ABSTRACT
Intro: Surface and environment disinfection is an important part of infection control strategies, especially in the ongoing COVID-19 pandemic. Ozone, a highly reactive oxidant, is a widely used disinfectant in many industries including food, healthcare and water treatment. It has a broad-spectrum activity and leaves no harmful residues. However, most demonstrated efficacy has been at high ozone levels (>1ppm) which can be harmful to humans in case of exposure. Here, we undertook a study to evaluate if exposure to ozone is effective in inactivating SARS-CoV-2 and feline coronavirus (FCoV) even at low concentrations. Method(s): Ozone at 0.07, 0.1 and 1.2 ppm were evaluated for its virucidal activity against SARS-CoV-2 and FCoV. An ozone gas generator (Medklinn Air + Surface Sterilizer (CerafusionTM Technology), Medklinn, Malaysia) supplied controlled levels of ozone to a custom-built chamber of 1.5 ft3 (1.5ft x 1ft x 1ft) where dry virus films containing 1 x 104 PFU of test virus were exposed to ozone gas for 0.5h, 1h, 3h, 5h, and 8h. The experiment was performed at ambient temperature (23-24oC) and relative humidity (RH) of 55% (FCoV only) and 85% (SARS-CoV-2 and FCoV). Finding(s): At low level of ozone of 0.1ppm, >90% reduction of both viruses was achieved after 3h exposure at 85% and 55% humidity. At 1.2ppm, >90% reduction of both viruses was achieved after 0.5h exposure at 85% humidity. Ozone at 0.07ppm, however, did not show good efficacy as reduction not exceeding 90% was achieved only after 8h exposure at 85% and 55% humidity. Conclusion(s): The study demonstrated that low concentration of ozone of at least 0.1 ppm reduced SARS-CoV-2 and FCoV by >90% when used at 85% humidity. The use of low level ozone presents a safer alternative for disinfecting enclosed spaces and greatly reduces any potential harmful health effects in case of accidental exposure.Copyright © 2023
ABSTRACT
BACKGROUND: Evidence is limited regarding the association between meteorological factors and COVID-19 transmission in low- and middle-income countries (LMICs). OBJECTIVE: To investigate the independent and interactive effects of temperature, relative humidity (RH), and ultraviolet (UV) radiation on the spread of COVID-19 in LMICs. METHODS: We collected daily data on COVID-19 confirmed cases, meteorological factors and non-pharmaceutical interventions (NPIs) in 2143 city- and district-level sites from 6 LMICs during 2020. We applied a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the independent and interactive effects of meteorological factors on COVID-19 transmission after controlling NPIs. We generated an overall estimate through pooling site-specific relative risks (RR) using a multivariate meta-regression model. RESULTS: There was a positive, non-linear, association between temperature and COVID-19 confirmed cases in all study sites, while RH and UV showed negative non-linear associations. RR of the 90th percentile temperature (28.1 °C) was 1.14 [95% confidence interval (CI): 1.02, 1.28] compared with the 50th percentile temperature (24.4 °C). RR of the10th percentile UV was 1.41 (95% CI: 1.29, 1.54). High temperature and high RH were associated with increased risks in temperate climate but decreased risks in tropical climate, while UV exhibited a consistent, negative association across climate zones. Temperature, RH, and UV interacted to affect COVID-19 transmission. Temperature and RH also showed higher risks in low NPIs sites. CONCLUSION: Temperature, RH, and UV appeared to independently and interactively affect the transmission of COVID-19 in LMICs but such associations varied with climate zones. Our results suggest that more attention should be paid to meteorological variation when the transmission of COVID-19 is still rampant in LMICs.
ABSTRACT
Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO2 ). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.
Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Environmental Pollutants , Humans , United States/epidemiology , COVID-19/epidemiology , Spain/epidemiology , Bayes Theorem , Communicable Disease Control , Air Pollution/analysis , Weather , Air Pollutants/toxicity , Air Pollutants/analysis , Italy/epidemiology , China/epidemiology , Disease Outbreaks , Gases , Particulate Matter/analysisABSTRACT
Globally, the spread and severity of COVID-19 have been distinctly non-uniform. Seasonality was suggested as a contributor to regional variability, but the relationship between weather and COVID-19 remains unclear and the focus of attention has been on outdoor conditions. Because humans spend most of their time indoors and because most transmission occurs indoors, we here, instead, investigate the hypothesis that indoor climate-particularly indoor relative humidity (RH)-may be the more relevant modulator of outbreaks. To study this association, we combined population-based COVID-19 statistics and meteorological measurements from 121 countries. We rigorously processed epidemiological data to reduce bias, then developed and experimentally validated a computational workflow to estimate indoor conditions based on outdoor weather data and standard indoor comfort conditions. Our comprehensive analysis shows robust and systematic relationships between regional outbreaks and indoor RH. In particular, we found intermediate RH (40-60%) to be robustly associated with better COVID-19 outbreak outcomes (versus RH < 40% or >60%). Together, these results suggest that indoor conditions, particularly indoor RH, modulate the spread and severity of COVID-19 outbreaks.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Humidity , Weather , TemperatureABSTRACT
BACKGROUND: The associations between meteorological factors and coronavirus disease 2019 (COVID-19) have been discussed globally; however, because of short study periods, the lack of considering lagged effects, and different study areas, results from the literature were diverse and even contradictory. OBJECTIVE: The primary purpose of this study is to conduct more reliable research to evaluate the lagged meteorological impacts on COVID-19 incidence by considering a relatively long study period and diversified high-risk areas in the United States. METHODS: This study adopted the distributed lagged nonlinear model with a spatial function to analyze COVID-19 incidence predicted by multiple meteorological measures from March to October of 2020 across 203 high-risk counties in the United States. The estimated spatial function was further smoothed within the entire continental United States by the biharmonic spline interpolation. RESULTS: Our findings suggest that the maximum temperature, minimum relative humidity, and precipitation were the best meteorological predictors. Most significantly positive associations were found from 3 to 11 lagged days in lower levels of each selected meteorological factor. In particular, a significantly positive association appeared in minimum relative humidity higher than 88.36% at 5-day lag. The spatial analysis also shows excessive risks in the north-central United States. SIGNIFICANCE: The research findings can contribute to the implementation of early warning surveillance of COVID-19 by using weather forecasting for up to two weeks in high-risk counties.
Subject(s)
COVID-19 , COVID-19/epidemiology , China/epidemiology , Humans , Humidity , Incidence , Meteorological Concepts , Meteorology , Spatio-Temporal Analysis , Temperature , United States/epidemiologyABSTRACT
During a pandemic, and given the need to quickly screen febrile and non-febrile humans, it is necessary to know the concordance between different thermometers (TMs) and understand how environmental factors influence the measurements made by these instruments. OBJECTIVE: The objective of this study is to identify the potential influence of environmental factors on the measurements made by four different TMs and the concordance between these instruments in a hospital setting. METHOD: The study employed a cross-sectional observational methodology. The participants were patients who had been hospitalised in the traumatology unit. The variables were body temperature, room temperature, room relative humidity, light, and noise. The instruments used were a Non Contract Infrared TM, Axillary Electronic TM, Gallium TM, and Tympanic TM. A lux meter, a sound level meter, and a thermohygrometer measured the ambient variables. RESULTS: The study sample included 288 participants. Weak significant relationships were found between noise and body temperature measured with Tympanic Infrared TM, r = -0.146 (p < 0.01) and likewise between environmental temperature and this same TM, r = 0.133 (p < 0.05). The concordance between the measurements made by the four different TMs showed an Intraclass Correlation Coefficient (ICC) of 0.479. CONCLUSIONS: The concordance between the four TMs was considered "fair".
Subject(s)
Body Temperature , Thermometers , Humans , Cross-Sectional Studies , Fever , HospitalsABSTRACT
Heightened by the COVID-19 pandemic there has been a global increase in urban greenspace appreciation. Indoor plants are equally important for improving mental health and air quality but despite evolving in humid (sub)tropical environments with aerial root types, planting systems ignore aerial resource supply. This study directly compared nutrient uptake preferences of aerial and soil-formed roots of three common houseplant species under high and ambient relative humidities. Growth and physiology parameters were measured weekly for Anthurium andreanum, Epipremnum aureum and Philodendron scandens grown in custom made growth chambers. Both aerial and soil-formed roots were then fed mixtures of nitrate, ammonium and glycine, with one source labelled with 15 N to determine uptake rates and maximum capacities. Aerial roots were consistently better at nitrogen uptake than soil roots but no species, root type or humidity condition showed a preference for a particular nitrogen source. All three species grew more in high humidity, with aerial roots demonstrating the greatest biomass increase. Higher humidities for indoor niches, together with fertiliser applications to aerial roots will support indoor plant growth, creating lush calming indoor environments for people inhabitants.
Subject(s)
Araceae , COVID-19 , Humans , Humidity , Pandemics , Plants , Soil , Nitrogen , Plant RootsABSTRACT
Environmental parameters have a significant impact on the spread of respiratory viral diseases (temperature (T), relative humidity (RH), and air saturation state). T and RH are strongly correlated with viral inactivation in the air, whereas supersaturated air can promote droplet deposition in the respiratory tract. This study introduces a new concept, the dynamic virus deposition ratio (α), that reflects the dynamic changes in viral inactivation and droplet deposition under varying ambient environments. A non-steady-state-modified Wells-Riley model is established to predict the infection risk of shared air space and highlight the high-risk environmental conditions. Findings reveal that a rise in T would significantly reduce the transmission of COVID-19 in the cold season, while the effect is not significant in the hot season. The infection risk under low-T and high-RH conditions, such as the frozen seafood market, is substantially underestimated, which should be taken seriously. The study encourages selected containment measures against high-risk environmental conditions and cross-discipline management in the public health crisis based on meteorology, government, and medical research.
ABSTRACT
AIMS: Assess the persistence of infectious SARS-CoV-2 virus and virus genomic material on three common food coverings. METHODS AND RESULTS: The stability of infectious virus and genomic material on plastic wrap, fruit wax, and cardboard takeout containers was measured. SARS-CoV-2 in simulated saliva was applied to the surface of these materials and allowed to dry. Samples were stored at 4°C or 20°C and a relative humidity of 30%, 50%, 65%, or 70% for up to 7 days. Viability was measured by TCID50 and the half-life for infectious virus was determined to be ~24 hours and ~8 hours at 4°C and 20°C, respectively, on all surfaces and RH tested. There was no loss of virus genomic material as measured by qRT-PCR at all conditions evaluated. CONCLUSIONS: SARS-CoV-2 virus remains infectious on food coverings for hours to days. It is estimated that a 99.9% reduction in titer requires 10 days at 4°C and 3 days at 20°C for all RH tested. SARS-CoV-2 genomic material showed no loss when assayed by qRT-PCR. Significance and Impact of Study: SARS-CoV-2 virus on food coverings loses infectivity over a certain period, but PCR assays can still detect virus genomic material throughout the same time. Thus, testing and controls may need to consider the fact that virus genomic material may still be detected when no infectious virus is present.
Subject(s)
COVID-19 , SARS-CoV-2 , Fruit , PlasticsABSTRACT
The ongoing pandemic created by COVID-19 has co-existed with humans for some time now, thus resulting in unprecedented disease burden. Previous studies have demonstrated the non-linear and single effects of meteorological factors on viral transmission and have a question of how to exclude the influence of unrelated confounding factors on the relationship. However, the interactions involved in such relationships remain unclear under complex weather conditions. Here, we used a panel smooth transition regression (PSTR) model to investigate the non-linear interactive impact of meteorological factors on daily new cases of COVID-19 based on a panel dataset of 58 global cities observed between Jul 1, 2020 and Jan 13, 2022. This new approach offers a possibility of assessing interactive effects of meteorological factors on daily new cases and uses fixed effects to control other unrelated confounding factors in a panel of cities. Our findings revealed that an optimal temperature range (0°C-20 °C) for the spread of COVID-19. The effect of RH (relative humidity) and DTR (diurnal temperature range) on infection became less positive (coefficient: 0.0427 to -0.0142; p < 0.05) and negative (coefficient: -0.0496 to -0.0248; p < 0.05) with increasing average temperature(T). The highest risk of infection occurred when the temperature was -10 °C and RH was >80% or when the temperature was 10 °C and DTR was 1 °C. Our findings highlight useful implications for policymakers and the general public.