scholarly journals Wpływ warunków meteorologicznych na zachorowalność na grypę w wybranych polskich miastach = Impact of meteorological conditions on influenza morbidity in the selected Polish cities

2021 ◽  
Vol 93 (1) ◽  
pp. 103-122
Author(s):  
Katarzyna Lindner-Cendrowska
Keyword(s):  
Wind Speed ◽  
Negative Binomial ◽  
Climatic Factors ◽  
Age Groups ◽  
Absolute Humidity ◽  
Weather Conditions ◽  
Adverse Weather ◽  
Strong Negative Association ◽  
Lag Model ◽  
The Impact

This study was designed to explore the impact of meteorological factors (air temperature, relative and absolute humidity, wind, cloudiness and precipitation) on influenza morbidity in four selected big cities in Poland – Cracow, Poznań, Warsaw and Wrocław. Atmospheric data obtained from four meteorological stations spread over six years (2013‑2018) were compared to influenza-like illnesses (ILI) reports, obtained from the Voivodship Units of the State Sanitary Inspection for the same locations and period. Data were analysed using Spearman correlation and negative binomial regressions to capture the nonlinear relationship between exposure to environmental conditions and influenza morbidity. Our study found a strong negative association of absolute air humidity with influenza infections (RR = 0.738) and positive relationship with minimal temperature (RR = 1.148). The effect of wind speed, cloudiness and precipitation on ILI was less evident. Proposed model is valid for all age groups in Polish cities, but suits the best to elderly citizens (65+). The model is also appropriate for different seasons, however only absolute humidity, minimal temperature and wind speed are considered significant variables all year round. Furthermore, we observed 6 to 9-days delay between particular adverse weather conditions and ILI morbidity increase, as 1-week lag model proved to have the highest predictive power (AIC = 8644.97). Although meteorological variables have statistically significant contribution to explain influenza morbidity, there are also other non-climatic factors, that can possibly influence the seasonality and complexity of influenza epidemiology in Polish cities.

scholarly journals Urban Road Crashes and Weather Conditions: Untangling the Effects

2019 ◽  
Vol 11 (11) ◽  
pp. 3176 ◽  
Author(s):  
António Lobo ◽  
Sara Ferreira ◽  
Isabel Iglesias ◽  
António Couto
Keyword(s):  
Negative Binomial ◽  
Weather Conditions ◽  
Crash Risk ◽  
Traffic Crash ◽  
Road Crashes ◽  
Road Users ◽  
Poisson Models ◽  
Adverse Weather ◽  
Single Vehicle ◽  
The Impact

Most previous studies show that inclement weather increases the risk of road users being involved in a traffic crash. However, some authors have demonstrated a little or even an opposite effect, observed both on crash frequency and severity. In urban roads, where a greater number of conflict points and heavier traffic represent a higher exposure to risk, the potential increase of crash risk caused by adverse weather deserves a special attention. This study investigates the impact of meteorological conditions on the frequency of road crashes in urban environment, using the city of Porto, Portugal as a case study. The weather effects were analyzed for different types of crashes: single-vehicle, multi-vehicle, property-damage-only, and injury crashes. The methodology is based on negative binomial and Poisson models with random parameters, considering the influence of daily precipitation and mean temperature, as well as the lagged effects of the precipitation accumulated during the previous month. The results show that rainy days are more prone to the occurrence of road crashes, although the past precipitation may attenuate such effect. Temperatures below 10 °C are associated with higher crash frequencies, complying with the impacts of precipitation in the context of the Portuguese climate characteristics.

Evaluating seasonal risk and the potential for windspeed reductions to reduce chill index at six locations using GrassGro

2012 ◽  
Vol 52 (10) ◽  
pp. 921 ◽  
Author(s):  
J. C. Broster ◽  
S. M. Robertson ◽  
R. L. Dehaan ◽  
B. J. King ◽  
M. A. Friend
Keyword(s):  
Wind Speed ◽  
Low Temperature ◽  
Heat Loss ◽  
Climatic Factors ◽  
Weather Conditions ◽  
Climate Data ◽  
Support Tool ◽  
Adverse Weather Conditions ◽  
Eastern Australia ◽  
Adverse Weather

The death of newborn lambs is a major factor influencing the reproductive efficiency of sheep enterprises. Adverse weather conditions (wind, precipitation and low temperature), either alone or in combination (chill index), can increase the level of newborn lamb mortality to over 50% of births for short periods through increased heat loss. The provision of shelter to reduce wind speed and therefore chill index (heat loss) has been shown to reduce lamb mortality; however, the reduction in mortality has been variable. This study used the decision support tool GrassGro to determine the likelihood of adverse weather conditions occurring at six locations across south-eastern Australia which varied widely in climate. Data were extracted for 24 consecutive weekly periods between May and October over 39 years (1968–2006) to evaluate daily precipitation, temperature, radiation, wind speed and chill index. The minimum, maximum and median values were calculated for all climatic factors for every week and year combination. The effectiveness of reducing wind speed to reduce the occurrence of a high chill index was also evaluated. The severity of these weather events varied between locations with the median weekly chill index rarely exceeding 1000 kJ/m2.h at Temora, but at both Hamilton and Orange this occurred in over two-thirds of the weeks examined. Reducing wind speed by 50% reduced the number of weeks with a median chill index exceeding 1000 kJ/m2.h in twice as many weeks at Hamilton and Yass compared with Orange. These results show that the potential for shelter to reduce chill index will vary according to the location and time of year. In locations where another climatic factor, such as low temperature or rainfall, has a greater influence on the chill index, shelter which only reduces wind speed, will be less effective than at locations where wind speed is the driver of chill index.

Modelling of 10 Gbps Free Space Optics Communication Link Using Array of Receivers in Moderate and Harsh Weather Conditions

2017 ◽  
Vol 38 (3) ◽  
Author(s):  
Amit Gupta ◽  
Nagpal Shaina
Keyword(s):  
Free Space ◽  
Weather Conditions ◽  
Quality Data ◽  
Laser Source ◽  
Communication Link ◽  
Free Space Optical ◽  
Space Optics ◽  
Received Power ◽  
Adverse Weather ◽  
The Impact

AbstractIntersymbol interference and attenuation of signal are two major parameters affecting the quality of transmission in Free Space Optical (FSO) Communication link. In this paper, the impact of these parameters on FSO communication link is analysed for delivering high-quality data transmission. The performance of the link is investigated under the influence of amplifier in the link. The performance parameters of the link like minimum bit error rate, received signal power and Quality factor are examined by employing erbium-doped fibre amplifier in the link. The effects of amplifier are visualized with the amount of received power. Further, the link is simulated for moderate weather conditions at various attenuation levels on transmitted signal. Finally, the designed link is analysed in adverse weather conditions by using high-power laser source for optimum performance.

scholarly journals Dominant climatic factors driving annual runoff changes at the catchment scale across China

2016 ◽  
Vol 20 (7) ◽  
pp. 2573-2587 ◽  
Author(s):  
Zhongwei Huang ◽  
Hanbo Yang ◽  
Dawen Yang
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Climate Changes ◽  
Climatic Factors ◽  
Southern China ◽  
Resource Planning ◽  
Annual Runoff ◽  
Net Radiation ◽  
Catchment Scale ◽  
The Impact

Abstract. With global climate changes intensifying, the hydrological response to climate changes has attracted more attention. It is beneficial not only for hydrology and ecology but also for water resource planning and management to understand the impact of climate change on runoff. In addition, there are large spatial variations in climate type and geographic characteristics across China. To gain a better understanding of the spatial variation of the response of runoff to changes in climatic factors and to detect the dominant climatic factors driving changes in annual runoff, we chose the climate elasticity method proposed by Yang and Yang (2011). It is shown that, in most catchments of China, increasing air temperature and relative humidity have negative impacts on runoff, while declining net radiation and wind speed have positive impacts on runoff, which slow the overall decline in runoff. The dominant climatic factors driving annual runoff are precipitation in most parts of China, net radiation mainly in some catchments of southern China, air temperature and wind speed mainly in some catchments in northern China.

Comparison of two gap-filling techniques for nitrous oxide fluxes from agricultural soil

2019 ◽  
Vol 99 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Rezvan Taki ◽  
Claudia Wagner-Riddle ◽  
Gary Parkin ◽  
Rob Gordon ◽  
Andrew VanderZaag
Keyword(s):  
Missing Values ◽  
Interpolation Method ◽  
Weather Conditions ◽  
Linear Interpolation ◽  
Bias Error ◽  
Research Station ◽  
Ann Model ◽  
Gap Filling ◽  
Adverse Weather ◽  
The Impact

Micrometeorological methods are ideally suited for continuous measurements of N2O fluxes, but gaps in the time series occur due to low-turbulence conditions, power failures, and adverse weather conditions. Two gap-filling methods including linear interpolation and artificial neural networks (ANN) were utilized to reconstruct missing N2O flux data from a corn–soybean–wheat rotation and evaluate the impact on annual N2O emissions from 2001 to 2006 at the Elora Research Station, ON, Canada. The single-year ANN method is recommended because this method captured flux variability better than the linear interpolation method (average R2 of 0.41 vs. 0.34). Annual N2O emission and annual bias resulting from linear and single-year ANN were compatible with each other when there were few and short gaps (i.e., percentage of missing values <30%). However, with longer gaps (>20 d), the bias error in annual fluxes varied between 0.082 and 0.344 kg N2O-N ha−1 for linear and 0.069 and 0.109 kg N2O-N ha−1 for single-year ANN. Hence, the single-year ANN with lower annual bias and stable approach over various years is recommended, if the appropriate driving inputs (i.e., soil temperature, soil water content, precipitation, N mineral content, and snow depth) needed for the ANN model are available.

scholarly journals An Advanced Deep Learning Approach for Multi-Object Counting in Urban Vehicular Environments

2021 ◽  
Vol 13 (12) ◽  
pp. 306
Author(s):  
Ahmed Dirir ◽  
Henry Ignatious ◽  
Hesham Elsayed ◽  
Manzoor Khan ◽  
Mohammed Adib ◽  
...  
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Weather Conditions ◽  
Research Area ◽  
Transportation Systems ◽  
Detection Accuracy ◽  
Adverse Weather ◽  
Object Counting ◽  
The Impact

Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle counting plays a crucial role in urban planning and management of the Intelligent Transportation Systems (ITS). Several approaches have been proposed in the literature to address this problem. However, the resulting detection accuracy is still not adequate. This paper proposes an efficient approach that uses deep learning concepts and correlation filters for multi-object counting and tracking. The performance of the proposed system is evaluated using a dataset consisting of 16 videos with different features to examine the impact of object density, image quality, angle of view, and speed of motion towards system accuracy. Performance evaluation exhibits promising results in normal traffic scenarios and adverse weather conditions. Moreover, the proposed approach outperforms the performance of two recent approaches from the literature.

scholarly journals Incorporating calendar effects to predict influenza seasonality in Milwaukee, Wisconsin

2019 ◽  
Vol 147 ◽  
Author(s):  
Ryan B. Simpson ◽  
Tania M. Alarcon Falconi ◽  
Aishwarya Venkat ◽  
Kenneth H. H. Chui ◽  
Jose Navidad ◽  
...  
Keyword(s):  
Public Schools ◽  
Negative Binomial ◽  
Age Groups ◽  
Influenza Surveillance ◽  
Influenza B ◽  
Sporting Events ◽  
Seasonal Incidence ◽  
Calendar Effects ◽  
Holiday Effects ◽  
The Impact

Abstract Social outings can trigger influenza transmission, especially in children and elderly. In contrast, school closures are associated with reduced influenza incidence in school-aged children. While influenza surveillance modelling studies typically account for holidays and mass gatherings, age-specific effects of school breaks, sporting events and commonly celebrated observances are not fully explored. We examined the impact of school holidays, social events and religious observances for six age groups (all ages, ⩽4, 5–24, 25–44, 45–64, ⩾65 years) on four influenza outcomes (tests, positives, influenza A and influenza B) as reported by the City of Milwaukee Health Department Laboratory, Milwaukee, Wisconsin from 2004 to 2009. We characterised holiday effects by analysing average weekly counts in negative binomial regression models controlling for weather and seasonal incidence fluctuations. We estimated age-specific annual peak timing and compared influenza outcomes before, during and after school breaks. During the 118 university holiday weeks, average weekly tests were lower than in 140 school term weeks (5.93 vs. 11.99 cases/week, P < 0.005). The dampening of tests during Winter Break was evident in all ages and in those 5–24 years (RR = 0.31; 95% CI 0.22–0.41 vs. RR = 0.14; 95% CI 0.09–0.22, respectively). A significant increase in tests was observed during Spring Break in 45–64 years old adults (RR = 2.12; 95% CI 1.14–3.96). Milwaukee Public Schools holiday breaks showed similar amplification and dampening effects. Overall, calendar effects depend on the proximity and alignment of an individual holiday to age-specific and influenza outcome-specific peak timing. Better quantification of individual holiday effects, tailored to specific age groups, should improve influenza prevention measures.

Investigating the Impact of Rainfall on Travel Speed

2014 ◽  
Vol 71 (3) ◽  
Author(s):  
Nordiana Mashros ◽  
Johnnie Ben-Edigbe ◽  
Hashim Mohammed Alhassan ◽  
Sitti Asmah Hassan
Keyword(s):  
Empirical Studies ◽  
Heavy Rain ◽  
Weather Conditions ◽  
Travel Speed ◽  
Operating Conditions ◽  
Speed Reduction ◽  
Light Rain ◽  
Rainfall Condition ◽  
Adverse Weather ◽  
The Impact

The road network is particularly susceptible to adverse weather with a range of impacts when different weather conditions are experienced. Adverse weather often leads to decreases in traffic speed and subsequently affects the service levels. The paper is aimed at investigating the impact of rainfall on travel speed and quantifying the extent to which travel speed reduction occurs. Empirical studies were conducted on principle road in Terengganu and Johor, respectively for three months. Traffic data were collected by way of automatic traffic counter and rainfall data from the nearest raingauge station were supplied by the Department of Irrigation and Drainage supplemented by local survey data. These data were filtered to obtain traffic flow information for both dry and wet operating conditions and then were analyzed to see the effect of rainfall on percentile speeds. The results indicated that travel speed at 15th, 50th and 85th percentiles decrease with increasing rainfall intensities. It was observed that allpercentile speeds decreased from a minimum of 1% during light rain to a maximum of 14% during heavy rain. Based on the hypothesis that travel speed differ significantly between dry and rainfall condition; the study found substantial changes in percentile speeds and concluded that rainfalls irrespective of their intensities have significant impact on the travel speed.

scholarly journals Evaluation of community coalition training effects on youth hospital-admitted injury incidence in Victoria, Australia: 2001–2017

2019 ◽  
Vol 26 (5) ◽  
pp. 463-470 ◽  
Author(s):  
Janneke Berecki-Gisolf ◽  
Bosco Rowland ◽  
Nicola Reavley ◽  
Barbara Minuzzo ◽  
John Toumbourou
Keyword(s):  
Risk Factors ◽  
Injury Risk ◽  
Negative Binomial ◽  
Hospital Admissions ◽  
Intervention Strategy ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Population Based ◽  
Injury Incidence ◽  
The Impact

BackgroundInjuries are one of the three leading causes of morbidity and mortality for young people internationally. Although community risk factors are modifiable causes of youth injury, there has been limited evaluation of community interventions. Communities That Care (CTC) offers a coalition training process to increase evidence-based practices that reduce youth injury risk factors.MethodUsing a non-experimental design, this study made use of population-based hospital admissions data to evaluate the impact on injuries for 15 communities that implemented CTC between 2001 and 2017 in Victoria, Australia. Negative binomial regression models evaluated trends in injury admissions (all, unintentional and transport), comparing CTC and non-CTC communities across different age groups.ResultsStatistically significant relative reductions in all hospital injury admissions in 0–4 year olds were associated with communities completing the CTC process and in 0–19 year olds when communities began their second cycle of CTC. When analysed by subgroup, a similar pattern was observed with unintentional injuries but not with transport injuries.ConclusionThe findings support CTC coalition training as an intervention strategy for preventing youth hospital injury admissions. However, future studies should consider stronger research designs, confirm findings in different community contexts, use other data sources and evaluate intervention mechanisms.

Effectiveness of Predictive Weather-Related Active Transportation and Demand Management Strategies for Network Management

2017 ◽  
Vol 2667 (1) ◽  
pp. 71-87 ◽  
Author(s):  
Zihan Hong ◽  
Hani S. Mahmassani ◽  
Xiang Xu ◽  
Archak Mittal ◽  
Ying Chen ◽  
...  
Keyword(s):  
Traffic Management ◽  
Demand Management ◽  
Management Strategies ◽  
Weather Conditions ◽  
Active Transportation ◽  
Operational Conditions ◽  
Traffic Conditions ◽  
Adverse Weather ◽  
Traffic Performance ◽  
The Impact

This paper presents the development, implementation, and evaluation of predictive active transportation and demand management (ATDM) and weather-responsive traffic management (WRTM) strategies to support operations for weather-affected traffic conditions with traffic estimation and prediction system models. First, the problem is defined as a dynamic process of traffic system evolution under the impact of operational conditions and management strategies (interventions). A list of research questions to be addressed is provided. Second, a systematic framework for implementing and evaluating predictive weather-related ATDM strategies is illustrated. The framework consists of an offline model that simulates and evaluates the traffic operations and an online model that predicts traffic conditions and transits information to the offline model to generate or adjust traffic management strategies. Next, the detailed description and the logic design of ATDM and WRTM strategies to be evaluated are proposed. To determine effectiveness, the selection of strategy combination and sensitivity of operational features are assessed with a series of experiments implemented with a locally calibrated network in the Chicago, Illinois, area. The analysis results confirm the models’ ability to replicate observed traffic patterns and to evaluate the system performance across operational conditions. The results confirm the effectiveness of the predictive strategies tested in managing and improving traffic performance under adverse weather conditions. The results also verify that, with the appropriate operational settings and synergistic combination of strategies, weather-related ATDM strategies can generate maximal effectiveness to improve traffic performance.

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