scholarly journals Perceived Influence of Weather Conditions on Rheumatic Pain in Romania

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Adina-Eliza Croitoru ◽  
Gabriela Dogaru ◽  
Titus Cristian Man ◽  
Simona Mălăescu ◽  
Marieta Motricală ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Pain Intensity ◽  
Air Temperature ◽  
Correlation Matrix ◽  
Great Majority ◽  
Weather Conditions ◽  
Weather Variables ◽  
Rheumatic Pain ◽  
Atmospheric Fronts ◽  
The Relationship

The main objective of this study was to analyze the perception of the influence of various weather conditions on patients with rheumatic pathology. A group of 394 patients, aged between 39 and 87 years and diagnosed with degenerative rheumatic diseases, were interviewed individually by using a questionnaire created specifically for this study. Further on, to assess the relationship between pain intensity and weather conditions, a frequency analysis based on Pearson’s correlation matrix was employed. The most important results are as follows: the great majority of the participants (more than 75%) believe that their rheumatic pain is definitely or to a great extent influenced by different weather conditions; most of the patients reported intensification of their pain with weather worsening, especially when cloudiness and humidity suddenly increase (83.8% and 82.0%, respectively), air temperature suddenly decreases (81.5%), and in fog or rain conditions (81.2%). In our research, alongside simple meteorological variables, we established that complex weather variables such as atmospheric fronts, in particular, the cold ones and winter anticyclonic conditions, greatly intensify the rheumatic pain, whereas summer anticyclonic conditions usually lead to a decrease in pain severity. In terms of relationships between pain intensity and weather conditions, we found the strongest correlations (ranging between 0.725 and 0.830) when temperature, relative humidity, and cloudiness are constantly high.

scholarly journals Assessment of the Relationship between Cerebrospinal Meningitis and Climate Variables in Kaduna State, Nigeria

2021 ◽  
pp. 33-41
Author(s):  
Joyce Imara Nchom ◽  
A. S. Abubakar ◽  
F. O. Arimoro ◽  
B. Y. Mohammed
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Linear Trend ◽  
Pearson Correlation ◽  
Maximum Temperature ◽  
Data Set ◽  
International Research Institute ◽  
Wind Speed Maximum ◽  
Weather Parameters ◽  
The Relationship

This study examines the relationship between Meningitis and weather parameters (air temperature, maximum temperature, relative humidity, and rainfall) in Kaduna state, Nigeria on a weekly basis from 2007–2019. Meningitis data was acquired weekly from Nigeria Centre for Disease Control (NCDC), Bureau of Statistics and weather parameters were sourced from daily satellite data set National Oceanic and Atmospheric Administration (NOAA), International Research Institute for Climate and Society (IRI). The daily data were aggregated weekly to suit the study. The data were analysed using linear trend and Pearson correlation for relationship. The linear trend results revealed a weekly decline in Cerebro Spinal Meningitis (CSM), wind speed, maximum and air temperature and an increase in relative humidity and rainfall. Generally, results reveal that the most important explanatory weather variables influencing CSM amongst the five (5) are the weekly maximum temperature and air temperature with a positive correlation of 0.768 and 0.773. This study recommends that keen interest be placed on temperature as they play an essential role in the transmission of this disease and most times aggravate the patients' condition.

scholarly journals Modeling Infection of Strawberry Flowers by Botrytis cinerea Using Field Data

2000 ◽  
Vol 90 (12) ◽  
pp. 1367-1374 ◽  
Author(s):  
Xiangming Xu ◽  
David C. Harris ◽  
Angela M. Berrie
Keyword(s):  
Vapor Pressure ◽  
Botrytis Cinerea ◽  
Vapor Pressure Deficit ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Gray Mold ◽  
Weather Variables ◽  
Infection Models ◽  
The Relationship ◽  
Field Plots

The incidence of strawberry flower infection by Botrytis cinerea was monitored in unsprayed field plots in three successive years together with meteorological data and numbers of conidia in the air. There were large differences in conidia numbers and weather conditions in the 3 years. Three sets of models were derived to relate inoculum and weather conditions to the incidence of flower infection; by inoculum only, by weather variables only, and by both inoculum and weather variables. All the models fitted the observed incidence satisfactorily. High inoculum led to more infection. Models using weather variables only gave more accurate predictions than models using inoculum only. Models using both weather variables and inoculum gave the best predictions, but the improvement over the models based on weather variables only was small. The relationship between incidence of flower infection and inoculum and weather variables was generally consistent between years. Of the weather variables examined, daytime vapor pressure deficit and nighttime temperature had the greatest effect in determining daily incidence of flower infection. Infection was favored by low day vapor pressure deficit and high night temperature. The accuracy and consistency of the weather-based models suggest they could be explored to assist in management of gray mold.

scholarly journals A Site-Specific, Weather-Based Disease Regression Model for Sclerotinia Blight of Peanut

Plant Disease ◽  
2007 ◽  
Vol 91 (11) ◽  
pp. 1436-1444 ◽  
Author(s):  
D. L. Smith ◽  
J. E. Hollowell ◽  
T. G. Isleib ◽  
B. B. Shew
Keyword(s):  
Relative Humidity ◽  
Soil Temperature ◽  
Air Temperature ◽  
Partial Resistance ◽  
Production Costs ◽  
Weather Data ◽  
Weather Variables ◽  
Site Specific ◽  
Sclerotinia Blight ◽  
Blight Disease

In North Carolina, losses due to Sclerotinia blight of peanut, caused by the fungus Sclerotinia minor, are an estimated 1 to 4 million dollars annually. In general, peanut (Arachis hypogaea) is very susceptible to Sclerotinia blight, but some partially resistant virginia-type cultivars are available. Up to three fungicide applications per season are necessary to maintain a healthy crop in years highly favorable for disease development. Improved prediction of epidemic initiation and identification of periods when fungicides are not required would increase fungicide efficiency and reduce production costs on resistant and susceptible cultivars. A Sclerotinia blight disease model was developed using regression strategies in an effort to describe the relationships between modeled environmental variables and disease increase. Changes in incremental disease incidence (% of newly infected plants of the total plant population per plot) for the 2002–2005 growing seasons were statistically transformed and described using 5-day moving averages of modeled site-specific weather variables (localized, mathematical estimations of weather data derived at a remote location) obtained from SkyBit (ZedX, Inc.). Variables in the regression to describe the Sclerotinia blight disease index included: mean relative humidity (linear and quadratic), mean soil temperature (quadratic), maximum air temperature (linear and quadratic), maximum relative humidity (linear and quadratic), minimum air temperature (linear and quadratic), minimum relative humidity (linear and quadratic), and minimum soil temperature (linear and quadratic). The model explained approximately 50% of the variability in Sclerotinia blight index over 4 years of field research in eight environments. The relationships between weather variables and Sclerotinia blight index were independent of host partial resistance. Linear regression models were used to describe progress of Sclerotinia blight on cultivars and breeding lines with varying levels of partial resistance. Resistance affected the rate of disease progress, but not disease onset. The results of this study will be used to develop site- and cultivar-specific spray advisories for Sclerotinia blight.

scholarly journals Weather Conditions Associated with the Release and Dispersal of Zymoseptoria tritici Spores in the Argentine Pampas Region

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
C. A. Cordo ◽  
C. I. Mónaco ◽  
R. Altamirano ◽  
A. E. Perelló ◽  
S. Larrán ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Control Strategies ◽  
Weather Conditions ◽  
Sampling Interval ◽  
Wheat Crop ◽  
Zymoseptoria Tritici ◽  
Spore Release ◽  
Wheat Stubble ◽  
One Year ◽  
The Relationship

The abundance of Zymoseptoria tritici ascospores and conidia in a field was examined throughout two one-year periods (1998-1999 and 1999-2000) establishing the relationship between spore release and weather variables. Radiation, temperature, intensity of rainfall, and relative humidity significantly affected the dispersal of ascospores and pycnidiospores of this pathogen. Spore traps collected both types of spores, at weekly intervals, at two different stages of the wheat crop (vegetative and wheat stubble stages) and different distances from the sources. Ascospores were the predominant sources of inoculum in the field. The numbers of ascospores and pycnidiospores declined with the increase of distance from the sources. The release of pycnidiospores was associated with the increase in rainfall intensity 7 days before the released event and the increase in radiation 60 days before the same event. Relative humidity 3 and 15 days before the release event was positively correlated with ascospores release and negatively correlated with radiation and temperature in all the sampling interval. Also for the first time, a positive correlation between radiation and pycnidiospores dispersal is reported. Understanding the relationship between environment conditions and spores dispersal event could improve the control strategies of the disease.

scholarly journals Effect of meteorological factors on influenza-like illness from 2012 to 2015 in Huludao, a northeastern city in China

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6919 ◽  
Author(s):  
Ying-Long Bai ◽  
De-Sheng Huang ◽  
Jing Liu ◽  
De-Qiang Li ◽  
Peng Guan
Keyword(s):  
Relative Humidity ◽  
Vapor Pressure ◽  
Air Temperature ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Lag Time ◽  
Temperature Minimum ◽  
The Relationship ◽  
Maximum Air Temperature ◽  
Minimum Air Temperature

Background This study aims to describe the epidemiological patterns of influenza-like illness (ILI) in Huludao, China and seek scientific evidence on the link of ILI activity with weather factors. Methods Surveillance data of ILI cases between January 2012 and December 2015 was collected in Huludao Central Hospital, meteorological data was obtained from the China Meteorological Data Service Center. Generalized additive model (GAM) was used to seek the relationship between the number of ILI cases and the meteorological factors. Multiple Smoothing parameter estimation was made on the basis of Poisson distribution, where the number of weekly ILI cases was treated as response, and the smoothness of weather was treated as covariates. Lag time was determined by the smallest Akaike information criterion (AIC). Smoothing coefficients were estimated for the prediction of the number of ILI cases. Results A total of 29, 622 ILI cases were observed during the study period, with children ILI cases constituted 86.77%. The association between ILI activity and meteorological factors varied across different lag periods. The lag time for average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity were 2, 2, 1, 1 and 0 weeks, respectively. Average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity could explain 16.5%, 9.5%, 18.0%, 15.9% and 7.7% of the deviance, respectively. Among the temperature indexes, the minimum temperature played the most important role. The number of ILI cases peaked when minimum temperature was around −13 °C in winter and 18 °C in summer. The number of cases peaked when the relative humidity was equal to 43% and then began to decrease with the increase of relative humidity. When the humidity exceeded 76%, the number of ILI cases began to rise. Conclusions The present study first analyzed the relationship between meteorological factors and ILI cases with special consideration of the length of lag period in Huludao, China. Low air temperature and low relative humidity (cold and dry weather condition) played a considerable role in the epidemic pattern of ILI cases. The trend of ILI activity could be possibly predicted by the variation of meteorological factors.

scholarly journals Effects of Air Temperature and Relative Humidity on Coronavirus Survival on Surfaces

2010 ◽  
Vol 76 (9) ◽  
pp. 2712-2717 ◽  
Author(s):  
Lisa M. Casanova ◽  
Soyoung Jeon ◽  
William A. Rutala ◽  
David J. Weber ◽  
Mark D. Sobsey
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Hepatitis Virus ◽  
Control Measures ◽  
Transmissible Gastroenteritis Virus ◽  
Indoor Environments ◽  
Environmental Surfaces ◽  
Transmissible Gastroenteritis ◽  
And Control ◽  
The Relationship

ABSTRACT Assessment of the risks posed by severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) on surfaces requires data on survival of this virus on environmental surfaces and on how survival is affected by environmental variables, such as air temperature (AT) and relative humidity (RH). The use of surrogate viruses has the potential to overcome the challenges of working with SARS-CoV and to increase the available data on coronavirus survival on surfaces. Two potential surrogates were evaluated in this study; transmissible gastroenteritis virus (TGEV) and mouse hepatitis virus (MHV) were used to determine effects of AT and RH on the survival of coronaviruses on stainless steel. At 4°C, infectious virus persisted for as long as 28 days, and the lowest level of inactivation occurred at 20% RH. Inactivation was more rapid at 20°C than at 4°C at all humidity levels; the viruses persisted for 5 to 28 days, and the slowest inactivation occurred at low RH. Both viruses were inactivated more rapidly at 40°C than at 20°C. The relationship between inactivation and RH was not monotonic, and there was greater survival or a greater protective effect at low RH (20%) and high RH (80%) than at moderate RH (50%). There was also evidence of an interaction between AT and RH. The results show that when high numbers of viruses are deposited, TGEV and MHV may survive for days on surfaces at ATs and RHs typical of indoor environments. TGEV and MHV could serve as conservative surrogates for modeling exposure, the risk of transmission, and control measures for pathogenic enveloped viruses, such as SARS-CoV and influenza virus, on health care surfaces.

scholarly journals Effect of Lockdown,Temperature,and Humidity on the Pattern of COVID-19 in Erbil Province,Kurdistan Region, Iraq

2021 ◽  
Vol 20 (2) ◽  
pp. 56-67
Author(s):  
Rundk Hwaiz ◽  
◽  
Katan Ali ◽  
Namir Al-Tawil
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Death Rate ◽  
Weather Conditions ◽  
World Health ◽  
The Novel ◽  
Number Of Patients ◽  
Temperature And Humidity ◽  
Novel Coronavirus ◽  
Health Organization

Background: COVID-19 was first reported in Erbil province in Iraq on March 19, 2020. The effect of lockdown on reducing the spread of the novel coronavirus and the effect of weather conditions (air temperature and humidity) on the daily reported number of cases and death rate of COVID-19 were investigated during April to July, 2020. Objective: To investigate the effect of lock down on reducing the spread of the novel coronavirus pandemic and the effect of weather conditions (air temperature and humidity) on the daily reported number of cases and death rate of COVID-19. Patients and Methods: The data collected during three different periods, the first (total lockdown), followed by the second period of lockdown relaxation, which was followed by the third period (interrupted relaxation of lockdown) that reported hundreds of new cases daily. The real-time PCR .assay was performed on suspected COVID-19 patients according to the protocol established by the World Health Organization. Results: Temperature and relative humidity were recorded in Erbil city in Iraq. Patients’ age ranged (2-70) years old. Out of (1469) patients confirmed positive with COVID-19, 57.7% of them were males, 31.3% were females, and the rest (11%) were children. The mean number of patients per day was 32.77 during the period of interrupted relaxation lockdown which was significantly higher than in the total-lock down period (3.88 patient), and the relaxation lockdown period (1.93 patient). The mortality rate per day was 0.77 during the period of interrupted relaxation lockdown was significantly higher than the rates (0.0%) of the other periods. Moreover, increasing the temperature increased the number of confirmed cases in July while, low relative humidity significantly increased the rate of reported cases. Conclusion: The increase in the number of reported cases of COVID-19, might be related to the interruption of lockdown. Moreover, the daily reported cases and mortality rates increased by increasing the temperature from April to June.

scholarly journals How is COVID-19 affected by weather? Meta-regression of 158 studies and recommendations for best practices in future research

2021 ◽  
Author(s):  
Ling Tan ◽  
David M. Schultz
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Best Practices ◽  
Air Temperature ◽  
Time Lag ◽  
Geographical Location ◽  
Weather Conditions ◽  
Future Research ◽  
Weather Variables ◽  
Meta Regression

AbstractBecause many viral respiratory diseases show seasonal cycles, weather conditions could affect the spread of COVID-19. Although many studies pursued this possible link early in the pandemic, their results were inconsistent. Here, we assembled 158 quantitative empirical studies examining the link between weather and COVID-19. A meta-regression analysis was performed on their 4,793 correlation coefficients to explain these inconsistent results. We found four principal findings. First, 80 of the 158 studies did not state the time lag between infection and reporting, rendering these studies ineffective in determining the weather–COVID-19 relationship. Second, the research outcomes depended on the statistical analysis methods employed in each study. Specifically, studies using correlation tests produced outcomes that were functions of the geographical locations of the data from the original studies, whereas studies using linear regression produced outcomes that were functions of the analyzed weather variables. Third, Asian countries had more positive associations for air temperature than other regions, possibly because the air temperature was undergoing its seasonal increase from winter to spring during the rapid outbreak of COVID-19 in these countries. Fourth, higher solar energy was associated with reduced COVID-19 spread, regardless of statistical analysis method and geographical location. These results help interpret the inconsistent results and motivate recommendations for best practices in future research. These recommendations include calculating the effects of a time lag between the weather and COVID-19, using regression analysis models, considering nonlinear effects, increasing the time period considered in the analysis to encompass more variety of weather conditions and to increase sample size, and eliminating multicollinearity between weather variables.

scholarly journals The influence of weather conditions on breeding dates of the common gull (Larus canus) in the south of Western Siberia

2021 ◽  
Vol 16 (3) ◽  
pp. 8-18
Author(s):  
M. Yu. Garyushkina ◽  
A. K. Yurlov
Keyword(s):  
Air Temperature ◽  
Large Scale ◽  
Climatic Factors ◽  
Weather Conditions ◽  
Egg Laying ◽  
Weather Variables ◽  
Weather Factors ◽  
Spring Temperatures ◽  
The Common ◽  
Using Data

Aim. The purpose of this research was to find out what local weather factors influence the nesting timing of the common gull (Larus canus). Material and Methods. The time of egg laying by the common gull was determined using data obtained during regular surveys over 8 years (1996‐1998, 2002‐2003, 2006‐2008) on the islands of Lake Bolshie Chany. Weather and climatic factors were assessed using open‐access databases. Results. It was been established that the start of egg‐laying in the colony of the common gull is determined by wind strength, the number of rainy days, the associated atmospheric pressure during the second decade of April, and the air temperature – the transition date at which the average daily air temperature rose above 0°C. In years with unstable spring temperatures, a relationship was revealed between the air temperature and the intensity of egg laying by the common gulls by day. In years when temperatures rise evenly, precipitation and wind speed become the main factors.Conclusion. We conclude that the egg‐laying dates of the common gull is influenced by weather variables during the whole nesting season and not predominantly by early season variables. We also show the importance of large‐scale climatic phenomena such as the EAWR in explaining variability in timing of the nesting of the common gull in Siberia. We suggest that future studies should focus on the effects of extremes in weather variables and global climatic phenomena.

scholarly journals Effects of Preharvest Precipitation, Air Temperature, and Humidity on the Occurrence of Soft Scald in ‘Honeycrisp’ Apples

HortScience ◽  
2009 ◽  
Vol 44 (6) ◽  
pp. 1645-1647 ◽  
Author(s):  
Renae E. Moran ◽  
Jennifer R. DeEll ◽  
William Halteman
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Soluble Solids ◽  
Precipitation Temperature ◽  
Fruit Maturity ◽  
Honeycrisp Apples ◽  
Soft Scald ◽  
Relationship Of ◽  
The Relationship ◽  
Maximum Air Temperature

The relationship of soft scald incidence (SSI) with precipitation, temperature, and fruit maturity indicators in ‘Honeycrisp’ apples was examined using 7 years of data in Maine and 6 years in Ontario, Canada. Relative humidity was also examined in Maine. Soft scald incidence was highly variable from year to year ranging from 1% to 85% in Maine and from 0% to 76% in Ontario. In Ontario, SSI was negatively related to soluble solids at harvest (partial r2 = 0.50; P = 0.0041) and negatively related to precipitation during 90 to 120 days from bloom (DFB; partial r2 = 0.28; P = 0.0344). In Maine, SSI was most strongly related to precipitation in the 90 to 120 DFB (partial r2 = 0.53; P = 0.0001), maximum air temperature 60 to 90 DFB (partial r2 = 0.21; P = 0.0001), and number of hours when relative humidity was greater than 85% (partial r2 = 0.11; P = 0.0001).

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