scholarly journals The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis (Preprint)

2020 ◽  
Author(s):  
Zonglin He ◽  
Yiqiao Chin ◽  
Shinning Yu ◽  
Jian Huang ◽  
Casper J P Zhang ◽  
...  
Keyword(s):  
Public Health ◽  
Relative Humidity ◽  
Large Scale ◽  
Meteorological Factors ◽  
Pearson Correlation ◽  
Herd Immunity ◽  
Positive Influence ◽  
Average Temperature ◽  
Health Measures ◽  
Additive Modeling

BACKGROUND The influence of meteorological factors on the transmission and spread of COVID-19 is of interest and has not been investigated. OBJECTIVE This study aimed to investigate the associations between meteorological factors and the daily number of new cases of COVID-19 in 9 Asian cities. METHODS Pearson correlation and generalized additive modeling (GAM) were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available. RESULTS The Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (<i>r</i>=–0.565, <i>P</i>&lt;.001), Shanghai (<i>r</i>=–0.47, <i>P</i>&lt;.001), and Guangzhou (<i>r</i>=–0.53, <i>P</i>&lt;.001). In Japan, however, a positive correlation was observed (<i>r</i>=0.416, <i>P</i>&lt;.001). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), GAM analysis showed the number of daily new confirmed cases to be positively associated with both average temperature and relative humidity, especially using lagged 3D modeling where the positive influence of temperature on daily new confirmed cases was discerned in 5 cities (exceptions: Beijing, Wuhan, Korea, and Malaysia). Moreover, the sensitivity analysis showed, by incorporating the city grade and public health measures into the model, that higher temperatures can increase daily new case numbers (beta=0.073, Z=11.594, <i>P</i>&lt;.001) in the lagged 3-day model. CONCLUSIONS The findings suggest that increased temperature yield increases in daily new cases of COVID-19. Hence, large-scale public health measures and expanded regional research are still required until a vaccine becomes widely available and herd immunity is established.

scholarly journals Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis

2020 ◽  
Author(s):  
Zonglin He ◽  
Yiqiao Chin ◽  
Jian Huang ◽  
Yi He ◽  
Babatunde O. Akinwunmi ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Disease Transmission ◽  
Large Scale ◽  
Meteorological Factors ◽  
Pearson Correlation ◽  
Average Temperature ◽  
Generalized Additive Modeling ◽  
Geographical Regions ◽  
Asian Cities ◽  
Additive Modeling

AbstractAIMTo investigate the associations of meteorological factors and the daily new cases of coronavirus disease (COVID-19) in nine Asian cities.METHODPearson’s correlation and generalized additive modeling were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available.RESULTSThe Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=-0.565, P<0.01), Shanghai (r=-0.471, P<0.01), and Guangzhou (r=-0.530, P<0.01), yet in contrast, positively correlated with that in Japan (r=0.441, P<0.01). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), generalized additive modeling analysis showed the number of daily new confirmed cases was positively associated with both average temperature and relative humidity, especially in lagged 3d model, where a positive influence of temperature on the daily new confirmed cases was discerned in 5 cities except in Beijing, Wuhan, Korea, and Malaysia. Nevertheless, the results were inconsistent across cities and lagged time, suggesting meteorological factors were unlikely to greatly influence the COVID-19 epidemic.CONCLUSIONThe associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and lagged time. Large-scale public health measures and expanded regional research are still required until a vaccine becomes available and herd immunity is established.Significance statementWith increasing COVID-19 cases across China and the world, and previous studies showing that meteorological factors may be associated with infectious disease transmission, the saying has it that when summer comes, the epidemic of COVID-19 may simultaneously fade away. We demonstrated the influence of meteorological factors on the daily domestic new cases of coronavirus disease (COVID-19) in nine Asian cities. And we found that the associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and time. We think this important topic may give better clues on prevention, management, and preparation for new events or new changes that could happen in the COVID-19 epidemiology in various geographical regions and as we move towards Summer.

scholarly journals Silver Linings Reported by Australians Experiencing Public Health Restrictions during the First Phase of the COVID-19 Pandemic: A Qualitative Report

2021 ◽  
Vol 18 (21) ◽  
pp. 11406
Author(s):  
Narelle Campbell ◽  
Sandra C. Thompson ◽  
Anna Tynan ◽  
Louise Townsin ◽  
Lauren A. Booker ◽  
...  
Keyword(s):  
Public Health ◽  
Qualitative Research ◽  
Large Scale ◽  
Well Being ◽  
Rapid Identification ◽  
National Study ◽  
The Public ◽  
Health Measures ◽  
Negative Impacts ◽  
Mental Well Being

This national study investigated the positives reported by residents experiencing the large-scale public health measures instituted in Australia to manage the first wave of the COVID-19 pandemic in 2020. Most Australians had not previously experienced the traditional public health measures used (social distancing, hand hygiene and restriction of movement) and which could potentially impact negatively on mental well-being. The research design included qualitative semi-structured phone interviews where participants described their early pandemic experiences. Data analysis used a rapid identification of themes technique, well-suited to large-scale qualitative research. The ninety participants (mean age 48 years; 70 women) were distributed nationally. Analysis revealed five themes linked with mental well-being and the concept of silver linings: safety and security, gratitude and appreciation, social cohesion and connections, and opportunities to reset priorities and resilience. Participants demonstrated support for the public health measures and evidence of individual and community resilience. They were cognisant of positives despite personal curtailment and negative impacts of public health directives. Stories of hope, strength, and acceptance, innovative connections with others and focusing on priorities and opportunities within the hardship were important strategies that others could use in managing adversity.

scholarly journals Phenological pattern reproductive of Attalea speciosa Mart ex Spreng. in pasture area in the central region of Rondônia.

FLORESTA ◽  
2020 ◽  
Vol 50 (2) ◽  
pp. 1335 ◽  
Author(s):  
Jhonatas Cortes Rosa ◽  
Andreza Pereira Mendonça ◽  
Claudemir Carlos Ribeiro ◽  
Sylviane Beck Ribeiro
Keyword(s):  
Relative Humidity ◽  
Climatic Factors ◽  
Pearson Correlation ◽  
Meteorological Variables ◽  
Average Temperature ◽  
Palm Trees ◽  
Monthly Total Precipitation ◽  
Monthly Total ◽  
Pasture Area ◽  
Reproductive Events

The objective of this work was to evaluate the phenology of the babassu (Attalea speciosa Mart ex Spreng.), aiming to subsidize information for non - timber management of the species in pasture area. For 48 months, the phenological patterns of babassu were studied, relating them to meteorological variables such as monthly average temperature, monthly total precipitation, relative humidity of the medium air and photoperiod. A total of 130 adult palm trees from natural regeneration were monitored in a pasture in the municipality of Ji-Paraná, RO, from January 2012 to December 2015. The data were analyzed by means of the activity indexes, the relation of the phenophases and meteorological variables by means of Pearson correlation. The population synchrony index was also evaluated. During the study, the population of Attalea speciosa showed flowering asynchronously in the population. In the process of formation and maturation of the fruits of the babassu, it was possible to observe that the time of total development of the fruits was in average 254 days. In young infructescence, the most influential climatic factors were temperature and photoperiod. In the green infructescence, climatic factors such as precipitation, relative humidity and photoperiod influenced negatively. The presence of mature infructescence occurred throughout the year, with the highest intensities in the month of November, and its activity related to the increase in temperature and duration of days. Phenological monitoring of babassu allowed to identify the intensity and predictability of reproductive events, thus enabling information to be provided to the plans for the sustainable exploitation of the species in pasture in the municipality of Ji-Paraná.

scholarly journals Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City, northeastern China, 2007–2018

2021 ◽  
Vol 15 (3) ◽  
pp. e0009217
Author(s):  
Wanwan Sun ◽  
Xiaobo Liu ◽  
Wen Li ◽  
Zhiyuan Mao ◽  
Jimin Sun ◽  
...  
Keyword(s):  
Public Health ◽  
High Temperature ◽  
Relative Humidity ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Additive Model ◽  
Hemorrhagic Fever ◽  
Epidemiological Data ◽  
Effect Of Temperature ◽  
Delayed Effects

Background Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS. Objective Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City. Methods Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007–2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors. Results During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04–2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31–5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01–1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01–1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00–1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02–1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02–1.76), -9 degrees Celsius (1.37, 95% CI: 1.04–1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03–1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level. Conclusions Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.

scholarly journals Serological assays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), March 2020

2020 ◽  
Vol 25 (16) ◽  
Author(s):  
Ranawaka APM Perera ◽  
Chris KP Mok ◽  
Owen TY Tsang ◽  
Huibin Lv ◽  
Ronald LW Ko ◽  
...  
Keyword(s):  
Public Health ◽  
Severe Acute Respiratory Syndrome ◽  
Large Scale ◽  
Herd Immunity ◽  
Cross Reactivity ◽  
Spike Protein ◽  
Infectious Dose ◽  
Virus Challenge ◽  
Illness Onset ◽  
Public Health Decision

Background The ongoing coronavirus disease (COVID-19) pandemic has major impacts on health systems, the economy and society. Assessing infection attack rates in the population is critical for estimating disease severity and herd immunity which is needed to calibrate public health interventions. We have previously shown that it is possible to achieve this in real time to impact public health decision making. Aim Our objective was to develop and evaluate serological assays applicable in large-scale sero-epidemiological studies. Methods We developed an ELISA to detect IgG and IgM antibodies to the receptor-binding domain (RBD) of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated its sensitivity and specificity in combination with confirmatory microneutralisation (MN) and 90% plaque reduction neutralisation tests (PRNT90) in 51 sera from 24 patients with virologically confirmed COVID-19 and in age-stratified sera from 200 healthy controls. Results IgG and IgM RBD ELISA, MN and PRNT90 were reliably positive after 29 days from illness onset with no detectable cross-reactivity in age-stratified controls. We found that PRNT90 tests were more sensitive in detecting antibody than MN tests carried out with the conventional 100 tissue culture infectious dose challenge. Heparinised plasma appeared to reduce the infectivity of the virus challenge dose and may confound interpretation of neutralisation test. Conclusion Using IgG ELISA based on the RBD of the spike protein to screen sera for SARS-CoV-2 antibody, followed by confirmation using PRNT90, is a valid approach for large-scale sero-epidemiology studies.

Effects of Meteorological Factors on PM10 Pollution in Yantai Urban Areas

2012 ◽  
Vol 178-181 ◽  
pp. 328-331
Author(s):  
Jian Guo Song ◽  
Ming Chang ◽  
Xin Zhi Wang ◽  
Wei Liu
Keyword(s):  
Relative Humidity ◽  
Frequency Distribution ◽  
Urban Areas ◽  
Meteorological Factors ◽  
Air Pressure ◽  
The Other ◽  
Average Temperature ◽  
The North

This paper makes analysis and statistics about the frequency distribution of average temperature, pressure, humidity and wind conditions between moderate pollution days of PM10(API>200) and conventional days from 2008 to 2010 in Yantai. The result shows that the frequency of PM10 pollution which occurred in winter is close to the sum of the other seasons. PM10 pollution days appears easily under such conditions: the average temperature below 10°C, average air pressure is higher than 101.0kPa, relative humidity is less than 70%, or average weed speed of 3-7m/s with the north-south wind.

scholarly journals EFFECTS OF METEOROLOGICAL VARIABLES ON Pinus caribaea GROWTH IN DIFFERENT AGES AT THE AMAZON REGION.

FLORESTA ◽  
2022 ◽  
Vol 52 (1) ◽  
pp. 113
Author(s):  
Gabriel Miranda Lima de Lima ◽  
Nei Sebastião Braga Gomes ◽  
Thiago Augusto da Cunha ◽  
Afonso Figueiredo Filho
Keyword(s):  
Relative Humidity ◽  
Pearson Correlation ◽  
Meteorological Variables ◽  
Pinus Caribaea ◽  
Annual Increment ◽  
Positive Correlation ◽  
Average Temperature ◽  
Different Ages ◽  
One Year ◽  
The Impact

This study compares the impact of five meteorological variables on the diametric growth of Pinus caribaea var. hondurensis Barrett & Golfari in Vilhena, Rondônia. One thousand nine hundred sixty-eight trees were evaluated and classified at different ages: 600 trees were one year old; 600 trees were two years old; 768 trees were 13 years. The diameter measurement at the soil level (SL) was conducted in young stands between one and two years old. In the stand with 13 years old, the diameter was measured at 1.3 m (DCH). Using a Pressler borer, 50 increment cores were removed at DCH to measure the tree rings in LINTAB™ 6. The diametric growth was evaluated through the Periodic Increment (PI) for young stands and Current Annual Increment (CAI) for adult stands. The following variables were considered: average temperature (°C), precipitation (mm), solar radiation (Kj m-²), real evapotranspiration (mm), and maximum relative humidity (%). The Pearson Correlation Coefficient (r) proposed by Callegari-Jacques and the coefficient of variation (CV%) were used to establish the relationship between growth and meteorological variables. For young stands, the variables with higher positive correlation were real evapotranspiration and maximum relative humidity. However, the variable with a higher positive correlation in adult stands was average temperature, demonstrating a strong correlation until the sixth year of the species. 

Mass Vaccination Programme: Public Health Success and Ethical Issues – Bangladesh Perspective

2020 ◽  
Vol 9 (3) ◽  
pp. 11-15
Author(s):  
Abu Sadat Mohammad Nurunnabi ◽  
Miliva Mozaffor ◽  
Mohammad Akram Hossain ◽  
Sadia Akther Sony
Keyword(s):  
Public Health ◽  
Vaccination Programme ◽  
Large Scale ◽  
Ethical Issues ◽  
Herd Immunity ◽  
Mass Vaccination ◽  
Global Public Health ◽  
National Programme ◽  
Serious Infections ◽  
Individual Protection

Vaccines are responsible for many global public health successes, such as the eradication of smallpox and significant reductions in other serious infections like diphtheria, pertussis, tetanus, polio and measles. However, mass vaccination has also been the subject of various ethical controversies for decades. Several factors need to be considered before any vaccine is deployed at national programme like the potential burden of disease in the country or region, the duration of the protection conferred, herd immunity in addition to individual protection, vaccine-related risks, financing and the logistical feasibility of the large-scale vaccination. Moreover, several ethical dilemmas revolve around authority and mandates for vaccination, informed consent, benefits vs. risks, and disparities in access to vaccination. This review paper aims to elaborate the ethical issues involved in mass vaccination programme and present some additional challenges in the context of a resource-poor settings of public health in Bangladesh.

scholarly journals Changes in Care Provision During COVID-19 Impact Patient Well-Being

2021 ◽  
Vol 8 ◽  
pp. 237437352110340
Author(s):  
Judy J Wang ◽  
Jessica R Levi ◽  
Heather A Edwards
Keyword(s):  
Public Health ◽  
Medical Care ◽  
Large Scale ◽  
Negative Impact ◽  
Well Being ◽  
Public Health Emergency ◽  
Care Provision ◽  
Health Measures ◽  
Routine Medical Care ◽  
The Impact

The fast onset and extensive impact of COVID-19 necessitated strict public health measures and temporary diversion of personnel and resources from other types of medical care. This study examined the prevalence of such disruptions and their impacts on patient-perceived well-being using an untargeted survey. The majority of surveyed patients experienced changes in their routine medical care. Of those whose appointments were postponed or canceled, most patients indicated an overall negative impact on their emotional and physical well-being. We highlighted the impact of disruptions in nonurgent medical care during a large-scale public health emergency.

scholarly journals Predicting the local COVID-19 outbreak around the world with meteorological conditions: a model-based qualitative study

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e041397
Author(s):  
Biqing Chen ◽  
Hao Liang ◽  
Xiaomin Yuan ◽  
Yingying Hu ◽  
Miao Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Qualitative Study ◽  
Meteorological Factors ◽  
Weather Data ◽  
Epidemic Control ◽  
Average Temperature ◽  
Term Model ◽  
The Future ◽  
Future Outbreak

ObjectivesThis study aims to investigate the relationship between daily weather and transmission rate of SARS-CoV-2, and to develop a generalised model for future prediction of the COVID-19 spreading rate for a certain area with meteorological factors.DesignA retrospective, qualitative study.Methods and analysisWe collected 382 596 records of weather data with four meteorological factors, namely, average temperature, relative humidity, wind speed, and air visibility, and 15 192 records of epidemic data with daily new confirmed case counts (1 587 209 confirmed cases in total) in nearly 500 areas worldwide from 20 January 2020 to 9 April 2020. Epidemic data were modelled against weather data to find a model that could best predict the future outbreak.ResultsSignificant correlation of the daily new confirmed case count with the weather 3 to 7 days ago were found. SARS-CoV-2 is easy to spread under weather conditions of average temperature at 5 to 15°C, relative humidity at 70% to 80%, wind speed at 1.5 to 4.5 m/s and air visibility less than 10 statute miles. A short-term model with these four meteorological variables was derived to predict the daily increase in COVID-19 cases; and a long-term model using temperature to predict the pandemic in the next week to month was derived. Taken China as a discovery dataset, it was well validated with worldwide data. According to this model, there are five viral transmission patterns, ‘restricted’, ‘controlled’, ‘natural’, ‘tropical’ and ‘southern’. This model’s prediction performance correlates with actual observations best (over 0.9 correlation coefficient) under natural spread mode of SARS-CoV-2 when there is not much human interference such as epidemic control.ConclusionsThis model can be used for prediction of the future outbreak, and illustrating the effect of epidemic control for a certain area.

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