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Am J Epidemiol ; 190(6): 1081-1087, 2021 06 01.
Article in English | MEDLINE | ID: covidwho-2275701


It is of critical importance to estimate changing disease-transmission rates and their dependence on population mobility. A common approach to this problem involves fitting daily transmission rates using a susceptible-exposed-infected-recovered-(SEIR) model (regularizing to avoid overfitting) and then computing the relationship between the estimated transmission rate and mobility. Unfortunately, there are often several very different transmission-rate trajectories that can fit the reported cases well, meaning that the choice of regularization determines the final solution (and thus the mobility-transmission rate relationship) selected by the SEIR model. Moreover, the classical approaches to regularization-penalizing the derivative of the transmission rate trajectory-do not correspond to realistic properties of pandemic spread. Consequently, models fitted using derivative-based regularization are often biased toward underestimating the current transmission rate and future deaths. In this work, we propose mobility-driven regularization of the SEIR transmission rate trajectory. This method rectifies the artificial regularization problem, produces more accurate and unbiased forecasts of future deaths, and estimates a highly interpretable relationship between mobility and the transmission rate. For this analysis, mobility data related to the coronavirus disease 2019 pandemic was collected by Safegraph (San Francisco, California) from major US cities between March and August 2020.

COVID-19/transmission , Disease Susceptibility/epidemiology , Disease Transmission, Infectious/statistics & numerical data , Models, Statistical , Population Dynamics/statistics & numerical data , Forecasting , Humans , SARS-CoV-2 , United States
ACS Appl Bio Mater ; 4(5): 3891-3908, 2021 05 17.
Article in English | MEDLINE | ID: covidwho-2265619


The outbreak of coronavirus disease (COVID-19) has transformed the daily lifestyles of people worldwide. COVID-19 was characterized as a pandemic owing to its global spread, and technologies based on engineered materials that help to reduce the spread of infections have been reported. Nanotechnology present in materials with enhanced physicochemical properties and versatile chemical functionalization offer numerous ways to combat the disease. Facemasks are a reliable preventive measure, although they are not 100% effective against viral infections. Nonwoven materials, which are the key components of masks, act as barriers to the virus through filtration. However, there is a high chance of cross-infection because the used mask lacks virucidal properties and can become an additional source of infection. The combination of antiviral and filtration properties enhances the durability and reliability of masks, thereby reducing the likelihood of cross-infection. In this review, we focus on masks, from the manufacturing stage to practical applications, and their abilities to combat COVID-19. Herein, we discuss the impacts of masks on the environment, while considering safe industrial production in the future. Furthermore, we discuss available options for future research directions that do not negatively impact the environment.

Masks/trends , Nanotechnology/trends , Pandemics/prevention & control , COVID-19/prevention & control , COVID-19/transmission , Decontamination , Disease Transmission, Infectious , Equipment Design , Filtration , Humans , Respiratory Aerosols and Droplets , SARS-CoV-2 , Textiles
Swiss Med Wkly ; 150: w20295, 2020 05 18.
Article in English | MEDLINE | ID: covidwho-2268435


Following the rapid dissemination of COVID-19 cases in Switzerland, large-scale non-pharmaceutical interventions (NPIs) were implemented by the cantons and the federal government between 28 February and 20 March 2020. Estimates of the impact of these interventions on SARS-CoV-2 transmission are critical for decision making in this and future outbreaks. We here aim to assess the impact of these NPIs on disease transmission by estimating changes in the basic reproduction number (R0) at national and cantonal levels in relation to the timing of these NPIs. We estimated the time-varying R0 nationally and in eleven cantons by fitting a stochastic transmission model explicitly simulating within-hospital dynamics. We used individual-level data from more than 1000 hospitalised patients in Switzerland and public daily reports of hospitalisations and deaths. We estimated the national R0 to be 2.8 (95% confidence interval 2.1–3.8) at the beginning of the epidemic. Starting from around 7 March, we found a strong reduction in time-varying R0 with a 86% median decrease (95% quantile range [QR] 79–90%) to a value of 0.40 (95% QR 0.3–0.58) in the period of 29 March to 5 April. At the cantonal level, R0 decreased over the course of the epidemic between 53% and 92%. Reductions in time-varying R0 were synchronous with changes in mobility patterns as estimated through smartphone activity, which started before the official implementation of NPIs. We inferred that most of the reduction of transmission is attributable to behavioural changes as opposed to natural immunity, the latter accounting for only about 4% of the total reduction in effective transmission. As Switzerland considers relaxing some of the restrictions of social mixing, current estimates of time-varying R0 well below one are promising. However, as of 24 April 2020, at least 96% (95% QR 95.7–96.4%) of the Swiss population remains susceptible to SARS-CoV-2. These results warrant a cautious relaxation of social distance practices and close monitoring of changes in both the basic and effective reproduction numbers.

Betacoronavirus/isolation & purification , Communicable Disease Control , Coronavirus Infections , Disease Transmission, Infectious , Pandemics/statistics & numerical data , Pneumonia, Viral , COVID-19 , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Disease Control/statistics & numerical data , Communicable Diseases, Emerging/prevention & control , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Disease Transmission, Infectious/prevention & control , Disease Transmission, Infectious/statistics & numerical data , Hospitalization/statistics & numerical data , Humans , Models, Statistical , Mortality , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , SARS-CoV-2 , Space-Time Clustering , Stochastic Processes
Pensar Prát. (Online) ; 25Fev. 2022. Ilus
Article in Portuguese | WHO COVID, LILACS (Americas) | ID: covidwho-2263919


Este estudo articulou relações entre o perfil de ciclistas de lazer e mudanças em seus hábitos de pedalar em função da pandemia provocada pelo SARS-CoV-2 (COVID 19). Os dados foram obtidos por formulário eletrônico e tratados em plataforma específica. O total de ciclistas respondentes foi de 87. Em perfil, obteve-se: idade, renda, nível de escolaridade e fontes de informação/notícias. Sobre como pedalam em função da pandemia, tivemos: pedala só ou em grupo e com ou sem máscara. Os resultados mostram que os ciclistas têm, predominantemente, idade acima de 30 anos, escolaridade universitária e renda acima de R$2.500. As mídias virtuais são a principal fonte de informação. A ação mais destacada para prevenir o contágio foi o uso de máscara; todavia, não houve relações significativas entre o perfil e novas formas de pedalar (AU).

This study articulated relationships between the profile of leisure cyclists and changes because of the pandemic caused by SARS-CoV-2 (COVID 19). Data were obtained by electronic form and processed in a specific platform. 87 was the total number of cyclists responding. In profile, obtained: age, monthly income, education level and sources of information/news; on the behavior in the practice of cycling we had pedal alone or in groups and with or without mask. The results show that cyclists are predominantly aged over 30 years old, have a university education and an income above R$2,500. Virtual media are the main source of information. The most prominent behavioral change was the use of a mask; however, there were no significant relationships between the profile and behavioral changes (AU).

Esta investigación articuló relaciones entre el perfil de ciclistas de ocio y cambios en la acción de pedalear en función de la pandemia por el SARS-CoV-2 (COVID 19). Los datos se obtuvieron por cuestionario electrónico, con 87 sujetos y tratados en plataforma específica. Los datos fueron: edad, niveles de renda y escolaridad y donde uno se informa; y sobre cambios se preguntó se pedalea solo o en grupo y si utiliza o no la máscara. Los resultados apuntan que la mayoría de los ciclistas tienen más de 30 años, nivel universitario y renda por arriba de R$2.500 e se informan por las medias virtuales. El principal cambio ha sido el uso de mascara. No se ha encontrado relaciones significativas entre el perfil y los cambios (AU).

Humans , Bicycling , Disease Transmission, Infectious , COVID-19 , Habits , Leisure Activities
Rev. bras. promoç. saúde (Impr.) ; 34: 1-9, 17/02/2021.
Article in Spanish | WHO COVID, LILACS (Americas) | ID: covidwho-2202501


Objetivo: Este artículo de investigación busca conocer la influencia de la propagación del virus COVID-19 a través de la temperatura y de la humedad en España y Brasil. Métodos: Para el cálculo de la variación mensual del índice de propagación del virus COVID-19 por provincias en España se han utilizado, en primer lugar, las series climáticas de la AEMET de España e INMETRO de Brasil. Se han extraído las medias correspondientes y después se han sometido los datos a un proceso de homogenización, para posteriormente poder calcular el incremento mensual de temperatura y de humedad por provincias y estados. Este proceso metodológico establece una relación directamente proporcional entre el aumento de la temperatura y de la humedad con el índice de propagación del virus COVID-19. Resultados: En España, las condiciones climáticas favorecerán la disminución o aumento del índice reproductivo del virus. En Brasil las condiciones climáticas no favorecerán la disminución del índice reproductivo del virus y, climatológicamente, no existe un periodo óptimo para una desescalada y vuelta a la normalidad. Las variaciones de las condiciones climáticas en Brasil no son significativas, por lo que el clima de Brasil no influye en la disminución de propagación del virus. Conclusión: El clima influye en la propagación del virus. Descriptores: COVID-19; Transmisión de Enfermedad Infecciosa; Clima; Temperatura; Humedad.

Objetivo: Este artigo de pesquisa busca conhecer a influência da propagação do vírus COVID-19 através da temperatura e umidade na Espanha e no Brasil. Métodos: Para calcular a variação mensal do índice de propagação do vírus COVID-19 por províncias da Espanha, primeiramente, utilzaram-se as séries climáticas da AEMET da Espanha e do INMETRO do Brasil. Extraíram-se as médias correspondentes, para posterior submissão dos dados a um processo de homogeneização, com o intuito de calcular o aumento mensal de temperatura e umidade por províncias e estados. Esse processo metodológico estabeleceu uma relação diretamente proporcional entre o aumento da temperatura e da umidade com a taxa de disseminação do vírus COVID-19. Resultados: Na Espanha, as condições climáticas favoreceram a diminuição ou aumento do índice reprodutivo do vírus. No Brasil, entretanto, as condições climáticas não favorecem a diminuição do índice reprodutivo do virus, comprovando que climatologicamente não existe um período ideal para uma desaceleração e retorno à normalidade. As variações nas condições climáticas no Brasil não são significativas, portanto o clima não influencia na diminuição da propagação do vírus neste país. Conclusão: O clima influencia a disseminação do vírus. Descritores: COVID-19; Transmissão de Doença Infecciosa; Clima; Temperatura; Umidade.

Objective: This research article seeks to know the influence of the spread of the COVID-19 virus through temperature and humidity in Spain and Brazil. Methods: In order to calculate the monthly variation in the COVID-19 virus spread index by provinces in Spain, at first, the climatic series of the AEMET of Spain and INMETRO of Brazil were used. The corresponding means have been extracted and then the data have been subjected to a homogenization process, to later be able to calculate the monthly increase in temperature and humidity by provinces and states. This methodological process establishes a directly proportional the climatic conditions favored the decrease or increase of the reproductive index of the virus. In Brazil, however, the climatic conditions do not favor the decrease in the reproductive index of the virus, proving that climatologically there is no optimal period for de-escalation and return to normality. The variations in climatic conditions in Brazil are not significant, so the climate does not influence the decrease in the spread of the virus. Conclusion: Climate influences the spread of the virus. Descriptors: COVID-19; Disease Transmission, Infectious; Climate; Temperature; Humidity. relationship between the increase in temperature and humidity with the spread rate of the COVID-19 virus. Results: In Spain the climatic conditions favored the decrease or increase of the reproductive index of the virus. In Brazil, however, the climatic conditions do not favor the decrease in the reproductive index of the virus, proving that climatologically there is no optimal period for de-escalation and return to normality. The variations in climatic conditions in Brazil are not significant, so the climate does not influence the decrease in the spread of the virus. Conclusion: Climate influences the spread of the virus.

Temperature , Disease Transmission, Infectious , Basic Reproduction Number , COVID-19 , Humidity
Funct Integr Genomics ; 23(1): 36, 2023 Jan 12.
Article in English | MEDLINE | ID: covidwho-2174405


In comparison to previously known severe respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, the newly emerged Omicron (B.1.1.529) variant shows higher infectivity in humans. Exceptionally high infectivity of this variant raises concern of its possible transmission via other intermediate hosts. The SARS-CoV-2 infectivity is established via the association of spike (S) protein receptor binding domain (RBD) with host angiotensin I converting enzyme 2 (hACE2) receptor. In the course of this study, we investigated the interaction between Omicron S protein RBD with the ACE2 receptor of 143 mammalian hosts including human by protein-protein interaction analysis. The goal of this study was to forecast the likelihood that the virus may infect other mammalian species that coexist with or are close to humans in the household, rural, agricultural, or zoological environments. The Omicron RBD was found to interact with higher binding affinity with the ACE2 receptor of 122 mammalian hosts via different amino acid residues from the human ACE2 (hACE2). The rat (Rattus rattus) ACE2 was found to show the strongest interaction with Omicron RBD with a binding affinity of -1393.6 kcal/mol. These distinct strong binding affinity of RBD of Omicron with host ACE2 indicates a greater potential of new host transmissibility and infection via intermediate hosts. Though expected but the phylogenetic position of the mammalian species may not dictate the Omicron RBD binding to the host ACE2 receptor suggesting an involvement of multiple factors in guiding host divergence of the variant.

Angiotensin-Converting Enzyme 2 , COVID-19 , Disease Transmission, Infectious , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Animals , Humans , Rats , Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/metabolism , COVID-19/virology , Mammals , Mutation , Phylogeny , Protein Binding , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/metabolism
Environ Sci Technol ; 57(1): 486-497, 2023 01 10.
Article in English | MEDLINE | ID: covidwho-2185452


Respiratory viruses, including influenza virus and SARS-CoV-2, are transmitted by the airborne route. Air filtration and ventilation mechanically reduce the concentration of airborne viruses and are necessary tools for disease mitigation. However, they ignore the potential impact of the chemical environment surrounding aerosolized viruses, which determines the aerosol pH. Atmospheric aerosol gravitates toward acidic pH, and enveloped viruses are prone to inactivation at strong acidity levels. Yet, the acidity of expiratory aerosol particles and its effect on airborne virus persistence have not been examined. Here, we combine pH-dependent inactivation rates of influenza A virus (IAV) and SARS-CoV-2 with microphysical properties of respiratory fluids using a biophysical aerosol model. We find that particles exhaled into indoor air (with relative humidity ≥ 50%) become mildly acidic (pH ∼ 4), rapidly inactivating IAV within minutes, whereas SARS-CoV-2 requires days. If indoor air is enriched with nonhazardous levels of nitric acid, aerosol pH drops by up to 2 units, decreasing 99%-inactivation times for both viruses in small aerosol particles to below 30 s. Conversely, unintentional removal of volatile acids from indoor air may elevate pH and prolong airborne virus persistence. The overlooked role of aerosol acidity has profound implications for virus transmission and mitigation strategies.

Air Pollution, Indoor , COVID-19 , Respiratory Aerosols and Droplets , Humans , Hydrogen-Ion Concentration , SARS-CoV-2 , Virus Inactivation , Disease Transmission, Infectious