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1.
Viruses ; 14(3)2022 03 16.
Article in English | MEDLINE | ID: covidwho-1742736

ABSTRACT

To understand how SARS-CoV-2 spreads indoors, in this study bovine coronavirus was aerosolized as simulant into a plexiglass chamber with coupons of metal, wood and plastic surfaces. After aerosolization, chamber and coupon surfaces were swiped to quantify the virus concentrations using quantitative polymerase chain reaction (qPCR). Bio-layer interferometry showed stronger virus association on plastic and metal surfaces, however, higher dissociation from wood in 80% relative humidity. Virus aerosols were collected with the 100 L/min wetted wall cyclone and the 50 L/min MD8 air sampler and quantitated by qPCR. To monitor the effect of the ventilation on the virus movement, PRD1 bacteriophages as virus simulants were disseminated in a ¾ scale air-conditioned hospital test room with twelve PM2.5 samplers at 15 L/min. Higher virus concentrations were detected above the patient's head and near the foot of the bed with the air inlet on the ceiling above, exhaust bottom left on the wall. Based on room layout, air measurements and bioaerosol collections computational flow models were created to visualize the movement of the virus in the room airflow. The addition of air curtain at the door minimized virus concentration while having the inlet and exhaust on the ceiling decreased overall aerosol concentration. Controlled laboratory experiments were conducted in a plexiglass chamber to gain more insight into the fundamental behavior of aerosolized SARS-CoV-2 and understand its fate and transport in the ambient environment of the hospital room.


Subject(s)
COVID-19 , Aerosols/analysis , Animals , Cattle , Climate , Hospitals , Humans , SARS-CoV-2/genetics
2.
Nature ; 580(7804): 432, 2020 04.
Article in English | MEDLINE | ID: covidwho-1735205

Subject(s)
Climate , Poverty , Politics
3.
J Infect Dis ; 225(6): 957-964, 2022 03 15.
Article in English | MEDLINE | ID: covidwho-1735580

ABSTRACT

Nonpharmaceutical interventions (NPIs) were widely introduced to combat the coronavirus disease 2019 (COVID-19) pandemic. These interventions also likely led to substantially reduced activity of respiratory syncytial virus (RSV). From late 2020, some countries observed out-of-season RSV epidemics. Here, we analyzed the role of NPIs, population mobility, climate, and severe acute respiratory syndrome coronavirus 2 circulation in RSV rebound through a time-to-event analysis across 18 countries. Full (re)opening of schools was associated with an increased risk for RSV rebound (hazard ratio [HR], 23.29 [95% confidence interval {CI}, 1.09-495.84]); every 5°C increase in temperature was associated with a decreased risk (HR, 0.63 [95% CI, .40-.99]). There was an increasing trend in the risk for RSV rebound over time, highlighting the role of increased population susceptibility. No other factors were found to be statistically significant. Further analysis suggests that increasing population susceptibility and full (re)opening of schools could both override the countereffect of high temperatures, which explains the out-of-season RSV epidemics during the COVID-19 pandemic.


Subject(s)
COVID-19/epidemiology , Respiratory Syncytial Virus Infections/epidemiology , Respiratory Syncytial Virus, Human , Climate , Humans , Pandemics , Respiratory Syncytial Virus Infections/prevention & control , Respiratory Syncytial Virus, Human/pathogenicity , Seasons , Temperature
4.
Sci Rep ; 12(1): 3821, 2022 03 09.
Article in English | MEDLINE | ID: covidwho-1735280

ABSTRACT

The effectiveness of containment measures has been shown to depend on both epidemiological and sociological mechanisms, most notably compliance with national lockdown rules. Yet, there has been growing discontent with social distancing rules during national lockdowns across several countries, particularly among certain demographic and socio-economic groups. Using a highly granular dataset on compliance of over 105,000 individuals between March and May 2020 in the United Kingdom (UK), we find that compliance with lockdown policies was initially high in the overall population during the earlier phase of the pandemic, but that compliance fell substantially over time, especially among specific segments of society. Warmer temperatures increased the non-compliance of individuals who are male, divorced, part-time employed, and/or parent of more than two children. Thus, while epidemiologically the virus spread was naturally more limited during the warmer period of 2020, sociologically the higher temperature led to lower individual-level compliance with public health measures. As long as new strains emerge, governments may therefore be required to complement vaccination campaigns with targeted and time limited restrictions. Since non-complying individuals at the beginning of the pandemic share certain characteristics with vaccination sceptics, understanding their compliance behaviour will remain essential for future policymaking.


Subject(s)
COVID-19/epidemiology , Climate , Adult , COVID-19/virology , Female , Humans , Male , Quarantine , SARS-CoV-2/isolation & purification , Socioeconomic Factors , Temperature , Time Factors , United Kingdom/epidemiology
5.
Int J Environ Res Public Health ; 17(10)2020 05 17.
Article in English | MEDLINE | ID: covidwho-1725622

ABSTRACT

This paper investigates whether the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) pandemic could have been favored by specific weather conditions and other factors. It is found that the 2020 winter weather in the region of Wuhan (Hubei, Central China)-where the virus first broke out in December and spread widely from January to February 2020-was strikingly similar to that of the Northern Italian provinces of Milan, Brescia and Bergamo, where the pandemic broke out from February to March. The statistical analysis was extended to cover the United States of America, which overtook Italy and China as the country with the highest number of confirmed COronaVIrus Disease 19 (COVID-19) cases, and then to the entire world. The found correlation patterns suggest that the COVID-19 lethality significantly worsens (4 times on average) under weather temperatures between 4 ∘ C and 12 ∘ C and relative humidity between 60% and 80%. Possible co-factors such as median population age and air pollution were also investigated suggesting an important influence of the former but not of the latter, at least, on a synoptic scale. Based on these results, specific isotherm world maps were generated to locate, month by month, the world regions that share similar temperature ranges. From February to March, the 4-12 ∘ C isotherm zone extended mostly from Central China toward Iran, Turkey, West-Mediterranean Europe (Italy, Spain and France) up to the United State of America, optimally coinciding with the geographic regions most affected by the pandemic from February to March. It is predicted that in the spring, as the weather gets warm, the pandemic will likely worsen in northern regions (United Kingdom, Germany, East Europe, Russia and North America) while the situation will likely improve in the southern regions (Italy and Spain). However, in autumn, the pandemic could come back and affect the same regions again. The Tropical Zone and the entire Southern Hemisphere, but in restricted colder southern regions, could avoid a strong pandemic because of the sufficiently warm weather during the entire year and because of the lower median age of their population. Google-Earth-Pro interactive-maps covering the entire world are provided as supplementary files.


Subject(s)
Climate , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Seasons , Age Factors , Betacoronavirus , COVID-19 , Coronavirus Infections/mortality , Humans , Pandemics , Pneumonia, Viral/mortality , SARS-CoV-2
6.
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
7.
Parasit Vectors ; 15(1): 23, 2022 Jan 10.
Article in English | MEDLINE | ID: covidwho-1627901

ABSTRACT

BACKGROUND: Yellow fever virus (YFV) is an arbovirus that, despite the existence of a safe and effective vaccine, continues to cause outbreaks of varying dimensions in the Americas and Africa. Between 2017 and 2019, Brazil registered un unprecedented sylvatic YFV outbreak whose severity was the result of its spread into zones of the Atlantic Forest with no signals of viral circulation for nearly 80 years. METHODS: To investigate the influence of climatic, environmental, and ecological factors governing the dispersion and force of infection of YFV in a naïve area such as the landscape mosaic of Rio de Janeiro (RJ), we combined the analyses of a large set of data including entomological sampling performed before and during the 2017-2019 outbreak, with the geolocation of human and nonhuman primates (NHP) and mosquito infections. RESULTS: A greater abundance of Haemagogus mosquitoes combined with lower richness and diversity of mosquito fauna increased the probability of finding a YFV-infected mosquito. Furthermore, the analysis of functional traits showed that certain functional groups, composed mainly of Aedini mosquitoes which includes Aedes and Haemagogus mosquitoes, are also more representative in areas where infected mosquitoes were found. Human and NHP infections were more common in two types of landscapes: large and continuous forest, capable of harboring many YFV hosts, and patches of small forest fragments, where environmental imbalance can lead to a greater density of the primary vectors and high human exposure. In both, we show that most human infections (~ 62%) occurred within an 11-km radius of the finding of an infected NHP, which is in line with the flight range of the primary vectors. CONCLUSIONS: Together, our data suggest that entomological data and landscape composition analyses may help to predict areas permissive to yellow fever outbreaks, allowing protective measures to be taken to avoid human cases.


Subject(s)
Brazil , Culicidae , Disease Outbreaks , Mosquito Vectors , Yellow Fever/transmission , Aedes/growth & development , Aedes/virology , Animals , Biodiversity , Brazil/epidemiology , Climate , Culicidae/growth & development , Culicidae/virology , Forests , Humans , Mosquito Vectors/classification , Mosquito Vectors/growth & development , Mosquito Vectors/virology , Risk Factors , Yellow Fever/epidemiology
8.
Sci Total Environ ; 819: 153073, 2022 May 01.
Article in English | MEDLINE | ID: covidwho-1621038

ABSTRACT

Advancing wet peatland 'paludiculture' innovation present enormous potential to sustain carbon-cycles, reduce greenhouse-gas (GHG) gas emissions and to transition communities to low-carbon economies; however, there is limited scientific-evidence to support and enable direct commercial viability of eco-friendly products and services. This timely study reports on a novel, paludiculture-based, integrated-multi-trophic-aquaculture (IMTA) system for sustainable food production in the Irish midlands. This freshwater IMTA process relies on a naturally occurring ecosystem of microalgae, bacteria and duckweed in ponds for managing waste and water quality that is powered by wind turbines; however, as it is recirculating, it does not rely upon end-of-pipe solutions and does not discharge effluent to receiving waters. This constitutes the first report on the effects of extreme weather events on the performance of this IMTA system that produces European perch (Perca fluviatilis), rainbow trout (Oncorhynchus mykiis) during Spring 2020. Sampling coincided with lockdown periods of worker mobility restriction due to COVID-19 pandemic. Observations revealed that the frequency and intensity of storms generated high levels of rainfall that disrupted the algal and bacterial ecosystem in the IMTA leading to the emergence and predominance of toxic cyanobacteria that caused fish mortality. There is a pressing need for international agreement on standardized set of environmental indicators to advance paludiculture innovation that addresses climate-change and sustainability. This study describes important technical parameters for advancing freshwater aquaculture (IMTA), which can be future refined using real-time monitoring-tools at farm level to inform management decision-making based on evaluating environmental indicators and weather data. The relevance of these findings to informing global sustaining and disruptive research and innovation in paludiculture is presented, along with alignment with UN Sustainable Development goals. This study also addresses global challenges and opportunities highlighting a commensurate need for international agreement on resilient indicators encompassing linked ecological, societal, cultural, economic and cultural domains.


Subject(s)
Aquaculture , Climate , Perches , Animals , COVID-19 , Communicable Disease Control , Environment , Humans , Pandemics , Wetlands
9.
BMJ ; 375: n2884, 2021 11 29.
Article in English | MEDLINE | ID: covidwho-1541877
10.
Sci Rep ; 11(1): 21415, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1506470

ABSTRACT

Bread wheat (Triticum aestivum L.) cultivars adapted to specific environments and resistant to prevalent pathogens are preferred for obtaining high yield. This study aimed to identify wheat genotypes with superior grain yield (GY) and yield associated traits from 168 genotypes of International Maize and Wheat Improvement Center's 13th Stem Rust Resistance Screening Nursery evaluated over two seasons during 2019 and 2020 under high disease pressure of both stem rust (SR) and yellow rust (YR) in a 21 × 8 α-lattice design with 3 replications in Kenya. Effects due to seasons were significant for YRAud, SRAud, 1000-kernel weight (TKW), days to heading (DH), plant height (PH) and number of spikelets spike-1 (SS), while genotypes and genotypes × season interaction effects were significant for all traits except number of kernels spike-1. Respectively, heritability values of 0.95, 0.93, 0.87, 0.86, 0.77 and 0.75 were observed for area under disease progress curve for SR (SRAud), YR (YRAud), TKW, DH, biomass (BM) and GY. Path analysis showed positive direct effects on GY via PH, SS, BM, and TKW. Biplot analysis identified 16 genotypes with superior desirable traits GY, BM and harvest index. The SR contributed the highest reduction in GY and TKW while YR contributed the most reduction in BM. These identified genotypes with superior GY combined with adequate resistance to both SR and YR are potentially valuable resources for improvement of locally adapted wheat cultivars.


Subject(s)
Edible Grain/genetics , Plant Diseases/genetics , Triticum/genetics , Alleles , Animals , Aphids , Basidiomycota/genetics , Biomass , Bread , Climate , Genome-Wide Association Study , Genotype , Kenya , Phenotype , Quantitative Trait Loci , Regression Analysis , Seasons , Temperature , Zea mays
11.
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
12.
Med J Aust ; 215(9): 410-411, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1502729
13.
Comput Math Methods Med ; 2021: 7196492, 2021.
Article in English | MEDLINE | ID: covidwho-1476882

ABSTRACT

COVID-19 has swept through the world since December 2019 and caused a large number of patients and deaths. Spatial prediction on the spread of the epidemic is greatly important for disease control and management. In this study, we predicted the cumulative confirmed cases (CCCs) from Jan 17 to Mar 1, 2020, in mainland China at the city level, using machine learning algorithms, geographically weighted regression (GWR), and partial least squares regression (PLSR) based on population flow, geolocation, meteorological, and socioeconomic variables. The validation results showed that machine learning algorithms and GWR achieved good performances. These models could not effectively predict CCCs in Wuhan, the first city that reported COVID-19 cases in China, but performed well in other cities. Random Forest (RF) outperformed other methods with a CV-R 2 of 0.84. In this model, the population flow from Wuhan to other cities (WP) was the most important feature and the other features also made considerable contributions to the prediction accuracy. Compared with RF, GWR showed a slightly worse performance (CV-R 2 = 0.81) but required fewer spatial independent variables. This study explored the spatial prediction of the epidemic based on multisource spatial independent variables, providing references for the estimation of CCCs in the regions lacking accurate and timely.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Computational Biology/methods , Geography , Machine Learning , Algorithms , China/epidemiology , Cities , Climate , Communicable Diseases , Environmental Monitoring , Epidemics , Humans , Least-Squares Analysis , Models, Statistical , Reproducibility of Results , SARS-CoV-2 , Social Class , Spatial Regression
14.
Nature ; 598(7879): 32, 2021 10.
Article in English | MEDLINE | ID: covidwho-1461979

Subject(s)
Climate , Floods , Cities
15.
J Occup Environ Med ; 63(8): e533-e541, 2021 08 01.
Article in English | MEDLINE | ID: covidwho-1402737

ABSTRACT

OBJECTIVE: To investigate the epidemiological characteristics of human infection with corona virus disease 2019 (COVID-19) in Moscow, Lima, Kuwait, and Singapore to analyze the effects of climate factors on the incidence of COVID-19. METHODS: Collect the daily incidence of COVID-19 and related climate data in four areas, construct a negative binomial regression model, and analyze the correlation between the incidence of COVID-19 and meteorological factors. RESULTS: AH was the climate factor affecting the incidence of COVID-19 in Moscow, Lima, and Singapore; Ta and RH were the climate factors affecting the incidence of COVID-19 in Kuwait. CONCLUSIONS: The incidence of COVID-19 in four areas were all associated with the humidity, and climate factors should be taken into consideration when epidemic prevention measures are taken, and environment humidification may be a feasible approach to decrease COVID-19 virus transmission.


Subject(s)
COVID-19 , Climate , Humans , Humidity , Models, Statistical , SARS-CoV-2 , Temperature
16.
Future Microbiol ; 16: 1105-1133, 2021 09.
Article in English | MEDLINE | ID: covidwho-1381356

ABSTRACT

SARS-CoV-2 is the etiological agent of the current pandemic worldwide and its associated disease COVID-19. In this review, we have analyzed SARS-CoV-2 characteristics and those ones of other well-known RNA viruses viz. HIV, HCV and Influenza viruses, collecting their historical data, clinical manifestations and pathogenetic mechanisms. The aim of the work is obtaining useful insights and lessons for a better understanding of SARS-CoV-2. These pathogens present a distinct mode of transmission, as SARS-CoV-2 and Influenza viruses are airborne, whereas HIV and HCV are bloodborne. However, these viruses exhibit some potential similar clinical manifestations and pathogenetic mechanisms and their understanding may contribute to establishing preventive measures and new therapies against SARS-CoV-2.


Subject(s)
COVID-19/history , Pandemics/history , SARS-CoV-2/physiology , SARS-CoV-2/pathogenicity , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/epidemiology , COVID-19/transmission , Climate , Disease Reservoirs/virology , Genome, Viral , History, 19th Century , History, 20th Century , History, 21st Century , Humans , Mutation , RNA Viruses/pathogenicity , RNA Viruses/physiology , Reinfection/epidemiology , Reinfection/history , Reinfection/transmission , Reinfection/virology , Respiratory Tract Infections/drug therapy , Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/history , Respiratory Tract Infections/transmission , Virus Replication
17.
Sci Rep ; 11(1): 16852, 2021 08 19.
Article in English | MEDLINE | ID: covidwho-1366829

ABSTRACT

The COVID-19 pandemic caused disruptions of public life and imposed lockdown measures in 2020 resulted in considerable reductions of anthropogenic aerosol emissions. It still remains unclear how the associated short-term changes in atmospheric chemistry influenced weather and climate on regional scales. To understand the underlying physical mechanisms, we conduct ensemble aerosol perturbation experiments with the Community Earth System Model, version 2. In the simulations reduced anthropogenic aerosol emissions in February generate anomalous surface warming and warm-moist air advection which promotes low-level cloud formation over China. Although the simulated response is weak, it is detectable in some areas, in qualitative agreement with the observations. The negative dynamical cloud feedback offsets the effect from reduced cloud condensation nuclei. Additional perturbation experiments with strongly amplified air pollution over China reveal a nonlinear sensitivity of regional atmospheric conditions to chemical/radiative perturbations. COVID-19-related changes in anthropogenic aerosol emissions provide an excellent testbed to elucidate the interaction between air pollution and climate.


Subject(s)
COVID-19/epidemiology , Climate , SARS-CoV-2/physiology , Aerosols , Air Pollutants , Atmosphere , COVID-19/transmission , China , Communicable Disease Control , Far East , Humans , Pandemics , Weather
18.
Lancet Planet Health ; 5(8): e494, 2021 08.
Article in English | MEDLINE | ID: covidwho-1361573

Subject(s)
Climate Change , Climate
19.
Sci Adv ; 7(24)2021 06.
Article in English | MEDLINE | ID: covidwho-1343932

ABSTRACT

Efforts to stem the transmission of coronavirus disease 2019 (COVID-19) led to rapid, global ancillary reductions in air pollutant emissions. Here, we quantify the impact on tropospheric ozone using a multiconstituent chemical data assimilation system. Anthropogenic NO x emissions dropped by at least 15% globally and 18 to 25% regionally in April and May 2020, which decreased free tropospheric ozone by up to 5 parts per billion, consistent with independent satellite observations. The global total tropospheric ozone burden declined by 6TgO3 (∼2%) in May and June 2020, largely due to emission reductions in Asia and the Americas that were amplified by regionally high ozone production efficiencies (up to 4 TgO3/TgN). Our results show that COVID-19 mitigation left a global atmospheric imprint that altered atmospheric oxidative capacity and climate radiative forcing, providing a test of the efficacy of NO x emissions controls for co-benefiting air quality and climate.


Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , Atmosphere/analysis , COVID-19/epidemiology , Environmental Exposure/analysis , Nitric Oxide/analysis , Ozone/analysis , COVID-19/virology , Climate , Environmental Monitoring , Global Health , Humans , SARS-CoV-2/isolation & purification
20.
Nat Commun ; 12(1): 4675, 2021 08 03.
Article in English | MEDLINE | ID: covidwho-1340998

ABSTRACT

Recent studies conclude that the global coronavirus (COVID-19) pandemic decreased power sector CO2 emissions globally and in the United States. In this paper, we analyze the statistical significance of CO2 emissions reductions in the U.S. power sector from March through December 2020. We use Gaussian process (GP) regression to assess whether CO2 emissions reductions would have occurred with reasonable probability in the absence of COVID-19 considering uncertainty due to factors unrelated to the pandemic and adjusting for weather, seasonality, and recent emissions trends. We find that monthly CO2 emissions reductions are only statistically significant in April and May 2020 considering hypothesis tests at 5% significance levels. Separately, we consider the potential impact of COVID-19 on coal-fired power plant retirements through 2022. We find that only a small percentage of U.S. coal power plants are at risk of retirement due to a possible COVID-19-related sustained reduction in electricity demand and prices. We observe and anticipate a return to pre-COVID-19 CO2 emissions in the U.S. power sector.


Subject(s)
COVID-19/epidemiology , Power Plants/statistics & numerical data , Air Pollutants/analysis , Carbon Dioxide/analysis , Climate , Coal/analysis , Coal/economics , Electricity , Fossil Fuels/analysis , Humans , Power Plants/economics , Power Plants/trends , SARS-CoV-2 , United States/epidemiology
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