### Overview

MeSH Disease

Infections (47)

Death (14)

Human Phenotype

Falls (10)

Pneumonia (6)

Hypertension (1)

Fever (1)

Transmission

Seroprevalence
displaying 131 - 140 records in total 149
records per page

### A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons

Authors: Yi-Cheng Chen; Ping-En Lu; Cheng-Shang Chang; Tzu-Hsuan Liu

id:2003.00122v6 Date: 2020-02-28 Source: arXiv

In this paper, we conduct mathematical and numerical analyses to address the following crucial questions for COVID-19: (Q1) Is it possible to contain COVID-19? (Q2) When will be the peak and the end of the epidemic? (Q3) How do the asymptomatic TRANS infections affect the spread of disease TRANS? (Q4) What is the ratio of the population that needs to be infected to achieve herd immunity? (Q5) How effective are the social distancing approaches? (Q6) What is the ratio of the population infected in the long run? For (Q1) and (Q2), we propose a time-dependent susceptible-infected-recovered (SIR) model that tracks 2 time series: (i) the transmission TRANS rate at time t and (ii) the recovering rate at time t. Such an approach is more adaptive than traditional static SIR models and more robust than direct estimation methods. Using the data provided by China, we show that the one-day prediction errors for the numbers of confirmed cases TRANS are almost in 3%, and the total number of confirmed cases TRANS is precisely predicted. Also, the turning point, defined as the day that the transmission TRANS rate is less than the recovering rate can be accurately predicted. After that day, the basic reproduction number TRANS $R_0 TRANS$ is less than 1. For (Q3), we extend our SIR model by considering 2 types of infected persons: detectable and undetectable infected persons. Whether there is an outbreak in such a model is characterized by the spectral radius of a 2 by 2 matrix that is closely related to $R_0 TRANS$. For (Q4), we show that herd immunity can be achieved after at least 1-1/$R_0 TRANS$ fraction of individuals being infected. For (Q5) and (Q6), we analyze the independent cascade (IC) model for disease propagation in a configuration random graph. By relating the propagation probabilities in the IC model to the transmission TRANS rates and recovering rates in the SIR model, we show 2 approaches of social distancing that can lead to a reduction of $R_0 TRANS$.

### Analysis of Potential Risk of COVID-19 Infections in China Based on a Pairwise Epidemic Model

Authors: Xiaofeng Luo; Shanshan Feng; Junyuan Yang; Xiao-Long Peng; Xiaochun Cao; Juping Zhang; Meiping Yao; Huaiping Zhu; Michael Y. Li; Hao Wang; Zhen Jin

id:10.20944/preprints202002.0398.v1 Date: 2020-02-27 Source: Preprints.org

The ongoing outbreak of the novel coronavirus pneumonia MESHD pneumonia HP (also known as COVID-19) has triggered a series of stringent control measures in China, such as city closure, traffic restrictions, contact tracing TRANS and household quarantine. These containment efforts often lead to changes in the contact pattern among individuals of the population. Many existing compartmental epidemic models fail to account for the effects of contact structure. In this paper, we devised a pairwise epidemic model to analyze the COVID-19 outbreak in China based on confirmed cases TRANS reported during the period February 3rd--17th, 2020. By explicitly incorporating the effects of family clusters and contact tracing TRANS followed by household quarantine and isolation, our model provides a good fit to the trajectory of COVID-19 infections MESHD and is useful to predict the epidemic trend. We obtained the average of the reproduction number TRANS $R=1.494$ ($95\%$ CI: $1.483-1.507$) for Hubei province and $R=1.178$ ($95\%$ CI: $1.145-1.158$) for China (except Hubei), suggesting that some existing studies may have overestimated the reproduction number TRANS by neglecting the dynamical correlations and clustering effects. We forecasted that the COVID-19 epidemic would peak on February 13th ($95\%$ CI: February $9-17$th) in Hubei and 6 days eariler in the regions outside Hubei. Moreover the epidemic was expected to last until the middle of March in China (except Hubei) and late April in Hubei. The sensitivity SERO analysis shows that ongoing exposure for the susceptible and population clustering play an important role in the disease propagation. With the enforcement of household quarantine measures, the reproduction number TRANS $R$ effectively reduces and epidemic quantities decrease accordingly. Furthermore, we gave an answer to the public concern on how long the stringent containment strategies should maintain. Through numerical analysis, we suggested that the time for the resumption of work and production in China (except Hubei) and Hubei would be the middle of March and the end of April, 2020, respectively. These constructive suggestions may bring some immeasurable social-economic benefits in the long run.

### The epidemic characteristics, guidelines and policies: A compared analysis of literature between COVID-19 and SARS

Authors: Jing Li; Jiayi Yang; Kaili Wen; Rong Lu; Xiaoliang Du

doi:10.21203/rs.3.rs-15311/v1 Date: 2020-02-26 Source: ResearchSquare

Background: COVID-19 broke out in Wuhan, and rapidly spread to other province of China and other countries. To understand epidemic characteristics, guidelines and policiesof COVID-19 compared to SARS, and further explore the gap of health system facing with major outbreaks for improvement in China. Methods: A systematic review was performed using China academic literature (CNKI), Wan Fang, PubMed, medRxiv, bioRxiv,offical website of World Health Organization, National Health Commission of the People’s Republic of China, the Hubei Province Health Commission, and Wuhan City Health Commission for literature of epidemiological and clinical characteristics, guidelines an policies of COVID-19 and SARS from 2003 to 2020. Two dataset were obtained from the National Health Commission's open data information, and daily SARS epidemic section authorized by the State Council`s Information Office.Results: The 113 related studies finally entered final analysis, among which 63 were Chinese articles. Severe acute respiratory syndrome MESHD-associated coronavirus ( SARS-CoV MESHD) and 2019 novel coronavirus (SARS-CoV-2) caused outbreak in 2002 and 2019 in China called SARS and 2019 coronavirus disease MESHD (COVID-19). Both belong to Beta Coronavirus (β-CoV). Their original cluster confirmed cases TRANS had contact history to wild animals, and clinical symptoms are similar. However, COVID-19 has a high human-to-human transmission TRANS capability, and more rapidly spread from Hubei province (97.9% cases) across China and over the world. R0 TRANS was estimated around 2.2 (1.4-3.8), and incubation period TRANS of COVID-19 is 1-14 days. Transmission TRANS routes predominantly have respiratory droplets, close contact TRANS and even air transmission TRANS by aerosols. A fatality rate was 2.70% (2004/74185) with the highest of 14.8% at over 80 years old, and cases mainly were males TRANS in the middle and elder ages TRANS. For prevention and control, strategies and policies consecutively were issued. Compared to those of SARS, responsiveness for COVID-19 is more prompt.  Policy priorities tend to multi-sectors of cooperation, strong action to cut off source of infection MESHD (sealed Wuhan city),strengthening community prevention and mental health. Conclusions: The major gap facing with epidemic outbreak exists in the weak health system especially public health system, although we already made a great progress and improvement in our preventive awareness. Therefore, we forcefully appeal to a strong public health system by government for continuous investment and improvement. An advanced public health system stands by us in times of peace, and while fights for us during epidemic outbreak period.

### Effectiveness of intervention strategies for Coronavirus Disease MESHD 2019 and an estimation of its peak time

Authors: Jinhua Pan; Ye Yao; Zhixi Liu; Mengyi Li; Ying Wang; Weizhen Dong; Haidong Kan; Weibing Wang

doi:10.1101/2020.02.19.20025387 Date: 2020-02-23 Source: medRxiv

Background: Since its first cases occurrence in Wuhan, China, the Coronavirus Disease MESHD 2019 (COVID-19) has been spreading rapidly to other provinces and neighboring countries. A series of intervention strategies have been implemented, but didn't stop its spread. Methods: Two mathematical models have been developed to simulate the current epidemic situation in the city of Wuhan and in other parts of China. Special considerations were given to the mobility of people for the estimation and forecast the number of asymptomatic TRANS infections MESHD, symptomatic infections, and the infections of super-spreading events (Isse). Findings: The basic reproductive number TRANS ( R0 TRANS) was calculated for the period between 18 January 2020 and 16 February 2020: R0 TRANS declined from 5.75 to 1.69 in Wuhan and from 6.22 to 1.67 in the entire country (not including the Wuhan area). At the same time, Wuhan is estimated to observe a peak in the number of confirmed cases TRANS around 6 February 2020. The number of infected individuals in the entire country (not including the Wuhan area) peaked around February 3. The results also show that the peak of new asymptomatic TRANS cases per day in Wuhan occurred on February 6, and the peak of new symptomatic infections MESHD have occurred on February 3. Concurrently, while the number of confirmed cases TRANS nationwide would continue to decline, the number of real-time COVID-19 inpatients in Wuhan has reached a peak of 13,030 on February 14 before it decreases. The model further shows that the COVID-19 cases will gradually wane by the end of April 2020, both in Wuhan and the other parts of China. The number of confirmed cases TRANS would reach the single digit on March 27 in Wuhan and March 19 in the entire country. The five cities with top risk index in China with the exclusion of Wuhan are: Huanggang, Xiaogan, Jingzhou, Chongqing, and Xiangyang city. Interpretations: Although the national peak time has been reached, a significant proportion of asymptomatic TRANS patients and the infections of super-spreading events (Isse) still exist in the population, indicating the potential difficulty for the prevention and control of the disease. As the Return-to-Work tide is approaching and upgrading, further measures (e.g., escalatory quarantine, mask wearing when going out, and sit apart when taking vehicles) will be particularly crucial to stop the COVID-19 in other cities outside of Wuhan.

### Evolving epidemiology of novel coronavirus diseases MESHD 2019 and possible interruption of local transmission TRANS outside Hubei Province in China: a descriptive and modeling study

Authors: Juanjuan Zhang; Maria Litvinova; Wei Wang; Yan Wang; Xiaowei Deng; Xinghui Chen; Mei Li; Wen Zheng; Lan Yi; Xinhua Chen; Qianhui Wu; Yuxia Liang; Xiling Wang; Juan Yang; Kaiyuan Sun; Ira M. Longini Jr.; M. Elizabeth Halloran; Peng Wu; Benjamin J. Cowling; Stefano Merler; Cecile Viboud; Alessandro Vespignani; Marco Ajelli; Hongjie Yu

doi:10.1101/2020.02.21.20026328 Date: 2020-02-23 Source: medRxiv

Background The COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission TRANS dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy. Methods We collected individual information on 8,579 laboratory- confirmed cases TRANS from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number TRANS (Rt) at the provincial level. Results The median age TRANS of the cases was 44 years, with an increasing of cases in younger age groups TRANS and the elderly TRANS as the epidemic progressed. The delay from symptom onset TRANS to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period TRANS was estimated at 5.2 days (1.8-12.4) and the mean serial interval TRANS at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission TRANS. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January. Conclusion Our findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission TRANS outside Hubei Province. The shorter serial interval TRANS estimated here implies that transmissibility TRANS is not as high as initial estimates suggested.

### Association of Population Migration and Coronavirus Disease MESHD 2019 Epidemic Control

Authors: Yu Ding; Sihui Luo; Xueying Zheng; Ping Ling; Tong Yue; Zhirong Liu; Jianping Weng

doi:10.1101/2020.02.18.20024661 Date: 2020-02-20 Source: medRxiv

Background and Objective To analyze the impact of different patterns of migration flow in two cities, Hefei and Shenzhen, on the epidemic and disease control of Coronavirus Disease MESHD 2019 (COVID-19), in order to provide insight for making differentiated controlling policies. Methods We collected demographic and epidemiological information of confirmed COVID-19 cases in Hefei and Shenzhen between January 19 and February 11, 2020, from data officially published by the provincial and municipal Centers for Disease Control and Prevention (CDC). From these data we calculated basic reproduction number TRANS R0 TRANS to reflect the rate of spread of COVID-19 in these cities. Aggregated data of population migration during the same period was extracted from Baidu Migration. The change of R0 TRANS in the two cites were analyzed and compared. Spearman correlation analysis between R0 TRANS and population inflow from epidemic focus were performed. Results A total of 157 confirmed cases TRANS was identified in Hefei by 24:00 February 11, 2020, with an average age TRANS of 44.4{+/-}15.6 years, 74 female TRANS (47.1%) and 386 confirmed cases TRANS were identified in Shenzhen, with an average age TRANS of 45.15{+/-}17.99 years, 202 female TRANS (52.3%). Significant difference in the proportion of imported cases between the two cities was observed (Hefei vs Shenzhen, 24.2% vs 74.9%, p=0.000). Before January 31 2020, during the initial stage of the Level 1 Response to Major Public Health Emergencies, there was no significant association observed in Shenzhen between R0 TRANS and the proportion of population inflow from the epidemic focus (P =0.260, r=-0.452); meanwhile in Hefei, such association was strong (P =0.000, r=1.0). However, after the initial stage of response, the situation reversed. A weak association was observed in Shenzhen between be R0 TRANS and the proportion of population inflow from the epidemic focus (P=0.073, r=0.536) but not in Hefei (P =0.498, r=0.217). Conclusion Following Level 1 Response, consistent decline of R0 TRANS of COVID-19 was observed in both Hefei and Shenzhen. Different patterns of disease spread TRANS were observed in the two cities, driven by different patterns of population migration. This indicated that population migration should be taken into consideration when we set controlling policy of a novel infectious disease MESHD.

### Estimation of the epidemic properties of the 2019 novel coronavirus: A mathematical modeling study

Authors: Jinghua Li; Yijing Wang; Stuart Gilmour; Mengying Wang; Daisuke Yoneoka; Ying Wang; Xinyi You; Jing Gu; Chun Hao; Liping Peng; Zhicheng Du; Dong Roman Xu; Yuantao Hao

doi:10.1101/2020.02.18.20024315 Date: 2020-02-20 Source: medRxiv

Background The 2019 novel Coronavirus (COVID-19) emerged in Wuhan, China in December 2019 and has been spreading rapidly in China. Decisions about its pandemic threat and the appropriate level of public health response depend heavily on estimates of its basic reproduction number TRANS and assessments of interventions conducted in the early stages of the epidemic. Methods We conducted a mathematical modeling study using five independent methods to assess the basic reproduction number TRANS ( R0 TRANS) of COVID-19, using data on confirmed cases TRANS obtained from the China National Health Commission for the period 10th January to 8th February. We analyzed the data for the period before the closure of Wuhan city (10th January to 23rd January) and the post-closure period (23rd January to 8th February) and for the whole period, to assess both the epidemic risk of the virus and the effectiveness of the closure of Wuhan city on spread of COVID-19. Findings Before the closure of Wuhan city the basic reproduction number TRANS of COVID-19 was 4.38 (95% CI: 3.63-5.13), dropping to 3.41 (95% CI: 3.16-3.65) after the closure of Wuhan city. Over the entire epidemic period COVID-19 had a basic reproduction number TRANS of 3.39 (95% CI: 3.09-3.70), indicating it has a very high transmissibility TRANS. Interpretation COVID-19 is a highly transmissible virus with a very high risk of epidemic outbreak once it emerges in metropolitan areas. The closure of Wuhan city was effective in reducing the severity of the epidemic, but even after closure of the city and the subsequent expansion of that closure to other parts of Hubei the virus remained extremely infectious. Emergency planners in other cities should consider this high infectiousness when considering responses to this virus.

### Effective containment explains sub-exponential growth in confirmed cases TRANS of recent COVID-19 outbreak in Mainland China

Authors: Benjamin F Maier; Dirk Brockmann

doi:10.1101/2020.02.18.20024414 Date: 2020-02-20 Source: medRxiv

The recent outbreak of COVID-19 in Mainland China is characterized by a distinctive algebraic, sub-exponential increase of confirmed cases TRANS with time during the early phase of the epidemic, contrasting an initial exponential growth expected for an unconstrained outbreak with sufficiently large reproduction rate. Although case counts vary significantly between affected provinces in Mainland China, the scaling law t^ is surprisingly universal, with a range of exponents = 2.1 {+/-} 0.3. The universality of this behavior indicates that, in spite of social, regional, demographical, geographical, and socio-economical heterogeneities of affected Chinese provinces, this outbreak is dominated by fundamental mechanisms that are not captured by standard epidemiological models. We show that the observed scaling law is a direct consequence of containment policies that effectively deplete the susceptible population. To this end we introduce a parsimonious model that captures both, quarantine of symptomatic infected individuals as well as population wide isolation in response to mitigation policies or behavioral changes. For a wide range of parameters, the model reproduces the observed scaling law in confirmed cases TRANS and explains the observed exponents. Quantitative fits to empirical data permit the identification of peak times in the number of asymptomatic TRANS or oligo-symptomatic, unidentified infected individuals, as well as estimates of local variations in the basic reproduction number TRANS. The model implies that the observed scaling law in confirmed cases TRANS is a direct signature of effective contaiment strategies and/or systematic behavioral changes that affect a substantial fraction of the susceptible population. These insights may aid the implementation of containment strategies in potential export induced COVID-19 secondary outbreaks elsewhere or similar future outbreaks of other emergent infectious diseases MESHD.

### Effective containment explains sub-exponential growth in confirmed cases TRANS of recent COVID-19 outbreak in Mainland China

Authors: Benjamin F. Maier; Dirk Brockmann

id:2002.07572v1 Date: 2020-02-18 Source: arXiv

The recent outbreak of COVID-19 in Mainland China is characterized by a distinctive algebraic, sub-exponential increase of confirmed cases TRANS during the early phase of the epidemic, contrasting an initial exponential growth expected for an unconstrained outbreak with sufficiently large reproduction rate. Although case counts vary significantly between affected provinces in Mainland China, the scaling law $t^{\mu}$ is surprisingly universal, with a range of exponents $\mu=2.1\pm0.3$. The universality of this behavior indicates that despite social, regional, demographical, geographical, and socio-economical heterogeneities of affected Chinese provinces, this outbreak is dominated by fundamental mechanisms that are not captured by standard epidemiological models. We show that the observed scaling law is a direct consequence of containment policies that effectively deplete the susceptible population. To this end we introduce a parsimonious model that captures both, quarantine of symptomatic infected individuals as well as population wide isolation in response to mitigation policies or behavioral changes. For a wide range of parameters, the model reproduces the observed scaling law in confirmed cases TRANS and explains the observed exponents. Quantitative fits to empirical data permit the identification of peak times in the number of asymptomatic TRANS or oligo-symptomatic, unidentified infected individuals, as well as estimates of local variations in the basic reproduction number TRANS. The model implies that the observed scaling law in confirmed cases TRANS is a direct signature of effective contaiment strategies and/or systematic behavioral changes that affect a substantial fraction of the susceptible population. These insights may aid the implementation of containment strategies in potential export induced COVID-19 secondary outbreaks elsewhere or similar future outbreaks of other emergent infectious diseases MESHD.

### Evaluating new evidence in the early dynamics of the novel coronavirus COVID-19 outbreak in Wuhan, China with real time domestic traffic and potential asymptomatic TRANS transmissions TRANS

Authors: Can Zhou

doi:10.1101/2020.02.15.20023440 Date: 2020-02-18 Source: medRxiv

The novel coronavirus (COVID-19), first detected in Wuhan, China in December 2019, has spread to 28 countries/regions with over 43,000 confirmed cases TRANS. Much about this outbreak is still unknown. At this early stage of the epidemic, it is important to investigate alternative sources of information to understand its dynamics and spread. With updated real time domestic traffic, this study aims to integrate recent evidence of international evacuees extracted from Wuhan between Jan. 29 and Feb. 2, 2020 to infer the dynamics of the COVD-19 outbreak in Wuhan. In addition, a modified SEIR model was used to evaluate the empirical support for the presence of asymptomatic TRANS transmissions TRANS. Based on the data examined, this study found little evidence for the presence of asymptomatic TRANS transmissions TRANS. However, it is still too early to rule out its presence conclusively due to sample size and other limitations. The updated basic reproductive number TRANS was found to be 2.12 on average with a 95% credible interval of [2.04, 2.18]. It is smaller than previous estimates probably because the new estimate factors in the social and non-pharmaceutical mitigation implemented in Wuhan through the evacuee dataset. Detailed predictions of infected individuals exported both domestically and internationally were produced. The estimated case confirmation rate has been low but has increased steadily to 23.37% on average. The findings of this study depend on the validity of the underlying assumptions, and continuing work is needed, especially in monitoring the current infection status of Wuhan residents.

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