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2.
Ann Glob Health ; 86(1): 95, 2020 08 06.
Artículo en Inglés | MEDLINE | ID: covidwho-729723

RESUMEN

Currently, Nigeria is still at the ascending phase of the COVID-19 curve with no sign of deceleration. Thus, the recent decision by governors of states in northern Nigeria to deport Almajirai (itinerant Islamic school pupils) from their states as part of efforts to contain COVID-19 transmission is likely to have a serious backlash. With hundreds of Almajirai testing positive to COVID-19, and millions of others untested, they constitute ubiquitous nodes of transmission. Their deportation has created multiple emigration channels that constitute prospective feeders to covert community transmission. This viewpoint examines this trend within the context of Nigeria's current [in]capacity to manage the spread of COVID-19 and concludes that greater risks seem to lie ahead unless the government takes stringent containment measures.


Asunto(s)
Control de Enfermedades Transmisibles , Infecciones por Coronavirus , Transmisión de Enfermedad Infecciosa , Evaluación de Necesidades , Pandemias , Neumonía Viral , Salud Pública , Betacoronavirus/aislamiento & purificación , Técnicas de Laboratorio Clínico/métodos , Técnicas de Laboratorio Clínico/estadística & datos numéricos , Control de Enfermedades Transmisibles/organización & administración , Control de Enfermedades Transmisibles/normas , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/transmisión , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Regulación Gubernamental , Humanos , Islamismo , Nigeria/epidemiología , Pandemias/prevención & control , Neumonía Viral/diagnóstico , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Neumonía Viral/transmisión , Política , Pobreza , Salud Pública/métodos , Salud Pública/normas
4.
PLoS One ; 15(8): e0237901, 2020.
Artículo en Inglés | MEDLINE | ID: covidwho-723873

RESUMEN

Among the different indicators that quantify the spread of an epidemic such as the on-going COVID-19, stands first the reproduction number which measures how many people can be contaminated by an infected person. In order to permit the monitoring of the evolution of this number, a new estimation procedure is proposed here, assuming a well-accepted model for current incidence data, based on past observations. The novelty of the proposed approach is twofold: 1) the estimation of the reproduction number is achieved by convex optimization within a proximal-based inverse problem formulation, with constraints aimed at promoting piecewise smoothness; 2) the approach is developed in a multivariate setting, allowing for the simultaneous handling of multiple time series attached to different geographical regions, together with a spatial (graph-based) regularization of their evolutions in time. The effectiveness of the approach is first supported by simulations, and two main applications to real COVID-19 data are then discussed. The first one refers to the comparative evolution of the reproduction number for a number of countries, while the second one focuses on French departments and their joint analysis, leading to dynamic maps revealing the temporal co-evolution of their reproduction numbers.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/transmisión , Modelos Estadísticos , Neumonía Viral/epidemiología , Neumonía Viral/transmisión , Análisis Espacio-Temporal , Algoritmos , Infecciones por Coronavirus/virología , Bases de Datos Factuales , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Francia/epidemiología , Humanos , Pandemias , Neumonía Viral/virología , Distribución de Poisson , Programas Informáticos
5.
PLoS Med ; 17(8): e1003244, 2020 08.
Artículo en Inglés | MEDLINE | ID: covidwho-710389

RESUMEN

BACKGROUND: Social distancing measures to address the US coronavirus disease 2019 (COVID-19) epidemic may have notable health and social impacts. METHODS AND FINDINGS: We conducted a longitudinal pretest-posttest comparison group study to estimate the change in COVID-19 case growth before versus after implementation of statewide social distancing measures in the US. The primary exposure was time before (14 days prior to, and through 3 days after) versus after (beginning 4 days after, to up to 21 days after) implementation of the first statewide social distancing measures. Statewide restrictions on internal movement were examined as a secondary exposure. The primary outcome was the COVID-19 case growth rate. The secondary outcome was the COVID-19-attributed mortality growth rate. All states initiated social distancing measures between March 10 and March 25, 2020. The mean daily COVID-19 case growth rate decreased beginning 4 days after implementation of the first statewide social distancing measures, by 0.9% per day (95% CI -1.4% to -0.4%; P < 0.001). We did not observe a statistically significant difference in the mean daily case growth rate before versus after implementation of statewide restrictions on internal movement (0.1% per day; 95% CI -0.04% to 0.3%; P = 0.14), but there is substantial difficulty in disentangling the unique associations with statewide restrictions on internal movement from the unique associations with the first social distancing measures. Beginning 7 days after social distancing, the COVID-19-attributed mortality growth rate decreased by 2.0% per day (95% CI -3.0% to -0.9%; P < 0.001). Our analysis is susceptible to potential bias resulting from the aggregate nature of the ecological data, potential confounding by contemporaneous changes (e.g., increases in testing), and potential underestimation of social distancing due to spillover effects from neighboring states. CONCLUSIONS: Statewide social distancing measures were associated with a decrease in the COVID-19 case growth rate that was statistically significant. Statewide social distancing measures were also associated with a decrease in the COVID-19-attributed mortality growth rate beginning 7 days after implementation, although this decrease was no longer statistically significant by 10 days.


Asunto(s)
Betacoronavirus/aislamiento & purificación , Control de Enfermedades Transmisibles , Infecciones por Coronavirus , Transmisión de Enfermedad Infecciosa , Pandemias , Neumonía Viral , Aislamiento Social , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/organización & administración , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/transmisión , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Estudios Longitudinales , Mortalidad , Pandemias/prevención & control , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Neumonía Viral/transmisión , Factores de Tiempo , Estados Unidos/epidemiología
7.
Nat Hum Behav ; 4(8): 856-865, 2020 08.
Artículo en Inglés | MEDLINE | ID: covidwho-690410

RESUMEN

The first case of COVID-19 was detected in Brazil on 25 February 2020. We report and contextualize epidemiological, demographic and clinical findings for COVID-19 cases during the first 3 months of the epidemic. By 31 May 2020, 514,200 COVID-19 cases, including 29,314 deaths, had been reported in 75.3% (4,196 of 5,570) of municipalities across all five administrative regions of Brazil. The R0 value for Brazil was estimated at 3.1 (95% Bayesian credible interval = 2.4-5.5), with a higher median but overlapping credible intervals compared with some other seriously affected countries. A positive association between higher per-capita income and COVID-19 diagnosis was identified. Furthermore, the severe acute respiratory infection cases with unknown aetiology were associated with lower per-capita income. Co-circulation of six respiratory viruses was detected but at very low levels. These findings provide a comprehensive description of the ongoing COVID-19 epidemic in Brazil and may help to guide subsequent measures to control virus transmission.


Asunto(s)
Betacoronavirus/aislamiento & purificación , Infecciones por Coronavirus , Transmisión de Enfermedad Infecciosa , Gripe Humana , Pandemias , Neumonía Viral , Adulto , Anciano , Brasil/epidemiología , Niño , Técnicas de Laboratorio Clínico/métodos , Técnicas de Laboratorio Clínico/estadística & datos numéricos , Coinfección/epidemiología , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/tratamiento farmacológico , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/terapia , Infecciones por Coronavirus/transmisión , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Femenino , Hospitalización/estadística & datos numéricos , Humanos , Lactante , Gripe Humana/diagnóstico , Gripe Humana/epidemiología , Gripe Humana/virología , Masculino , Mortalidad , Neumonía Viral/diagnóstico , Neumonía Viral/mortalidad , Neumonía Viral/terapia , Neumonía Viral/transmisión , Factores Socioeconómicos
8.
Infect Dis Poverty ; 9(1): 83, 2020 Jul 06.
Artículo en Inglés | MEDLINE | ID: covidwho-657687

RESUMEN

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak has seriously endangered the health and lives of Chinese people. In this study, we predicted the COVID-19 epidemic trend and estimated the efficacy of several intervention strategies in the mainland of China. METHODS: According to the COVID-19 epidemic status, we constructed a compartmental model. Based on reported data from the National Health Commission of People's Republic of China during January 10-February 17, 2020, we estimated the model parameters. We then predicted the epidemic trend and transmission risk of COVID-19. Using a sensitivity analysis method, we estimated the efficacy of several intervention strategies. RESULTS: The cumulative number of confirmed cases in the mainland of China will be 86 763 (95% CI: 86 067-87 460) on May 2, 2020. Up until March 15, 2020, the case fatality rate increased to 6.42% (95% CI: 6.16-6.68%). On February 23, 2020, the existing confirmed cases reached its peak, with 60 890 cases (95% CI: 60 350-61 431). On January 23, 2020, the effective reproduction number was 2.620 (95% CI: 2.567-2.676) and had dropped below 1.0 since February 5, 2020. Due to governmental intervention, the total number of confirmed cases was reduced by 99.85% on May 2, 2020. Had the isolation been relaxed from February 24, 2020, there might have been a second peak of infection. However, relaxing the isolation after March 16, 2020 greatly reduced the number of existing confirmed cases and deaths. The total number of confirmed cases and deaths would increase by 8.72 and 9.44%, respectively, due to a 1-day delayed diagnosis in non-isolated infected patients. Moreover, if the coverage of close contact tracing was increased to 100%, the cumulative number of confirmed cases would be decreased by 88.26% on May 2, 2020. CONCLUSIONS: The quarantine measures adopted by the Chinese government since January 23, 2020 were necessary and effective. Postponing the relaxation of isolation, early diagnosis, patient isolation, broad close-contact tracing, and strict monitoring of infected persons could effectively control the COVID-19 epidemic. April 1, 2020 would be a reasonable date to lift quarantine in Hubei and Wuhan.


Asunto(s)
Control de Enfermedades Transmisibles/métodos , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/transmisión , Pandemias/prevención & control , Neumonía Viral/prevención & control , Neumonía Viral/transmisión , Betacoronavirus , China/epidemiología , Control de Enfermedades Transmisibles/legislación & jurisprudencia , Infecciones por Coronavirus/epidemiología , Transmisión de Enfermedad Infecciosa/legislación & jurisprudencia , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Predicción , Humanos , Modelos Estadísticos , Programas Nacionales de Salud/estadística & datos numéricos , Neumonía Viral/epidemiología
9.
Swiss Med Wkly ; 150: w20313, 2020 07 13.
Artículo en Inglés | MEDLINE | ID: covidwho-651678

RESUMEN

The reproduction number is broadly considered as a key indicator for the spreading of the COVID-19 pandemic. Its estimated value is a measure of the necessity and, eventually, effectiveness of interventions imposed in various countries. Here we present an online tool for the data-driven inference and quantification of uncertainties for the reproduction number, as well as the time points of interventions for 51 European countries. The study relied on the Bayesian calibration of the SIR model with data from reported daily infections from these countries. The model fitted the data, for most countries, without individual tuning of parameters. We also compared the results of SIR and SEIR models, which give different estimates of the reproduction number, and provided an analytical relationship between the respective numbers. We deployed a Bayesian inference framework with efficient sampling algorithms, to present a publicly available graphical user interface (https://cse-lab.ethz.ch/coronavirus) that allows the user to assess and compare predictions for pairs of European countries. The results quantified the rate of the disease’s spread before and after interventions, and provided a metric for the effectiveness of non-pharmaceutical interventions in different countries. They also indicated how geographic proximity and the times of interventions affected the progression of the epidemic.


Asunto(s)
Número Básico de Reproducción/estadística & datos numéricos , Infecciones por Coronavirus , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Monitoreo Epidemiológico , Pandemias , Neumonía Viral , Teorema de Bayes , Betacoronavirus/aislamiento & purificación , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/transmisión , Transmisión de Enfermedad Infecciosa/prevención & control , Mediciones Epidemiológicas , Europa (Continente)/epidemiología , Humanos , Pandemias/prevención & control , Pandemias/estadística & datos numéricos , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Neumonía Viral/transmisión , Incertidumbre
11.
J Public Health (Oxf) ; 42(3): 656-658, 2020 Aug 18.
Artículo en Inglés | MEDLINE | ID: covidwho-639185

RESUMEN

An ongoing outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread in the world, whereas asymptomatic carriers may also play a critical role in the pandemic. We report a familial cluster of COVID-19 caused by one family member before his onset of illness, indicating that it seems to be potentially infectious during the incubation period, even earlier than we expected. Close contact, especially in a small enclosed space, might be the cause of familial transmission. The unsynchronized changes in the clinical symptoms and COVID-19 nucleic acid were found in this case, so consecutive nucleic acid detection of pretty suspected cases was recommended. Family members, especially of whom the confirmed cases contacted with since one incubation period before onset rather than 2 days before onset, should be regarded as close contact and centrally isolated in case of asymptomatic infection already existed in the family.


Asunto(s)
Infecciones Asintomáticas/epidemiología , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/transmisión , Brotes de Enfermedades/estadística & datos numéricos , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Familia/psicología , Pandemias/estadística & datos numéricos , Neumonía Viral/epidemiología , Neumonía Viral/transmisión , Betacoronavirus , China/epidemiología , Análisis por Conglomerados , Humanos
13.
Infect Dis Poverty ; 9(1): 87, 2020 Jul 10.
Artículo en Inglés | MEDLINE | ID: covidwho-640469

RESUMEN

BACKGROUND: The new coronavirus disease COVID-19 began in December 2019 and has spread rapidly by human-to-human transmission. This study evaluated the transmissibility of the infectious disease and analyzed its association with temperature and humidity to study the propagation pattern of COVID-19. METHODS: In this study, we revised the reported data in Wuhan based on several assumptions to estimate the actual number of confirmed cases considering that perhaps not all cases could be detected and reported in the complex situation there. Then we used the equation derived from the Susceptible-Exposed-Infectious-Recovered (SEIR) model to calculate R0 from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R0 and temperature and humidity for four major cities in China to see the association between the transmissibility of COVID-19 and the weather variables. RESULTS: It was estimated that the cumulative number of confirmed cases had exceeded 45 000 by February 13, 2020 in Wuhan. The average R0 in Wuhan was 2.7, significantly higher than those in other cities ranging from 1.8 to 2.4. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R0 in Wuhan. R0 negatively correlated with both temperature and humidity, which was significant at the 0.01 level. CONCLUSIONS: The transmissibility of COVID-19 was strong and importance should be attached to the intervention of its transmission especially in Wuhan. According to the correlation between R0 and weather, the spread of disease will be suppressed as the weather warms.


Asunto(s)
Número Básico de Reproducción , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/transmisión , Neumonía Viral/epidemiología , Neumonía Viral/transmisión , Betacoronavirus/patogenicidad , China/epidemiología , Ciudades , Infecciones por Coronavirus/prevención & control , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Humedad , Pandemias/prevención & control , Neumonía Viral/prevención & control , Análisis de Regresión , Temperatura
15.
J Infect ; 81(3): 427-434, 2020 Sep.
Artículo en Inglés | MEDLINE | ID: covidwho-628179

RESUMEN

BACKGROUND: Significant nosocomial transmission of SARS-CoV-2 has been demonstrated. Understanding the prevalence of SARS-CoV-2 carriage amongst HCWs at work is necessary to inform the development of HCW screening programmes to control nosocomial spread. METHODS: Cross-sectional 'snapshot' survey from April-May 2020; HCWs recruited from six UK hospitals. Participants self-completed a health questionnaire and underwent a combined viral nose and throat swab, tested by Polymerase Chain Reaction (PCR) for SARS-CoV-2 with viral culture on majority of positive samples. FINDINGS: Point prevalence of SARS-CoV-2 carriage across the sites was 2.0% (23/1152 participants), median cycle threshold value 35.70 (IQR:32.42-37.57). 17 were previously symptomatic, two currently symptomatic (isolated anosmia and sore throat); the remainder declared no prior or current symptoms. Symptoms in the past month were associated with threefold increased odds of testing positive (aOR 3.46, 95%CI 1.38-8.67; p = 0.008). SARS-CoV-2 virus was isolated from only one (5%) of nineteen cultured samples. A large proportion (39%) of participants reported symptoms in the past month. INTERPRETATION: The point-prevalence is similar to previous estimates for HCWs in April 2020, though a magnitude higher than in the general population. Based upon interpretation of symptom history and testing results including viral culture, the majority of those testing positive were unlikely to be infectious at time of sampling. Development of screening programmes must balance the potential to identify additional cases based upon likely prevalence, expanding the symptoms list to encourage HCW testing, with resource implications and risks of excluding those unlikely to be infectious with positive tests. FUNDING: Public Health England.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Personal de Salud/estadística & datos numéricos , Neumonía Viral/epidemiología , Adulto , Anciano , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/transmisión , Estudios Transversales , Inglaterra , Femenino , Humanos , Masculino , Cuerpo Médico de Hospitales/estadística & datos numéricos , Persona de Mediana Edad , Pandemias , Neumonía Viral/diagnóstico , Neumonía Viral/transmisión , Estudios Prospectivos , ARN Viral , Reacción en Cadena en Tiempo Real de la Polimerasa , Encuestas y Cuestionarios , Adulto Joven
17.
Am J Infect Control ; 48(9): 1068-1073, 2020 09.
Artículo en Inglés | MEDLINE | ID: covidwho-597575

RESUMEN

BACKGROUND: Coronavirus disease 2019 (COVID-19) is already a pandemic. Few studies investigated the epidemic characteristics of the COVID-19 outbreak in the well-developed cities. METHODS: Epidemiological data of 136 confirmed COVID-19 cases were collected from the dataset of COVID-19 in Tianjin. All confirmed cases were categorized according to their potential infection sources. Daily numbers of confirmed cases of each category were plotted by date of onset, and the epidemic form of each category was inferred. RESULTS: Among the 136 confirmed COVID-19 cases, 48 cases were categorized as imported cases and their close contacts, which were the majority of early cases. A total of 43 cases were found an epidemiological link to the Baodi department store, and they were inferred to be a common-source outbreak. Additionally, 35 cases were considered as familial clusters of COVID-19 cases, and 10 cases were sporadic. The 45 cases were inferred to be a propagated epidemic. CONCLUSIONS: Local transmission of COVID-19 mainly occurred within families and a poorly ventilated public place in Tianjin. Besides the imported cases, the pattern of local transmission of COVID-19 was a mixture of the propagated epidemic and the common-source outbreak in Tianjin.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Brotes de Enfermedades , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Neumonía Viral/epidemiología , Adulto , China/epidemiología , Ciudades/epidemiología , Infecciones por Coronavirus/transmisión , Femenino , Humanos , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/transmisión
18.
Proc Natl Acad Sci U S A ; 117(26): 14857-14863, 2020 06 30.
Artículo en Inglés | MEDLINE | ID: covidwho-595563

RESUMEN

Various mitigation measures have been implemented to fight the coronavirus disease 2019 (COVID-19) pandemic, including widely adopted social distancing and mandated face covering. However, assessing the effectiveness of those intervention practices hinges on the understanding of virus transmission, which remains uncertain. Here we show that airborne transmission is highly virulent and represents the dominant route to spread the disease. By analyzing the trend and mitigation measures in Wuhan, China, Italy, and New York City, from January 23 to May 9, 2020, we illustrate that the impacts of mitigation measures are discernable from the trends of the pandemic. Our analysis reveals that the difference with and without mandated face covering represents the determinant in shaping the pandemic trends in the three epicenters. This protective measure alone significantly reduced the number of infections, that is, by over 78,000 in Italy from April 6 to May 9 and over 66,000 in New York City from April 17 to May 9. Other mitigation measures, such as social distancing implemented in the United States, are insufficient by themselves in protecting the public. We conclude that wearing of face masks in public corresponds to the most effective means to prevent interhuman transmission, and this inexpensive practice, in conjunction with simultaneous social distancing, quarantine, and contact tracing, represents the most likely fighting opportunity to stop the COVID-19 pandemic. Our work also highlights the fact that sound science is essential in decision-making for the current and future public health pandemics.


Asunto(s)
Infecciones por Coronavirus/transmisión , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Exposición por Inhalación/estadística & datos numéricos , Neumonía Viral/transmisión , Infecciones por Coronavirus/epidemiología , Transmisión de Enfermedad Infecciosa/clasificación , Transmisión de Enfermedad Infecciosa/prevención & control , Humanos , Exposición por Inhalación/prevención & control , Máscaras/estadística & datos numéricos , Pandemias , Neumonía Viral/epidemiología , Prevención Primaria/métodos , Prevención Primaria/estadística & datos numéricos , Cuarentena/métodos , Cuarentena/estadística & datos numéricos , Dispositivos de Protección Respiratoria/estadística & datos numéricos , Estados Unidos
20.
Proc Natl Acad Sci U S A ; 117(26): 14642-14644, 2020 06 30.
Artículo en Inglés | MEDLINE | ID: covidwho-595209

RESUMEN

To prevent the spread of coronavirus disease 2019 (COVID-19), some types of public spaces have been shut down while others remain open. These decisions constitute a judgment about the relative danger and benefits of those locations. Using mobility data from a large sample of smartphones, nationally representative consumer preference surveys, and economic statistics, we measure the relative transmission reduction benefit and social cost of closing 26 categories of US locations. Our categories include types of shops, entertainments, and service providers. We rank categories by their trade-off of social benefits and transmission risk via dominance across 13 dimensions of risk and importance and through composite indexes. We find that, from February to March 2020, there were larger declines in visits to locations that our measures indicate should be closed first.


Asunto(s)
Conducta , Infecciones por Coronavirus/prevención & control , Transmisión de Enfermedad Infecciosa/prevención & control , Exposición por Inhalación/prevención & control , Modelos Estadísticos , Pandemias/prevención & control , Neumonía Viral/prevención & control , Prevención Primaria/estadística & datos numéricos , Cuarentena/estadística & datos numéricos , Espacios Confinados , Trazado de Contacto/métodos , Trazado de Contacto/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/transmisión , Costos y Análisis de Costo , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Exposición por Inhalación/estadística & datos numéricos , Museos , Neumonía Viral/epidemiología , Neumonía Viral/transmisión , Prevención Primaria/economía , Prevención Primaria/métodos , Cuarentena/economía , Cuarentena/métodos , Medición de Riesgo , Instituciones Académicas , Teléfono Inteligente/estadística & datos numéricos , Instalaciones Deportivas y Recreativas , Estados Unidos
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