Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 193
Filter
1.
J Infect Dev Ctries ; 16(5): 759-767, 2022 May 30.
Article in English | MEDLINE | ID: covidwho-1879509

ABSTRACT

INTRODUCTION: Climate conditions may influence the transmission of COVID-19. Thus, the aim of this study was to evaluate the impact of temperature and relative humidity on COVID-19 cases and related deaths during the initial phase of the epidemic in Brazil. METHODOLOGY: An ecological study based on secondary data was conducted. Daily data on new COVID-19 cases, deaths, and climate indicators were collected from February 20 to April 18, 2020 (n = 59 days) for all state capital cities in Brazil and the Federal District (Brasília). The climate indicators included mean temperature, temperature amplitude, mean relative humidity, relative humidity amplitude, and percentage of days with mean relative humidity ≤ 65 %. Correlation and multiple linear regression analyses were performed for all cities and stratified by quintiles of the COVID-19 incidence rate. RESULTS: The mean daily temperature was positively correlated with the number of days until the first COVID-19 case was reported. A lower mean relative humidity was correlated with a lower number of cases and deaths in Brazil, especially when the relative humidity was ≤ 65 %. Higher temperatures and humidity amplitudes were correlated with lower COVID-19 mortality. Additionally, after controlling for humidity, cumulative cases of COVID-19 were inversely associated with temperature in cities with mean temperatures less than 25.8 °C. CONCLUSIONS: Variations in temperature and humidity across the Brazilian territory may have influenced the spread of the novel coronavirus during the initial phase of the epidemic.


Subject(s)
COVID-19 , Brazil/epidemiology , COVID-19/epidemiology , Cities/epidemiology , Humans , Humidity , Temperature
2.
Viruses ; 14(5)2022 May 15.
Article in English | MEDLINE | ID: covidwho-1855822

ABSTRACT

Surface to hand transfer of viruses represents a potential mechanism for human exposure. An experimental process for evaluating the touch transfer of aerosol-deposited material is described based on controlling surface, tribological, and soft matter components of the transfer process. A range of high-touch surfaces were evaluated. Under standardized touch parameters (15 N, 1 s), relative humidity (RH) of the atmosphere around the contact transfer event significantly influenced transfer of material to the finger-pad. At RH < 40%, transfer from all surfaces was <10%. Transfer efficiency increased markedly as RH increased, reaching a maximum of approximately 50%. The quantity of material transferred at specific RHs above 40% was also dependent on roughness of the surface material and the properties of the aerosol-deposited material. Smooth surfaces, such as melamine and stainless steel, generated higher transfer efficiencies compared to those with textured roughness, such as ABS pinseal and KYDEX® plastics. Pooled human saliva was transferred at a lower rate compared to artificial saliva, indicating the role of rheological properties. The artificial saliva data were modeled by non-linear regression and the impact of environmental humidity and temperature were evaluated within a Quantitative Microbial Risk Assessment model using SARS-CoV-2 as an example. This illustrated that the trade-off between transfer efficiency and virus survival may lead to the highest risks of fomite transmissions in indoor environments with higher humidity.


Subject(s)
COVID-19 , Viruses , Aerosols , Humans , Humidity , SARS-CoV-2 , Saliva , Saliva, Artificial
4.
Environ Sci Pollut Res Int ; 29(12): 18077-18102, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1826827

ABSTRACT

After more than a year from the first confirmed cases of coronavirus (COVID-19) disease, the role of meteorological factors in the transmission of the virus still needs to be correctly determined. In this scenario of deep uncertainty, the present study aims to investigate the effects of temperature and relative humidity on daily new cases of COVID-19. For this purpose, the COVID-19's development of infection in fourteen Algerian cities characterized by different climatic conditions, during the period from April 1, 2020, to August 31, 2020, has been investigated. A detailed time series analysis along with linear regression was used to state a possible correlation among some climate's factor variability (temperature and relative humidity) and daily new confirmed cases of COVID-19. The results showed a weak correlation between daily new cases of COVID-19 and meteorological factors throughout the selected regions. In addition, we concluded that the COVID-19 could fit to high or low values of temperature and relative humidity, and other factors not climates could affect the spreading of the virus like demography and human contact. So, after the discovery of the vaccine and before vaccination of 70% of the world's population, living with the virus has become an inevitable reality, and it is mandatory to apply the sanitary procedures to slow down the COVID-19 transmission.


Subject(s)
COVID-19 , Pandemics , Africa, Northern , Algeria/epidemiology , COVID-19/epidemiology , Humans , Humidity , SARS-CoV-2 , Temperature
5.
Sci Rep ; 11(1): 22027, 2021 11 11.
Article in English | MEDLINE | ID: covidwho-1758313

ABSTRACT

Rising temperature levels during spring and summer are often argued to enable lifting of strict containment measures even in the absence of herd immunity. Despite broad scholarly interest in the relationship between weather and coronavirus spread, previous studies come to very mixed results. To contribute to this puzzle, the paper examines the impact of weather on the COVID-19 pandemic using a unique granular dataset of over 1.2 million daily observations covering over 3700 counties in nine countries for all seasons of 2020. Our results show that temperature and wind speed have a robust negative effect on virus spread after controlling for a range of potential confounding factors. These effects, however, are substantially larger during mealtimes, as well as in periods of high mobility and low containment, suggesting an important role for social behaviour.


Subject(s)
COVID-19/epidemiology , Humans , Humidity , Pandemics , Risk Factors , SARS-CoV-2/isolation & purification , Seasons , Social Behavior , Temperature , Weather , Wind
6.
Environ Sci Pollut Res Int ; 29(15): 21811-21825, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1750802

ABSTRACT

The COVID-19 pandemic affected the world through its ability to cause widespread infection. The Middle East including the Kingdom of Saudi Arabia (KSA) has also been hit by the COVID-19 pandemic like the rest of the world. This study aims to examine the relationships between meteorological factors and COVID-19 case counts in three cities of the KSA. The distribution of the COVID-19 case counts was observed for all three cities followed by cross-correlation analysis which was carried out to estimate the lag effects of meteorological factors on COVID-19 case counts. Moreover, the Poisson model and negative binomial (NB) model with their zero-inflated versions (i.e., ZIP and ZINB) were fitted to estimate city-specific impacts of weather variables on confirmed case counts, and the best model is evaluated by comparative analysis for each city. We found significant associations between meteorological factors and COVID-19 case counts in three cities of KSA. We also perceived that the ZINB model was the best fitted for COVID-19 case counts. In this case study, temperature, humidity, and wind speed were the factors that affected COVID-19 case counts. The results can be used to make policies to overcome this pandemic situation in the future such as deploying more resources through testing and tracking in such areas where we observe significantly higher wind speed or higher humidity. Moreover, the selected models can be used for predicting the probability of COVID-19 incidence across various regions.


Subject(s)
COVID-19 , Meteorological Concepts , Pandemics , COVID-19/epidemiology , Cities/epidemiology , Humans , Humidity , Saudi Arabia/epidemiology , Temperature , Wind
7.
Environ Res ; 211: 113110, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1748018

ABSTRACT

Coronavirus Disease-2019 (COVID-19) started in Wuhan province of China in November 2019 and within a short time, it was declared as a worldwide pandemic by World Health Organisation due to the very fast worldwide spread of the virus. There are a few studies that look for the correlation with infected individuals and different environmental parameters using early data of COVID-19 but there is no study so far that deals with the variation of effective reproduction number and environmental factors. Effective reproduction number is the driving parameter of the spread of a pandemic and it is important to study the effect of various environmental factors on effective reproduction number to understand the effect of those factors on the spread of the virus. We have used time-dependent models to investigate the variation of different time-dependent driving parameters of COVID-19 like effective reproduction number and contact rate using data from India as a test case. India is a large population country that is highly affected due to the COVID-19 pandemic and has a wide span of different temperature and humidity regions and is ideal for such study. We have studied the impact of temperature and humidity on the spread of the virus of different Indian states using time-dependent epidemiological models SIRD, and SEIRD for a long time scale. We have used a linear regression method to look for any dependency between the effective reproduction number with the relative humidity, absolute humidity, and temperature. The effective reproduction number shows a negative correlation with both relative and absolute humidity for most of the Indian states, which are statistically significant. This implies that relative and absolute humidity may have an important role in the variation of effective reproduction number. Most of the states (six out of ten) show a positive correlation while two (out of ten) show a negative correlation between effective reproduction number and average air temperature for both SIRD and SEIRD models.


Subject(s)
COVID-19 , Basic Reproduction Number , COVID-19/epidemiology , Humans , Humidity , Pandemics , SARS-CoV-2 , Temperature
8.
Environ Res ; 211: 113134, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1748017

ABSTRACT

Numerous studies have been conducted worldwide to investigate if an association exists between meteorological factors and the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection incidence. Although research studies provide conflicting results, which can be partially explained by different methods used, some clear trends emerge on the role of weather conditions and SARS-CoV-2 infection, especially for temperature and humidity. This study sheds more light on the relationship between meteorological factors and SARS-CoV-2 infection incidence in 23 Italian and 52 Spanish cities. For the purposes of this study, daily air temperature, absolute and relative humidity, wind speed, ultraviolet radiation, and rainfall are considered exposure variables. We conducted a two-stage meta-regression. In the first stage, we estimated the exposure-response association through time series regression analysis at the municipal level. In the second stage, we pooled the association parameters using a meta-analytic model. The study demonstrates an association between meteorological factors and SARS-CoV-2 infection incidence. Specifically, low levels of ambient temperatures and absolute humidity were associated with an increased relative risk. On the other hand, low and high levels of relative humidity and ultraviolet radiation were associated with a decreased relative risk. Concerning wind speed and rainfall, higher values contributed to the reduction of the risk of infection. Overall, our results contribute to a better understanding of how the meteorological factors influence the spread of the SARS-CoV-2 and should be considered in a wider context of existing robust literature that highlight the importance of measures such as social distancing, improved hygiene, face masks and vaccination campaign.


Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , China , Cities/epidemiology , Humans , Humidity , Immunization Programs , Incidence , Italy/epidemiology , Meteorological Concepts , SARS-CoV-2 , Spain/epidemiology , Temperature , Time Factors , Ultraviolet Rays
9.
Chem Commun (Camb) ; 57(26): 3243-3246, 2021 Apr 04.
Article in English | MEDLINE | ID: covidwho-1747172

ABSTRACT

The hygroscopicity of respiratory aerosol determines their particle size distribution and regulates solute concentrations to which entrained microorganisms are exposed. Here, we report the hygroscopicity of simulated lung fluid (SLF) particles. While the response of aqueous particles follow simple mixing rules based on composition, we observe phase hysteresis with increasing and decreasing relative humidity (RH) and clear uptake of water prior to deliquescence. These results indicate that RH history may control the state of respiratory aerosol in the environment and influence the viability of microorganisms.


Subject(s)
Aerosols/analysis , Wettability , Body Fluids/chemistry , Humans , Humidity , Lung/chemistry , Particle Size , Water/chemistry
10.
Sci Total Environ ; 821: 153310, 2022 May 15.
Article in English | MEDLINE | ID: covidwho-1730093

ABSTRACT

BACKGROUND: In summer 2020 under the COVID-19 pandemic, the Ministry of Health, Labour and Welfare has made public warnings that specific preventive measures such as maskwearing and stay-at-home orders, may increase heatstroke risk. In our previous work, we found a lower risk of heatstroke-related ambulance dispatches (HSAD) during the COVID-19 period, however, it is uncertain whether similar risk reductions can be observed in different vulnerable subgroups. This study aimed to determine the HSAD risk during the COVID-19 pandemic by age, severity, and incident place subgroups. METHOD: A summer-specific (June-September), time-series analysis was performed, using daily HSAD and meteorological data from 47 Japanese prefectures from 2017 to 2020. A two-stage analysis was applied to determine the association between HSAD and COVID-19 pandemic, adjusting for maximum temperature, humidity, seasonality, and relevant temporal adjustments. A generalized linear model was utilized in the first stage to estimate the prefecture-specific effect estimates. Thereafter, a fixed effect meta-analysis in the second stage was implemented to pool the first stage estimates. Subsequently, subgroup analysis via an interaction by age, severity, and incident place was used to analyze the HSAD risk among subgroups. RESULTS: A total of 274,031 HSAD cases was recorded across 47 Japanese prefectures. The average total number of HSAD in the pre-COVID-19 period was 69,721, meanwhile, the COVID-19 period was 64,869. Highest reductions in the risks was particularly observed in the young category (ratio of relative risk (RRR) = 0.54, 95% Confidential Interval (CI): 0.51, 0.57) compared to the elderly category. Whereas highest increment in the risks were observed in severe/death (RRR = 1.25, 95% CI: 1.13, 1.37) compared to the mild category. CONCLUSION: COVID-19 situation exhibited a non-uniform change in the HSAD risk for all subgroups, with the magnitude of the risks varying by age, severity, and incident place.


Subject(s)
Ambulances , COVID-19 , Heat Stroke , Ambulances/statistics & numerical data , COVID-19/epidemiology , Emergency Medical Services , Heat Stroke/epidemiology , Humans , Humidity , Japan , Pandemics
11.
Environ Res ; 211: 112931, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1704319

ABSTRACT

Background Although associations between key weather indicators (i.e. temperature and humidity) and COVID-19 mortality have been reported, the relationship between these exposures at different timings in early infection stages (from virus exposure up to a few days after symptom onset) and the probability of death after infection (also called case fatality rate, CFR) has yet to be determined. Methods We estimated the instantaneous CFR of eight European countries using Bayesian inference in conjunction with stochastic transmission models, taking account of delays in reporting the number of newly confirmed cases and deaths. The exposure-lag-response associations between fatality rate and weather conditions to which patients were exposed at different timings were obtained using distributed lag nonlinear models coupled with mixed-effect models. Results Our results show that the Odds Ratio (OR) of death is negatively associated with the temperature, with two maxima (OR = 1.29 (95% CI: 1.23, 1.35) at -0.1°C; OR = 1.12 (95% CI: 1.08, 1.16) at 0.1°C) occurring at the time of virus exposure and after symptom onset. Two minima (OR = 0.81 (95% CI: 0.71, 0.92) at 23.2°C; OR = 0.71 (95% CI: 0.63, 0.80) at 21.7°C) also occurred at these two distinct periods correspondingly. Low humidity (below 50%) during the early stages and high humidity (approximately 89%) after symptom onset were related to the lower fatality. Conclusion Environmental conditions may affect not only the initial viral load when patients are exposed to the virus, but also individuals' immune response around symptom onset. Warmer temperatures and higher humidity after symptom onset were linked to lower fatality.


Subject(s)
COVID-19 , Bayes Theorem , Europe/epidemiology , Humans , Humidity , Temperature
12.
Environ Res ; 208: 112484, 2022 May 15.
Article in English | MEDLINE | ID: covidwho-1693480

ABSTRACT

This paper investigates at the world level the influence of climate on the transmission of the SARS-CoV-2 virus. For that purpose, panel regressions of the number of cases and deaths from 134 countries are run on a set of explanatory variables (air temperature, relative humidity, precipitation, and wind) along with control variables (government interventions and population size and density). The analysis is completed with a panel threshold regression to check for potential non-linearities of the weather variables on virus transmission. The main findings support the role of climate in the circulation of the virus across countries. The detailed analysis reveals that relative humidity reduces the number of cases and deaths in both low and high regimes, while temperature and wind reduce the number of deaths.


Subject(s)
COVID-19 , Climate , Communicable Disease Control , Pandemics , COVID-19/epidemiology , COVID-19/prevention & control , Government , Humans , Humidity , Pandemics/prevention & control , SARS-CoV-2 , Temperature , Weather
13.
Pol Arch Intern Med ; 132(1)2022 01 28.
Article in English | MEDLINE | ID: covidwho-1675433

ABSTRACT

INTRODUCTION: COVID­19 is an infectious disease caused by SARS-CoV-2. Little is known on the impact of weather conditions on the transmission of COVID­19. OBJECTIVES: We aimed to assess correlations between 6 different meteorologic parameters and the transmission dynamics of the COVID­19 pandemic in 16 administrative regions (voivodeships) of Poland. PATIENTS AND METHODS: Data for analysis were obtained from epidemiologic reports of the Polish Ministry of Health. For each voivodeship, one synoptic station was selected to provide meteorologic data on daily maximum and minimum temperatures, variability of daily temperature, sunshine duration, relative humidity, and wind speed. The periods with significant weather impact were determined using multiple linear regression. Cross­correlation function (CCF) and random forest models were used to assess correlations between meteorologic parameters and the incidence of COVID­19 as well as the number of hospitalizations for COVID­19. RESULTS: In all voivodeships, the incidence of new COVID­19 cases correlated with relative humidity (CCF = 0.41), daily maximum temperature (CCF = -0.41), variability of daily temperature (CCF = -0.40), and sunshine duration (CCF = 0.35). For all parameters, a similar time lag of 10 to 14 days was noted. There were no significant correlations for wind speed in most voivodeships. The risk of hospitalization for COVID­19 correlated with daily maximum temperature (CCF = -0.48; time lag, 10 days) and sunshine duration (CCF = -0.45; time lag, 10 days). CONCLUSIONS: The delayed effects of the meteorologic factors on the incidence of COVID­19 and the risk of hospitalization for COVID­19 were observed. In each voivodeship, the dynamics of COVID­19 transmission was most strongly affected by relative humidity and daily maximum temperature.


Subject(s)
COVID-19 , Humans , Humidity , Pandemics , Poland/epidemiology , SARS-CoV-2 , Weather
14.
Environ Res ; 209: 112887, 2022 06.
Article in English | MEDLINE | ID: covidwho-1664913

ABSTRACT

BACKGROUND: The SARS-CoV-2 virus pandemic is primarily transmitted by direct contact between infected and uninfected people, though, there are still many unknown factors influencing the survival and transmission of the virus. Air temperature is one of the main susceptible factors. This study aimed to explore the impact of air and land surface temperatures on Covid-19 transmission in a region of Iran. METHOD: Daily Land Surface Temperature (LST) measured by satellite and Air Temperature measured by weather station were used as the predictors of Covid-19 transmission. The data were obtained from February 2020 to April 2021. Spatio-temporal kriging was used in order to predict LST in some days in which no image was recorded by the satellite. The validity of the predicted values was assessed by Bland-Altman technique. The impact of the predictors was analyzed by Distributed Lag Non-linear Model (DLNM). In addition to main effect of temperature, its linear as well as non-linear interaction effect with relative humidity were considered using Generalized Additive Model (GAM) and a bivariate response surface model. Sensitivity analyses were done to select models' parameters, autocorrelation model and function of associations. RESULTS: The dose-response curve revealed that the impact of both predictors was not obvious, though, the risk of transmission tended to be positive due to low values of temperatures. Although the linear interaction effect was not statistically significant, but joint patterns showed that the impact of both LST and AT tended to be different when humidity values were changed. CONCLUSION: However the findings suggested that both LST and AT were not statistically important predictors, but they tended to predict the Covid-19 transmission in some lags. Because of local based evidence, the wide confidence intervals and then non-significant values should be cautiously interpreted.


Subject(s)
COVID-19 , COVID-19/epidemiology , Humans , Humidity , Iran/epidemiology , SARS-CoV-2 , Temperature , Weather
15.
Proc Natl Acad Sci U S A ; 119(4)2022 01 25.
Article in English | MEDLINE | ID: covidwho-1642082

ABSTRACT

The phase state of respiratory aerosols and droplets has been linked to the humidity-dependent survival of pathogens such as SARS-CoV-2. To inform strategies to mitigate the spread of infectious disease, it is thus necessary to understand the humidity-dependent phase changes associated with the particles in which pathogens are suspended. Here, we study phase changes of levitated aerosols and droplets composed of model respiratory compounds (salt and protein) and growth media (organic-inorganic mixtures commonly used in studies of pathogen survival) with decreasing relative humidity (RH). Efflorescence was suppressed in many particle compositions and thus unlikely to fully account for the humidity-dependent survival of viruses. Rather, we identify organic-based, semisolid phase states that form under equilibrium conditions at intermediate RH (45 to 80%). A higher-protein content causes particles to exist in a semisolid state under a wider range of RH conditions. Diffusion and, thus, disinfection kinetics are expected to be inhibited in these semisolid states. These observations suggest that organic-based, semisolid states are an important consideration to account for the recovery of virus viability at low RH observed in previous studies. We propose a mechanism in which the semisolid phase shields pathogens from inactivation by hindering the diffusion of solutes. This suggests that the exogenous lifetime of pathogens will depend, in part, on the organic composition of the carrier respiratory particle and thus its origin in the respiratory tract. Furthermore, this work highlights the importance of accounting for spatial heterogeneities and time-dependent changes in the properties of aerosols and droplets undergoing evaporation in studies of pathogen viability.


Subject(s)
Calcium Chloride/chemistry , Models, Chemical , SARS-CoV-2/chemistry , Serum Albumin/chemistry , Sodium Chloride/chemistry , COVID-19/virology , Diffusion , Disinfection/methods , Humans , Humidity , Kinetics , Microbial Viability , Phase Transition , Surface Properties
16.
Infect Dis Poverty ; 10(1): 139, 2021 Dec 23.
Article in English | MEDLINE | ID: covidwho-1638985

ABSTRACT

BACKGROUND: Since the appearance of severe acute respiratory coronavirus 2 (SARS-CoV-2) and the coronavirus disease 2019 (COVID-19) pandemic, a growing body of evidence has suggested that weather factors, particularly temperature and humidity, influence transmission. This relationship might differ for the recently emerged B.1.617.2 (delta) variant of SARS-CoV-2. Here we use data from an outbreak in Sydney, Australia that commenced in winter and time-series analysis to investigate the association between reported cases and temperature and relative humidity. METHODS: Between 16 June and 10 September 2021, the peak of the outbreak, there were 31,662 locally-acquired cases reported in five local health districts of Sydney, Australia. The associations between daily 9:00 am and 3:00 pm temperature (°C), relative humidity (%) and their difference, and a time series of reported daily cases were assessed using univariable and multivariable generalized additive models and a 14-day exponential moving average. Akaike information criterion (AIC) and the likelihood ratio statistic were used to compare different models and determine the best fitting model. A sensitivity analysis was performed by modifying the exponential moving average. RESULTS: During the 87-day time-series, relative humidity ranged widely (< 30-98%) and temperatures were mild (approximately 11-17 °C). The best-fitting (AIC: 1,119.64) generalized additive model included 14-day exponential moving averages of 9:00 am temperature (P < 0.001) and 9:00 am relative humidity (P < 0.001), and the interaction between these two weather variables (P < 0.001). Humidity was negatively associated with cases no matter whether temperature was high or low. The effect of lower relative humidity on increased cases was more pronounced below relative humidity of about 70%; below this threshold, not only were the effects of humidity pronounced but also the relationship between temperature and cases of the delta variant becomes apparent. CONCLUSIONS: We suggest that the control of COVID-19 outbreaks, specifically those due to the delta variant, is particularly challenging during periods of the year with lower relative humidity and warmer temperatures. In addition to vaccination, stronger implementation of other interventions such as mask-wearing and social distancing might need to be considered during these higher risk periods.


Subject(s)
COVID-19 , Australia/epidemiology , Humans , Humidity , Pandemics , SARS-CoV-2 , Temperature
17.
Eur Rev Med Pharmacol Sci ; 26(1): 305-311, 2022 01.
Article in English | MEDLINE | ID: covidwho-1638619

ABSTRACT

The pandemic of COVID-19 started spreading more exponentially across Pakistan since the end of February 2020. Numerous models and factors have been used to estimate predictions of the prevalence and severity of COVID-19 infections around the globe. While many factors play a role in the spread of COVID-19, climate and weather conditions are considered key elements in the transmission of COVID-19. Many researchers believe that recent increases in COVID-19 cases correlate strongly with local temperatures and factors (such as humidity, weather conditions, etc.) related to it. In this manuscript we test the hypothesis that SARS-CoV-2 spread is temperature-dependent by using the available data derived from Pakistan. The present review focuses on the relationship between temperature and COVID-19, examining the virus's viability and infectivity under various conditions. Our findings indicate that the trough and crest of the COVID-19 wave observed in 2020 are likely to repeat in the summer and winter of 2021, respectively. In Pakistan, temperatures, and humidity significantly affect the COVID-19 transmission and incidence. Like other types of beta-coronaviruses (ß-CoVs), the spread of COVID-19 may depend upon a great deal on temperature.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Weather , Humans , Humidity , Incidence , Pakistan/epidemiology , Pandemics , SARS-CoV-2 , Seasons , Temperature
18.
Environ Res ; 208: 112690, 2022 05 15.
Article in English | MEDLINE | ID: covidwho-1611725

ABSTRACT

The meteorological conditions may affect COVID-19 transmission. However, the roles of seasonality and macro-climate are still contentious due to the limited time series for early-stage studies. We studied meteorological factors' effects on COVID-19 transmission in Brazil from February 25 to November 15, 2020. We aimed to explore whether this impact showed seasonal characteristics and spatial variations related to the macro-climate. We applied two-way fixed-effect models to identify the effects of meteorological factors on COVID-19 transmission and used spatial analysis to explore their spatial-temporal characteristics with a relatively long-time span. The results showed that cold, dry and windless conditions aggravated COVID-19 transmission. The daily average temperature, humidity, and wind speed negatively affected the daily new cases. Humidity and temperature played a dominant role in this process. For the time series, the influences of meteorological conditions on COVID-19 had a periodic fluctuation of 3-4 months (in line with the seasons in Brazil). The turning points of this fluctuation occurred at the turn of seasons. Spatially, the negative effects of temperature and humidity on COVID-19 transmission clustered in the northeastern and central parts of Brazil. This is consistent with the range of arid climate types. Overall, the seasonality and similar climate types should be considered to estimate the spatial-temporal COVID-19 patterns. Winter is a critical time to be alert for COVID-19, especially in the northern part of Brazil.


Subject(s)
COVID-19 , Brazil/epidemiology , COVID-19/epidemiology , Humans , Humidity , Meteorological Concepts , SARS-CoV-2 , Seasons , Temperature
19.
J Environ Manage ; 302(Pt B): 114085, 2022 Jan 15.
Article in English | MEDLINE | ID: covidwho-1587288

ABSTRACT

The coronavirus disease 2019 (COVID-19) has been first reported in December 2019 and rapidly spread worldwide. As other severe acute respiratory syndromes, it is a widely discussed topic whether seasonality affects the COVID-19 infection spreading. This study presents two different approaches to analyse the impact of social activity factors and weather variables on daily COVID-19 cases at county level over the Continental U.S. (CONUS). The first one is a traditional statistical method, i.e., Pearson correlation coefficient, whereas the second one is a machine learning algorithm, i.e., random forest regression model. The Pearson correlation is analysed to roughly test the relationship between COVID-19 cases and the weather variables or the social activity factor (i.e. social distance index). The random forest regression model investigates the feasibility of estimating the number of county-level daily confirmed COVID-19 cases by using different combinations of eight factors (county population, county population density, county social distance index, air temperature, specific humidity, shortwave radiation, precipitation, and wind speed). Results show that the number of daily confirmed COVID-19 cases is weakly correlated with the social distance index, air temperature and specific humidity through the Pearson correlation method. The random forest model shows that the estimation of COVID-19 cases is more accurate with adding weather variables as input data. Specifically, the most important factors for estimating daily COVID-19 cases are the population and population density, followed by the social distance index and the five weather variables, with temperature and specific humidity being more critical than shortwave radiation, wind speed, and precipitation. The validation process shows that the general values of correlation coefficients between the daily COVID-19 cases estimated by the random forest model and the observed ones are around 0.85.


Subject(s)
COVID-19 , Humans , Humidity , SARS-CoV-2 , Temperature , United States , Weather
20.
PLoS One ; 16(9): e0255338, 2021.
Article in English | MEDLINE | ID: covidwho-1518352

ABSTRACT

Global shortages of N95 respirators have led to an urgent need of N95 decontamination and reuse methods that are scientifically validated and available world-wide. Although several large scale decontamination methods have been proposed (hydrogen peroxide vapor, UV-C); many of them are not applicable in remote and low-resource settings. Heat with humidity has been demonstrated as a promising decontamination approach, but care must be taken when implementing this method at a grassroots level. Here we present a simple, scalable method to provide controlled humidity and temperature for individual N95 respirators which is easily applicable in low-resource settings. N95 respirators were subjected to moist heat (>50% relative humidity, 65-80°C temperature) for over 30 minutes by placing them in a sealed container immersed in water that had been brought to a rolling boil and removed from heat, and then allowing the containers to sit for over 45 minutes. Filtration efficiency of 0.3-4.99 µm incense particles remained above 97% after 5 treatment cycles across all particle size sub-ranges. This method was then repeated at a higher ambient temperature and humidity in Mumbai, using standard utensils commonly found in South Asia. Similar temperature and humidity profiles were achieved with no degradation in filtration efficiencies after 6 cycles. Higher temperatures (>70°C) and longer treatment times (>40 minutes) were obtained by insulating the outer vessel. We also showed that the same method can be applied for the decontamination of surgical masks. This simple yet reliable method can be performed even without electricity access using any heat source to boil water, from open-flame stoves to solar heating, and provides a low-cost route for N95 decontamination globally applicable in resource-constrained settings.


Subject(s)
COVID-19/prevention & control , Decontamination/methods , Equipment Reuse/statistics & numerical data , Hot Temperature , Humidity , Masks/standards , N95 Respirators/standards , Asia/epidemiology , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Filtration , Humans , SARS-CoV-2
SELECTION OF CITATIONS
SEARCH DETAIL