An exploratory investigation into the influence of risk factors on driver injury severity in angle crashes: A random parameter bivariate ordered probit model approach.

OBJECTIVE: Angle crashes have been acknowledged as a concerning issue in the traffic safety field, though there is limited understanding of the contributions of risk factors to injury severity. This article aims to examine the impact of risk factors and unobserved heterogeneity on the severity of driver injuries in angle collisions by utilizing angle crash data in the United States from 2016 to 2021. METHODS: The relationship between risk factors and driver injury severities in angle crashes was investigated using a random parameter bivariate ordered probit model (RPBOP) with 4 categories of injury severity classified as outcome variables, including no injury, possible injury, minor injury, and serious jury. Risk factors were considered as explanatory variables, classified as driver characteristics, vehicle characteristics, road characteristics, environmental characteristics, time characteristics, and crash characteristics. Bayesian inference was used to assess the unobserved heterogeneity in risk factors, and marginal effects were computed to analyze the effect of each factor on injury outcomes. RESULTS: The findings demonstrate that risk factors have varying effects on driver involvement in angle crashes. Certain factors exhibited unobserved heterogeneity, including young drivers (ages 25-44), older drivers (over age 59), road grade, and collision point orientation. On the other hand, other factors, such as female gender, motorcycles, intersections, speed limit (>50 mph), poor lighting conditions, adverse weather, urban areas, and workdays, were shown to significantly increase the likelihood of driver injury in angle collisions, as well as increase susceptibility to fatal injury. CONCLUSIONS: This article offers new insights into reducing driver injuries in angle crashes and has the potential to inform policy development aimed at preventing such incidents. Further research could utilize multisource data fusion and investigate the spatiotemporal stability of risk factors to enhance the generalizability of angle collision prevention strategies.

Exploring temporal instability effects on bicyclist injury severities determinants for intersection and non-intersection-related crashes.

Cycling is a sustainable and healthy mode of transportation with direct links to reducing traffic congestion, lowering greenhouse gas emissions, and improving air quality. However, from a safety perspective, bicyclists represent a risky road user group with a higher likelihood of sustaining severe injuries when involved in vehicle crashes. With various determinants known to affect bicyclist injury severity and vary across locations, this study investigates the factors affecting bicyclist injury severity and temporal instability, considering the location of crashes. More specifically, the objective of this study is to understand differences in injury severities of intersection and non-intersection-related single-bicycle-vehicle crashes using four year crash data from the state of Florida. Random parameters logit models with heterogeneity in the means and variances are developed to model bicyclist injury severity outcomes (no injury, minor injury, and severe injury) for intersection and non-intersection crashes. Several variables affecting injury severities are considered in model estimation, including weather, roadway, vehicle, driver, and bicyclist characteristics. The temporal stability of the model parameters is assessed for different locations and years using a series of likelihood ratio tests. Results indicate that the determinants of bicyclist injury severities change over time and location, resulting in different injury severities of bicyclists, with non-intersection crashes consistently resulting in more severe bicyclist injuries. Using a simulation-based out-of-sample approach, predictions are made to understand the benefits of replicating driving behaviour and facilities similar to intersections for non-intersection locations, which could benefit in reducing bicyclist injury severity probabilities.

The Impact of Climate Change on Global Oncology.

Climate change is the greatest threat to human health of our time, with significant implications for global cancer control efforts. The changing frequency and behavior of climate-driven extreme weather events results in more frequent and increasingly unanticipated disruptions in access to cancer care. Given the significant threat that climate change poses to cancer control efforts, oncology professionals should champion initiatives that help protect the health and safety of patients with cancer, such as enhancing emergency preparedness and response efforts and reducing emissions from our own professional activities, which has health cobenefits for the entire population.

Climate change adaptation stories: Co-creating climate services with reindeer herders in Finland.

Reindeer husbandry in the Arctic region is strongly affected by the local climate. Reindeer herders are used to coping with adverse weather, climate, and grazing conditions through autonomous adaptation. However, today's rapidly changing Arctic environment poses new challenges to the management of herding activities. Finding means for combining traditional and scientific knowledge without depriving any of the systems of its fundamental strengths is hence deemed necessary. In this work, we apply a transdisciplinary framework for knowledge co-production involving international researchers and reindeer herders from different cooperatives in northern Finland. Through 'climate change adaptation stories', we co-explore how climate predictions can inform herders' decision making during the herding season. Relevant decisions include the anticipation of summer harvest time, the inopportune periods of cold weather in spring, and insect harassment in summer. Despite their potential benefits for climate-sensitive decisions, climate predictions have seen limited uptake, mainly due to their probabilistic nature and lower quality compared with shorter-term weather forecasts. The analysis of two different adaptation stories shows that seasonal predictions of temperature for May and June can successfully advise about the likelihood of having an earlier than normal harvest. This information can be obtained up to three months in advance, helping herders to better arrange their time for other activities. Likewise, sub-seasonal predictions of temperature during April and May can be useful to anticipate the occurrence of backwinter episodes, which can support herders in deciding whether to feed reindeer in pens for longer, avoiding putting the survival of calves at risk. This study, which would benefit from co-evaluation in real world settings and consideration of additional adaptation stories, sets the basis for a successful co-production of climate services with Arctic reindeer herders. This research shows the potential to enhance the resilience of Polar regions, offering opportunities for adaptation while supporting the sustainability and culture of traditional practices of Arctic communities.

Extreme Weather Events and Asthma.

The objective of this article is to review recent literature on the implications of extreme weather events such as thunderstorms, wildfires, tropical cyclones, freshwater flooding, and temperature extremes in relationship to asthma symptoms. Several studies have shown worsening of asthma symptoms with thunderstorms, wildfires, tropical cyclones, freshwater flooding, and temperature extremes. In particular, thunderstorm asthma can be exacerbated by certain factors such as temperature, precipitation, and allergen sensitization. Therefore, it is imperative that the allergy and immunology community be aware of the health effects associated with these extreme weather events in order to educate patients and engage in mitigation strategies.

Eluates from façades at the beginning of their service time affect aquatic and sediment organisms.

Biocides are used in building materials to prevent microbial growth during storage (in-can preservatives) as well as after application (film preservatives). These compounds can leach out from the material into the environment and harm non-target organisms. In this study, the ecotoxicological effect of leachates at the beginning of a façade lifetime, on sediment and aquatic organisms was examined. For this purpose, leaching tests were carried out in the setting of a natural weathering experiment and a laboratory immersion with façade samples consisting of render/paint systems. The leaching experiments were performed with three different formulations, namely no biocides containing control, a formulation containing only in-can preservatives (benzisothiazolinone (BIT), methylchloroisothiazolinone (CMIT), and methylisothiazolinone (MIT)), and, as is common in organic building materials, containing both in-can and film preservatives (octylisothiazolinone (OIT) and terbutryn (TB)). In order to elucidate the effects of in-can and film preservative-containing eluates the toxicity of the generated leachables was evaluated on the model of several aquatic and sediment organisms, namely luminescent bacteria (Vibrio fischeri), green algae (Scenedesmus subspicatus), Salmonella typhimurium TA1535/pSK1002 (umu-test), fish-egg (Danio rerio), Chironomus riparius, and Lumbriculus variegatus. It was demonstrated that in-can preservatives leach out rapidly at the beginning of a façade lifetime and despite the short half-life of these compounds in aqueous solutions, they could be detected at high concentrations in the eluates. Furthermore, eluates from early sampling times, predominantly containing in-can preservatives, were found to cause toxic effects on sediment and aquatic organisms. The results demonstrate that in-can preservatives can impose a significant stress factor on the environment.

Predicting wastewater treatment plant influent in mixed, separate, and combined sewers using nearby surface water discharge for better wastewater-based epidemiology sampling design.

For wastewater sample collection approaches supporting public health applications, few high hydrologic activity normalizing guidelines currently consider readily available environmental flow data that may earlier capture information regarding periods of influent mixing and dilution of wastewater with groundwater and runoff. This study aimed to identify wastewater sampling rules for high hydrological activity events, allowing for an earlier decision point in the control of dilution before sample collection. We defined the sampling rules via data-driven models (Random Forest and linear regression) using environmental data (i.e., wastewater treatment facility influent rates, nearby stream discharge flow, and precipitation). These models were applied to five treatment plants in Jefferson County, Kentucky (USA) in mixed, separate, and combined sewers with different population sizes. We proposed cutoffs of 10 %, 25 %, and 50 % flow conditions for orientation towards public health samples. The results showed a strong nonlinear relationship between nearby stream discharge and treatment facility flow rates, which was used to infer the hydrological conditions that produce high volumes of diluted wastewater in the sewer system. Accumulated Local Effects and SHapley Additive exPlanations aided in deciphering the relationship between the predictors and response variables of the Random Forest models. The influent rate to the treatment plant from the previous day and two USGS stream gages were needed to adequately predict the degree of infiltration and inflow mixing on a given day. Surface water discharge data can be used to provide an earlier workflow decision point during wet weather periods to improve understanding of flow conditions for wastewater-based epidemiological studies to inform laboratory analysis and data interpretation. Not only total flow, but also the specific proportions of infiltration and inflow to wastewater volume in influent should be considered when analyzing data for normalization purposes, and our method provides a starting point for doing so rapidly and at low cost.

The effects of diurnal temperature range on mortality and emergency department presentations in Victoria state of Australia: A time-series analysis.

State of Victoria, Australia (SVA) has a wide variation of diurnal temperatures (DTR). DTR has been reported to be associated with risk of mortality and morbidity. We examined the association between exposure to DTR and risk of all-cause mortality and emergency department (ED) presentations in the SVA. We obtained data on daily counts of deaths and ED presentations, and weather data from 1 st January 2000─2019. We applied a quasi-Poisson time-series regression analysis to examine the association between daily DTR exposures and risk of mortality and ED presentations. The analyses were queried by age, sex, seasons, ED presentations triages, and departure status. Risk of mortality and ED presentation increased by 0.33% (95% CI: 0.24%-0.43%), and 0.094% (95% CI: 0.077%-0.11%) in relation to one degree increase in the daily DTR. The association between DTR and ED presentations was stronger in children (0-15 years) (0.38% [95% CI: 0.34%-0.42%]) and the elderly (75+ years) (0.34% [95% CI: 0.29%-0.39%]). Resuscitation, which was consistently accounted for the highest vulnerability to DTR variation, increased by 0.79% (95% CI: 0.60%-0.99%). This study suggests that the risk of mortality and ED presentations associates with the increase of DTR. Children, the elderly, and their caregivers need to be made aware of the health risk posed by DTR.

Comparison of ventilatory and oxygen consumption measurements of yearling Thoroughbred colts and fillies exercising unridden on an all-weather track.

Sex effects on ventilatory and oxygen consumption (V̇O2) measurements during exercise have been identified in humans. This study's aim was to evaluate the hypothesis that there are sex effects on ventilatory and V̇O2 measurements in exercising, untrained yearling Thoroughbreds (Tb). Forty-one Tbs (16 colts, 25 fillies; 19.8 ± 1.4 months old) were recruited. Physiological, ventilatory and exercise data were gathered from horses exercising unridden at high intensity on an all-weather track from a global positioning-heart rate unit and a portable ergospirometry system. Data were analysed with an unpaired Student's t-test and the Benjamini-Hochberg correction for multiple testing (P ≤ 0.05 significant). Mean bodyweight (BW, P = 0.002) and wither height (P = 0.04) were greater for colts than fillies. There were no differences in physiological and exercise data and absolute peak V̇O2 between groups. However, fillies had a higher mass specific peak V̇O2 (P = 0.03) than colts (121.5 ± 21.6 mL/kg.min vs. 111.9 ± 27.4 mL/kg.min). The peak breathing frequency was greater for fillies (P < 0.001) while the peak inspiratory (P < 0.001) and expiratory air flow (P < 0.001), peak expiratory tidal volume (VTE; P < 0.001) and peak minute ventilation (V̇E; P = 0.01) were greater for colts; there were no differences for peak VTE and V̇E when adjusted for BW. Differences in BW explain the differences in mass specific peak V̇O2 between groups. Given their morphological differences, it is likely that lung volumes and airway diameters are smaller for fillies, resulting in greater resistance and lower air flows and volumes. Further research is required to investigate the ventilatory differences and how they may change with maturation and impact performance.

Age-specific effects of density and weather on body condition and birth rates in a large herbivore, the Przewalski's horse.

Reproduction in young females can show a particularly sensitive response to environmental challenges, although empirical support from individual-based long-term studies is scarce. Based on a 20-year data set from a free-roaming Przewalski's horse population (Equus ferus przewalskii), we studied effects of large-herbivore density (horses + cattle) and weather conditions experienced during different life stages on females' annual birth rates. Foaling probability was very low in 2-year-olds, reaching maximum values in 5 to 10-year-olds, followed by a decrease in older females indicating reproductive senescence. Mother's previous reproductive investment affected her current reproduction; young and old mothers (as opposed to middle-aged ones), which had nursed a foal for at least 60 days during the previous year, reproduced with a lower probability. Foaling probability and body condition of young females were lower when large-herbivore density was high. Reproduction was also influenced by interactive weather effects during different life stages. Low late-summer precipitation during the females' year of birth was associated with a pronounced decrease in foaling probability in response to harsh late-winter temperatures prior to the mating season. In turn, increased amounts of late-summer rain during this early age together with more late-summer rain during the females' current pregnancy led to an increased reproductive probability in 2-3-year-olds. These results were corroborated by the ameliorating effects of late-summer rain on body condition in such females. In conclusion, our findings highlight the interactive importance of weather conditions experienced during early life, and of density and weather during current pregnancy on foaling probability, particularly in young females.

A Bayesian spatio-temporal study of the association between meteorological factors and the spread of COVID-19.

BACKGROUND: The spread of COVID-19 has brought challenges to health, social and economic systems around the world. With little to no prior immunity in the global population, transmission has been driven primarily by human interaction. However, as with common respiratory illnesses such as influenza some authors have suggested COVID-19 may become seasonal as immunity grows. Despite this, the effects of meteorological conditions on the spread of COVID-19 are poorly understood. Previous studies have produced contrasting results, due in part to limited and inconsistent study designs. METHODS: This study investigates the effects of meteorological conditions on COVID-19 infections in England using a Bayesian conditional auto-regressive spatio-temporal model. Our data consists of daily case counts from local authorities in England during the first lockdown from March-May 2020. During this period, legal restrictions limiting human interaction remained consistent, minimising the impact of changes in human interaction. We introduce a lag from weather conditions to daily cases to accommodate an incubation period and delays in obtaining test results. By modelling spatio-temporal random effects we account for the nature of a human transmissible virus, allowing the model to isolate meteorological effects. RESULTS: Our analysis considers cases across England's 312 local authorities for a 55-day period. We find relative humidity is negatively associated with COVID-19 cases, with a 1% increase in relative humidity corresponding to a reduction in relative risk of 0.2% [95% highest posterior density (HPD): 0.1-0.3%]. However, we find no evidence for temperature, wind speed, precipitation or solar radiation being associated with COVID-19 spread. The inclusion of weekdays highlights systematic under reporting of cases on weekends with between 27.2-43.7% fewer cases reported on Saturdays and 26.3-44.8% fewer cases on Sundays respectively (based on 95% HPDs). CONCLUSION: By applying a Bayesian conditional auto-regressive model to COVID-19 case data we capture the underlying spatio-temporal trends present in the data. This enables us to isolate the main meteorological effects and make robust claims about the association of weather variables to COVID-19 incidence. Overall, we find no strong association between meteorological factors and COVID-19 transmission.

Effects of temperature and humidity on cerebrovascular disease hospitalization in a super-aging society.

Weather conditions influence the incidence of cardiovascular disease. However, few studies have investigated the association between weather temperature and humidity and cerebrovascular disease hospitalizations in a super-aging society. We included 606,807 consecutive patients with cerebrovascular disease admitted to Japanese acute-care hospitals between 2015 and 2019. The primary outcome was the number of cerebrovascular disease hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of mean temperature and humidity, 1 day before hospital admission, with cerebrovascular disease hospitalizations, after adjusting for air pollution, hospital, and patient demographics. Lower mean temperatures and humidity < 70% or humidity ≧ 70% are associated with an increased incidence of cerebrovascular disease hospitalization (coefficient, - 1.442 [- 1.473 to - 1.411] per °C, p < 0.001, coefficient, - 0.084 [- 0.112 to - 0.056] per%, p < 0.001, and coefficient, 0.136 [0.103 to 0.168] per %, p < 0.001, respectively). Lower mean temperatures and extremely lower or higher humidity are associated with an increased incidence of cerebrovascular disease hospitalization in a super-aging society.

Moniliformin Occurrence in Serbian Maize over Four Years: Understanding Weather-Dependent Variability.

Moniliformin (MON) represents one of the most widespread emerging mycotoxins, whose presence in food and feed can potentially cause harmful effects on the health of both the public and animals. In order to investigate MON occurrence, a total of four hundred (n = 400) samples of unprocessed maize were sampled from different regions (Backa, Banat, and Srem) of Serbia during a period of four years (2018-2021) and were analyzed using a validated liquid chromatography with tandem mass spectrometry (LC-MS/MS) method. The influence of regional differences and variations from year to year in terms of weather conditions on the occurrence of MON was also assessed. The obtained validation parameters indicated that the LC-MS/MS method is applicable to the determination of MON in maize samples. It can be observed from the acquired findings that all samples were contaminated with MON, while concentration levels varied between the samples, especially from different sampling years. The maize samples showed the greatest levels of MON concentration during the dry and hot climatic conditions experienced in 2021. In maize samples harvested in the period 2018-2020, the MON concentration levels detected were about two to three times lower compared to the year 2021. Additionally, a comprehensive investigation into the correlation between weather conditions and the occurrence of MON in maize grown in Serbia was undertaken by reviewing the outcomes of research undertaken in the past decade.

Association between cognitive function and dusty weather: a propensity score matching study.

BACKGROUND: With a rapidly aging global population, the health of older adults is a national priority for countries across the world. Dusty weather has been demonstrated to be a potential risk factor of cognitive function among the elderly population. However, there is a paucity of studies exploring the associations between dusty weather and cognitive function among the older in China. METHODS: Data on individual characteristics were obtained from the China Health and Retirement Longitudinal Survey (CHARLS) 2018, whereas data on air pollution were sourced from environmental monitoring stations in China. Cognitive function, including general cognitive function, episodic memory, and linguistic competence, was assessed by self- or informant-questionnaires. We used propensity score matching and linear regression to investigate the relationship between dusty weather and cognitive function. Sensitivity analyses were conducted to test the robustness of the results. RESULTS: This study included 8,604 participants older than 60 years old. After controlling air pollutant weather, dusty weather was demonstrated to be positively associated with a decline in cognitive function (Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), 4.0, 95% confidence interval (CI): 3.11, 4.89; Mini-Mental State Exam (MMSE), 0.63, 95% CI: 0.34, 0.92). Results of sensitivity analysis showed that our research findings are robust. CONCLUSION: Older adults living in dusty weather regions suffered a higher level of cognitive impairment, and such adverse effects were more substantial among females compared with their male counterparts. Targeted health interventions to help older adults living in regions where dusty weather occurs frequently are suggested to be proposed.

Food retail environments, extreme weather, and their overlap: Exploratory analysis and recommendations for U.S. food policy.

Extreme weather events are increasing in frequency and severity due to climate change, yet many of their impacts on human populations are not well understood. We examine the relationship between prior extreme weather events and food environment characteristics. To do so, we conduct a U.S. county-level analysis that assesses the association between extreme weather events and two common food retail environment dimensions. Overall, we find a relationship between higher levels of historic extreme weather exposure and lower food availability and accessibility. In addition, we find heterogeneity in association across the distribution of the number of extreme weather events and event type. Specifically, we find that more localized extreme weather events are more associated with a reduction of access and availability than broad geographic events. Our findings suggest that as extreme weather events amplify in intensity and increase in frequency, new approaches for mitigating less acute and longer-term impacts are needed to address how extreme weather may interact with and reinforce existing disparities in food environment factors. Furthermore, our research argues that integrated approaches to improving vulnerable food retail environments will become an important component of extreme weather planning and should be a consideration in both disaster- and food-related policy.

Aerosol optical properties over the South Atlantic and southern ocean during the 2010-2012 summer seasons as part of the global maritime aerosol network.

Aerosols have implications to climate and biogeochemical cycles in the global oceans. At sites under indirect influence of dust emitted by the Patagonian semi-desert, a debate exists on the potential fertilization effects of iron enriched aerossol. Considering this subject we conducted measurements of aerosols optical properties using a Microtops II sun photometer to access aerosol size distributions and other intrinsic properties oversea from Atlantic Southern mid-latitudes to Antarctica. Oceanographic cruises were developed between December 2010 to April 2011 and October 2011 to April 2012, in the context of the Brazilian Antarctic Program, and between November 2011 to December 2011. This survey was taken as part of the Global Maritime Aerosol Network (MAN/NASA). Our data of AOD (500 nm) along the South American coast depicts a steady decrease southwards following the decreased latitudinal continental extent. However, the influence of the aerosols blown from Patagonia semi-desert region was clear from latitude 53°S to 64°S. The predominance of aerosol fine mode was observed in Central Atlantic and close to the Drake Passage. An unexpected aerosol coarse mode predominance was found close to the Antarctic Peninsula. We attribute that to a possible weathering of rock outcrops due to the strong westerly winds in that region.

Drought trends projection under future climate change scenarios for Iran region.

The study highlights the potential characteristics of droughts under future climate change scenarios. For this purpose, the changes in Standardized Precipitation Evapotranspiration Index (SPEI) under the A1B, A2, and B1 climate change scenarios in Iran were assessed. The daily weather data of 30 synoptic stations from 1992 to 2010 were analyzed. The HadCM3 statistical model in the LARS-WG was used to predict the future weather conditions between 2011 and 2112, for three 34-year periods; 2011-2045, 2046-2079, and 2080-2112. In regard to the findings, the upward trend of the potential evapotranspiration in parallel with the downward trend of the precipitation in the next 102 years in three scenarios to the base timescale was transparent. The frequency of the SPEI in the base month indicated that 17.02% of the studied months faced the drought. Considering the scenarios of climate change for three 34-year periods (i.e., 2011-2045, 2046-2079, and 2080-2112) the average percentages of potential drought occurrences for all the stations in the next three periods will be 8.89, 16.58, and 27.27 respectively under the B1 scenario. While the predicted values under the A1B scenario are 7.63, 12.66, and 35.08%respectively. The relevant findings under the A2 scenario are 6.73, 10.16, 40.8%. As a consequence, water shortage would be more serious in the third period of study under all three scenarios. The percentage of drought occurrence in the future years under the A2, B1, and A1B will be 19.23%, 17.74%, and 18.84%, respectively which confirms the worst condition under the A2 scenario. For all stations, the number of months with moderate drought was substantially more than severe and extreme droughts. Considering the A2 scenario as a high emission scenario, the analysis of SPEI frequency illustrated that the proportion of dry periods in regions with humid and cool climate is more than hot and warm climates; however, the duration of dry periods in warmer climates is longer than colder climates. Moreover, the temporal distribution of precipitation and potential evapotranspiration indicated that in a large number of stations, there is a significant difference between them in the middle months of the year, which justifies the importance of prudent water management in warm months.