# bib

id: cord-340369-y8o5j2be
author: Zhang, Juanjuan
date: 2020-03-20
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url: https://doi.org/10.1101/2020.03.19.20039107
doi: 10.1101/2020.03.19.20039107
summary:
  To estimate changes in age-mixing patterns associated with COVID-19 interventions, we performed contact surveys in two cities, Wuhan, the epicenter of the outbreak, and Shanghai, one of the largest and most densely populated cities in southeast China. Based on the estimated age-specific mixing patterns and susceptibility to COVID-19 infection, we developed a SIR model of SARS-CoV-2 transmission and tested the impact of social distancing measures on disease dynamics. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted March 20, 2020. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted March 20, 2020.

title:
  Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China

abstract:
  Strict interventions were successful to control the novel coronavirus (COVID-19) outbreak in China. As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection and disease, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. Children 0-14 years were 59% (95% CI 7-82%) less susceptible than individuals 65 years and over. A transmission model calibrated against these data indicates that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. These findings can help guide global intervention policies.


id: cord-341135-gmi1ewc2
title: Early dynamics of transmission and control of COVID-19: a mathematical modelling study
author: Kucharski, Adam J
date: 2020-02-02
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url: https://doi.org/10.1101/2020.01.31.20019901
doi: 10.1101/2020.01.31.20019901
summary:
  Methods: We combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. We estimate how transmission has varied over time, identify a decline in the reproduction number in late January to near 1, coinciding with the introduction of large scale control measures, and show the potential implications of estimated transmission for outbreak risk new locations. Based on the median reproduction number estimated during January before travel restrictions were introduced, we estimated that a single introduction of 2019-nCoV with SARS-like or MERS-like individual-level variation in transmission would have a 20-28% probability of causing a large outbreak ( Figure 3A ). Combining a mathematical model with multiple datasets, we found that the median daily reproduction number, R t , of SARS-CoV-2 in Wuhan likely varied between 1.6-2.6 in January 2020 prior to travel restrictions being introduced.

abstract:
  Background: An outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Methods: We combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. Findings: We estimated that the median daily reproduction number, Rt , declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population. Interpretation: Our results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually.


id: cord-342012-1w3x0g42
title: Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China
author: Wu, Joseph T.
date: 2020-03-19
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url: https://doi.org/10.1038/s41591-020-0822-7
doi: 10.1038/s41591-020-0822-7
summary:
  For a completely novel pathogen, especially one with a high (say, >2) basic reproductive number (the expected number of secondary cases generated by a primary case in a completely susceptible population) relative to other recently emergent and seasonal directly transmissible respiratory pathogens 4 , assuming homogeneous mixing and mass action dynamics, the majority of the population will be infected eventually unless drastic public health interventions are applied over prolonged periods and/or vaccines become available sufficiently quickly. We therefore extended our previously published transmission dynamics model 4 , updated with real-time input data and enriched with additional new data sources, to infer a preliminary set of clinical severity estimates that could guide clinical and public health decision-making as the epidemic continues to spread globally. Given that we have parameterized the model using death rates inferred from projected case numbers (from traveler data) and observed death numbers in Wuhan, the precise fatality risk estimates may not be generalizable to those outside the original epicenter, especially during subsequent phases of the epidemic.

abstract:
  As of 29 February 2020 there were 79,394 confirmed cases and 2,838 deaths from COVID-19 in mainland China. Of these, 48,557 cases and 2,169 deaths occurred in the epicenter, Wuhan. A key public health priority during the emergence of a novel pathogen is estimating clinical severity, which requires properly adjusting for the case ascertainment rate and the delay between symptoms onset and death. Using public and published information, we estimate that the overall symptomatic case fatality risk (the probability of dying after developing symptoms) of COVID-19 in Wuhan was 1.4% (0.9–2.1%), which is substantially lower than both the corresponding crude or naïve confirmed case fatality risk (2,169/48,557 = 4.5%) and the approximator(1) of deaths/deaths + recoveries (2,169/2,169 + 17,572 = 11%) as of 29 February 2020. Compared to those aged 30–59 years, those aged below 30 and above 59 years were 0.6 (0.3–1.1) and 5.1 (4.2–6.1) times more likely to die after developing symptoms. The risk of symptomatic infection increased with age (for example, at ~4% per year among adults aged 30–60 years).


id: cord-342268-azi9i2a8
author: Zhao, Shi
date: 2020-02-20
txt: ./txt/cord-342268-azi9i2a8.txt
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url: https://doi.org/10.1093/jtm/taaa022
doi: 10.1093/jtm/taaa022
abstract: nan
summary:
  title: Quantifying the association between domestic travel and the exportation of novel coronavirus (2019-nCoV) cases from Wuhan, China in 2020: a correlational analysis In this work, we quantified the association between the domestic travel load and the number of cases exported from Wuhan to other cityclusters in mainland China. We examined the association between the load of domestic passengers departed from Wuhan and the number of confirmed cases to the 10 city-clusters (including the three municipalities, Beijing, Shanghai and Chongqing). 1 We found a statistically significant positive association between the load of passengers multiplied by the local infectivity in Wuhan and the number of cases reported outside Wuhan, see Table 1 . The association between domestic train transportation and novel coronavirus outbreak in China, from 2019 to 2020: a data-driven correlational report Estimating the potential total number of novel Coronavirus (2019-nCoV) cases in Wuhan City, China Preprint published by the

title:
  Quantifying the association between domestic travel and the exportation of novel coronavirus (2019-nCoV) cases from Wuhan, China in 2020: a correlational analysis


id: cord-342822-d7jx06mh
title: The epidemiologic parameters for COVID-19: A Systematic Review and Meta-Analysis
author: Izadi, N.
date: 2020-05-06
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url: http://medrxiv.org/cgi/content/short/2020.05.02.20088385v1?rss=1
doi: 10.1101/2020.05.02.20088385
summary:
  Knowledge regarding epidemiological characteristics and parameters of the infectious diseases such as, incubation period (time from exposure to the agent until the first symptoms develop), serial interval (duration between symptom onset of a primary case and symptom onset of its secondary cases), basic reproduction number (R 0 ) (the transmission potential of a disease) and other epidemiologic parameters is important for modelling and estimation of epidemic trends and also implementation and evaluation of preventive procedures (8) (9) (10) (11) . Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions

abstract:
  Introduction: The World Health Organization (WHO) declared the outbreak to be a public health emergency and international concern and recognized it as a pandemic. The aim of this study was to estimate the epidemiologic parameters of novel coronavirus (COVID-19) pandemic for clinical and epidemiological help. Methods: Four electronic databases including Web of Science, Medline (PubMed), Scopus and Google Scholar were searched for literature published from early December 2019 up to 23 March 2020. The "metan" command was used to perform a fixed or random effects analysis. Cumulative meta-analysis was performed using the "metacum" command. Results: Totally 76 observational studies were included in the analysis. The pooled estimate for R0 was 2.99 (95% CI: 2.71-3.27) for COVID-19. The overall R0 was 3.23, 1.19, 3.6 and 2.35 for China, Singapore, Iran and Japan, respectively. The overall Serial Interval, doubling time, incubation period were 4.45, 4.14 and 4.24 days for COVID-19. In addition, the overall estimation for growth rate and case fatality rate for COVID-19 were 0.38% and 3.29%, respectively. Conclusion: Calculating the pooled estimate of the epidemiological parameters of COVID-19 as an emerging disease, could reveal epidemiological features of the disease that consequently pave the way for health policy makers to think more about control strategies. Keywords: Epidemiologic Parameters; R0; Serial Interval; Doubling Time; Case Fatality Rate;COVID-19


id: cord-343715-y594iewi
title: Organ-specific manifestations of COVID-19 infection
author: Gavriatopoulou, Maria
date: 2020-07-27
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url: https://www.ncbi.nlm.nih.gov/pubmed/32720223/
doi: 10.1007/s10238-020-00648-x
summary:
  Patients infected with this new coronavirus present with a variety of symptoms, which range from asymptomatic disease to mild and moderate symptoms (mild pneumonia), severe symptoms (dyspnoea, hypoxia, or > 50% lung involvement on imaging) and symptoms of critical illness (acute respiratory distress syndrome, respiratory failure, shock or multiorgan system dysfunction). A large retrospective observational study from China showed that among 214 hospitalized patients with confirmed SARS-CoV-2 infection, 36.4% had neurological manifestations [114] . The correlation of disease severity with neurological symptoms was confirmed by another retrospective study from France, reporting a prevalence of 84% of neurological manifestations in 58 hospitalized patients with acute respiratory distress syndrome (ARDS) due to COVID-19 [115] . Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series

abstract:
  Although COVID-19 presents primarily as a lower respiratory tract infection transmitted via air droplets, increasing data suggest multiorgan involvement in patients that are infected. This systemic involvement is postulated to be mainly related to the SARS-CoV-2 virus binding on angiotensin-converting enzyme 2 (ACE2) receptors located on several different human cells. Lung involvement is the most common serious manifestation of the disease, ranging from asymptomatic disease or mild pneumonia, to severe disease associated with hypoxia, critical disease associated with shock, respiratory failure and multiorgan failure or death. Among patients with COVID-19, underlying cardiovascular comorbidities including hypertension, diabetes and especially cardiovascular disease, has been associated with adverse outcomes, whereas the emergence of cardiovascular complications, including myocardial injury, heart failure and arrhythmias, has been associated with poor survival. Gastrointestinal symptoms are also frequently encountered and may persist for several days. Haematological complications are frequent as well and have been associated with poor prognosis. Furthermore, recent studies have reported that over a third of infected patients develop a broad spectrum of neurological symptoms affecting the central nervous system, peripheral nervous system and skeletal muscles, including anosmia and ageusia. The skin, the kidneys, the liver, the endocrine organs and the eyes are also affected by the systemic COVID-19 disease. Herein, we provide a comprehensive overview of the organ-specific systemic manifestations of COVID-19.


id: cord-343767-nnx8adtl
author: Liu, Ziyuan
date: 2020-08-12
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url: https://doi.org/10.3390/ijerph17165831
doi: 10.3390/ijerph17165831
summary:
  To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies. In this paper, the immune algorithm, the q-value method, and the improved ant colony algorithm are applied to the model to solve the path planning problem of the transport of medical waste. The studies of this paper are to establish a number of transport stations and an efficient medical waste transport model between hospitals and transport stations and, eventually, optimize the transportation paths. For the path optimization problem between the transport station and the hospitals, we used the ant colony optimization algorithm and the tabu search algorithm to solve it, which is a vehicle routing problem with load constraints (CVRP).

title:
  Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune–Ant Colony Algorithm

abstract:
  In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony–tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China—considered the first city to suffer from COVID-19—was chosen as an example of verification; the two-level model and the immune algorithm–ant colony optimization–tabu search (IA–ACO–TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.


id: cord-344423-jhdfscyw
title: Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city
author: Lian, Xinbo
date: 2020-06-30
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url: https://www.sciencedirect.com/science/article/pii/S004896972034078X?v=s5
doi: 10.1016/j.scitotenv.2020.140556
summary:
  The lockdown had a substantial environmental impact, because traffic pollution and industrial emissions are important factors affecting air quality and public health in the region. Due to the lack of central heating and chemical industry, in addition to the emissions from coal-fired enterprises such as power plants and the pollution transported from surrounding rural biomass burning activities, vehicle emissions are responsible for the most important pollution source affecting the air quality and public health in Wuhan (Daoru Liu, J o u r n a l P r e -p r o o f 5 2020). Compared with the corresponding periods, the rate of good days (AQI < 100) increased by 37.4%, which means that during the lockdown, the air quality in Wuhan had no significant effect on human health, and only some pollutants may have had a weak impact on the health of a small number of unusually sensitive people.

abstract:
  Abstract A series of strict lockdown measures were implemented in the areas of China worst affected by coronavirus disease 19, including Wuhan, to prevent the disease spreading. The lockdown had a substantial environmental impact, because traffic pollution and industrial emissions are important factors affecting air quality and public health in the region. After the lockdown, the average monthly air quality index (AQI) in Wuhan was 59.7, which is 33.9% lower than that before the lockdown (January 23, 2020) and 47.5% lower than that during the corresponding period (113.6) from 2015 to 2019. Compared with the conditions before the lockdown, fine particulate matter (PM2.5) decreased by 36.9% and remained the main pollutant. Nitrogen dioxide (NO2) showed the largest decrease of approximately 53.3%, and ozone (O3) increased by 116.6%. The proportions of fixed-source emissions and transported external-source emissions in this area increased. After the lockdown, O3 pollution was highly negatively correlated with the NO2 concentration, and the radiation increase caused by the PM2.5 reduction was not the main reason for the increase in O3. This indicates that the generation of secondary pollutants is influenced by multiple factors and is not only governed by emission reduction.


id: cord-344480-6tcush4w
title: Back to the spring of Wuhan: facts and hope of COVID-19 outbreak
author: Zhou, Guangbiao
date: 2020-03-14
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url: https://doi.org/10.1007/s11684-020-0758-9
doi: 10.1007/s11684-020-0758-9
abstract: nan
summary:
  The updated genome sequence of SARS-CoV-2 has been shared to the public, clinical trials are undergoing, and scientists from China and overseas are working together to combat this public health emergency. Epidemiological research priorities for public health control of the ongoing global novel coronavirus (2019-nCoV) outbreak The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding Therapeutic strategies in an outbreak scenario to treat the novel coronavirus originating in Wuhan, China.


id: cord-344688-uu3b529c
title: Pain Management During the COVID-19 Pandemic in China: Lessons Learned
author: Song, Xue-Jun
date: 2020-04-22
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url: https://doi.org/10.1093/pm/pnaa143
doi: 10.1093/pm/pnaa143
abstract: nan
summary:
  In the initial stages of the pandemic spanning late January to early February, medical systems in Wuhan faced overwhelming shortages of health care workers and key medical resources including medical-grade personal protective equipment, as well as limited space in hospitals for managing the surge of patients with COVID-19. With the help of public health systems, we were able to keep most patients home and provide them with necessary medical services including telemedicine support. Telemedicine became a convenient and effective way to provide necessary medical services to patients with chronic pain during the initial periods of the epidemic, as it allowed patients with nonemergent conditions to remain at home and allowed hospitalized patients who had been discharged early to maintain continuity of care. The epidemic provided many medical professionals an opportunity to incorporate telemedicine into pain management for the first time due to the urgent need for remote health care services.


id: cord-345724-6u9q0ox9
author: Zhu, Xiaolin
date: 2020-02-11
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url: https://doi.org/10.1101/2020.02.09.20021360
doi: 10.1101/2020.02.09.20021360
summary:
  The aim of this study is to model the current dynamics of 2019-nCoV at city level and predict the trend in the next 30 days under three possible scenarios in mainland China. We used the trained model to predict the future dynamics up to March 12, 2020 under different scenarios: the current trend maintained, control efforts expanded, and person-to-person contact increased due to work resuming. Although these studies at the early stage of outbreak help us understand the key epidemiological characteristics of 2019-nCoV, the fine-scale and updated epidemic trend in individual Chinese cities remains unknown, which is more helpful for allocating medical resources to achieve the optimal result of preventing disease spreading. We predicted daily infected cases of each city up to March 12, 2020 under three different scenarios (scenario 1 -the current trend maintained; scenario 2 -control efforts expanded; and scenario 3 -person-to-person contacts increased due to work resuming).

title:
  Spatially Explicit Modeling of 2019-nCoV Epidemic Trend based on Mobile Phone Data in Mainland China

abstract:
  IAs of February 11, 2020, all prefecture-level cities in mainland China have reported confirmed cases of 2019 novel coronavirus (2019-nCoV), but the city-level epidemical dynamics is unknown. The aim of this study is to model the current dynamics of 2019-nCoV at city level and predict the trend in the next 30 days under three possible scenarios in mainland China. We developed a spatially explicit epidemic model to consider the unique characteristics of the virus transmission in individual cities. Our model considered that the rate of virus transmission among local residents is different from those with Wuhan travel history due to the self-isolation policy. We introduced a decay rate to quantify the effort of each city to gradually control the disease spreading. We used mobile phone data to obtain the number of individuals in each city who have travel history to Wuhan. This city-level model was trained using confirmed cases up to February 10, 2020 and validated by new confirmed cases on February 11, 2020. We used the trained model to predict the future dynamics up to March 12, 2020 under different scenarios: the current trend maintained, control efforts expanded, and person-to-person contact increased due to work resuming. We estimated that the total infections in mainland China would be 72172, 54348, and 149774 by March 12, 2020 under each scenario respectively. Under the current trend, all cities will show the peak point of daily new infections by February 21. This date can be advanced to February 14 with control efforts expanded or postponed to February 26 under pressure of work resuming. Except Wuhan that cannot eliminate the disease by March 12, our model predicts that 95.4%, 100%, and 75.7% cities will have no new infections by the end of February under three scenarios. The spatial pattern of our prediction could help the government allocate resources to cities that have a more serious epidemic in the next 30 days.


id: cord-347204-cafr7f38
title: Modelling the effects of Wuhan’s lockdown during COVID-19, China
author: Yuan, Zheming
date: 2020-07-01
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url: https://www.ncbi.nlm.nih.gov/pubmed/32742034/
doi: 10.2471/blt.20.254045
summary:
  FINDINGS: Delaying the start date of control measures by only 3 days would have increased the estimated 30 699 confirmed cases of COVID-19 by 1 March 2020 in regions outside Wuhan by 34.6% (to 41 330 people). We present a simple model based on online data on population movements and confirmed numbers of people infected to quantify the consequences of the control measures in Wuhan on the ongoing spread of COVID-19 across mainland China. To determine the number of people represented by the migration index per unit, we used data on population movements during the 2019 Spring Festival travel rush in China (over 40 days from 21 January 2019 to 1 March 2019). We therefore concluded that the first key factor (x 1 ) affecting the final cumulative number of confirmed cases in cities outside Wuhan on 1 March 2020 was the sum of people travelling out of Wuhan during 20-26 January 2020 (there were few population movements after 27 January 2020 because of the control measures).

abstract:
  OBJECTIVE: To design a simple model to assess the effectiveness of measures to prevent the spread of coronavirus disease 2019 (COVID-19) to different regions of mainland China. METHODS: We extracted data on population movements from an internet company data set and the numbers of confirmed cases of COVID-19 from government sources. On 23 January 2020 all travel in and out of the city of Wuhan was prohibited to control the spread of the disease. We modelled two key factors affecting the cumulative number of COVID-19 cases in regions outside Wuhan by 1 March 2020: (i) the total the number of people leaving Wuhan during 20–26 January 2020; and (ii) the number of seed cases from Wuhan before 19 January 2020, represented by the cumulative number of confirmed cases on 29 January 2020. We constructed a regression model to predict the cumulative number of cases in non-Wuhan regions in three assumed epidemic control scenarios. FINDINGS: Delaying the start date of control measures by only 3 days would have increased the estimated 30 699 confirmed cases of COVID-19 by 1 March 2020 in regions outside Wuhan by 34.6% (to 41 330 people). Advancing controls by 3 days would reduce infections by 30.8% (to 21 235 people) with basic control measures or 48.6% (to 15 796 people) with strict control measures. Based on standard residual values from the model, we were able to rank regions which were most effective in controlling the epidemic. CONCLUSION: The control measures in Wuhan combined with nationwide traffic restrictions and self-isolation reduced the ongoing spread of COVID-19 across China.


id: cord-347257-s0w95qdn
title: The effect of human mobility and control measures on the COVID-19 epidemic in China
author: Kraemer, Moritz U. G.
date: 2020-03-25
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url: https://doi.org/10.1126/science.abb4218
doi: 10.1126/science.abb4218
summary:
  We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside Wuhan. We estimated the incubation period from 38 travelling cases returning from Wuhan with known dates of symptom onset, entry and exit. In order to accurately forecast the number of cases on Jan 28th, we must also include the relative amount of mobility out of Wuhan into various provinces in the regression model. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China

abstract:
  The ongoing COVID-19 outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions have been undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.


id: cord-348327-rgikd4g8
author: Ueyama, Hiroki
date: 2020-06-19
txt: ./txt/cord-348327-rgikd4g8.txt
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url: https://doi.org/10.1097/cce.0000000000000148
doi: 10.1097/cce.0000000000000148
summary:
  STUDY SELECTION: Studies were included in our meta-analysis if it was published in peer-reviewed journals and recorded patient characteristics of severe versus nonsevere or survivor versus nonsurvivor in coronavirus disease 2019 infection. The following search terms were applied to include all relevant studies documenting gender information on COVID-19 infection and its association with outcomes: "coronavirus 2019 or 2019-nCoV or sars cov 2 or COVID-19 or COVID; sex or gender or male or female or clinical characteristic or clinical features of clinical course or risk factor. Studies were included in our meta-analysis when it was: 1) published in peer-reviewed journals and 2) study that recorded patient characteristics of severe versus nonsevere or survivor versus nonsurvivor in COVID-19 infection. The salient findings of this meta-analysis are that males were more likely to develop severe COVID-19 infections compared with females, while there was no significant difference in mortality between gender.

title:
  Gender Difference Is Associated With Severity of Coronavirus Disease 2019 Infection: An Insight From a Meta-Analysis

abstract:
  OBJECTIVES: Coronavirus disease 2019 is a novel infection now causing pandemic around the world. The gender difference in regards to the severity of coronavirus disease 2019 infection has not been well described thus far. Our aim was to investigate how gender difference can affect the disease severity of coronavirus disease 2019 infection. DATA SOURCES: A comprehensive literature search of PubMed and Embase databases was conducted from December 1, 2019, to March 26, 2020. An additional manual search of secondary sources was conducted to minimize missing relevant studies. There were no language restrictions. STUDY SELECTION: Studies were included in our meta-analysis if it was published in peer-reviewed journals and recorded patient characteristics of severe versus nonsevere or survivor versus nonsurvivor in coronavirus disease 2019 infection. DATA EXTRACTION: Two investigators independently screened the search, extracted the data, and assessed the quality of the study. DATA SYNTHESIS: Our search identified 15 observational studies with a total of 3,494 patients (1,935 males and 1,559 females) to be included in our meta-analysis. Males were more likely to develop severe coronavirus disease 2019 infection compared with females (odds ratio, 1.31; 95% CI, 1.07–1.60). There was no significant heterogeneity (I(2) = 12%) among the studies. CONCLUSIONS: This meta-analysis suggests that the male gender may be a predictor of more severe coronavirus disease 2019 infection. Further accumulation of evidence from around the world is warranted to confirm our findings.


id: cord-349276-viq01q8l
title: Governance, technology and citizen behavior in pandemic: Lessons from COVID-19 in East Asia
author: Shaw, Rajib
date: 2020-04-30
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url: https://api.elsevier.com/content/article/pii/S2590061720300272
doi: 10.1016/j.pdisas.2020.100090
summary:
  The above description shows that within two months (from 13th of January, when first case was reported in Thailand, outside China to 13th of March, when USA declared emergency), the virus has taken a significant number of lives, affected a large number of people, and brought down many countries, including the economic hubs under lockdown. (1) The occurrence of first confirmed case and subsequent successful initial management: From the beginning of the COVID-19 situation, the Korean government, centered around the Korea Centers for Disease Control and Prevention (KCDC), has shared information with related organizations and established an effective response system. On top of that, as the government-wide response became more vital due to the rapid increase in the number of confirmed cases, MoIS took charge of the monitoring and management of people self-isolating, finding and surveying those who had visited the Wuhan region and may be contagious, locating and securing temporary living facilities and lifetime treatment centers through Countermeasures Support Headquarters (CSHQs).

abstract:
  Abstract Corona Virus (CODID-19) was first reported in Wuhan in December 2019, then spread in different parts of China, and gradually became a global pandemic in March 2020. While the death toll is still increasing, the epicenter of casualty has shifted from Asia to Europe, and that of the affected people has shifted to USA. This paper analyzes the responses in East Asian countries, in China, Japan and South Korea, and provides some commonalities and lessons. While countries have different governance mechanism, it was found that a few governance decisions in respective countries made a difference, along with strong community solidarity and community behavior. Extensive use of emerging technologies is made along with medical/health care treatment to make the response more effective and reduce the risk of the spread of the disease. Although the pandemic was a global one, its responses were local, depending on the local governance, socio-economic and cultural context.


id: cord-350338-lcsa06gm
author: Wang, Kun
date: 2020-05-03
txt: ./txt/cord-350338-lcsa06gm.txt
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extension: .txt
mime: text/plain
url: https://doi.org/10.1093/cid/ciaa538
doi: 10.1093/cid/ciaa538
summary:
  title: Clinical and laboratory predictors of in-hospital mortality in patients with COVID-19: a cohort study in Wuhan, China We then validated these models by randomly collecting COVID-19 patients in the Infection department of Union Hospital in Wuhan from January 1, 2020, to February 20, 2020. The laboratory model developed with age, high-sensitivity C-reactive protein (hsCRP), peripheral capillary oxygen saturation (SpO2), neutrophil and lymphocyte count, D-dimer, aspartate aminotransferase (AST) and glomerular filtration rate (GFR) had a significantly stronger discriminatory power than the clinical model (p=0.0157), with AUC of 0.98 (95% CI, 0.92-0.99); threshold, -2.998; sensitivity, 100.00%; specificity, 92.82% and NPV, 100.00%. We developed a clinical model and laboratory model for predicting the in-hospital mortality of COVID-19 patients, the AUCs (95% CI) were 0.88 (0.80, 0.95) and 0.98 (0.92, 0.99) in training cohort, and 0.83 (0.68, 0.93) and 0.88 (0.77, 0.95) in validation cohort, respectively. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China

title:
  Clinical and laboratory predictors of in-hospital mortality in patients with COVID-19: a cohort study in Wuhan, China

abstract:
  BACKGROUND: This study aimed to develop mortality-prediction models for patients with Coronavirus disease 2019 (COVID-19). METHODS: The training cohort were consecutive patients with COVID-19 in the First People’s Hospital of Jiangxia District in Wuhan from January 7, 2020 to February 11, 2020. We selected baseline clinical and laboratory data through the stepwise Akaike information criterion and ensemble XGBoost model to build mortality-prediction models. We then validated these models by randomly collecting COVID-19 patients in the Infection department of Union Hospital in Wuhan from January 1, 2020, to February 20, 2020. RESULTS: 296 patients with COVID-19 were enrolled in the training cohort, 19 of whom died during hospitalization and 277 were discharged from the hospital. The clinical model developed with age, history of hypertension and coronary heart disease showed AUC of 0.88 (95% CI, 0.80-0.95); threshold, -2.6551; sensitivity, 92.31%; specificity, 77.44% and negative predictive value (NPV), 99.34%. The laboratory model developed with age, high-sensitivity C-reactive protein (hsCRP), peripheral capillary oxygen saturation (SpO2), neutrophil and lymphocyte count, D-dimer, aspartate aminotransferase (AST) and glomerular filtration rate (GFR) had a significantly stronger discriminatory power than the clinical model (p=0.0157), with AUC of 0.98 (95% CI, 0.92-0.99); threshold, -2.998; sensitivity, 100.00%; specificity, 92.82% and NPV, 100.00%. In the subsequent validation cohort (N=44), the AUCs (95% CI) were 0.83 (0.68, 0.93) and 0.88 (0.75, 0.96) for clinical model and laboratory model, respectively. CONCLUSIONS: We developed two predictive models for the in-hospital mortality of patients with COVID-19 in Wuhan and validated in patients from another center.


id: cord-350822-m3t7l9zw
title: Work stress among Chinese nurses to support Wuhan in fighting against COVID‐19 epidemic
author: Mo, Yuanyuan
date: 2020-05-20
txt: ./txt/cord-350822-m3t7l9zw.txt
cache: ./cache/cord-350822-m3t7l9zw.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1111/jonm.13014
doi: 10.1111/jonm.13014
summary:
  AIMS: To investigate the work stress among Chinese nurses who are supporting Wuhan in fighting against Coronavirus Disease 2019 (COVID‐19) infection and to explore the relevant influencing factors. The purpose of the present study was to investigate the work stress load among Chinese nurses who support Wuhan in fighting against COVID-19 infection and to explore the relevant influencing factors for the development of psychological interventions for Chinese nurses in order that they can adjust to public health emergencies. The results showed that whether the participants are the only child in their families, working hours per week and anxiety were the main factors influencing the stress load of nurses assisting in the fight against COVID-19, which can explain 52.1% of the total variation, as shown in Table 2 .

abstract:
  AIMS: To investigate the work stress among Chinese nurses who are supporting Wuhan in fighting against Coronavirus Disease 2019 (COVID‐19) infection and to explore the relevant influencing factors. BACKGROUND: The COVID‐19 epidemic has posed a major threat to public health. Nurses have always played an important role in infection prevention, infection control, isolation, containment and public health. However, available data on the work stress among these nurses are limited. METHODS: A cross‐sectional survey. An online questionnaire was completed by 180 anti‐epidemic nurses from Guangxi. Data collection tools, including the Chinese version of the Stress Overload Scale (SOS) and the Self‐rating Anxiety Scale (SAS), were used. Descriptive single factor correlation and multiple regression analyses were used in exploring the related influencing factors. RESULTS: The SOS (39.91 ± 12.92) and SAS (32.19 ± 7.56) scores of this nurse group were positively correlated (r = 0.676, p < .05). Multiple regression analysis showed that only children, working hours per week and anxiety were the main factors affecting nurse stress (p = .000, .048, .000, respectively). CONCLUSIONS: Nurses who fight against COVID‐19 were generally under pressure. IMPLICATIONS FOR NURSING MANAGEMENT: Nurse leaders should pay attention to the work stress and the influencing factors of the nurses who are fighting against COVID‐19 infection, and offer solutions to retain mental health among these nurses.


id: cord-351167-4gpq5syb
title: 2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus
author: Koenig, Kristi L.
date: 2020-01-31
txt: ./txt/cord-351167-4gpq5syb.txt
cache: ./cache/cord-351167-4gpq5syb.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32191174/
doi: 10.5811/westjem.2020.1.46760
summary:
  2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies.

abstract:
  2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV.


id: cord-351567-ifoe8x28
title: SARS-CoV-2 and Coronavirus Disease 2019: What We Know So Far
author: Rabi, Firas A.
date: 2020-03-20
txt: ./txt/cord-351567-ifoe8x28.txt
cache: ./cache/cord-351567-ifoe8x28.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.3390/pathogens9030231
doi: 10.3390/pathogens9030231
summary:
  However, by that time, travelers had carried the virus to many countries, sparking memories of the previous coronavirus epidemics, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), and causing widespread media attention and panic. To assess the magnitude of the risk posed by the SARS-CoV-2, we review four parameters that we believe important: the transmission rate, the incubation period, the case fatality rate (CFR), and the determination of whether asymptomatic transmission can occur. A small study of 17 patients showed that nasal viral load peaks within days of symptom onset, suggesting that transmission of disease is more likely to occur early in the course of infection [40] . Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19)-China 2020 Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia

abstract:
  In December 2019, a cluster of fatal pneumonia cases presented in Wuhan, China. They were caused by a previously unknown coronavirus. All patients had been associated with the Wuhan Wholefood market, where seafood and live animals are sold. The virus spread rapidly and public health authorities in China initiated a containment effort. However, by that time, travelers had carried the virus to many countries, sparking memories of the previous coronavirus epidemics, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), and causing widespread media attention and panic. Based on clinical criteria and available serological and molecular information, the new disease was called coronavirus disease of 2019 (COVID-19), and the novel coronavirus was called SARS Coronavirus-2 (SARS-CoV-2), emphasizing its close relationship to the 2002 SARS virus (SARS-CoV). The scientific community raced to uncover the origin of the virus, understand the pathogenesis of the disease, develop treatment options, define the risk factors, and work on vaccine development. Here we present a summary of current knowledge regarding the novel coronavirus and the disease it causes.


id: cord-351600-bqw9ks4a
author: Zhang, Shuai
date: 2020-07-16
txt: ./txt/cord-351600-bqw9ks4a.txt
cache: ./cache/cord-351600-bqw9ks4a.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1186/s13054-020-03123-x
doi: 10.1186/s13054-020-03123-x
summary:
  title: Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study We aimed to explore the risk factors of 14-day and 28-day mortality and develop a model for predicting 14-day and 28-day survival probability among adult hospitalized patients with COVID-19. Nomogram scoring systems for predicting the 14-day and 28-day survival probability of patients with COVID-19 were developed and exhibited strong discrimination and calibration power in the two external validation cohorts (C-index, 0.878 and 0.839). CONCLUSION: Older age, high lactate dehydrogenase level, evaluated neutrophil-to-lymphocyte ratio, and high direct bilirubin level were independent predictors of 28-day mortality in adult hospitalized patients with confirmed COVID-19. We aimed to explore the risk factors of 28-day mortality and develop a nomogram scoring system for predicting 28-day survival probability among patients with COVID-19.

title:
  Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study

abstract:
  BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a public health emergency of global concern. We aimed to explore the risk factors of 14-day and 28-day mortality and develop a model for predicting 14-day and 28-day survival probability among adult hospitalized patients with COVID-19. METHODS: In this multicenter, retrospective, cohort study, we examined 828 hospitalized patients with confirmed COVID-19 hospitalized in Wuhan Union Hospital and Central Hospital of Wuhan between January 12 and February 9, 2020. Among the 828 patients, 516 and 186 consecutive patients admitted in Wuhan Union Hospital were enrolled in the training cohort and the validation cohort, respectively. A total of 126 patients hospitalized in Central Hospital of Wuhan were enrolled in a second external validation cohort. Demographic, clinical, radiographic, and laboratory measures; treatment; proximate causes of death; and 14-day and 28-day mortality are described. Patients’ data were collected by reviewing the medical records, and their 14-day and 28-day outcomes were followed up. RESULTS: Of the 828 patients, 146 deaths were recorded until May 18, 2020. In the training set, multivariate Cox regression indicated that older age, lactate dehydrogenase level over 360 U/L, neutrophil-to-lymphocyte ratio higher than 8.0, and direct bilirubin higher than 5.0 μmol/L were independent predictors of 28-day mortality. Nomogram scoring systems for predicting the 14-day and 28-day survival probability of patients with COVID-19 were developed and exhibited strong discrimination and calibration power in the two external validation cohorts (C-index, 0.878 and 0.839). CONCLUSION: Older age, high lactate dehydrogenase level, evaluated neutrophil-to-lymphocyte ratio, and high direct bilirubin level were independent predictors of 28-day mortality in adult hospitalized patients with confirmed COVID-19. The nomogram system based on the four factors revealed good discrimination and calibration, suggesting good clinical utility.


id: cord-351651-6dbt99h0
title: Potential Factors Influencing Repeated SARS Outbreaks in China
author: Sun, Zhong
date: 2020-03-03
txt: ./txt/cord-351651-6dbt99h0.txt
cache: ./cache/cord-351651-6dbt99h0.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32138266/
doi: 10.3390/ijerph17051633
summary:
  Thus, if bats were the natural hosts of SARS-CoVs, cold temperature and low humidity in these times might provide conducive environmental conditions for prolonged viral survival in these regions concentrated with bats. A study on the genome sequence of diseased pangolins smuggled from Malaysia to China found that pangolins carry coronavirus, suggesting that pangolins may be intermediate hosts for SARS-COV-2 [35] . However, the only source of bats that have been publicly identified as carrying virus phylogenetically close to SARS-CoV-2 is far away from Wuhan in Zhoushan, Zhejiang. However, to confirm this scenario, it is necessary to find wild bats in Wuhan and its neighboring areas that carry CoVs identical to those isolated from various SARS-2 patients. This mini-review evaluated the common epidemiological patterns of both SARS epidemics in China and identified cold, dry winter as a common environmental condition conducive for SARS virus infection to human beings.

abstract:
  Within last 17 years two widespread epidemics of severe acute respiratory syndrome (SARS) occurred in China, which were caused by related coronaviruses (CoVs): SARS-CoV and SARS-CoV-2. Although the origin(s) of these viruses are still unknown and their occurrences in nature are mysterious, some general patterns of their pathogenesis and epidemics are noticeable. Both viruses utilize the same receptor—angiotensin-converting enzyme 2 (ACE2)—for invading human bodies. Both epidemics occurred in cold dry winter seasons celebrated with major holidays, and started in regions where dietary consumption of wildlife is a fashion. Thus, if bats were the natural hosts of SARS-CoVs, cold temperature and low humidity in these times might provide conducive environmental conditions for prolonged viral survival in these regions concentrated with bats. The widespread existence of these bat-carried or -released viruses might have an easier time in breaking through human defenses when harsh winter makes human bodies more vulnerable. Once succeeding in making some initial human infections, spreading of the disease was made convenient with increased social gathering and holiday travel. These natural and social factors influenced the general progression and trajectory of the SARS epidemiology. However, some unique factors might also contribute to the origination of SARS in Wuhan. These factors are discussed in different scenarios in order to promote more research for achieving final validation.


id: cord-351880-iqr419fp
author: Fan, Changyu
date: 2020-03-04
txt: ./txt/cord-351880-iqr419fp.txt
cache: ./cache/cord-351880-iqr419fp.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32143519/
doi: 10.3390/ijerph17051679
summary:
  Total 1999 2000 2000 2000 2000 2000 11,999 Hubei 1514 1508 1487 1465 1477 1547 8998 Henan 113 134 109 159 170 125 810 Anhui 59 58 55 53 56 46 327 Hunan 57 46 68 54 41 36 302 Jiangxi 58 40 53 57 49 34 291 Chongqing 34 29 34 33 33 35 198 Zhejiang 22 29 25 33 25 33 167 Sichuan 22 30 45 21 22 27 167 Fujian 14 17 16 15 39 19 120 Jiangsu 38 13 16 19 13 11 110 Shandong 12 18 11 13 8 12 74 Guangdong 7 8 18 18 14 8 73 Hebei 0 1 5 Tianjin 1 0 0 1 0 1 3 Shanghai 0 1 0 1 0 1 3 Inner Mongolia 1 0 0 0 1 0 2 Xizang 0 0 1 0 0 1 2 Ningxia 0 0 1 0 0 0 1 According to the current infectious features of 2019-nCoV, which are that middle-aged and elderly people have a high risk of infection, and transmission can occur between individuals, families and communities, we assessed several main variables.

title:
  Prediction of Epidemic Spread of the 2019 Novel Coronavirus Driven by Spring Festival Transportation in China: A Population-Based Study

abstract:
  After the 2019 novel coronavirus (2019-nCoV) outbreak, we estimated the distribution and scale of more than 5 million migrants residing in Wuhan after they returned to their hometown communities in Hubei Province or other provinces at the end of 2019 by using the data from the 2013–2018 China Migrants Dynamic Survey (CMDS). We found that the distribution of Wuhan’s migrants is centred in Hubei Province (approximately 75%) at a provincial level, gradually decreasing in the surrounding provinces in layers, with obvious spatial characteristics of circle layers and echelons. The scale of Wuhan’s migrants, whose origins in Hubei Province give rise to a gradient reduction from east to west within the province, and account for 66% of Wuhan’s total migrants, are from the surrounding prefectural-level cities of Wuhan. The distribution comprises 94 districts and counties in Hubei Province, and the cumulative percentage of the top 30 districts and counties exceeds 80%. Wuhan’s migrants have a large proportion of middle-aged and high-risk individuals. Their social characteristics include nuclear family migration (84%), migration with families of 3–4 members (71%), a rural household registration (85%), and working or doing business (84%) as the main reason for migration. Using a quasi-experimental analysis framework, we found that the size of Wuhan’s migrants was highly correlated with the daily number of confirmed cases. Furthermore, we compared the epidemic situation in different regions and found that the number of confirmed cases in some provinces and cities in Hubei Province may be underestimated, while the epidemic situation in some regions has increased rapidly. The results are conducive to monitoring the epidemic prevention and control in various regions.


id: cord-352030-hnm54k4r
author: Liu, Jie
date: 2020-03-13
txt: ./txt/cord-352030-hnm54k4r.txt
cache: ./cache/cord-352030-hnm54k4r.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.03.09.20033118
doi: 10.1101/2020.03.09.20033118
summary:
  These included age, sex, occupation (doctor, or nurse), body mass index (BMI ≥ 24, or <24 kg/m 2 ), current smoking status (yes, or no), disease severity (non-severe, or severe), date of symptom onset, symptoms before hospital admission (fever, cough, fatigue, sore throat, myalgia, sputum production, difficulty breathing or chest tightness, chill, loss of appetite, diarrhea, and chest pain), coexisting conditions (e.g. hypertension, diabetes, etc.), laboratory testing indicators on admission (leucocyte count, lymphocyte count, platelet count, D-dimer, creatinine, creatine kinase, lactose dehydrogenase, alanine aminotransferase, aspartate aminotransferase, hemoglobin, ferritin, C-reactive protein, Amyloid A, total bilirubin, procalcitonin, erythrocyte sedimentation rate, interleukin-6 (IL-6) and lymphocyte subsets, etc.), radiologic assessments of chest CT (lung involvement, lung lobe involvement, predominant CT changes, predominant distribution of opacities, etc.), treatment measures (antibiotics agents, antiviral agents, traditional Chinese medicine, immune globulin, thymosin, corticosteroids and oxygen therapy), and complications (e.g. pneumonia, acute respiratory distress syndrome, acute cardiac injury, acute kidney injury, shock, etc.).

title:
  Epidemiological, Clinical Characteristics and Outcome of Medical Staff Infected with COVID-19 in Wuhan, China: A Retrospective Case Series Analysis

abstract:
  Backgrounds Since December 2019, a novel coronavirus epidemic has emerged in Wuhan city, China and then rapidly spread to other areas. As of 20 Feb 2020, a total of 2,055 medical staff confirmed with coronavirus disease 2019 (COVID-19) caused by SARS-Cov-2 in China had been reported. We sought to explore the epidemiological, clinical characteristics and prognosis of novel coronavirus-infected medical staff. Methods In this retrospective study, 64 confirmed cases of novel coronavirus-infected medical staff admitted to Union Hospital, Wuhan between 16 Jan, 2020 to 15 Feb, 2020 were included. Two groups concerned were extracted from the subjects based on duration of symptoms: group 1 (<= 10 days) and group 2 (>10 days). Epidemiological and clinical data were analyzed and compared across groups. The Kaplan-Meier plot was used to inspect the change in hospital discharge rate. The Cox regression model was utilized to identify factors associated with hospital discharge. Findings The median age of medical staff included was 35 years old. 64% were female and 67% were nurses. None had an exposure to Huanan seafood wholesale market or wildlife. A small proportion of the cohort had contact with specimens (5%) as well as patients in fever clinics (8%) and isolation wards (5%). Fever (67%) was the most common symptom, followed by cough (47%) and fatigue (34%). The median time interval between symptoms onset and admission was 8.5 days. On admission, 80% of medical staff showed abnormal IL-6 levels and 34% had lymphocytopenia. Chest CT mainly manifested as bilateral (61%), subpleural (80%) and ground-glass (52%) opacities. During the study period, no patients was transferred to intensive care unit or died, and 34 (53%) had been discharged. Higher body mass index (BMI) (HR 0.14; 95% CI 0.03-0.73), fever (HR 0.24; 95% CI 0.09-0.60) and higher levels of IL-6 on admission (HR 0.31; 95% CI 0.11-0.87) were unfavorable factors for discharge. Interpretation In this study, medical staff infected with COVID-19 have relatively milder symptoms and favorable clinical course, which may be partly due to their medical expertise, younger age and less underlying diseases. Smaller BMI, absence of fever symptoms and normal IL-6 levels on admission are favorable for discharge for medical staff. Further studies should be devoted to identifying the exact patterns of SARS-CoV-2 infection among medical staff.


id: cord-352509-qrzt4zva
author: Chen, Haohui
date: 2020-03-16
txt: ./txt/cord-352509-qrzt4zva.txt
cache: ./cache/cord-352509-qrzt4zva.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.03.11.20033688
doi: 10.1101/2020.03.11.20033688
summary:
  This study examines publicly available online search data in China to investigate the spread of public awareness of the 2019 novel coronavirus (COVID-19) outbreak. We use the continuing Wuhan coronavirus outbreak as our case study to estimate the effects of social distance and SARS memory on the spread of public awareness. The effects of social distance and SARS memory on the lead-time advantage are estimated according to Eq. 4, controlled by Euclidean distances, GDP per capita and the city''s administrative level (Table 1) . That means cities of strong SARS memory and which are closer to Wuhan in terms of Social distances develop early awareness. Through controlling for development, administrative levels, and Euclidean distances, we observe cities that were struck by SARS and have more migration to the epicentre, Wuhan, showed earlier, stronger and more durable public awareness of the outbreak.

title:
  Social distance and SARS memory: impact on the public awareness of 2019 novel coronavirus (COVID-19) outbreak

abstract:
  This study examines publicly available online search data in China to investigate the spread of public awareness of the 2019 novel coronavirus (COVID-19) outbreak. We found that cities that suffered from SARS and have greater migration ties to the epicentre, Wuhan, had earlier, stronger and more durable public awareness of the outbreak. Our data indicate that forty-eight such cities developed awareness up to 19 days earlier than 255 comparable cities, giving them an opportunity to better prepare. This study suggests that it is important to consider memory of prior catastrophic events as they will influence the public response to emerging threats.


id: cord-352797-xuaqump9
title: Influence of Asymptomatic Carriers With COVID-19 on Transplantation Resumption in Wuhan
author: Bian, Xiaoen
date: 2020-06-22
txt: ./txt/cord-352797-xuaqump9.txt
cache: ./cache/cord-352797-xuaqump9.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32740319/
doi: 10.1097/tp.0000000000003356
abstract: nan
summary:
  As of May 24, 6 574 093 NAT tests have been completed, with a total of 227 new asymptomatic carriers and 1 new confirmed case 1 . Due to the superficial understanding of COVID-19 and presence of asymptomatic infection in Wuhan, we instituted a protocol to prevent organ donor transmission of COVID-19. Before transplantation both deceased donors and potential recipients undergo SARS-CoV-2 NAT and antibody tests as well as CT scans, which are repeated twice, to avoid the known false negative rates of single tests in COVID-19 patients and detect patients in the early stages of developing symptomatic disease. To minimize transmission caused by asymptomatic carriers, potential deceased donors are quarantined in intensive care for >7 days while being tested. There have been no cases of COVID-19 detected among organ transplant donors and recipients. Wuhan Reopened for a Week, and No Case of Asymptomatic Infection Was Confirmed A case of coronavirus disease 2019-infected liver transplant donor


id: cord-353862-7xe3fvd5
title: Maternal and neonatal outcomes of pregnant women with COVID-19 pneumonia: a case-control study
author: Li, Na
date: 2020-03-30
txt: ./txt/cord-353862-7xe3fvd5.txt
cache: ./cache/cord-353862-7xe3fvd5.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32249918/
doi: 10.1093/cid/ciaa352
summary:
  METHODS: We conducted a case-control study to compare clinical characteristics, maternal and neonatal outcomes of pregnant women with and without COVID-19 pneumonia. An earlier study by Chen et al reported nine pregnant women with COVID-19 pneumonia, who took cesarean section in a tertiary hospital of Wuhan [8] . To date, none of previous studies have investigated the adverse effects of COVID-19 infection on pregnancy, by comparing maternal and neonatal outcomes of pregnant women with COVID-19 pneumonia to those without pneumonia. Similar to two previous reports of nine and one pregnant women with confirmed COVID-19 infection [8, 22] , we did not find any evidence to support the vertical transmission of SARS-CoV-2 from mother to fetus via placenta or during cesarean section. Second, we collected the data of sixteen pregnant women with laboratory confirmed COVID-19 pneumonia and eighteen suspected cases with typical CT imaging.

abstract:
  BACKGROUND: The ongoing epidemics of coronavirus disease 2019 (COVID-19) have caused serious concerns about its potential adverse effects on pregnancy. There are limited data on maternal and neonatal outcomes of pregnant women with COVID-19 pneumonia. METHODS: We conducted a case-control study to compare clinical characteristics, maternal and neonatal outcomes of pregnant women with and without COVID-19 pneumonia. RESULTS: During January 24 to February 29, 2020, there were sixteen pregnant women with confirmed COVID-19 pneumonia and eighteen suspected cases who were admitted to labor in the third trimester. Two had vaginal delivery and the rest took cesarean section. Few patients presented respiratory symptoms (fever and cough) on admission, but most had typical chest CT images of COVID-19 pneumonia. Compared to the controls, COVID-19 pneumonia patients had lower counts of white blood cells (WBC), neutrophils, C-reactive protein (CRP), and alanine aminotransferase (ALT) on admission. Increased levels of WBC, neutrophils, eosinophils, and CRP were found in postpartum blood tests of pneumonia patients. There were three (18.8%) and three (16.7%) of the mothers with confirmed or suspected COVID-19 pneumonia had preterm delivery due to maternal complications, which were significantly higher than the control group. None experienced respiratory failure during hospital stay. COVID-19 infection was not found in the newborns and none developed severe neonatal complications. CONCLUSION: Severe maternal and neonatal complications were not observed in pregnant women with COVID-19 pneumonia who had vaginal delivery or caesarean section. Mild respiratory symptoms of pregnant women with COVID-19 pneumonia highlight the need of effective screening on admission.


id: cord-354095-4sweo53l
author: Qiu, Yun
date: 2020-05-09
txt: ./txt/cord-354095-4sweo53l.txt
cache: ./cache/cord-354095-4sweo53l.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1007/s00148-020-00778-2
doi: 10.1007/s00148-020-00778-2
summary:
  First, our instrumental variable approach helps isolate the causal effect of virus transmissions from other confounded factors; second, our estimate is based on an extended time period of the COVID-19 pandemic (until the end of February 2020) that may mitigate potential biases in the literature that relies on a shorter sampling period within 1-28 January 2020; third, our modeling makes minimum assumptions of virus transmissions, such as imposing fewer restrictions on the relationship between the unobserved determinants of new cases and the number of cases in the past; fourth, our model simultaneously considers comprehensive factors that may affect virus transmissions, including multiple policy instruments (such as closed management of communities and shelter-at-home order), population flow, within-and between-city transmissions, economic and demographic conditions, weather patterns, and preparedness of health care system.

title:
  Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China

abstract:
  This study models local and cross-city transmissions of the novel coronavirus in China between January 19 and February 29, 2020. We examine the role of various socioeconomic mediating factors, including public health measures that encourage social distancing in local communities. Weather characteristics 2 weeks prior are used as instrumental variables for causal inference. Stringent quarantines, city lockdowns, and local public health measures imposed in late January significantly decreased the virus transmission rate. The virus spread was contained by the middle of February. Population outflow from the outbreak source region posed a higher risk to the destination regions than other factors, including geographic proximity and similarity in economic conditions. We quantify the effects of different public health measures in reducing the number of infections through counterfactual analyses. Over 1.4 million infections and 56,000 deaths may have been avoided as a result of the national and provincial public health measures imposed in late January in China.


id: cord-354717-4vrqzbof
author: Linton, Natalie M.
date: 2020-02-17
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url: https://doi.org/10.3390/jcm9020538
doi: 10.3390/jcm9020538
summary:
  title: Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk. Using publicly available data from the ongoing epidemic with known case event dates, the present study aimed to estimate the incubation period and other time intervals that govern the interpretation of epidemiological dynamics of COVID-19 infections. The median time from illness onset to hospital admission was estimated at 3.3 days (95% CI: 2.7, 4.0) among living cases and 6.5 days (95% CI: 5.2, 8.0) among deceased cases using the gamma distribution, which provided the best fit for both sets of data.

title:
  Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data

abstract:
  The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3–4 days without truncation and at 5–9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.


id: cord-355528-y4a1g6km
title: COVID-19, Modern Pandemic: A Systematic Review From Front-Line Health Care Providers’ Perspective
author: Balla, Mamtha
date: 2020-03-30
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url: https://doi.org/10.14740/jocmr4142
doi: 10.14740/jocmr4142
summary:
  The main aim of this systematic review is to provide a comprehensive clinical summary of all the available data from high-quality research articles relevant to the epidemiology, demographics, trends in hospitalization and outcomes, clinical signs and symptoms, diagnostic methods and treatment methods of COVID-19, thus increasing awareness in health care providers. Coronavirus disease 2019 (COVID19) infection, which is a global pandemic declared on March 11, 2020, by World Health Organization (WHO), was reported to have infected 168,000 cases worldwide in about 148 countries and territories and killed more than 6,610 people around the world as of March 16, 2020 [1]. According to the study by Xu et al, 60% of people diagnosed with COVID-19 had traveled to Wuhan or nearby regions (60%), 36% had close contact with novel coronavirus pneumonia (NCP) patients and 4% had no definite exposure [12] . Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan

abstract:
  Coronavirus disease 2019 (COVID-19) caused infection in 168,000 cases worldwide in about 148 countries and killed more than 6,610 people around the world as of March 16, 2020, as per the World Health Organization (WHO). Compared to severe acute respiratory syndrome and Middle East respiratory syndrome, there is the rapid transmission, long incubation period, and disease containment is becoming extremely difficult. The main aim of this systematic review is to provide a comprehensive clinical summary of all the available data from high-quality research articles relevant to the epidemiology, demographics, trends in hospitalization and outcomes, clinical signs and symptoms, diagnostic methods and treatment methods of COVID-19, thus increasing awareness in health care providers. We also discussed various preventive measures to combat COVID-19 effectively. A systematic and protocol-driven approach is needed to contain this disease, which was declared as a global pandemic on March 11, 2020, by the WHO.


id: cord-355531-1cpli8kv
author: LIANG, Jingbo
date: 2020-04-06
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url: https://doi.org/10.1101/2020.03.31.20049387
doi: 10.1101/2020.03.31.20049387
summary:
  However, most of the recent studies focused on the early outbreaks without considering improvements in diagnostic capability and effects of prevention measures together, thus the estimated results may only reflect the facts in a given period of time. Methods: We constructed a stochastic susceptible-exposed-infected-quarantined-recovered (SEIQR) model, embedding with latent periods under different prevention measures and proportions of documented infections to characterize the Wuhan COVID-19 transmission cross different stages of the outbreak. In this study, we have developed a stochastic susceptible-exposed-infected-quarantinedrecovered (SEIQR) model, embedding with latent periods and the transportation restriction control under the different proportion of documented infections to describe the Wuhan COVID-19 transmission pattern after the initial outbreak stage. This is the first study to demonstrate the effects of transportation restriction measures together with the improvement of diagnostic capacity on the transmission dynamics in Wuhan.

title:
  The impacts of diagnostic capability and prevention measures on transmission dynamics of COVID-19 in Wuhan

abstract:
  Background: Although the rapidly rising transmission trend of COVID-19 in Wuhan has been controlled in late February 2020, the outbreak still caused a global pandemic afterward. Understanding Wuhan COVID-19 transmission dynamics and the effects of prevention approaches is of significant importance for containing virus global transmission. However, most of the recent studies focused on the early outbreaks without considering improvements in diagnostic capability and effects of prevention measures together, thus the estimated results may only reflect the facts in a given period of time. Methods: We constructed a stochastic susceptible-exposed-infected-quarantined-recovered (SEIQR) model, embedding with latent periods under different prevention measures and proportions of documented infections to characterize the Wuhan COVID-19 transmission cross different stages of the outbreak. The epidemiological parameters were estimated using a particle filtering approach. Results: Our model successfully reproduced the dynamics of the Wuhan local epidemic with two peaks on February 4 and February 12 separately. Prevention measures determined the time of reaching the first peak and caused an 87% drop in the R_t from 3.09 (95% CI, 2.10 to 3.63) to 0.41 (95% CI, 0.18 to 0.66). An improved diagnostic capability created the second peak and increased the number of documented infections. The proportion of documented infections changed from 23% (95% CI, 20% to 26%) to 37% (95% CI, 33% to 41%) when the detection kits were released after January 26, and later up to 73% (95% CI, 64% to 80%) after the diagnostic criteria were improved.


