scholarly journals Relationship between Weather Variables and New Daily COVID-19 Cases in Dhaka, Bangladesh

2020 ◽  
Vol 12 (20) ◽  
pp. 8319
Author(s):  
M. Mofijur ◽  
I.M. Rizwanul Fattah ◽  
A.B.M. Saiful Islam ◽  
M.N. Uddin ◽  
S.M. Ashrafur Rahman ◽  
...  
Keyword(s):  
Air Quality ◽  
Minimum Temperature ◽  
Rank Correlation ◽  
Maximum Temperature ◽  
Weather Variables ◽  
Strong Negative Correlation ◽  
Average Temperature ◽  
Climate Indicators ◽  
The Relationship ◽  
Spearman Rank Correlation Test

The present study investigated the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman rank correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature, and wind speed with the COVID-19 outbreak in Dhaka, Bangladesh. The study found that, among the seven indicators, only two indicators (minimum temperature and average temperature) had a significant relationship with new COVID-19 cases. The study also found that air quality index (AQI) had a strong negative correlation with cumulative cases of COVID-19 in Dhaka city. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 spread in Dhaka and other countries around the world.

scholarly journals Relationship between Climate Variables and New Daily COVID-19 Cases in Dhaka, Bangladesh

2020 ◽  
Author(s):  
M. Mofijur ◽  
Islam Md Rizwanul Fattah ◽  
A. B. M. Saiful Islam ◽  
S.M. Ashrafur Rahman ◽  
Mohammad Asaduzzaman Chowdhury
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Dhaka City ◽  
Climate Variables ◽  
Average Temperature ◽  
Climate Indicators ◽  
The World ◽  
The Relationship

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

scholarly journals Effect of temperature and precipitation on the daily new cases and daily new death in seven cities around the globe

2020 ◽  
Author(s):  
Amar Prashad Chaudhary ◽  
Adna Nelson K ◽  
Harish S ◽  
Mydhily S ◽  
Chaitanya KJ ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
Effect Of Temperature ◽  
Maximum Temperature ◽  
Weather Variables ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
The World

AbstractBackgroundThis study was done to understand the effect of temperature and precipitation in COVID-19.ObjectiveTo study the effect of temperature and precipitation on transmission of COVID-19.To study the effect of temperature and precipitation on daily death of COVID-19.MethodologyWe collected 3 consecutive month data of seven cities around the world which were effected most by the COVID-19. Data included weather variables i.e temperature (average temperature, maximum temperature and minimum temperature), precipitation, daily new cases and daily new death.ConclusionIncrease in average temperature reduces daily death and increase in maximum temperature reduces transmission.

scholarly journals The effect of average temperature on suicide rates in five urban California counties, 1999–⁠2019: an ecological time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sierra Cheng ◽  
Rebecca Plouffe ◽  
Stephanie M. Nanos ◽  
Mavra Qamar ◽  
David N. Fisman ◽  
...  
Keyword(s):  
Public Health ◽  
Suicide Rate ◽  
Minimum Temperature ◽  
The United States ◽  
Additive Models ◽  
Maximum Temperature ◽  
Mortality Data ◽  
Average Temperature ◽  
Suicide Rates ◽  
Average Maximum

Abstract Background Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. Methods Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. Results There were over 38,000 deaths by suicide in California’s five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025–1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021–1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023–1.0153) were similar. Conclusion This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

scholarly journals Use of Weather Variables to Quantify Sorghum Ergot Potential in South Africa

Plant Disease ◽  
1998 ◽  
Vol 82 (1) ◽  
pp. 26-29 ◽  
Author(s):  
N. W. McLaren ◽  
B. C. Flett
Keyword(s):  
Minimum Temperature ◽  
Pollen Viability ◽  
Breakdown Point ◽  
Field Trials ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Weather Variables ◽  
Data Set ◽  
Study Results

Quantification of resistance to ergot requires that the observed ergot severity within a sorghum line be compared with expected ergot severity (ergot potential) to compensate for differences in environmental favorability for the disease among flowering dates and seasons. The ergot potential required to induce the onset of disease is referred to as the ergot breakdown point of that line. In earlier studies, the ergot potential of a specific flowering date was defined as the mean ergot severity in all sorghum heads over all lines in the nursery which commenced flowering on that date in a genetically broad-based sorghum nursery. In this study, results of field trials enabled accurate prediction of ergot potential by using a multiple regression analysis which included three weather variables—namely, pre-flowering minimum temperature (mean of days 23 to 27 pre-flowering), mean daily maximum temperature, and mean daily maximum relative humidity (mean of days 1 to 5 post-flowering; R2 = 0.90; P = 0.91E-5). Evaluation of predicted and observed ergot severity in an independent data set gave an index of agreement of d = 0.94 and R2 = 0.84 (P = 0.106E-4), showing that ergot severity, assuming the presence of viable inoculum, can be accurately predicted. Low pre-flowering minimum temperature was associated with reduced pollen viability, which appeared to be the primary factor predisposing lines to ergot.

scholarly journals Effects of Climatological Parameters on the Outbreak Spread of COVID-19 in Highly Affected Regions of Spain

2020 ◽  
Author(s):  
Khurram Shahzad ◽  
Umer Shahzad ◽  
Najaf Iqbal ◽  
Farrukh Shahzad ◽  
Zeeshan Fareed
Keyword(s):  
Air Quality ◽  
Pearson Correlation ◽  
Rank Correlation ◽  
Spearman Correlation ◽  
Pm 2.5 ◽  
Average Temperature ◽  
Castilla Y Leon ◽  
Panel Regressions ◽  
La Mancha ◽  
Rapid Spread

Abstract The Coronavirus (COVID-19) pandemic is infecting the human population, killing people, and destroying livelihoods. This research sought to explore the associations of daily average temperature (AT) and air quality (PM 2.5) with the daily new cases of COVID-19 in the top four regions of Spain (Castilla y Leon, Castilla-La Mancha, Catalonia, and Madrid). We apply Pearson correlation, Spearman correlation, Kendall’s rank correlation, and panel regressions to quantify the overall co-movement between temperature, air quality, and daily cases of COVID-19 from February to 17th April 2020. Overall empirical results show that temperature and air quality exert pressure to increase new COVID-19 infections. Our findings are contrary to the earlier studies, which show a significant impact of temperature in reducing the COVID-19 spread. The conclusions of this work can serve as an input to mitigate the rapid spread of COVID-19 in Spain and reform policies accordingly.

scholarly journals HUBUNGAN FENOMENA GROUPTHINK DENGAN GAYA KEPEMIMPINAN KETUA RT DI DESA CIKARAWANG

2019 ◽  
Vol 17 (1) ◽  
pp. 28-37
Author(s):  
Distra Asniar Asniar ◽  
Sarwititi Sarwoprasodjo
Keyword(s):  
Leadership Styles ◽  
Leadership Style ◽  
Qualitative Data ◽  
Rank Correlation ◽  
Spearman Rank Correlation ◽  
Causal Factors ◽  
Group Members ◽  
Relationship Of ◽  
The Relationship ◽  
Spearman Rank Correlation Test

Neighborhood activities are a process that can be used to see the level of group members' participation, often member participation is influenced by several things, such as groupthink phenomenon and group leader leadership style. The purpose of this study was to: (1) identify groupthink causal factors in groups, (2), identify leadership styles found in neighborhood, and (3) analyze the relationship of leadership style with groupthink phenomena in groups. This study uses a quantitative approach supported by qualitative data with 30 neighborhood as respondents. The subjects of this study were neighborhood groups located in Cikarawang Village, Dramaga District, Bogor Regency. Analysis of research data using the Spearman rank correlation test. The results show that there was no relationship between the leadership style of the chair and groupthink phenomena in the neighborhood activities. This condition influences the neighborhood leader dominant leadership style is laissez faire, so it has no relation to the decline in criticism of neighborhood members in groupthink phenomena.

scholarly journals Impact of climatic parameters on COVID-19 pandemic progression in India: analysis and prediction

2020 ◽  
Author(s):  
Namrata Deyal ◽  
Vipin Tiwari ◽  
Nandan Bisht
Keyword(s):  
Atmospheric Pressure ◽  
Rank Correlation ◽  
Sir Model ◽  
New Delhi ◽  
Moderate Correlation ◽  
Climatic Parameters ◽  
Spearman Rank Correlation ◽  
Average Temperature ◽  
Highly Correlated ◽  
Spearman Rank Correlation Test

COVID-19 is spreading rapidly worldwide and various factors of it have to be analysed. We analyze the effect of climatic parameters (Average Temperature (AT), Atmospheric Pressure (AP), Relative Humidity (RH), Solar Radiation (SR) and Wind Speed (WS)) on the COVID-19 epidemic during 25 March 2020 to 15 June 2020 in most affected states of India i.e. Maharashtra, Delhi and Tamilnadu. We quantitatively establish the correlation between these parameters by using Kendall & Spearman rank correlation test. The results indicate that the positive cases are highly correlated with the AT (r^2 >0.6,p<0.001) in Delhi where as a moderate correlation ( r^2<0.6,p<0.001) has been estimated for Maharashtra and Tamilnadu. Similarly, an intermediate range of correlation coefficient has been observed for other climatic parameters. The range of climatic parameters have been found corresponding to maximum number of cases results as AT (25~40 0 C), RH (40~70%), AT (740~965 mmHg), SR (200-250 W/mt2) and WS (.5~14 m/sec). Time series analysis depicts that the positive cases and mortality are increasing rapidly. COVID-19 epidemic peak is predicted and would be appearing October 2020 using SIR model for capital of India (New Delhi). The outcomes of this study will be helpful for the containment of COVID-19 worldwide.

scholarly journals Weather Indicators and Improving Air Quality in Association with COVID-19 Pandemic in India

2021 ◽  
Author(s):  
Rabin Chakrabortty ◽  
Subodh Chandra Pal ◽  
Manoranjan Ghosh ◽  
Alireza Arabameri ◽  
Asish Saha ◽  
...  
Keyword(s):  
Air Quality ◽  
Spatial Pattern ◽  
Human Activities ◽  
Maximum Temperature ◽  
New Delhi ◽  
Climate Variables ◽  
Urban Planner ◽  
Average Temperature ◽  
Health Expert ◽  
Monitoring Stations

Abstract The COVID-19 pandemic enforced nationwide lockdown, which has restricted human activities from March 24 to May 3 2020, resulted an improved air quality across India. The present research investigates the connection between COVID-19 pandemic imposed lockdown and its relation with present air quality in India; besides, relationship with climate variables and daily new affected cases of Coronavirus and mortality in India during the lockdown period has also been examined. The selected seven air quality pollutant parameters (PM10, PM2.5, CO, NO2, SO2, NH3 and O3) at 223 monitoring stations and temperature recorded in New Delhi were used to investigate the spatial pattern of air quality throughout the lockdown. The results showed that the air quality has improved across the country and average temperature and maximum temperature were connected to the outbreak of the COVID-19 pandemic. This study will assist the policy practitioner, researcher, urban planner, and health expert to make suitable strategies against the spreading of COVID-19 in India and abroad.

scholarly journals Relationship Between Climate Change and Rice Production of Bangladesh: A data analysis using MCMC method

2021 ◽  
Author(s):  
Atiqur Chowdhury
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Rice Production ◽  
Predictor Variables ◽  
Maximum Temperature ◽  
Temperature Minimum ◽  
Model Sets ◽  
Average Rainfall ◽  
Temperature And Humidity ◽  
The Relationship

Abstract In this study, we analyzed publicly available agricultural data on rice production in Bangladesh between 2008 to 2017 to address the relationship between climate changes and rice production in Bangladesh by estimating predictor variables, i.e., average rainfall and maximum temperature, minimum temperature, and humidity. A generalized linear regression model sets up for each rice (Aush, Aman, Boro) with the climate variables (average rainfall, maximum temperature, minimum temperature, and humidity). We used Markov-Chain-Monte-Carlo's (MCMC)'s Gibbs sampling on the collected data to approximate marginal posterior distribution from the prior distribution to see the profound relationship between those predictor variables and the predicted variables (Aush, Aman, Boro). We also saw whether any storm's impact could modify the relationship between climate change variables and rice production in Bangladesh.

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