# ent

id: cord-273531-q9ah287w
type: ORG
entity:
  National Health Commission Ministry of Human Resources and Social Security Ministry of Finance Measures


id: cord-351880-iqr419fp
type: DISEASE
entity:
  coronavirus 2019 nCoV has spread internationally since the initial report of cases by Wuhan Municipal Health Commission China


id: cord-283891-m36un1y2
type: WORK_OF_ART
entity:
  The Lancet Geographical Detectors Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region China


id: cord-351659-ujbxsus4
type: WORK_OF_ART
entity:
  Principles and Practice National Health and Family Planning Commission of China Report on China s mi grant population development


id: cord-327721-y39751g4
type: ORG
entity:
  the Past Possible Urgent Prevention and Treatment Options for Severe Acute Respiratory Infections Caused


id: cord-352108-py93yvjy
type: ORG
entity:
  U S Collaborative Project for Neural Tube Defect Prevention National Neural Tube Defects Prevention Program


id: cord-286334-d9v5xtx7
type: DISEASE
entity:
  influenza A H1N1 pdm09 Only one case had a history of influenza vaccination Various on referral ECMO related parameters were extracted as well as contemporaneous laboratory results These were statistically compared between patients who died n 8


id: cord-286334-d9v5xtx7
type: DISEASE
entity:
  influenza A H1N1 pdm09 pandemic with or without the use of ECMO In one study from Australia where ECMO was used of 68 patients with confirmed influenza A 53 A H1N1 pdm09 8 un subtyped infection


# bib

id: cord-009688-kjx6cvzh
author: Zhao, Ze-Yu
date: 2020-04-17
txt: ./txt/cord-009688-kjx6cvzh.txt
cache: ./cache/cord-009688-kjx6cvzh.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162736/
doi: 10.1186/s40249-020-00654-x
summary:
  title: Relative transmissibility of shigellosis among male and female individuals: a modeling study in Hubei Province, China Owing to the different incidences in males and females, this study aims to analyze the features involved in the transmission of shigellosis among male (subscript m) and female (subscript f) individuals using a newly developed sex-based model. METHODS: The data of reported shigellosis cases were collected from the China Information System for Disease Control and Prevention in Hubei Province from 2005 to 2017. With the aim of exploring the transmission features in different gender and age groups, the SEIAR model was adopted to fit the data of shigellosis cases reported from 2005 to 2017 in Hubei Province, China. A mathematical study was implemented using a sexand age-based model to analyze the transmission characteristics of reported shigellosis cases in Hubei Province, China, from 2005 to 2017.

title:
  Relative transmissibility of shigellosis among male and female individuals: a modeling study in Hubei Province, China

abstract:
  BACKGROUND: Developing countries exhibit a high disease burden from shigellosis. Owing to the different incidences in males and females, this study aims to analyze the features involved in the transmission of shigellosis among male (subscript m) and female (subscript f) individuals using a newly developed sex-based model. METHODS: The data of reported shigellosis cases were collected from the China Information System for Disease Control and Prevention in Hubei Province from 2005 to 2017. A sex-based Susceptible–Exposed–Infectious/Asymptomatic–Recovered (SEIAR) model was applied to explore the dataset, and a sex-age-based SEIAR model was applied in 2010 to explore the sex- and age-specific transmissions. RESULTS: From 2005 to 2017, 130 770 shigellosis cases (including 73 981 male and 56 789 female cases) were reported in Hubei Province. The SEIAR model exhibited a significant fitting effect with the shigellosis data (P < 0.001). The median values of the shigellosis transmission were 2.3225 × 10(8) for SAR(mm) (secondary attack rate from male to male), 2.5729 × 10(8) for SAR(mf), 2.7630 × 10(-8) for SAR(fm), and 2.1061 × 10(-8) for SAR(ff). The top five mean values of the transmission relative rate in 2010 (where the subscript 1 was defined as male and age ≤ 5 years, 2 was male and age 6 to 59 years, 3 was male and age ≥ 60 years, 4 was female and age ≤ 5 years, 5 was female and age 6 to 59 years, and 6 was male and age ≥ 60 years) were 5.76 × 10(-8) for β(61), 5.32 × 10(-8) for β(31), 4.01 × 10(-8) for β(34), 7.52 × 10(-9) for β(62), and 6.04 × 10(-9) for β(64). CONCLUSIONS: The transmissibility of shigellosis differed among male and female individuals. The transmissibility between the genders was higher than that within the genders, particularly female-to-male transmission. The most important route in children (age ≤ 5 years) was transmission from the elderly (age ≥ 60 years). Therefore, the greatest interventions should be applied in females and the elderly.


id: cord-035307-r74ovkbd
author: Liu, Shuchang
date: 2020-11-11
txt: ./txt/cord-035307-r74ovkbd.txt
cache: ./cache/cord-035307-r74ovkbd.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657065/
doi: 10.1007/s10745-020-00199-5
summary:
  Our study results indicate over the period between the SARS epidemic to the outbreak of the COVID-19 pandemic, attitudes towards the consumption of wildlife in China have changed significantly. Therefore, our aim in this study was to determine changes in attitudes towards wildlife consumption in Chinese adults in relation to the SARS and COVID-19 outbreaks with a particular focus on Hubei Province.

title:
  Attitudes towards Wildlife Consumption inside and outside Hubei Province, China, in Relation to the SARS and COVID-19 Outbreaks

abstract:
  We designed a self-administered 20-item questionnaire to determine changes in attitudes towards wildlife consumption in Chinese adults during the SARS epidemic in 2002–2003 and on-going COVID-19 pandemic that was first identified in December 2019. A total of 348 adults (177 males and 171 females) with a mean age of 29.4 ± 8.5 years participated, the majority (66.7%) from Hubei. The percentages of participants who had eaten wildlife significantly decreased from 27.0% during SARS to 17.8% during COVID-19 (P = 0.032). The most common reason participants provided for consuming wildlife was to try something novel (64.9% during SARS and 54.8% during COVID-19). More than half of participants (≥53.5%) reported that they had stopped eating wildlife meat because most species of wildlife are legally protected. Our study results indicate over the period between the SARS epidemic to the outbreak of the COVID-19 pandemic, attitudes towards the consumption of wildlife in China have changed significantly.


id: cord-265680-ztk6l2n2
author: Deng, J
date: 2020-08-31
txt: ./txt/cord-265680-ztk6l2n2.txt
cache: ./cache/cord-265680-ztk6l2n2.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32866270/
doi: 10.1093/qjmed/hcaa262
abstract: nan
summary:
  title: High COVID-19 mortality in the UK: Lessons to be learnt from Hubei Province – Are under-detected "silent hypoxia" and subsequently low admission rate to blame? With centralised isolation and timely treatment to prevent transmission and deterioration of the infection, and with occasional transfers of patients with worsening symptoms to ICU, this drastically decreased the mortality over the entire epidemic in Hubei [ Table 1 ]. As a result, no new cases were found, with only https://mc.manuscriptcentral.com/qjm the 68,135 confirmed cases in Table 1 is a highly reliable reflection of the epidemic in Hubei after the initial chaotic statistics in January. For example, by the end of July, New York had most Covid deaths in the US with 32,683 fatalities, yet a "Nightingale" hospital costing $52 million treated only 79 virus patients. New diagnosis and treatment scheme for novel coronavirus infected pneumonia

title:
  High COVID-19 mortality in the UK: Lessons to be learnt from Hubei Province – Are under-detected “silent hypoxia” and subsequently low admission rate to blame?


id: cord-271980-8x5g8r7c
title: Ambient nitrogen dioxide pollution and spread ability of COVID-19 in Chinese cities
author: Yao, Ye
date: 2020-09-30
txt: ./txt/cord-271980-8x5g8r7c.txt
cache: ./cache/cord-271980-8x5g8r7c.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1016/j.ecoenv.2020.111421
doi: 10.1016/j.ecoenv.2020.111421
summary:
  When examining the correlation between NO 2 and R 0 of COVID-19, we estimated the associations of NO 2 concentration with R 0 both inside and outside Hubei province (r & p) in the same period by using multiple linear regression models after controlling for temperature and relative humidity (as covariates in the regression model) separately. We also examined the corresponding temporal associations between NO 2 and R 0 of COVID-19 across the different cities inside and outside Hubei Province using multiple linear regression models after controlling for temperature and relative humidity separately. The cross-sectional analysis indicates that, after adjustment for temperature and relative humidity, R 0 was positively associated with NO 2 concentration at city level (meta χ 2 =10.18, J o u r n a l P r e -p r o o f p=0.037) (Figure 3) .

abstract:
  This study aims to explore the relationship between ambient NO(2) levels and the transmission ability (basic reproductive number, R(0)) of COVID-19 in 63 Chinese cities. After adjustment for temperature and relative humidity, R(0) was positively associated with NO(2) concentration at city level. The temporal analysis within Hubei province indicated that all the 11 Hubei cities (except Xianning City) had significant positive correlations between NO(2) concentration (with 12-day time lag) and R(0) (r>0.51, p<0.005). Since the association between ambient NO(2) and R(0) indicated NO(2) may increase underlying risk of infection in the transmission process of COVID-19. In addition, NO(2) is also an indicator of traffic-related air pollution, the association between NO(2) and COVID-19’s spread ability suggest that reduced population movement may have reduced the spread of the SARS-CoV-2.


id: cord-273531-q9ah287w
title: Characteristics of COVID-19 Near China''s Epidemic Center
author: Li, Yang
date: 2020-06-26
txt: ./txt/cord-273531-q9ah287w.txt
cache: ./cache/cord-273531-q9ah287w.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32599100/
doi: 10.1016/j.ajic.2020.06.191
summary:
  Background: This study described and analyzed the age, gender, infection sources, and timing characteristics of the 416 confirmed cases in two cities near the center of China''s COVID-19 outbreak. Methods: This study used publicly available data to examine gender, age, source of infection, date returned from Hubei, date of disease onset, date of first medical visit, date of final diagnosis, and date of recovery of COVID-19 cases. Results: Public-use data revealed similar risks of infection by age and that the numbers of new and final diagnoses of confirmed cases first increased, peaked at about two weeks, and then gradually decreased. The first novel coronavirus pneumonia (COVID19) case was identified in Wuhan, Hubei Province, China, on December 12, 2019, after which the disease gradually spread. The variables used in the analysis were: gender, age, source of infection, date returned from Hubei, date of disease onset, date of first medical visit, date of final diagnosis, and date of recovery.

abstract:
  Background: This study described and analyzed the age, gender, infection sources, and timing characteristics of the 416 confirmed cases in two cities near the center of China's COVID-19 outbreak. Methods: This study used publicly available data to examine gender, age, source of infection, date returned from Hubei, date of disease onset, date of first medical visit, date of final diagnosis, and date of recovery of COVID-19 cases. Results: Public-use data revealed similar risks of infection by age and that the numbers of new and final diagnoses of confirmed cases first increased, peaked at about two weeks, and then gradually decreased. The main sources of infection were firsthand or secondhand exposure in Hubei Province and contact with confirmed cases, which mostly involved contact with infected household members. The mean periods from disease onset to first medical visit, first visit to final diagnosis, and final diagnosis to recovery were 4.44, 3.18, and 13.42 days, respectively. Conclusions: The results suggest that the measures taken to control the rate of infection were effective. Prevention and control efforts should respond as quickly as possible, isolate and control activities of individuals leaving infected areas, and restrict household contact transmission.


id: cord-283891-m36un1y2
author: Hu, Bisong
date: 2020-05-17
txt: ./txt/cord-283891-m36un1y2.txt
cache: ./cache/cord-283891-m36un1y2.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1016/j.ijid.2020.05.048
doi: 10.1016/j.ijid.2020.05.048
summary:
  Methods We used spatiotemporal data of COVID-19 cases in mainland China and two categories of location-based service (LBS) data of mobile devices from the primary and secondary epidemic sources to calculate Pearson correlation coefficient,r, and spatial stratified heterogeneity, q, statistics. Here, using location-based service (LBS) data of mobile devices, we analyzed the spatiotemporal association of the confirmed COVID-19 cases and human movements from the sources of the epidemic outbreak, and revealed the first, second and potential third generation spreads of the COVID-19 epidemic in mainland China. Based on the above datasets of COVID-19 cases in mainland China and two categories of location-based service data of mobile devices from the epidemic sources, we calculated their Pearson correlation coefficient, r, and spatial stratified heterogeneity (SSH), q, statistics.

title:
  First, second and potential third generation spreads of the COVID-19 epidemic in mainland China: an early exploratory study incorporating location-based service data of mobile devices

abstract:
  Abstract Objectives The outbreak of atypical pneumonia caused by the novel coronavirus (COVID-19) has currently become a global concern. The generations of the epidemic spread are not well known, yet these are critical parameters to facilitate an understanding of the epidemic. A seafood wholesale market and Wuhan city, China, were recognized as the primary and secondary epidemic sources. Human movements nationwide from the two epidemic sources revealed the characteristics of the first-generation and second-generation spreads of the COVID-19 epidemic, as well as the potential third-generation spread. Methods We used spatiotemporal data of COVID-19 cases in mainland China and two categories of location-based service (LBS) data of mobile devices from the primary and secondary epidemic sources to calculate Pearson correlation coefficient,r, and spatial stratified heterogeneity, q, statistics. Results Two categories of device trajectories had generally significant correlations and determinant powers of the epidemic spread. Bothr and q statistics decreased with distance from the epidemic sources and their associations changed with time. At the beginning of the epidemic, the mixed first-generation and second-generation spreads appeared in most cities with confirmed cases. They strongly interacted to enhance the epidemic in Hubei province and the trend was also significant in the provinces adjacent to Hubei. The third-generation spread started in Wuhan from January 17 to 20, 2020, and in Hubei from January 23 to 24. No obvious third-generation spread was detected outside Hubei. Conclusions The findings provide important foundations to quantify the effect of human movement on epidemic spread and inform ongoing control strategies. The spatiotemporal association between the epidemic spread and human movements from the primary and secondary epidemic sources indicates a transfer from second to third generations of the infection. Urgent control measures include preventing the potential third-generation spread in mainland China, eliminating it in Hubei, and reducing the interaction influence of first-generation and second-generation spreads.


id: cord-285965-mar8zt2t
author: Su, Liang
date: 2020-03-25
txt: ./txt/cord-285965-mar8zt2t.txt
cache: ./cache/cord-285965-mar8zt2t.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1080/22221751.2020.1744483
doi: 10.1080/22221751.2020.1744483
summary:
  This study aims to analyze the different clinical characteristics between children and their families infected with severe acute respiratory syndrome coronavirus 2. Here, we report the clinical manifestations, laboratory test results, imaging characteristics, and treatment regimen of nine SARS-CoV-2 infected children and their families in Jinan, Shandong province to increase awareness of this disease, especially in children. A retrospective review was conducted of the clinical, lab tests, and radiologic findings for nine children and their families admitted to the Jinan Infectious Diseases Hospital identified to be nucleic acid-positive for SARS-CoV-2 from 24 January 2020 to 24 February 2020. All the patients were recorded with basic information and epidemiological histories [4] including (1) History of travel or residence in Wuhan and surrounding areas or other reported cases within 14 days of onset; (2) History of contact with new coronavirus infection (nucleic acid-positive) 14 days before onset; (3) history of contact with patients with fever or respiratory symptoms from Wuhan and surrounding areas, or from communities with case reports within 14 days before onset; (4) Cluster onset, along with disease condition changes.

title:
  The different clinical characteristics of corona virus disease cases between children and their families in China – the character of children with COVID-19

abstract:
  This study aims to analyze the different clinical characteristics between children and their families infected with severe acute respiratory syndrome coronavirus 2. Clinical data from nine children and their 14 families were collected, including general status, clinical, laboratory test, and imaging characteristics. All the children were detected positive result after their families onset. Three children had fever (22.2%) or cough (11.2%) symptoms and six (66.7%) children had no symptom. Among the 14 adult patients, the major symptoms included fever (57.1%), cough (35.7%), chest tightness/pain (21.4%), fatigue (21.4%) and sore throat (7.1%). Nearly 70% of the patients had normal (71.4%) or decreased (28.6%) white blood cell counts, and 50% (7/14) had lymphocytopenia. There were 10 adults (71.4%) showed abnormal imaging. The main manifestations were pulmonary consolidation (70%), nodular shadow (50%), and ground glass opacity (50%). Five discharged children were admitted again because their stool showed positive result in SARS-CoV-2 PCR. COVID-19 in children is mainly caused by family transmission, and their symptoms are mild and prognosis is better than adult. However, their PCR result in stool showed longer time than their families. Because of the mild or asymptomatic clinical process, it is difficult to recognize early for pediatrician and public health staff.


id: cord-286334-d9v5xtx7
author: Li, Rui
date: 2020-04-30
txt: ./txt/cord-286334-d9v5xtx7.txt
cache: ./cache/cord-286334-d9v5xtx7.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32092392/
doi: 10.1016/j.jinf.2020.02.013
abstract: nan
summary:
  More detailed monitoring on how these physiological parameters change over time (perhaps including more complex cytokine studies), in these severely ill, influenza A(H1N1)pdm09-infected patients admitted to ICU-ECMO units, may eventually yield data to improve their management and clinical outcomes. 5 In the current study, we characterized a new HCV subtypes among chronic hepatitis C patients in Yunnan, China, initially designated as 6xi, further analyzed its evolutionary history and investigated its baseline RAS by next generation sequencing (NGS) method. The samples met the following inclusion criteria: (1) hepatitis C antibody-positive for 6 months with normal serum alanine aminotransferase (ALT) levels; (2) subject was residing in Yunnan province and was over 18 years old; (3) complete demographic information and clinical data were available; (4) consented to the use of patient information in studies on HCV epidemics; and (5) were treatment-naïve during sampling.

title:
  Analysis of angiotensin-converting enzyme 2 (ACE2) from different species sheds some light on cross-species receptor usage of a novel coronavirus 2019-nCoV


id: cord-291750-4s93wniq
title: Global COVID-19 fatality analysis reveals Hubei-like countries potentially with severe outbreaks
author: Lv, Boyan
date: 2020-04-14
txt: ./txt/cord-291750-4s93wniq.txt
cache: ./cache/cord-291750-4s93wniq.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32302605/
doi: 10.1016/j.jinf.2020.03.029
summary:
  The outbreak of 2019 novel coronavirus diseases (COVID-19) is ongoing in China, 1 but appears to reach late stage and also just starts to devastate other countries. We collected data of the officially released cumulative numbers of confirmed cases and deaths (from 23 January to 13 March 2020) with respect to mainland China, epicenter of the outbreak (i.e., Hubei Province and Wuhan City), outside Hubei (in China) and outside Wuhan (in Hubei), as well as to typical countries reported with a substantial number of deaths including South Korea, Japan, Iran, Italy, USA, France and Spain ( Fig. 1 ) . In view of the detailed P values among all pairs (Table S1 ), we suppose the ranking for the severity of COVID-19 outbreaks in different countries/regions in terms of CFRs as follows: Iran > Wuhan > Hubei ≈USA ≈Italy > outside Wuhan ≈Spain ≈Japan ≈France > South Korea ≈outside Hubei.

abstract:
  • CFR in Iran in the early stage of the outbreak is highest among all the countries. • CFRs in the USA and Italy are similar to Hubei Province in the early stage. • CFRs in South Korea are similar to outside Hubei, indicating less severity. • Our findings highlight the severity of outbreaks globally, particular in the USA.


id: cord-292537-9ra4r6v6
title: Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models
author: Liu, Fenglin
date: 2020-08-27
txt: ./txt/cord-292537-9ra4r6v6.txt
cache: ./cache/cord-292537-9ra4r6v6.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32853285/
doi: 10.1371/journal.pone.0238280
summary:
  For the study of infectious diseases like COVID-19, SARS, and Ebola, most of the literature used descriptive research or model methods to assess indicators and analyze the effect of interventions, such as combining migration data to evaluate the potential infection rate [18, 19] , understanding the impact of factors like environmental temperature and vaccines that might be potentially linked to the diseases [20, 21] , using basic and time-varying reproduction number (R 0 & R t ) to estimate changeable transmission dynamics of epidemic conditions [22] [23] [24] [25] [26] [27] , calculating and predicting the fatal risk to display any stage of outbreak [28] [29] [30] , or providing suggestions and interventions from risk management and other related aspects based on the results of modeling tools or historical lessons [31] [32] [33] [34] [35] [36] [37] [38] [39] .

abstract:
  In December 2019, the novel coronavirus pneumonia (COVID-19) occurred in Wuhan, Hubei Province, China. The epidemic quickly broke out and spread throughout the country. Now it becomes a pandemic that affects the whole world. In this study, three models were used to fit and predict the epidemic situation in China: a modified SEIRD (Susceptible-Exposed-Infected-Recovered-Dead) dynamic model, a neural network method LSTM (Long Short-Term Memory), and a GWR (Geographically Weighted Regression) model reflecting spatial heterogeneity. Overall, all the three models performed well with great accuracy. The dynamic SEIRD prediction APE (absolute percent error) of China had been ≤ 1.0% since Mid-February. The LSTM model showed comparable accuracy. The GWR model took into account the influence of geographical differences, with R(2) = 99.98% in fitting and 97.95% in prediction. Wilcoxon test showed that none of the three models outperformed the other two at the significance level of 0.05. The parametric analysis of the infectious rate and recovery rate demonstrated that China's national policies had effectively slowed down the spread of the epidemic. Furthermore, the models in this study provided a wide range of implications for other countries to predict the short-term and long-term trend of COVID-19, and to evaluate the intensity and effect of their interventions.


id: cord-296669-1md8j11e
author: Li, Xin
date: 2020-08-04
txt: ./txt/cord-296669-1md8j11e.txt
cache: ./cache/cord-296669-1md8j11e.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32759877/
doi: 10.3390/ijerph17155627
summary:
  The degrees of the depression, anxiety, insomnia, and distress symptoms of our participants were assessed using the Chinese versions of the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), the Insomnia Severity Index-7 (ISI-7), and the revised 7-item Impact of Event Scale (IES-7) scales, respectively, which found that the prevalence rates of depression, anxiety, insomnia, and distress caused by COVID-19 were 45.5%, 49.5%, 30.9%, and 68.1%, respectively. Mental disorders, including depression, anxiety, insomnia, and distress, caused by COVID-19 were assessed in our study by Chinese versions of validated measurement tools [24] [25] [26] [27] : the Patient Health Questionnaire-9 (PHQ-9; the total score ranged from 0 to 27) [24] , the Generalized Anxiety Disorder-7 (GAD-7; the total score ranged from 0 to 21) [25] , the Insomnia Severity Index-7 (ISI-7; the total score ranged from 0 to 28) [26] , and the revised 7-item Impact of Event Scale (IES-7; the total score ranged from 0 to 28) [27] .

title:
  Factors Associated with Mental Health Results among Workers with Income Losses Exposed to COVID-19 in China

abstract:
  The outbreak and worldwide spread of COVID-19 has resulted in a high prevalence of mental health problems in China and other countries. This was a cross-sectional study conducted using an online survey and face-to-face interviews to assess mental health problems and the associated factors among Chinese citizens with income losses exposed to COVID-19. The degrees of the depression, anxiety, insomnia, and distress symptoms of our participants were assessed using the Chinese versions of the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), the Insomnia Severity Index-7 (ISI-7), and the revised 7-item Impact of Event Scale (IES-7) scales, respectively, which found that the prevalence rates of depression, anxiety, insomnia, and distress caused by COVID-19 were 45.5%, 49.5%, 30.9%, and 68.1%, respectively. Multivariable logistic regression analysis was performed to identify factors associated with mental health outcomes among workers with income losses during COVID-19. Participants working in Hubei province with heavy income losses, especially pregnant women, were found to have a high risk of developing unfavorable mental health symptoms and may need psychological support or interventions.


id: cord-309032-idjdzs97
author: Zhou, Feng
date: 2020-10-09
txt: ./txt/cord-309032-idjdzs97.txt
cache: ./cache/cord-309032-idjdzs97.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/33045428/
doi: 10.1016/j.ijid.2020.09.1487
summary:
  Several studies conducted in China, Italy and the United States have reported some epidemiological characteristics of COVID-19 in the initial phase (Grasselli et al., 2020 , Liang et al., 2020 , Price-Haywood et al., 2020 , Richardson et al., 2020 , Wu and McGoogan, 2020 , However, there is still a lack of research on the space-time characteristics in the populations of imported and local cases respectively which is of great significance. In this study, we described the spatiotemporal distribution of the COVID-19 in eighteen provinces of China (outside Hubei province) and investigated the epidemiological characteristics in the population of imported cases and local cases, from the beginning of this epidemic until it was under good control. We further assessed the critical influence factors associated with time interval from symptom onset to hospitalization (TOH) and length of hospital stay (LOS), including demographic and temporal and spatial characteristics.

title:
  Epidemiological Characteristics and Factors Associated with Critical Time Intervals of COVID-19 in Eighteen Provinces, China: A Retrospective Study

abstract:
  Background As COVID-19 ravages continuously around the world, more information on the epidemiological characteristics and factors associated with time interval between critical events is needed to contain the pandemic and to assess the effectiveness of interventions. Methods Individual information on confirmed cases from January 21 to March 2 was collected from provincial or municipal health commissions. We identified the difference between imported and local cases in the epidemiological characteristics. Two models were established to estimate the factors associated with time interval from symptom onset to hospitalization (TOH) and length of hospital stay (LOS) respectively. Results Among 7,042 cases, 3392 (48.17%) were local cases and 3304 (46.92%) were imported cases. Since the first intervention was adopted in Hubei on January 23, the daily reported imported cases reached a peak on January 28 and gradually decreased since then. Imported cases were on average younger (41 vs. 48), and had more male (58.66% vs. 47.53%) compared to local cases. Furthermore, imported cases had more contacts with other confirmed cases (2.80 ± 2.33 vs. 2.17 ± 2.10), which were mainly within family members (2.26 ± 2.18 vs. 1.57 ± 2.06). The TOH and LOS were 2.67 ± 3.69 and 18.96 ± 7.63 days respectively, and a longer TOH was observed in elderly living in the provincial capital cities that were higher migration intensity with Hubei. Conclusions Measures to restrict traffic can effectively reduce imported spread. However, household transmission is still not controlled, particularly for the infection of imported cases to elderly women. It is still essential to surveil and educate patients about the early admission or isolation.


id: cord-313675-fsjze3t2
title: Modeling COVID-19: Forecasting and analyzing the dynamics of the outbreak in Hubei and Turkey
author: Aslan, ibrahim Halil
date: 2020-04-15
txt: ./txt/cord-313675-fsjze3t2.txt
cache: ./cache/cord-313675-fsjze3t2.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.04.11.20061952
doi: 10.1101/2020.04.11.20061952
summary:
  We provide forecasts for the peak of the outbreak and the total number of cases/deaths in Turkey, for varying levels of social distancing, quarantine, and COVID-19 testing. In addition, we also provide 15-day forecasts of the fatality rate of the outbreak, the number of cases, and the number of deaths depending on the data (Chinese physicians, 2020; Coronavirus COVID-19 Global Cases by Johns Hopkins CSSE, 2020; World Health Organization, 2020b) and outputs of our SEIQR model. The rate of reported cases i q denotes the number of individuals who transition from the infected class I to the reported class I q per day; it is also directly related to the daily number of COVID-19 tests carried out during the outbreak. In this part, we estimate the parameters in the system (1), so we fit our model with the daily reported cumulative number of cases and deaths, which are provided by (World Health Organization, 2020b) and (Chinese physicians, 2020).

abstract:
  As the pandemic of Coronavirus Disease 2019 (COVID-19) rages throughout the world, accurate modeling of the dynamics thereof is essential. However, since the availability and quality of data varies dramatically from region to region, accurate modeling directly from a global perspective is difficult, if not altogether impossible. Nevertheless, via local data collected by certain regions, it is possible to develop accurate local prediction tools, which may be coupled to develop global models. In this study, we analyze the dynamics of local outbreaks of COVID-19 via a coupled system of ordinary differential equations (ODEs). Utilizing the large amount of data available from the ebbing outbreak in Hubei, China as a testbed, we estimate the basic reproductive number, R0 of COVID-19 and predict the total cases, total deaths, and other features of the Hubei outbreak with a high level of accuracy. Through numerical experiments, we observe the effects of quarantine, social distancing, and COVID-19 testing on the dynamics of the outbreak. Using knowledge gleaned from the Hubei outbreak, we apply our model to analyze the dynamics of outbreak in Turkey. We provide forecasts for the peak of the outbreak and the total number of cases/deaths in Turkey, for varying levels of social distancing, quarantine, and COVID-19 testing.


id: cord-313700-enivzp1f
author: Lio, Chon Fu
date: 2020-06-19
txt: ./txt/cord-313700-enivzp1f.txt
cache: ./cache/cord-313700-enivzp1f.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.7717/peerj.9428
doi: 10.7717/peerj.9428
summary:
  title: The common personal behavior and preventive measures among 42 uninfected travelers from the Hubei province, China during COVID-19 outbreak: a cross-sectional survey in Macao SAR, China A further survey of comparison of personal preventive measures before and during disease outbreak showed increased alert and practice of personal protection and hygiene during the spread (Table 3) , such as wearing a mask when outdoor (16.7% and 95.2%, P < 0.001), wearing a mask every time when contact or talk with people (10% and 95%, P < 0.001), often wash hands with soap/liquid soap (85.7% and 100%, P = 0.031), use of alcohol-based hand sanitizers or disinfected wipes as substitute if handwashing facility not available (71.4% and 95.2%, P = 0.006), cleaning clothes and personal belongings immediately once get back home (35.7% and 78.6%, P < 0.001), cleaning mobile phone regularly (43.9% and 65.9%, P = 0.012). Good personal hygiene and adequate preventive measures such as less gathering, frequent handwashing, in addition to wearing a mask outdoor, were common grounds among 42 uninfected participants during the stay in Hubei province under COVID-19 outbreak.

title:
  The common personal behavior and preventive measures among 42 uninfected travelers from the Hubei province, China during COVID-19 outbreak: a cross-sectional survey in Macao SAR, China

abstract:
  BACKGROUND: The novel coronavirus diseases 2019 (COVID-19) caused over 1.7 million confirmed cases and cumulative mortality up to over 110,000 deaths worldwide as of 14 April 2020. A total of 57 Macao citizens were obligated to stay in Hubei province, China, where the highest COVID-19 prevalence was noted in the country and a “lockdown” policy was implemented for outbreak control for more than one month. They were escorted from Wuhan City to Macao via a chartered airplane organized by Macao SAR government and received quarantine for 14 days with none of the individual being diagnosed with COVID-19 by serial RNA tests from the nasopharyngeal specimens and sera antibodies. It was crucial to identify common characteristics among these 57 uninfected individuals. METHODS: A questionnaire survey was conducted to extract information such as behavior, change of habits and preventive measures. RESULTS: A total of 42 effective questionnaires were analyzed after exclusion of 14 infants and children with age under fifteen as ineligible for the survey and missing of one questionnaire, with a response rate of 97.7% (42 out of 43). The proportion of female composed more than 70% of this group of returners. The main reason for visiting Hubei in 88.1% of respondents was to visit relatives. Over 88% of respondents did not participate in high-risk activities due to mobility restriction. All (100%) denied contact with suspected or confirmed COVID-19 cases. Comparison of personal hygiene habits before and during disease outbreak showed a significant increase in practice including wearing a mask when outdoor (16.7% and 95.2%, P < 0.001) and often wash hands with soap or liquid soap (85.7% and 100%, P = 0.031).


id: cord-317465-ucwuptgg
title: Human Mobility Restrictions and the Spread of the Novel Coronavirus (2019-nCoV) in China
author: FANG, H.
date: 2020-03-26
txt: ./txt/cord-317465-ucwuptgg.txt
cache: ./cache/cord-317465-ucwuptgg.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.03.24.20042424
doi: 10.1101/2020.03.24.20042424
summary:
  In this paper, we exploit the exogenous variations in human mobility created by lockdowns of Chinese cities during the outbreak of the Novel Coronavirus (2019-nCoV), and utilize a variety of high-quality data sets, to study the effectiveness of an unprecedented cordon sanitaire of the epicenter of COVID-19, and provide a comprehensive analysis on the role of human mobility restrictions in the delaying and the halting of the spread of the COVID-19 pandemic. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities'' new infection cases ( Figure 4 ). In this paper, we quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus, and estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities'' new infection cases.

abstract:
  We quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ a set of difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. We find that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities' new infection cases. We find, using simulations with these estimates, that the lockdown of the city of Wuhan on January 23, 2020 contributed significantly to reducing the total infection cases outside of Wuhan, even with the social distancing measures later imposed by other cities. We find that the COVID-19 cases would be 64.81% higher in the 347 Chinese cities outside Hubei province, and 52.64% higher in the 16 non-Wuhan cities inside Hubei, in the counterfactual world in which the city of Wuhan were not locked down from January 23, 2020. We also find that there were substantial undocumented infection cases in the early days of the 2019-nCoV outbreak in Wuhan and other cities of Hubei province, but over time, the gap between the officially reported cases and our estimated "actual" cases narrows significantly. We also find evidence that enhanced social distancing policies in the 63 Chinese cities outside Hubei province are effective in reducing the impact of population inflows from the epicenter cities in Hubei province on the spread of 2019-nCoV virus in the destination cities elsewhere.


id: cord-321727-xyowl659
author: Wang, Lishi
date: 2020-07-20
txt: ./txt/cord-321727-xyowl659.txt
cache: ./cache/cord-321727-xyowl659.txt
extension: .txt
mime: text/plain
url: https://api.elsevier.com/content/article/pii/S0048969720319070
doi: 10.1016/j.scitotenv.2020.138394
summary:
  We report a new methodology, the Patient Information Based Algorithm (PIBA), for estimating the death rate of a disease in real-time using publicly available data collected during an outbreak. PIBA estimated the death rate based on data of the patients in Wuhan and then in other cities throughout China. The death rates based on PIBA were used to predict the daily numbers of deaths since the week of February 25, 2020, in China overall, Hubei province, Wuhan city, and the rest of the country except Hubei province. The PIBA uses patient data in real-time to build a model that estimates and predicts death rates for the near future. Based on the days between confirmation of COVID-19 and the days of death in the hospital, calculated from Wuhan, as mentioned in method 1 and information from the whole country and Hubei Province, we tested the number of days from diagnosis to death, that most likely reflects the actual death rate.

title:
  Real-time estimation and prediction of mortality caused by COVID-19 with patient information based algorithm

abstract:
  The global COVID-19 outbreak is worrisome both for its high rate of spread, and the high case fatality rate reported by early studies and now in Italy. We report a new methodology, the Patient Information Based Algorithm (PIBA), for estimating the death rate of a disease in real-time using publicly available data collected during an outbreak. PIBA estimated the death rate based on data of the patients in Wuhan and then in other cities throughout China. The estimated days from hospital admission to death was 13 (standard deviation (SD), 6 days). The death rates based on PIBA were used to predict the daily numbers of deaths since the week of February 25, 2020, in China overall, Hubei province, Wuhan city, and the rest of the country except Hubei province. The death rate of COVID-19 ranges from 0.75% to 3% and may decrease in the future. The results showed that the real death numbers had fallen into the predicted ranges. In addition, using the preliminary data from China, the PIBA method was successfully used to estimate the death rate and predict the death numbers of the Korean population. In conclusion, PIBA can be used to efficiently estimate the death rate of a new infectious disease in real-time and to predict future deaths. The spread of 2019-nCoV and its case fatality rate may vary in regions with different climates and temperatures from Hubei and Wuhan. PIBA model can be built based on known information of early patients in different countries.


id: cord-325012-yjay3t38
title: Distribution of the COVID-19 epidemic and correlation with population emigration from Wuhan, China
author: Chen, Ze-Liang
date: 2020-02-28
txt: ./txt/cord-325012-yjay3t38.txt
cache: ./cache/cord-325012-yjay3t38.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32118644/
doi: 10.1097/cm9.0000000000000782
summary:
  Data on population migration from Wuhan city and Hubei province were extracted from Baidu Qianxi, and their correlation with the number of cases was analyzed. The relative risk according to time increased steadily from January 20 onwards and the upward trend continued as of January 30 [ Figure 2C ], indicating that the number of cases nationwide is on the rise. From January 1 to 23, 2020, the population that migrated out of Wuhan city and Hubei province increased steadily, peaking on January 21 and 22 [ Figure 4A ]. To analyze the correlation between the number of cases and the emigration in Wuhan city and Hubei province, population migration data were collected from Baidu Qianxi. The correlation coefficient between the provincial number of cases and emigration from Wuhan increased to 0.943, with the highest coefficient of 0.996 observed between Wuhan and other cities of Hubei provinces [ Figure 4E and 4F; Supplementary Tables 3 and 4 , http://links.lww.com/ CM9/A210].

abstract:
  BACKGROUND: The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks. METHODS: The official case report on the COVID-19 epidemic was collected as of January 30, 2020. Time and location information on COVID-19 cases was extracted and analyzed using ArcGIS and WinBUGS software. Data on population migration from Wuhan city and Hubei province were extracted from Baidu Qianxi, and their correlation with the number of cases was analyzed. RESULTS: The COVID-19 confirmed and death cases in Hubei province accounted for 59.91% (5806/9692) and 95.77% (204/213) of the total cases in China, respectively. Hot spot provinces included Sichuan and Yunnan, which are adjacent to Hubei. The time risk of Hubei province on the following day was 1.960 times that on the previous day. The number of cases in some cities was relatively low, but the time risk appeared to be continuously rising. The correlation coefficient between the provincial number of cases and emigration from Wuhan was up to 0.943. The lockdown of 17 cities in Hubei province and the implementation of nationwide control measures efficiently prevented an exponential growth in the number of cases. CONCLUSIONS: The population that emigrated from Wuhan was the main infection source in other cities and provinces. Some cities with a low number of cases showed a rapid increase in case load. Owing to the upcoming Spring Festival return wave, understanding the risk trends in different regions is crucial to ensure preparedness at both the individual and organization levels and to prevent new outbreaks.


id: cord-326599-n0vmb946
author: Leung, Char
date: 2020-03-18
txt: ./txt/cord-326599-n0vmb946.txt
cache: ./cache/cord-326599-n0vmb946.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32183920/
doi: 10.1017/ice.2020.81
summary:
  title: The difference in the incubation period of 2019 novel coronavirus (SARS-CoV-2) infection between travelers to Hubei and non-travelers: The need of a longer quarantine period Data collected from the individual cases reported by the media were used to estimate the distribution of the incubation period of travelers to Hubei and non-travelers. Against this background, the present work estimated the distribution of incubation periods of patients infected in and outside Hubei. The very first observation of the incubation period of SARS-CoV-2 came from the National Health Such difference might be due to the difference in infectious dose since travelers to Hubei might be exposed to different sources of infection multiple times during their stay in Hubei. Incubation period of 2019 novel coronavirus (COVID-19) infections among travellers from Wuhan

title:
  The difference in the incubation period of 2019 novel coronavirus (SARS-CoV-2) infection between travelers to Hubei and non-travelers: The need of a longer quarantine period

abstract:
  Data collected from the individual cases reported by the media were used to estimate the distribution of the incubation period of travelers to Hubei and non-travelers. Upon the finding of longer and more volatile incubation period in travelers, the duration of quarantine should be extended to three weeks.


id: cord-327096-m87tapjp
title: Epidemic analysis of COVID-19 in China by dynamical modeling
author: Peng, Liangrong
date: 2020-02-18
txt: ./txt/cord-327096-m87tapjp.txt
cache: ./cache/cord-327096-m87tapjp.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.02.16.20023465
doi: 10.1101/2020.02.16.20023465
summary:
  As shown in Fig. 3e-f , the predicted total infected cases at the end of epidemic, as well as the the inflection point, at which the basic reproduction number is less than 1 6 , both show a positive correlation with the infection rate β and the quarantined time δ −1 and a negative correlation with the protection rate α. 16.20023465 doi: medRxiv preprint of COVID-19 since its onset in Mainland * , Hubei * , and Wuhan (Beijing and Shanghai are not considered due to their too small numbers of infected cases on Jan. 20th). Based on detailed analysis of the public data of NHC of China from Jan. 20th to Feb. 9th, we estimate several key parameters for COVID-19, like the latent time, the quarantine time and the basic reproduction number in a relatively reliable way, and predict the inflection point, possible ending time and final total infected cases for Hubei, Wuhan, Beijing, Shanghai, etc.

abstract:
  The outbreak of the novel coronavirus (2019-nCoV) epidemic has attracted world- wide attention. Herein, we propose a mathematical model to analyzes this epidemic, based on a dynamic mechanism that incorporating the intrinsic impact of hidden la- tent and infectious cases on the entire process of transmission. Meanwhile, this model is validated by data correlation analysis, predicting the recent public data, and back- tracking, as well as sensitivity analysis. The dynamical model reveals the impact of various measures on the key parameters of the epidemic. According to the public data of NHCs from 01/20 to 02/09, we predict the epidemic peak and possible end time for 5 different regions. The epidemic in Beijing and Shanghai, Mainland/Hubei and Hubei/Wuhan, are expected to end before the end of February, and before mid- March respectively. The model indicates that, the outbreak in Wuhan is predicted to be ended in the early April. As a result, more effective policies and more efforts on clinical research are demanded. Moreover, through the backtracking simulation, we infer that the outbreak of the epidemic in Mainland/Hubei, Hubei/Wuhan, and Wuhan can be dated back to the end of December 2019 or the beginning of January 2020.


id: cord-327721-y39751g4
author: Zhang, Yan
date: 2020-07-19
txt: ./txt/cord-327721-y39751g4.txt
cache: ./cache/cord-327721-y39751g4.txt
extension: .txt
mime: text/plain
url: https://api.elsevier.com/content/article/pii/S0165032720325428
doi: 10.1016/j.jad.2020.07.097
summary:
  BACKGROUND: The outbreak of the new coronavirus pneumonia (NCP) in Wuhan, Hubei, has caused very serious consequences and severely affected people''s lives and mental health. METHODS: This study used self-designed questionnaires and artificial intelligence (AI) to assess and analyze the emotional state of over 30,000 college students during the outbreak period in January (T1) and home quarantine in February (T2). From these data, it indicated that during the period of home isolation, college students in Hubei Province showed more negative emotions due to their long-term exposure to the epidemic. There is also the stress symptom of "seeming as being infected" caused by too much browsing of the relevant news every day, which directly affects the emotions of students, they became more sensible and anxious to disease, this is a mental tension (Peng et al., 2019) . This survey found that there is an emotional "infection point" in February among college students, especially in the Hubei area.

title:
  Emotional “inflection point” in public health emergencies with the 2019 New Coronavirus Pneumonia (NCP) in China

abstract:
  BACKGROUND: The outbreak of the new coronavirus pneumonia (NCP) in Wuhan, Hubei, has caused very serious consequences and severely affected people's lives and mental health. The outbreak will cause bad emotions such as tension, anxiety, fear, and so on. College students who have returned home from school face infection, isolation, and delay in starting school, and thus, their emotional stress should be observed. METHODS: This study used self-designed questionnaires and artificial intelligence (AI) to assess and analyze the emotional state of over 30,000 college students during the outbreak period in January (T1) and home quarantine in February (T2). This survey used online questionnaire (www.wjx.cn) to investigate the emotion information of college students. RESULTS: In the T1 survey, the "Typhoon Eye Effect" appeared. College students in Hubei are calmer than those outside Hubei in T1. However, in T2, an emotional "infection point" appeared, there was an "Exposure Effect", the negative emotions of students in Hubei largely increased and became higher than students outside Hubei. CONCLUSION: This survey found that there is an emotional "infection point" in February among college students, especially in the Hubei area. College students in Hubei are calmer than those outside Hubei in T1. In contrast, college students in Hubei were more nervous and scared than those outside Hubei in T2. This epidemic has caused the students to experience significant pressure and negative emotions. Therefore, universities and society should pay attention to their emotional adjustment, there are some suggestions such as establish the mental health organizations, test students' emotion status regularly.


id: cord-332898-gi23un26
title: CIRD-F: Spread and Influence of COVID-19 in China
author: Zhou, Lingyun
date: 2020-04-07
txt: ./txt/cord-332898-gi23un26.txt
cache: ./cache/cord-332898-gi23un26.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1007/s12204-020-2168-1
doi: 10.1007/s12204-020-2168-1
summary:
  By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries. We also use a capital asset pricing model with dummy variable [6] [7] , which is called CAPM-DV model, to quantify the influence of official policies on different industries. Therefore, we use CIRD-F model for Hubei to predict the tendency of the epidemic in China, which shows that the policies help reduce about 68% possible infections. Furthermore, we use CAPM-DV model to calculate the economic impacts of the epidemic and official policies on different industries.

abstract:
  The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models for prediction, such as cabin models and individual-based models, are either oversimplified or too meticulous, and the influence of the epidemic was studied much more than that of official policies. To predict the epidemic tendency, we consider four groups of people, and establish a propagation dynamics model. We also create a negative feedback to quantify the public vigilance to the epidemic. We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country. Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78 191 (prediction interval, 74 872 to 82 474). By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries.


id: cord-333265-na7f0yam
title: Forecasting of COVID-19 Spread with dynamic transmission rate
author: Zeng, Yiping
date: 2020-08-21
txt: ./txt/cord-333265-na7f0yam.txt
cache: ./cache/cord-333265-na7f0yam.txt
extension: .txt
mime: text/plain
url: https://www.sciencedirect.com/science/article/pii/S2666449620300232?v=s5
doi: 10.1016/j.jnlssr.2020.07.003
summary:
  In Section 3, based on the least square method, the improved model is optimized by considering accumulated number of infected individuals and daily new cases. 1) The exposed individuals and infected individuals have same probability to infect susceptible individuals, that is β 1 =β 2 ; 2) There is no pedestrian flow between Hubei and outside Hubei, and COVID-19 spreads in the corresponding area; 3) Removed individual from the system has no ability to infect others; 4) The transmission rate β is assumed to follow an exponential function considering the fact that fewer individuals are infected after measures are in placed; 5) The removal rate γ is supposed to follow a power exponent function, and the removal rate increases as the time processes due to the better treatment. In our model, the transmission rate β is assumed to follow exponential function by considering the fact that fewer individuals are infected after measures to prevent the virus spread.

abstract:
  Abstract The COVID-19 was firstly reported in Wuhan, Hubei province, and it was brought to all over China by people travelling for Chinese New Year. The pandemic coronavirus with its catastrophic effects is now a global concern. Forecasting of COVID-19 spread has attracted a great attention for public health emergency. However, few researchers look into the relationship between dynamic transmission rate and preventable measures by authorities. In this paper, the SEIR (Susceptible Exposed Infectious Recovered) model is employed to investigate the spread of COVID-19. The epidemic spread is divided into two stages: before and after intervention. Before intervention, the transmission rate is assumed to be a constant since individual, community and government response has not taken into place. After intervention, the transmission rate is reduced dramatically due to the societal actions or measures to reduce and prevent the spread of disease. The transmission rate is assumed to follow an exponential function, and the removal rate is assumed to follow a power exponent function. The removal rate is increased with the evolution of the time. Using the real data, the model and parameters are optimized. The transmission rate without measure is calculated to be 0.033 and 0.030 for Hubei and outside Hubei province, respectively. After the model is established, the spread of COVID-19 in Hubei province, France and USA is predicted. From results, USA performs the worst according to the dynamic ratio. The model has provided a mathematical method to evaluate the effectiveness of the government response and can be used to forecast the spread of COVID-19 with better performance.


id: cord-339743-jxj10857
title: Synchronized travel restrictions across cities can be effective in COVID-19 control
author: Liu, H.
date: 2020-04-06
txt: ./txt/cord-339743-jxj10857.txt
cache: ./cache/cord-339743-jxj10857.txt
extension: .txt
mime: text/plain
url: http://medrxiv.org/cgi/content/short/2020.04.02.20050781v1?rss=1
doi: 10.1101/2020.04.02.20050781
summary:
  Previous studies established the impact of population outflow from Wuhan on the spatial spread of coronavirus in China and hinted the impact of the other three mobility patterns, i.e., population outflow from Hubei province excluding Wuhan, population inflow from cities outside Hubei, and intra-city population movement. Here we apply the cumulative confirmed cases and mobility data of 350 Chinese cities outside Hubei to explore the relationships between all mobility patterns and epidemic spread, and estimate the impact of local travel restrictions, both in terms of level and timing, on the epidemic control based on mobility change. We assume, after the Wuhan lockdown, the local travel restrictions in cities outside Hubei contributed to the epidemic control by influencing population mobility. The daily population outflow from Hubei (excluding Wuhan), inter-city population movement, and intra-city population movement after Feb 03, 2019, aligned by the Chinese lunar calendar with Jan 23, 2020, were used as proxy mobility data for the no local travel restrictions status in cities outside Hubei.

abstract:
  Mobility control measures are of crucial importance for public health planning in combating the COVID-19 pandemic. Previous studies established the impact of population outflow from Wuhan on the spatial spread of coronavirus in China and hinted the impact of the other three mobility patterns, i.e., population outflow from Hubei province excluding Wuhan, population inflow from cities outside Hubei, and intra-city population movement. However, the overall impact of all mobility patterns, or the impact of the different timing of mobility restriction intervention, are not systematically analyzed. Here we apply the cumulative confirmed cases and mobility data of 350 Chinese cities outside Hubei to explore the relationships between all mobility patterns and epidemic spread, and estimate the impact of local travel restrictions, both in terms of level and timing, on the epidemic control based on mobility change. The relationships were identified by using Pearson correlation analysis and stepwise multivariable linear regression, while scenario simulation was used to estimate the mobility change caused by local travel restrictions. Our analysis shows that: (1) all mobility patterns correlated with the spread of the coronavirus in Chinese cities outside Hubei, while the corrleations droppd with the implemetation of travel restrictions; (2) the cumulative confirmed cases in two weeks after the Wuhan lockdown was mainly brought by three patterns of inter-city population movement, while those in the third and fourth weeks after was significantly influenced by the number of intra-city population movement; (3) the local travel restrictions imposed by cities outside Hubei have averted 1,960 (95%PI: 1,474-2,447) more infections, taking 22.4% (95%PI: 16.8%-27.9%) of confirmed ones, in two weeks after the Wuhan lockdown, while more synchronized implementation would further decrease the number of confirmed cases in the same period by 15.7% (95%PI:15.4%-16.0%) or 1,378 (95%PI: 1,353-1,402) cases; and (4) local travel restrictions on different mobility patterns have different degrees of protection on cities with or without initial confirmed cases until the Wuhan lockdown. Our results prove the effectiveness of local travel restrictions and highlight the importance of synchronized implementation of mobility control across cities in mitigating the COVID-19 transmission.


id: cord-345877-rhybnlw0
author: Pei, Lijun
date: 2020-04-27
txt: ./txt/cord-345877-rhybnlw0.txt
cache: ./cache/cord-345877-rhybnlw0.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32341718/
doi: 10.1007/s11571-020-09588-4
summary:
  Initially, the numbers of the accumulative confirmed patients in different cities, provinces and geographical locations in China were predicted very accurately in the short term period of infection. 2, the novel fitting method of the outbreak of 2019-nCoV in China is proposed, and the selection of the data and basic functions is presented. Initially, I will present the novel fitting method for the prediction of NACP and the plateau phase of 2019-nCoV in China. In future studies, the data should be fitted to the new relaxed confirmed standards of Hubei Province and Wuhan City in order to predict the number of the accumulative confirmed patients and the plateau phase of the 2019-nCoV infection. In the present study, the novel fitting method was employed to predict the NACP and the plateau phase of the 2019-nCoV infection in different regions of China.

title:
  Prediction of numbers of the accumulative confirmed patients (NACP) and the plateau phase of 2019-nCoV in China

abstract:
  In the present study, I propose a novel fitting method to describe the outbreak of 2019-nCoV in China. The fitted data were selected carefully from the non-Hubei part and Hubei Province of China respectively. For the non-Hubei part, the time period of data collection corresponds from the beginning of the policy of isolation to present day. But for Hubei Province, the subjects of Wuhan City and Hubei Province were included from the time of admission to the Huoshenshan Hospital to present day in order to ensure that all or the majority of the confirmed and suspected patients were collected for diagnosis and treatment. The employed basic functions for fitting are the hyperbolic tangent functions [Formula: see text] since in these cases the 2019-nCoV is just an epidemic. Subsequently, the 2019-nCoV will initially expand rapidly and tend to disappear. Therefore, the numbers of the accumulative confirmed patients in different cities, provinces and geographical regions will initially increase rapidly and subsequently stabilize to a plateau phase. The selection of the basic functions for fitting is crucial. In the present study, I found that the hyperbolic tangent functions [Formula: see text] could satisfy the aforementioned properties. By this novel method, I can obtain two significant results. They base on the conditions that the rigorous isolation policy is executed continually. Initially, I can predict the numbers very accurately of the cumulative confirmed patients in different cities, provinces and parts in China, notably, in Wuhan City with the smallest relative error estimated to [Formula: see text] , in Hubei Province with the smallest relative error estimated to [Formula: see text] and in the non-Hubei part of China with the smallest relative error of [Formula: see text] 0.195% in the short-term period of infection. In addition, perhaps I can predict the times when the plateau phases will occur respectively in different regions in the long-term period of infection. Generally for the non-Hubei part of China, the plateau phase of the outbreak of the 2019-nCoV will be expected this March or at the end of this February. In the non-Hubei region of China it is expected that the epidemic will cease on the 30th of March 2020 and following this date no new confirmed patient will be expected. The predictions of the time of Inflection Points and maximum NACP for some important regions may be also obtained. A specific plan for the prevention measures of the 2019-nCoV outbreak must be implemented. This will involve the present returning to work and resuming production in China. Based on the presented results, I suggest that the rigorous isolation policy by the government should be executed regularly during daily life and work duties. Moreover, as many as possible the confirmed and suspected cases should be collected to diagnose or treat.


id: cord-351659-ujbxsus4
title: A retrospective analysis of the dynamic transmission routes of the COVID-19 in mainland China
author: Jiang, Xiandeng
date: 2020-08-19
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url: https://doi.org/10.1038/s41598-020-71023-9
doi: 10.1038/s41598-020-71023-9
summary:
  We propose a time-varying sparse vector autoregressive (VAR) model to retrospectively analyze and visualize the dynamic transmission routes of this outbreak in mainland China over January 31–February 19, 2020. Our results demonstrate that the influential inter-location routes from Hubei have become unidentifiable since February 4, 2020, whereas the self-transmission in each provincial-level administrative region (location, hereafter) was accelerating over February 4–15, 2020. Implications of our results suggest that in addition to the origin of the outbreak, virus preventions are of crucial importance in locations with the largest migrant workers percentages (e.g., Jiangxi, Henan and Anhui) to controlling the spread of COVID-19. This enables the detection and visualization of time-varying inter-location and self-transmission routes of the COVID-19 on the daily basis. On the fifth day (February 4, 2020), no influential transmission routes were found from Hubei to directly affect other locations, and there were only three influential routes identified nationally, including Zhejiang-Shaanxi, www.nature.com/scientificreports/ Zhejiang-Jiangxi and Jiangxi-Shanghai.

abstract:
  The fourth outbreak of the Coronaviruses, known as the COVID-19, has occurred in Wuhan city of Hubei province in China in December 2019. We propose a time-varying sparse vector autoregressive (VAR) model to retrospectively analyze and visualize the dynamic transmission routes of this outbreak in mainland China over January 31–February 19, 2020. Our results demonstrate that the influential inter-location routes from Hubei have become unidentifiable since February 4, 2020, whereas the self-transmission in each provincial-level administrative region (location, hereafter) was accelerating over February 4–15, 2020. From February 16, 2020, all routes became less detectable, and no influential transmissions could be identified on February 18 and 19, 2020. Such evidence supports the effectiveness of government interventions, including the travel restrictions in Hubei. Implications of our results suggest that in addition to the origin of the outbreak, virus preventions are of crucial importance in locations with the largest migrant workers percentages (e.g., Jiangxi, Henan and Anhui) to controlling the spread of COVID-19.


id: cord-351880-iqr419fp
author: Fan, Changyu
date: 2020-03-04
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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-352108-py93yvjy
title: Birth Defects Data from Surveillance Hospitals in Hubei Province, China, 200l – 2008
author: Tu, Lh
date: 2012-03-31
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url: https://www.ncbi.nlm.nih.gov/pubmed/23113146/
doi: nan
summary:
  title: Birth Defects Data from Surveillance Hospitals in Hubei Province, China, 200l – 2008 METHODS: The prevalence of birth defects in perinatal infants delivered after 28 weeks or more was analyzed in Hubei surveillance hospitals during 200l–2008. The two leading birth defects were cleft lip and/or palate and polydactyly, followed by congenital heart disease, hydrocephaly, external ear malformation and neural tube defects. Data published on Annual Report of the National Maternal and Child Health Care Surveillance and Communications in June, 2009 indicated that the prenatal diagnosis rate in Hubei province in 2008 was 14.29%, a bit lower than eastern coastal cities and provinces. Eight years'' BD data indicate that the BD prevalence was rising and the BD prevalence in Hubei province should be valued; prevention program of BD shall be better performed to decrease prevalence of birth deformation in perinatal infants based on improved perinatal care and prenatal diagnosis.

abstract:
  BACKGROUND: To determine the prevalence and characteristics of birth defects in perinatal infants in Hubei Province during 200l–2008. METHODS: The prevalence of birth defects in perinatal infants delivered after 28 weeks or more was analyzed in Hubei surveillance hospitals during 200l–2008. RESULTS: The incidence of birth defects in perinatal infants from 200l to 2008 was 120.0 per 10,000 births, and was increased by about 41% from 81. 1 in 2001 to 138.5 per 10,000 births in 2008. The incidence in the first 4 years (2005–2008) was much higher than the latter four (2001–2004) (χ(2)=77.64, P <0.05). The difference in prevalence between urban and rural was of no significance in 2008 (χ(2)=0.03, P >0.05), but that between male and female was significant (χ(2)=5.24, P <0.05), as the former prevalence was much higher. The prevalence of birth defects was slightly higher among mothers over 35 years old than those under 35 years old, but with no significance (χ(2)=1.98, P >0.05). The two leading birth defects were cleft lip and/or palate and polydactyly, followed by congenital heart disease, hydrocephaly, external ear malformation and neural tube defects. The prevalence of congenital heart disease was rising. CONCLUSIONS: Eight years’ birth defects data indicate that the birth defect rate was on the rise and the birth defects prevalence in Hubei province should be valued.


id: cord-354095-4sweo53l
author: Qiu, Yun
date: 2020-05-09
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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.


