scholarly journals Analysis of Spatiotemporal Characteristics of Pandemic SARS Spread in Mainland China

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Chunxiang Cao ◽  
Wei Chen ◽  
Sheng Zheng ◽  
Jian Zhao ◽  
Jinfeng Wang ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Mainland China ◽  
Emerging Infectious Diseases ◽  
Epidemiological Data ◽  
Transmission Dynamics ◽  
Bayesian Maximum Entropy ◽  
Covariance Model ◽  
Spatial And Temporal Scales ◽  
Epidemiological Characteristics ◽  
Spatiotemporal Transmission

Severe acute respiratory syndrome (SARS) is one of the most severe emerging infectious diseases of the 21st century so far. SARS caused a pandemic that spread throughout mainland China for 7 months, infecting 5318 persons in 194 administrative regions. Using detailed mainland China epidemiological data, we study spatiotemporal aspects of this person-to-person contagious disease and simulate its spatiotemporal transmission dynamics via the Bayesian Maximum Entropy (BME) method. The BME reveals that SARS outbreaks show autocorrelation within certain spatial and temporal distances. We use BME to fit a theoretical covariance model that has a sine hole spatial component and exponential temporal component and obtain the weights of geographical and temporal autocorrelation factors. Using the covariance model, SARS dynamics were estimated and simulated under the most probable conditions. Our study suggests that SARS transmission varies in its epidemiological characteristics and SARS outbreak distributions exhibit palpable clusters on both spatial and temporal scales. In addition, the BME modelling demonstrates that SARS transmission features are affected by spatial heterogeneity, so we analyze potential causes. This may benefit epidemiological control of pandemic infectious diseases.

scholarly journals Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea

2018 ◽  
Vol 15 (11) ◽  
pp. 2369 ◽  
Author(s):  
Yunhwan Kim ◽  
Hohyung Ryu ◽  
Sunmi Lee
Keyword(s):  
Infectious Diseases ◽  
Transmission Rate ◽  
Emerging Infectious Diseases ◽  
Epidemiological Data ◽  
Agent Based Modeling ◽  
Transmission Dynamics ◽  
Republic Of Korea ◽  
Agent Based ◽  
The Republic ◽  
High Level

Super-spreading events have been observed in the transmission dynamics of many infectious diseases. The 2015 MERS-CoV outbreak in the Republic of Korea has also shown super-spreading events with a significantly high level of heterogeneity in generating secondary cases. It becomes critical to understand the mechanism for this high level of heterogeneity to develop effective intervention strategies and preventive plans for future emerging infectious diseases. In this regard, agent-based modeling is a useful tool for incorporating individual heterogeneity into the epidemic model. In the present work, a stochastic agent-based framework is developed in order to understand the underlying mechanism of heterogeneity. Clinical (i.e., an infectivity level) and social or environmental (i.e., a contact level) heterogeneity are modeled. These factors are incorporated in the transmission rate functions under assumptions that super-spreaders have stronger transmission and/or higher links. Our agent-based model has employed real MERS-CoV epidemic features based on the 2015 MERS-CoV epidemiological data. Monte Carlo simulations are carried out under various epidemic scenarios. Our findings highlight the roles of super-spreaders in a high level of heterogeneity, underscoring that the number of contacts combined with a higher level of infectivity are the most critical factors for substantial heterogeneity in generating secondary cases of the 2015 MERS-CoV transmission.

scholarly journals Taiwan’s Successful COVID-19 Mitigation and Containment Strategy: Achieving Quasi Population Immunity

2020 ◽  
pp. 1-4 ◽  
Author(s):  
Li-Chien Chien ◽  
Christian K. Beÿ ◽  
Kristi L. Koenig
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Health Management ◽  
Mainland China ◽  
Emerging Infectious Diseases ◽  
Contact Tracing ◽  
Population Immunity ◽  
Containment Strategy ◽  
Local Transmission ◽  
Pharmaceutical Interventions

ABSTRACT The authors describe Taiwan’s successful strategy in achieving control of coronavirus disease (COVID-19) without economic shutdown, despite the prediction that millions of infections would be imported from travelers returning from Chinese New Year celebrations in Mainland China in early 2020. As of September 2, 2020, Taiwan reports 489 cases, 7 deaths, and no locally acquired COVID-19 cases for the last 135 days (greater than 4 months) in its population of over 23.8 million people. Taiwan created quasi population immunity through the application of established public health principles. These non-pharmaceutical interventions, including public masking and social distancing, coupled with early and aggressive identification, isolation, and contact tracing to inhibit local transmission, represent a model for optimal public health management of COVID-19 and future emerging infectious diseases.

scholarly journals The severe acute respiratory syndrome epidemic in mainland China dissected

2011 ◽  
Vol 3 (1) ◽  
pp. 2 ◽  
Author(s):  
Wuchun Cao ◽  
Sake J. De Vlas ◽  
Jan H. Richardus
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Mainland China ◽  
Emerging Infectious Diseases ◽  
Case Fatality ◽  
Epidemiological Data ◽  
Control Measures ◽  
Political Commitment ◽  
Younger Age ◽  
Surrounding Areas ◽  
The Impact

This paper provides a review of a recently published series of studies that give a detailed and comprehensive documentation of the severe acute respiratory syndrome (SARS) epidemic in mainland China, which severely struck the country in the spring of 2003. The epidemic spanned a large geographical extent but clustered in two areas: first in Guangdong Province, and about 3 months later in Beijing with its surrounding areas. Reanalysis of all available epidemiological data resulted in a total of 5327 probable cases of SARS, of whom 343 died. The resulting case fatality ratio (CFR) of 6.4% was less than half of that in other SARS-affected countries or areas, and this difference could only partly be explained by younger age of patients and higher number of community acquired infections. Analysis of the impact of interventions demonstrated that strong political commitment and a centrally coordinated response was the most important factor to control SARS in mainland China, whereas the most stringent control measures were all initiated when the epidemic was already dying down. The long-term economic consequence of the epidemic was limited, much consumption was merely postponed, but for Beijing irrecoverable losses to the tourist sector were considerable. An important finding from a cohort study was that many former SARS patients currently suffer from avascular osteo­necrosis, as a consequence of the treatment with corticosteroids during their infection. The SARS epidemic provided valuable information and lessons relevant in controlling outbreaks of newly emerging infectious diseases, and has led to fundamental reforms of the Chinese health system. In particular, a comprehensive nation-wide internet-based disease reporting system was established.

scholarly journals Factors Influencing Intentions to Care For Emerging Infectious Disease Patients among National and Public Hospitals Nurses

2021 ◽  
Vol 28 (1) ◽  
pp. 11-22
Author(s):  
Hea-Jin Moon ◽  
Ju Young Park
Keyword(s):  
Infectious Disease ◽  
Social Support ◽  
Infectious Diseases ◽  
Pearson Correlation ◽  
Emerging Infectious Diseases ◽  
Emerging Infectious Disease ◽  
Public Hospitals ◽  
Self Report ◽  
Moral Sensitivity ◽  
Epidemiological Characteristics

Purpose: The purpose of this study was to identify the effect of nurses' nursing professionalism, moral sensitivity, and social support on intention to care for patients with emerging infectious diseases.Methods: A structured self-report questionnaire was used to measure nursing professionalism, moral sensitivity, social support, and intention to care for patients with emerging infectious diseases. Data were collected from April 9~20, 2019. Participants were 200 nurse nurses working in national and public hospitals. Data were analyzed using Pearson correlation coefficients, and Multiple regression with the SPSS/WIN 24.0 program.Results: The perceived behavioral control (β=.48, p<.001), control beliefs (β=-.26, p<.001), moral sensitivity (β=.23, p<.001), normative beliefs (β=.17, p=.002), subjective norms (β=.17, p=.001), and attitude toward behavior (β=.10, p=.036) were a significant predictor of the intention to care for emerging infectious disease patients (Adj. R<sup>2</sup>=.65).Conclusion: In order to confidently carry out nursing activities for patients with emerging infectious diseases, sufficient education on the epidemiological characteristics of emerging infectious diseases must be provided and education programs developed and applied with simulation similar to those of actual care for emerging infectious disease patients.

scholarly journals Persistent infections support maintenance of a coronavirus in a population of Australian bats (Myotis macropus)

2017 ◽  
Vol 145 (10) ◽  
pp. 2053-2061 ◽  
Author(s):  
J. JEONG ◽  
C. S. SMITH ◽  
A. J. PEEL ◽  
R. K. PLOWRIGHT ◽  
D. H. KERLIN ◽  
...  
Keyword(s):  
Public Health ◽  
Data Analysis ◽  
Infectious Diseases ◽  
Epidemic Model ◽  
Emerging Infectious Diseases ◽  
Viral Transmission ◽  
Transmission Dynamics ◽  
Persistent Infections ◽  
Study Population ◽  
Reservoir Hosts

SUMMARYUnderstanding viral transmission dynamics within populations of reservoir hosts can facilitate greater knowledge of the spillover of emerging infectious diseases. While bat-borne viruses are of concern to public health, investigations into their dynamics have been limited by a lack of longitudinal data from individual bats. Here, we examine capture–mark–recapture (CMR) data from a species of Australian bat (Myotis macropus) infected with a putative novel Alphacoronavirus within a Bayesian framework. Then, we developed epidemic models to estimate the effect of persistently infectious individuals (which shed viruses for extensive periods) on the probability of viral maintenance within the study population. We found that the CMR data analysis supported grouping of infectious bats into persistently and transiently infectious bats. Maintenance of coronavirus within the study population was more likely in an epidemic model that included both persistently and transiently infectious bats, compared with the epidemic model with non-grouping of bats. These findings, using rare CMR data from longitudinal samples of individual bats, increase our understanding of transmission dynamics of bat viral infectious diseases.

scholarly journals Reconstruction of the transmission dynamics of the first COVID-19 epidemic wave in Thailand

2021 ◽  
Author(s):  
Chaiwat Wilasang ◽  
Natcha Jitsuk ◽  
Chayanin Sararat ◽  
Charin Modchang
Keyword(s):  
Disease Transmission ◽  
Infected Individual ◽  
Mainland China ◽  
Stochastic Modelling ◽  
Epidemiological Data ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Thai Government ◽  
And Control ◽  
Epidemic Wave

Abstract Thailand was the first country reporting the first Coronavirus disease 2019 (COVID-19) infected individual outside mainland China. Here we delineated the course of the COVID-19 outbreak together with the timeline of the control measures and public health policies employed by the Thai government during the first wave of the COVID-19 outbreak in Thailand. Based on the comprehensive epidemiological data, we reconstructed the dynamics of COVID-19 transmission in Thailand using a stochastic modelling approach. Our stochastic model incorporated effects of individual heterogeneity in infectiousness on the disease transmission, which allows us to capture relevant features of superspreading events. We found that our model could accurately capture the transmission dynamics of the first COVID-19 epidemic wave in Thailand. The model predicted that at the end of the first wave, the number of cumulative confirmed cases was 3,091 (95%CI: 2,782 - 3,400). We also estimated the time-varying reproduction number (Rt) during the first epidemic wave. We found that after implementing the nationwide interventions, the Rt in Thailand decreased from the peak value of 5.67 to a value below one in less than one month, indicating that the control measures employed by the Thai government during the first COVID-19 epidemic wave were effective. Finally, effects of transmission heterogeneity and control measures on the likelihood of outbreak extinction were also investigated.

scholarly journals Media/Psychological Impact on Multiple Outbreaks of Emerging Infectious Diseases

2007 ◽  
Vol 8 (3) ◽  
pp. 153-164 ◽  
Author(s):  
Rongsong Liu ◽  
Jianhong Wu ◽  
Huaiping Zhu
Keyword(s):  
Infectious Diseases ◽  
Compartmental Model ◽  
Psychological Impact ◽  
Emerging Infectious Diseases ◽  
Transmission Dynamics ◽  
Periodic Oscillations ◽  
Nonlinear Incidence ◽  
Incidence Function ◽  
Contact Patterns ◽  
Nonlinear Incidence Function

We use a compartmental model to illustrate a possible mechanism for multiple outbreaks or even sustained periodic oscillations of emerging infectious diseases due to the psychological impact of the reported numbers of infectious and hospitalized individuals. This impact leads to the change of avoidance and contact patterns at both individual and community levels, and incorporating this impact using a simple nonlinear incidence function into the model shows qualitative differences of the transmission dynamics.

scholarly journals Spatiotemporal transmission dynamics of co-circulating dengue, Zika, and chikungunya viruses in Fortaleza, Brazil: 2011–2017

2020 ◽  
Vol 14 (10) ◽  
pp. e0008760
Author(s):  
Lilit Kazazian ◽  
Antonio S. Lima Neto ◽  
Geziel S. Sousa ◽  
Osmar José do Nascimento ◽  
Marcia C. Castro
Keyword(s):  
Spatial Clustering ◽  
Scan Statistics ◽  
Transmission Dynamics ◽  
Competitive Interactions ◽  
Time Intervals ◽  
Spatial And Temporal Scales ◽  
The City ◽  
Spatiotemporal Transmission ◽  
Neighborhood Level ◽  
Time Scan

The mosquito-borne viruses dengue (DENV), Zika (ZIKV), and chikungunya (CHIKV), now co-endemic in the Americas, pose growing threats to health worldwide. However, it remains unclear whether there exist interactions between these viruses that could shape their epidemiology. This study advances knowledge by assessing the transmission dynamics of co-circulating DENV, ZIKV, and CHIKV in the city of Fortaleza, Brazil. Spatiotemporal transmission dynamics of DENV, ZIKV, and CHIKV were analyzed using georeferenced data on over 210,000 reported cases from 2011 to 2017 in Fortaleza, Brazil. Local spatial clustering tests and space-time scan statistics were used to compare transmission dynamics across all years. The transmission of co-circulating viruses in 2016 and 2017 was evaluated at fine spatial and temporal scales using a measure of spatiotemporal dependence, the τ-statistic. Results revealed differences in the diffusion of CHIKV compared to previous DENV epidemics and spatially distinct transmission of DENV/ZIKV and CHIKV during the period of their co-circulation. Significant spatial clustering of viruses of the same type was observed within 14-day time intervals at distances of up to 6.8 km (p<0.05). These results suggest that arbovirus risk is not uniformly distributed within cities during co-circulation. Findings may guide outbreak preparedness and response efforts by highlighting the clustered nature of transmission of co-circulating arboviruses at the neighborhood level. The potential for competitive interactions between the arboviruses should be further investigated.

scholarly journals Downgrading disease transmission risk estimates using terminal importations

2018 ◽  
Author(s):  
Spencer J Fox ◽  
Steven E Bellan ◽  
T Alex Perkins ◽  
Michael A Johansson ◽  
Lauren Ancel Meyers
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
A Priori ◽  
Emerging Infectious Diseases ◽  
Epidemiological Data ◽  
Transmission Risk ◽  
Risk Estimates ◽  
Imported Cases ◽  
Ecological Suitability ◽  
Local Transmission

AbstractAs emerging and re-emerging infectious diseases like dengue, Ebola, chikungunya, and Zika threaten new populations worldwide, officials scramble to assess local severity and transmissibility, with little to no epidemiological history to draw upon. Standard methods for assessing autochthonous (local) transmission risk make either indirect estimates based on ecological suitability or direct estimates only after local cases accumulate. However, an overlooked source of epidemiological data that can meaningfully inform risk assessments prior to outbreak emergence is the absence of transmission by imported cases. Here, we present a method for updating a priori ecological estimates of transmission risk using real-time importation data. We demonstrate our method using Zika importation and transmission data from Texas in 2016, a high-risk region in the southern United States. Our updated risk estimates are lower than previously reported, with only six counties in Texas likely to sustain a Zika epidemic, and consistent with the number of autochthonous cases detected in 2017. Importation events can thereby provide critical, early insight into local transmission risks as infectious diseases expand their global reach.

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