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1.
Sci Rep ; 11(1): 24477, 2021 12 29.
Article in English | MEDLINE | ID: covidwho-1599359

ABSTRACT

Assessing the impact of temperature on COVID-19 epidemiology is critical for implementing non-pharmaceutical interventions. However, few studies have accounted for the nature of contagious diseases, i.e., their dependent happenings. We aimed to quantify the impact of temperature on the transmissibility and virulence of COVID-19 in Tokyo, Japan, employing two epidemiological measurements of transmissibility and severity: the effective reproduction number ([Formula: see text]) and case fatality risk (CFR). We estimated the [Formula: see text] and time-delay adjusted CFR and to subsequently assess the nonlinear and delayed effect of temperature on [Formula: see text] and time-delay adjusted CFR. For [Formula: see text] at low temperatures, the cumulative relative risk (RR) at the first temperature percentile (3.3 °C) was 1.3 (95% confidence interval (CI): 1.1-1.7). As for the virulence to humans, moderate cold temperatures were associated with higher CFR, and CFR also increased as the temperature rose. The cumulative RR at the 10th and 99th percentiles of temperature (5.8 °C and 30.8 °C) for CFR were 3.5 (95% CI: 1.3-10.0) and 6.4 (95% CI: 4.1-10.1). Our results suggest the importance to take precautions to avoid infection in both cold and warm seasons to avoid severe cases of COVID-19. The results and our proposed approach will also help in assessing the possible seasonal course of COVID-19 in the future.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Temperature , Basic Reproduction Number , Cold Temperature , Humans , Mortality , Pandemics/prevention & control , Risk , SARS-CoV-2/pathogenicity , Seasons , Severity of Illness Index , Tokyo/epidemiology , Virulence
2.
Sensors (Basel) ; 21(24)2021 Dec 07.
Article in English | MEDLINE | ID: covidwho-1594451

ABSTRACT

Water temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), and salinity levels are the critical cultivation factors for freshwater aquaculture. This paper proposes a novel wireless multi-sensor system by integrating the temperature, pH, DO, and EC sensors with an ESP 32 Wi-Fi module for monitoring the water quality of freshwater aquaculture, which acquires the sensing data and salinity information directly derived from the EC level. The information of water temperature, pH, DO, EC, and salinity levels was displayed in the ThingSpeak IoT platform and was visualized in a user-friendly manner by ThingView APP. Firstly, these sensors were integrated with an ESP32 Wi-Fi platform. The observations of sensors and the estimated salinity from the EC level were then transmitted by a Wi-Fi network to an on-site Wi-Fi access point (AP). The acquired information was further transmitted to the ThingSpeak IoT and displayed in the form of a web-based monitoring system which can be directly visualized by online browsing or the ThingView APP. Through the complete processes of pre-calibration, in situ measurement, and post-calibration, the results illustrate that the proposed wireless multi-sensor IoT system has sufficient accuracy, reliable confidence, and a good tolerance for monitoring the water quality of freshwater aquaculture.


Subject(s)
Aquaculture , Water Quality , Electrocardiography , Fresh Water , Temperature
3.
Infect Dis Poverty ; 10(1): 139, 2021 Dec 23.
Article in English | MEDLINE | ID: covidwho-1581998

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
4.
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
5.
BMC Infect Dis ; 21(1): 1194, 2021 Nov 27.
Article in English | MEDLINE | ID: covidwho-1538060

ABSTRACT

BACKGROUND: To examine whether outdoor transmission may contribute to the COVID-19 epidemic, we hypothesized that slower outdoor wind speed is associated with increased risk of transmission when individuals socialize outside. METHODS: Daily COVID-19 incidence reported in Suffolk County, NY, between March 16th and December 31st, 2020, was the outcome. Average wind speed and maximal daily temperature were collated by the National Oceanic and Atmospheric Administration. Negative binomial regression was used to model incidence rates while adjusting for susceptible population size. RESULTS: Cases were very high in the initial wave but diminished once lockdown procedures were enacted. Most days between May 1st, 2020, and October 24th, 2020, had temperatures 16-28 °C and wind speed diminished slowly over the year and began to increase again in December 2020. Unadjusted and multivariable-adjusted analyses revealed that days with temperatures ranging between 16 and 28 °C where wind speed was < 8.85 km per hour (KPH) had increased COVID-19 incidence (aIRR = 1.45, 95% C.I. = [1.28-1.64], P < 0.001) as compared to days with average wind speed ≥ 8.85 KPH. CONCLUSION: Throughout the U.S. epidemic, the role of outdoor shared spaces such as parks and beaches has been a topic of considerable interest. This study suggests that outdoor transmission of COVID-19 may occur by noting that the risk of transmission of COVID-19 in the summer was higher on days with low wind speed. Outdoor use of increased physical distance between individuals, improved air circulation, and use of masks may be helpful in some outdoor environments where airflow is limited.


Subject(s)
COVID-19 , Wind , Communicable Disease Control , Humans , SARS-CoV-2 , Temperature
6.
Int J Environ Res Public Health ; 18(21)2021 11 06.
Article in English | MEDLINE | ID: covidwho-1512309

ABSTRACT

This paper presents a complex and extensive experimental evaluation of fine particle emissions released by an FDM 3D printer for four of the most common printing materials (ABS, PLA, PET-G, and TPU). These thermoplastic filaments were examined at three printing temperatures within their recommended range. In addition, these measurements were extended using various types of printing nozzles, which influenced the emissions considerably. This research is based on more than a hundred individual measurements for which a standardized printing method was developed. The study presents information about differences between particular printing conditions in terms of the amount of fine particles emitted as well as the particle size distributions during printing periods. This expands existing knowledge about the emission of ultrafine particles during 3D printing, and it can help reduce the emissions of these devices to achieve cleaner and safer 3D printer operations.


Subject(s)
Air Pollution, Indoor , Particulate Matter , Air Pollution, Indoor/analysis , Particle Size , Particulate Matter/analysis , Printing, Three-Dimensional , Temperature
8.
Sci Rep ; 11(1): 22027, 2021 11 11.
Article in English | MEDLINE | ID: covidwho-1510609

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
9.
Environ Res ; 204(Pt D): 112348, 2022 03.
Article in English | MEDLINE | ID: covidwho-1509773

ABSTRACT

Since the start of the COVID-19 pandemic many studies investigated the correlation between climate variables such as air quality, humidity and temperature and the lethality of COVID-19 around the world. In this work we investigate the use of climate variables, as additional features to train a data-driven multivariate forecast model to predict the short-term expected number of COVID-19 deaths in Brazilian states and major cities. The main idea is that by adding these climate features as inputs to the training of data-driven models, the predictive performance improves when compared to equivalent single input models. We use a Stacked LSTM as the network architecture for both the multivariate and univariate model. We compare both approaches by training forecast models for the COVID-19 deaths time series of the city of São Paulo. In addition, we present a previous analysis based on grouping K-means on AQI curves. The results produced will allow achieving the application of transfer learning, once a locality is eventually added to the task, regressing out using a model based on the cluster of similarities in the AQI curve. The experiments show that the best multivariate model is more skilled than the best standard data-driven univariate model that we could find, using as evaluation metrics the average fitting error, average forecast error, and the profile of the accumulated deaths for the forecast. These results show that by adding more useful features as input to a multivariate approach could further improve the quality of the prediction models.


Subject(s)
Air Pollution , COVID-19 , Air Pollution/analysis , Brazil , Humans , Humidity , Pandemics , SARS-CoV-2 , Temperature
10.
Sci Rep ; 11(1): 21812, 2021 11 08.
Article in English | MEDLINE | ID: covidwho-1505841

ABSTRACT

An estimation of the impact of climatic conditions-measured with an index that combines temperature and humidity, the IPTCC-on the hospitalizations and deaths attributed to SARS-CoV-2 is proposed. The present paper uses weekly data from 54 French administrative regions between March 23, 2020 and January 10, 2021. Firstly, a Granger causal analysis is developed and reveals that past values of the IPTCC contain information that allow for a better prediction of hospitalizations or deaths than that obtained without the IPTCC. Finally, a vector autoregressive model is estimated to evaluate the dynamic response of hospitalizations and deaths after an increase in the IPTCC. It is estimated that a 10-point increase in the IPTCC causes hospitalizations to rise by 2.9% (90% CI 0.7-5.0) one week after the increase, and by 4.1% (90% CI 2.1-6.4) and 4.4% (90% CI 2.5-6.3) in the two following weeks. Over ten weeks, the cumulative effect is estimated to reach 20.1%. Two weeks after the increase in the IPTCC, deaths are estimated to rise by 3.7% (90% CI 1.6-5.8). The cumulative effect from the second to the tenth weeks reaches 15.8%. The results are robust to the inclusion of air pollution indicators.


Subject(s)
Air Pollutants , Air Pollution , COVID-19/epidemiology , COVID-19/mortality , Climate , Hospitalization/statistics & numerical data , SARS-CoV-2 , Algorithms , Bayes Theorem , Decision Making , France/epidemiology , Hospitals , Humans , Humidity , Infectious Disease Medicine , Reproducibility of Results , Respiration Disorders , Seasons , Temperature
11.
Sci Rep ; 11(1): 21723, 2021 11 05.
Article in English | MEDLINE | ID: covidwho-1503978

ABSTRACT

Coronavirus with intact infectivity attached to PPE surfaces pose significant threat to the spread of COVID-19. We tested the hypothesis that an electroceutical fabric, generating weak potential difference of 0.5 V, disrupts the infectivity of coronavirus upon contact by destabilizing the electrokinetic properties of the virion. Porcine respiratory coronavirus AR310 particles (105) were placed in direct contact with the fabric for 1 or 5 min. Following one minute of contact, zeta potential of the porcine coronavirus was significantly lowered indicating destabilization of its electrokinetic properties. Size-distribution plot showed appearance of aggregation of the virus. Testing of the cytopathic effects of the virus showed eradication of infectivity as quantitatively assessed by PI-calcein and MTT cell viability tests. This work provides the rationale to consider the studied electroceutical fabric, or other materials with comparable property, as material of choice for the development of PPE in the fight against COVID-19.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Electrochemistry/methods , Textiles , Animals , Anti-Infective Agents , Body Fluids , Cell Line , Cell Survival , Fluoresceins , Humans , Hydrogen Peroxide , Kinetics , Nanoparticles , Propidium , SARS-CoV-2 , Swine , Temperature , Tetrazolium Salts , Thiazoles , Virion , Wound Healing
12.
J Occup Environ Med ; 63(6): 462-468, 2021 06 01.
Article in English | MEDLINE | ID: covidwho-1494061

ABSTRACT

OBJECTIVE: To estimate the association between weather and COVID-19 fatality rates during US stay-at-home orders. METHODS: With a county-level longitudinal design, this study analyzed COVID-19 deaths from public health departments' daily reports and considered exposure as the 18 to 22 day-period before death. Models included state-level social distancing measures, Census Bureau demographics, daily weather information, and daily air pollution. The primary measures included minimum and maximum daily temperature, precipitation, ozone concentration, PM2.5 concentrations, and U.V. light index. RESULTS: A 1 °F increase in the minimum temperature was associated with 1.9% (95% CI, 0.2% to 3.6%) increase in deaths 20 days later. An ozone concentration increase of 1 ppb (part per billion) decreased daily deaths by 2.0% (95% CI, 0.1% to 3.6%); ozone levels below 38 ppb negatively correlated with deaths. CONCLUSIONS: Increased mobility may drive the observed association of minimum daily temperature on COVID-19 deaths.


Subject(s)
COVID-19/mortality , Weather , Air Pollutants/analysis , COVID-19/prevention & control , Humans , Models, Theoretical , Ozone/analysis , Physical Distancing , SARS-CoV-2 , Temperature , United States/epidemiology
13.
Sensors (Basel) ; 21(21)2021 Oct 30.
Article in English | MEDLINE | ID: covidwho-1488704

ABSTRACT

Since students and teachers spend much of their time in educational buildings, it is critical to provide good levels of indoor environmental quality (IEQ). The current COVID-19 pandemic has shown that maintaining a good indoor air quality level is an effective measure to control the transmission of the SARS-CoV-2 virus. This study used sensors to monitor key IEQ factors and assess several natural ventilation scenarios in a classroom of the University of Granada. Subsequently, the IEQ factors (temperature, relative humidity, CO2 concentration, acoustic environment, and air velocity) were evaluated for the selected ventilation scenarios in the occupied classroom, and the field monitoring was carried out in two different assessment periods, winter and summer. The obtained results show that the CO2 concentration levels were well below the recommended limits. However, the maintenance of the recommended thermal and acoustic IEQ factors was significantly affected by the natural ventilation strategies (temperature and relative humidity values were very close to the outside values, and the background sound pressure level was over 35 dBA during the entire assessment). The proper measurements and careful selection of the appropriate ventilation scenarios become of utmost importance to ensure that the ventilation rates required by the health authorities are achieved.


Subject(s)
Air Pollution, Indoor , COVID-19 , Air Pollution, Indoor/analysis , Environmental Monitoring , Humans , Pandemics , SARS-CoV-2 , Spain , Temperature , Ventilation
15.
Am J Infect Control ; 49(11): 1445-1447, 2021 11.
Article in English | MEDLINE | ID: covidwho-1482406

ABSTRACT

Infrared temperature measurement is a common form of mass screening for febrile illnesses such as COVID-19 infection. Efficacy of infrared monitoring is debated, and external factors can affect accuracy. We determine that outside temperature, wind, and humidity can affect infrared temperature measurements and partially account for inaccurate results.


Subject(s)
COVID-19 , Body Temperature , Humans , Humidity , Mass Screening , SARS-CoV-2 , Temperature
16.
Sci Rep ; 11(1): 20791, 2021 10 21.
Article in English | MEDLINE | ID: covidwho-1479819

ABSTRACT

Implementation of various restrictions to eradicate viral diseases has globally affected human activity and subsequently nature. But how can the altered routines of human activity (restrictions, lockdowns) affect wildlife behaviour? This study compared the differences between human and wildlife occurrences in the study forest area with acreage of 5430.6 ha in 2018 (African swine fever outbreak, complete entrance ban), 2019 (standard pattern) and 2020 (COVID-19 restrictions) during the breeding season. The number of visitors was lower by 64% in 2018 (non-respecting of the entry ban by forest visitors) compared to standard 2019, while in 2020, the number of visitors increased to 151%. In the COVID-19 period, distinct peaks in the number of visitors were observed between 8-11 AM and 4-7 PM. The peaks of wildlife activity were recorded between 4-7 AM and 9-12 PM. Animals avoided the localities that were visited by humans during the people-influenced time (24 h after people visit), which confirmed the direct negative impact of human activities on wildlife.


Subject(s)
African Swine Fever/epidemiology , Animals, Wild , COVID-19/epidemiology , Communicable Disease Control/methods , Disease Outbreaks , Human Activities , Animals , Female , Geography , Humans , Male , Pandemics , Regression Analysis , SARS-CoV-2 , Swine , Temperature , Virus Diseases/epidemiology
17.
Sci Rep ; 11(1): 20877, 2021 10 22.
Article in English | MEDLINE | ID: covidwho-1479811

ABSTRACT

Adenovirus vectors offer a platform technology for vaccine development. The value of the platform has been proven during the COVID-19 pandemic. Although good stability at 2-8 °C is an advantage of the platform, non-cold-chain distribution would have substantial advantages, in particular in low-income countries. We have previously reported a novel, potentially less expensive thermostabilisation approach using a combination of simple sugars and glass micro-fibrous matrix, achieving excellent recovery of adenovirus-vectored vaccines after storage at temperatures as high as 45 °C. This matrix is, however, prone to fragmentation and so not suitable for clinical translation. Here, we report an investigation of alternative fibrous matrices which might be suitable for clinical use. A number of commercially-available matrices permitted good protein recovery, quality of sugar glass and moisture content of the dried product but did not achieve the thermostabilisation performance of the original glass fibre matrix. We therefore further investigated physical and chemical characteristics of the glass fibre matrix and its components, finding that the polyvinyl alcohol present in the glass fibre matrix assists vaccine stability. This finding enabled us to identify a potentially biocompatible matrix with encouraging performance. We discuss remaining challenges for transfer of the technology into clinical use, including reliability of process performance.


Subject(s)
Adenoviridae/genetics , Adenovirus Vaccines/chemistry , COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , Vaccine Potency , Adenoviruses, Simian , Biocompatible Materials , Calorimetry, Differential Scanning , Glass , HEK293 Cells , Humans , Light , Magnetic Resonance Spectroscopy , Materials Testing , Microscopy, Confocal , Microscopy, Electron, Scanning , Polyvinyl Alcohol , Rabies Vaccines , Scattering, Radiation , Spectroscopy, Fourier Transform Infrared , Sugars/chemistry , Temperature , Thermogravimetry , Trehalose/chemistry
18.
BMC Public Health ; 21(1): 1693, 2021 09 16.
Article in English | MEDLINE | ID: covidwho-1477394

ABSTRACT

BACKGROUND: Many persons with active SARS-CoV-2 infection experience mild or no symptoms, presenting barriers to COVID-19 prevention. Regular temperature screening is nonetheless used in some settings, including university campuses, to reduce transmission potential. We evaluated the potential impact of this strategy using a prospective university-affiliated cohort. METHODS: Between June and August 2020, 2912 participants were enrolled and tested for SARS-CoV-2 by PCR at least once (median: 3, range: 1-9). Participants reported temperature and symptoms daily via electronic survey using a previously owned or study-provided thermometer. We assessed feasibility and acceptability of daily temperature monitoring, calculated sensitivity and specificity of various fever-based strategies for restricting campus access to reduce transmission, and estimated the association between measured temperature and SARS-CoV-2 test positivity using a longitudinal binomial mixed model. RESULTS: Most participants (70.2%) did not initially have a thermometer for taking their temperature daily. Across 5481 total person months, the average daily completion rate of temperature values was 61.6% (median: 67.6%, IQR: 41.8-86.2%). Sensitivity for SARS-CoV-2 ranged from 0% (95% CI 0-9.7%) to 40.5% (95% CI 25.6-56.7%) across all strategies for self-report of possible COVID-19 symptoms on day of specimen collection, with corresponding specificity of 99.9% (95% CI 99.8-100%) to 95.3% (95% CI 94.7-95.9%). An increase of 0.1 °F in individual mean body temperature on the same day as specimen collection was associated with 1.11 increased odds of SARS-CoV-2 positivity (95% CI 1.06-1.17). CONCLUSIONS: Our study is the first, to our knowledge, that examines the feasibility, acceptability, and effectiveness of daily temperature screening in a prospective cohort during an infectious disease outbreak, and the only study to assess these strategies in a university population. Daily temperature monitoring was feasible and acceptable; however, the majority of potentially infectious individuals were not detected by temperature monitoring, suggesting that temperature screening is insufficient as a primary means of detection to reduce transmission of SARS-CoV-2.


Subject(s)
COVID-19 , Feasibility Studies , Humans , Prospective Studies , SARS-CoV-2 , Temperature , Universities
19.
Appl Environ Microbiol ; 87(21): e0137121, 2021 10 14.
Article in English | MEDLINE | ID: covidwho-1470497

ABSTRACT

Phage Phi6 is an enveloped virus considered a possible nonpathogenic surrogate for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other viral pathogens in transmission studies. Larger input amounts of bacteriophage Phi6 are shown to delay and protect the phage from environmental decay, both when the phages are dried in plastic tubes and when they are stored in saline solution at 4°C. In contrast, when bacteriophage Phi6 is placed in LB (Luria-Bertani) growth medium (instead of saline) prior to placement on the plastic surface, the influence of the starting concentration on viral recovery is negligible. Protection is reflected in the phage half-lives at higher concentrations being longer than the half-lives at lower concentrations. Because experiments supporting the possibility of fomite transmission of SARS-CoV-2 and other viruses rely upon the survival of infectious virus following inoculation onto various surfaces, large initial amounts of input virus on a surface may generate artificially inflated survival times compared to realistic lower levels of virus that a subject would normally encounter. This is not only because there are extra half-lives to go through at higher concentrations but also because the half-lives themselves are extended at higher virus concentrations. It is important to design surface drying experiments for pathogens with realistic levels of input virus and to consider the role of the carrier and matrix if the results are to be clinically relevant. IMPORTANCE During the coronavirus disease 2019 (COVID-19) pandemic, much attention has been paid to the environmental decay of SARS-CoV-2 due to the proposed transmission of the virus via fomites. However, published experiments have commenced with inocula with very high virus titers, an experimental design not representative of real-life conditions. The study described here evaluated the impact of the initial virus titer on the environmental decay of an enveloped virus, using a nonpathogenic surrogate for the transmission of SARS-CoV-2, enveloped bacteriophage Phi6. We establish that higher concentrations of virus can protect the virus from environmental decay, depending on conditions. This has important implications for stability studies of SARS-CoV-2 and other viruses. Our results point to a limitation in the fundamental methodology that has been used to attribute fomite transmission for almost all respiratory viruses.


Subject(s)
Bacteriophage phi 6 , Pseudomonas syringae/virology , Culture Media , Desiccation , Fomites/virology , Half-Life , Plastics , SARS-CoV-2 , Saline Solution , Temperature , Virus Inactivation
20.
Nat Commun ; 12(1): 5968, 2021 10 13.
Article in English | MEDLINE | ID: covidwho-1467102

ABSTRACT

There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (Re) in 409 cities in 26 countries, with a decrease of 0.087 (95% CI: 0.025; 0.148) for a 10 °C increase. Early interventions have a greater effect on Re with a decrease of 0.285 (95% CI 0.223; 0.347) for a 5th - 95th percentile increase in the government response index. The variation in the effective reproduction number explained by government interventions is 6 times greater than for mean temperature. We find little evidence of meteorological conditions having influenced the early stages of local epidemics and conclude that population behaviour and government interventions are more important drivers of transmission.


Subject(s)
COVID-19/transmission , Meteorological Concepts , SARS-CoV-2/pathogenicity , Basic Reproduction Number , COVID-19/epidemiology , Cities , Cross-Sectional Studies , Humans , Meta-Analysis as Topic , Pandemics , Regression Analysis , Seasons , Temperature , Weather
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