (2011) land use and population for any given year based on a large collection of historical subnational- and national-level statistics, and then disaggregate data on production and tangible assets by economic sector into a high-resolution grid. Raster datasets generated by the model enable reconstructing exposure within the footprint of any extreme event both at the time of occurrence and anytime between 1870 and 2020. This allows the separation of the effects of climate change from the effects of exposure change.

Burden of disease attributable to unsafe drinking water, sanitation, and hygiene in domestic settings: a global analysis for selected adverse health outcomes

Assessments of disease burden are important to inform national, regional, and global strategies and to guide investment. We aimed to estimate the drinking water, sanitation, and hygiene (WASH)-attributable burden of disease for diarrhoea, acute respiratory infections, undernutrition, and soil-transmitted helminthiasis, using the WASH service levels used to monitor the UN Sustainable Development Goals (SDGs) as counterfactual minimum risk-exposure levels. We assessed the WASH-attributable disease burden of the four health outcomes overall and disaggregated by region, age, and sex for the year 2019. We calculated WASH-attributable fractions of diarrhoea and acute respiratory infections by country using modelled WASH exposures and exposure-response relationships from two updated meta-analyses. We used the WHO and UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene public database to estimate population exposure to different WASH service levels. WASH-attributable undernutrition was estimated by combining the population attributable fractions (PAF) of diarrhoea caused by unsafe WASH and the PAF of undernutrition caused by diarrhoea. Soil-transmitted helminthiasis was fully attributed to unsafe WASH. We estimate that 1·4 (95% CI 1·3-1·5) million deaths and 74 (68-80) million disability-adjusted life-years (DALYs) could have been prevented by safe WASH in 2019 across the four designated outcomes, representing 2·5% of global deaths and 2·9% of global DALYs from all causes. The proportion of diarrhoea that is attributable to unsafe WASH is 0·69 (0·65-0·72), 0·14 (0·13-0·17) for acute respiratory infections, and 0·10 (0·09-0·10) for undernutrition, and we assume that the entire disease burden from soil-transmitted helminthiasis was attributable to unsafe WASH. WASH-attributable burden of disease estimates based on the levels of service established under the SDG framework show that progress towards the internationally agreed goal of safely managed WASH services for all would yield major public-health returns. WHO and Foreign, Commonwealth & Development Office.

Climate change will exacerbate population exposure to future heat waves in the China-Pakistan economic corridor

The China-Pakistan Economic Corridor (CPEC) is a climate change-sensitive region, facing frequent and intense heat waves (HWs). The CPEC is expected to experience a simultaneous increase in population and temperature in the coming decades, which could exacerbate human exposure to future HWs. However, it is unknown how much of the population would likely be exposed to HWs in the CPEC under changing climate. This study used the Coupled Model Inter-comparison Project 6 (CMIP6) models and population projections to estimate population exposure to daytime, nighttime, and compound HWs in the CPEC during 2071–2100, relative to 1985–2014 under four Shared Socioeconomic Pathways (SSPs). The results indicate that the study region will probably experience the highest number of nighttime HWs, followed by daytime and compound HWs in the northern, southwestern, and southern parts of the CPEC. The largest population would likely be exposed in the eastern and southwestern CPEC under SSP3-70|SSP3, followed by SSP5-8.5|SSP5, SSP2-4.5|SSP2, and SSP1-2.6|SSP1. The results reveal that the climatic and interactive effects could significantly escalate the population exposure to future HWs in the CPEC. The probability of 2015-HWs-like events and population exposure to such extremes would probably be higher in the eastern CPEC. The return period of 2015-HW-like events would decrease, which indicates their frequent occurrence under the selected SSPs. The findings of the study highlight the need for urgent actions to limit greenhouse gas emissions and to adopt effective adaptation measures in order to avoid the negative consequences of HWs on the local population in the future.

Assessing rail-based environmental noise exposure using CNOSSOS-EU

Since December 2018 a harmonised approach for the assessment of transportation noise, known as CNOSSOS-EU, became obligatory for EU Member States in the calculation of strategic noise mapping. This paper provides an assessment of rail-based environmental noise in Ireland via a comparative analysis of acoustic modelling for rail sources in the Irish context by comparing the CNOSSOS-EU method and the previously utilised interim method RMR-1996 with field measurements. The paper also presents comparative estimates of population exposure calculated using CNOSSOS-EU and RMR-1996. It was found that the results generated by the CNOSSOS-EU model were closer to field measurements when compared to the RMR-1996 model. Noise modelling also indicated that populations estimated to be exposed to levels of railway noise > 55 dB(A) generated by the national rail fleet were higher using CNOSSOS-EU (i.e. 91,692 more persons) relative to the RMR-1996 method. Rail noise generated by the Luas tram rail network generated marginally less population exposure for railway noise > 55 dB(A) (i.e. 2,905 less persons) relative to RMR-1996. As such, the paper contributes to the assessment of the new CNOSSOS-EU model for rail in the EU and addresses the relative lack of research focusing on rail modelling and population exposure estimation under the END. This paper contributes to a better understanding of the extent that populations are exposed to railway noise using CNOSSOS-EU across Europe.

Road traffic noise in European cities: Learnings from a European-wide study on the health impacts of road traffic noise.

Road traffic noise is one of the main environmental risks to health and wellbeing. We aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe. We analyzed 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24h day-evening-night noise level indicator (Lden) starting at exposure levels of 55 dB Lden for the adult population aged 20 and over and estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB Lden. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Almost 60 million adults were exposed to road traffic noise levels above 55 dB Lden, 11 million adults were highly annoyed and more than 3600 deaths from IHD could be prevented annually. A considerable number of adults are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase data availability at the city level are needed to provide a more accurate and comprehensive assessment of the health impacts of road traffic noise.

71 Estimation of incidence of MIS-C in Cape Town, South Africa

BackgroundMultisystem inflammatory syndrome is a severe manifestation of SARS-CoV-2 in children. The incidence of MIS-C after SARS-CoV-2 infection is poorly understood. There are very few cohorts describing MIS-C in Africa despite MIS-C being more common in Black children worldwide.MethodsA cohort of children with MIS-C and healthy children was recruited from May 2020 to May 2021 from the two main paediatric hospitals in Cape Town, South Africa. Clinical and demographic data were collected, and serum was tested for SARS-CoV-2 antibodies. The incidence of MIS-C was calculated using an estimation of population exposure from seroprevalence in the healthy group. Summary data, non-parametric comparisons and logistic regression analyses were performed.ResultsSixty-eight children with MIS-C were recruited with a median age of 7 years and 97 healthy children were recruited with a 30% seroprevalence. The estimated incidence of MIS-C was 22/100 000 SARS-COV-2 infections in children under 14 years old in the city at that time. Black children were over-represented in the MIS-C group (62% vs 37%, p = 0.002). The most common clinical features in MIS-C were fever (100%), tachycardia (98.5%), rash (85.3%), conjunctivitis (77.9%), abdominal pain (60.3%) and hypotension (60.3%). Median levels of haemoglobin, sodium, CRP, ferritin, cardiac (pro-BNP, trop-T) and coagulation markers (D-dimer and fibrinogen), neutrophil and white cell count were markedly deranged in MIS-C. Cardiac, pulmonary, central nervous and renal organ systems were involved in 71%, 29.4%, 27.9% and 27.9% respectively. Ninety-four point one per cent patient received intravenous immune globulin, 64.7% received methylprednisolone and 61.7% received both. ICU admission was required in 39.7% patient while 38.2% required inotropic support, 38.2% required oxygen therapy, 11.8% required invasive ventilation and 6% required peritoneal dialysis. The median hospital stay duration was 7 days with no deaths.ConclusionThe lack of reports from Southern Africa does not reflect a lack of cases of MIS-C. The clinical manifestations and outcomes of MIS-C in this region highlight the need for improved surveillance, reporting and data to inform diagnosis and treatment.ImplicationsTo our knowledge, these are the first data on MIS-C in Africa. This shows that children in Africa are indeed presenting with MIS-C which will increase surveillance around the continent.

Assessment of gamma radiation levels in soil samples from Sylhet using High Purity Germanium Detector and Estimation of population exposure

Assessment of gamma radiation levels in soil samples from Sylhet using High Purity Germanium Detector and Estimation of population exposure

Evaluation of a Multiplex Bead Assay against Single-Target Assays for Detection of IgG Antibodies to SARS-CoV-2.

ABSTRACTSerological assays for SARS-CoV-2 antibodies must be validated for performance with a large panel of clinical specimens. Most existing assays utilize a single antigen target and may be subject to reduced diagnostic specificity. This study evaluated a multiplex assay that detects antibodies to three SARS-CoV-2 targets. Human serum specimens (n = 323) with known previous SARS-CoV-2 exposure status were tested on a commercially available multiplex bead assay (MBA) measuring IgG to SARS-CoV-2 spike protein receptor-binding domain (RBD), nucleocapsid protein (NP), and RBD/NP fusion antigens. Assay performance was evaluated against reverse transcriptase PCR (RT-PCR) results and also compared with test results for two single-target commercial assays. The MBA had a diagnostic sensitivity of 89.8% and a specificity of 100%, with serum collection at >28 days following COVID-19 symptom onset showing the highest seropositivity rates (sensitivity: 94.7%). The MBA performed comparably to single-target assays with the ability to detect IgG against specific antigen targets, with 19 (5.9%) discrepant specimens compared to the NP IgG assay and 12 (3.7%) compared to the S1 RBD IgG assay (kappa coefficients 0.92 and 0.88 compared to NP IgG and S1 RBD IgG assays, respectively. These findings highlight inherent advantages of using a SARS-CoV-2 serological test with multiple antigen targets; specifically, the ability to detect IgG against RBD and NP antigens simultaneously. In particular, the 100.0% diagnostic specificity exhibited by the MBA in this study is important for its implementation in populations with low SARS-CoV-2 seroprevalence or where background antibody reactivity to SARS-CoV-2 antigens has been detected.IMPORTANCE Reporting of SARS-CoV-2 infections through nucleic acid or antigen based diagnostic tests severely underestimates the true burden of exposure in a population. Serological data assaying for antibodies against SARS-CoV-2 antigens offers an alternative source of data to estimate population exposure, but most current immunoassays only include a single target for antibody detection. This report outlines a direct comparison of a multiplex bead assay to two other commercial single-target assays in their ability to detect IgG against SARS-CoV-2 antigens. Against a well-defined panel of 323 serum specimens, diagnostic sensitivity and specificity were very high for the multiplex assay, with strong agreement in IgG detection for single targets compared to the single-target assays. Collection of more data for individual- and population-level seroprofiles allows further investigation into more accurate exposure estimates and research into the determinants of infection and convalescent responses.

Exposure to tobacco, alcohol and 'Junk food' content in reality TV programmes broadcast in the UK between August 2019-2020.

Exposure to alcohol, tobacco and foods high in fat, sugar or salt (HFSS) content in media is a risk factor for smoking, alcohol use and HFSS consumption in young people. We report an analysis of tobacco, alcohol and HFSS content in a sample of reality TV programmes broadcast on TV and video-on-demand services throughout a 1-year period. We used 1-min interval coding to quantify content in all episodes of 20 different reality TV programmes between August 2019 and August 2020 and estimated population exposure to a sample of these programmes using viewing data and UK population estimates. We coded 13244 intervals from 264 episodes. Tobacco content appeared in 227 intervals (2%) across 43 episodes (2%), alcohol in 5167 intervals (39%) across 258 episodes (98%) and HFSS in 1752 intervals (13%) across 234 episodes (88%). A sample of 15 series delivered ~157.4 million tobacco, 3.5 billion alcohol and 1.9 billion HFSS gross impressions to the UK population, including 24000, 12.6 million and 21.4 million, to children, respectively. Tobacco, alcohol and HFSS content are common in reality TV programmes. These programmes deliver exposure to tobacco, alcohol and HFSS imagery, which are a potential driver of tobacco use, alcohol use and HFSS consumption in young people.