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.

Consistent Infection Prevention: Vital During Routine and Emerging Infectious Diseases Care

2017 ◽  
Vol 22 (1) ◽  
Author(s):  
Terri Rebmann ◽  
Ruth Carrico
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
Infection Prevention ◽  
Healthcare Providers ◽  
Emerging Infectious Diseases ◽  
Occupational Exposures ◽  
The United States ◽  
Vital Role ◽  
Routine Practice ◽  
Adequate Knowledge

Emerging infectious diseases impact healthcare providers in the United States and globally. Nurses play a vital role in protecting the health of patients, visitors, and fellow staff members during routine practice and biological disasters, such as bioterrorism, pandemics, or outbreaks of emerging infectious diseases. One vital nursing practice is proper infection prevention procedures. Failure to practice correctly and consistently can result in occupational exposures or disease transmission. This article reviews occupational health risks, and pharmacological and nonpharmacological interventions for nurses who provide care to patients with new or re-emerging infectious diseases. Infection prevention education based on existing infection prevention competencies is critical to ensure adequate knowledge and safe practice both every day and in times of limited resources. Challenges specific to infectious disease disasters are discussed, as well as the role of microorganisms and nurse education for infection prevention.

scholarly journals Genomic surveillance of COVID-19 cases in Beijing

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Pengcheng Du ◽  
Nan Ding ◽  
Jiarui Li ◽  
Fujie Zhang ◽  
Qi Wang ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
High Frequency ◽  
Epidemiological Data ◽  
Genomic Diversity ◽  
Nucleotide Polymorphisms ◽  
Genomic Evolution ◽  
Single Nucleotide ◽  
Imported Cases ◽  
Single Nucleotide Variations ◽  
Local Transmission

Abstract The spread of SARS-CoV-2 in Beijing before May, 2020 resulted from transmission following both domestic and global importation of cases. Here we present genomic surveillance data on 102 imported cases, which account for 17.2% of the total cases in Beijing. Our data suggest that all of the cases in Beijing can be broadly classified into one of three groups: Wuhan exposure, local transmission and overseas imports. We classify all sequenced genomes into seven clusters based on representative high-frequency single nucleotide polymorphisms (SNPs). Genomic comparisons reveal higher genomic diversity in the imported group compared to both the Wuhan exposure and local transmission groups, indicating continuous genomic evolution during global transmission. The imported group show region-specific SNPs, while the intra-host single nucleotide variations present as random features, and show no significant differences among groups. Epidemiological data suggest that detection of cases at immigration with mandatory quarantine may be an effective way to prevent recurring outbreaks triggered by imported cases. Notably, we also identify a set of novel indels. Our data imply that SARS-CoV-2 genomes may have high mutational tolerance.

Mapping the Potential for Infectious Disease Transmission in a Wide-Body Aircraft Cabin

2019 ◽  
Author(s):  
Seif Mahmoud ◽  
James S. Bennett ◽  
Mohammad H. Hosni ◽  
Byron Jones
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
Radial Distance ◽  
Transmission Risk ◽  
Disease Spread ◽  
Health Concern ◽  
Tracer Gas ◽  
Infectious Disease Transmission ◽  
Gas Concentration ◽  
Aircraft Cabin

Abstract With more than two billion passengers annually, in-flight transmission of infectious diseases is a major global health concern. It is widely believed that principal transmission risk associated with air travel for most respiratory infectious diseases is limited to within two rows of an infectious passenger. However, several passengers became infected despite sitting several rows away from the contagious passenger. This work thoroughly investigated the potential for disease spread inside airplane cabins using tracer gas to quantify airborne dispersion. Measurements were conducted in a full-scale, 11-row mock-up of a wide-body aircraft cabin. Heated mannequins to simulate passengers’ thermal load were placed on the cabin seats. Tracer gas was injected at the breathing level at four different hypothetical contagious passenger locations. The tracer gas concentration was measured radially up to 3.35 m away from the injection location representing four rows of a standard aircraft. A four-port sampling tree was used to collect samples at the breathing level at four different radial locations simultaneously. Each port was sampled for 30 minutes. A total of 42 tests were conducted in matching pairs to alleviate potential statistical or measurements bias. The results showed that the airflow pattern inside the mock-up airplane cabin plays a major role in determining tracer gas concentration meaning that the concentration at the same radial distance in different directions are not necessarily the same. Also, due to the air distribution pattern and cabin walls, concentrations at some seats may be higher than the source seat.

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 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 SIR Mathematical Model of Convalescent Plasma Transfusion Applied to the COVID-19 Pandemic Data in Indonesia to Control the Spread of the Disease

2021 ◽  
Vol 2084 (1) ◽  
pp. 012022
Author(s):  
Hennie Husniah ◽  
Ruhanda ◽  
Asep Kuswandi Supriatna
Keyword(s):  
Mathematical Model ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Emerging Infectious Diseases ◽  
Mortality Rates ◽  
Sir Model ◽  
Difficult Problem ◽  
Plasma Transfusion ◽  
Preventive Actions ◽  
Discrete Mathematical Model

Abstract In this paper we develop a mathematical model of disease transmission dynamics. Although some vaccines for some infectious diseases are available, there are some cases where handling new emerging infectious diseases, such as COVID-19 pandemic, is still a difficult problem to handle. Preventive actions, such as wearing masks, distance guarding, frequent hand washing, and others are still the most important interventions in handling the transmission of this disease. Recently, several countries have allowed the use of convalescent plasma transfusion (CPT) in the management of moderate and severe COVID-19 patients. Several early studies of this use have yielded prospective results with reduced mortality rates. A recent work also shows that using a simple discrete mathematical model of CPT could reduce the outbreak of disease transmission, in the sense of reducing the peak number of active cases and the length of the outbreak itself. In this paper, we use a continuous SIR model applied to COVID-19 pandemic data in Indonesia to address an important question whether convalescent plasma transfusion may reduce the transmission of the disease.

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 Emerging Infectious Diseases and Blood Safety: Modeling the Transfusion-Transmission Risk

2017 ◽  
Vol 31 (3) ◽  
pp. 154-164 ◽  
Author(s):  
Philip Kiely ◽  
Manoj Gambhir ◽  
Allen C Cheng ◽  
Zoe K McQuilten ◽  
Clive R Seed ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Emerging Infectious Diseases ◽  
Transmission Risk ◽  
Blood Safety

scholarly journals Complex Dynamics of An Epidemic Model With Saturated Media Coverage and Recovery

2021 ◽  
Author(s):  
Tangjuan Li ◽  
Yanni Xiao
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
Media Coverage ◽  
Multiple Equilibria ◽  
Complex Dynamics ◽  
Emerging Infectious Diseases ◽  
Backward Bifurcation ◽  
Threshold Condition ◽  
Medical Resources ◽  
Saturated Media

Abstract During the outbreak of emerging infectious diseases, media coverage and medical resource play important roles in affecting the disease transmission. To investigate the effects of the saturation of media coverage and limited medical resources, we proposed a mathematical model with extra compartment of media coverage and two nonlinear functions. We theoretically obtained that saturated recovery significantly contributes the occurrence of backward bifurcation and rich dynamics. Then it is reasonable to only considering nonlinear recovery, we theoretically showed that backward bifurcation can occur and multiple equilibria may coexist under certain conditions in this case. And numerical simulations reveals the rich dynamic behaviors, including forward-backward bifurcation, Hopf bifurcation, Saddle-Node bifurcation, Homoclinic bifurcation and unstable limit cycle. Comparing the system with linear recovery, where the threshold dynamic are almost completely characterized by a threshold condition called the basic reproduction number, we concluded that only saturated media impact hardly induces the complicated dynamics, while the nonlinear recovery function, associated with limitation of medical resources, may induce the coexistence of the disease-free equilibrium (DFE) and a endemic state or multiple endemic states, which means that the limitation of medical resources causes much difficulties in eliminating the infectious diseases.

scholarly journals Mitigating Climate Change’s Impact on Tick-Borne Zoonotic Disease Emergence

2021 ◽  
Author(s):  
Conner Philson ◽  
Lyndsey Gray ◽  
Lindsey Pedroncelli ◽  
William Ota
Keyword(s):  
Climate Change ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Disease Risk ◽  
Global Climate ◽  
Emerging Infectious Diseases ◽  
Blood Feeding ◽  
Zoonotic Disease ◽  
World Health ◽  
Climate Change Research

Disease transmission from animals to humans — called a zoonotic disease — is responsible for nearly 60% of emerging infectious diseases. While zoonotic diseases already pose a major risk to humanity, global climate change and its causal human behaviors are compounding zoonotic disease risk. Dynamic species distributions, increased species overlap, and alterations in human land use increase the risk of disease transmission from non-humans to humans. Ticks, which carry many human disease-causing agents, are a primary example. As 23% of emerging infectious diseases globally are spread by blood-feeding arthropods, such as ticks, managing and monitoring tick distributions and their overlap and potential contact with humans is vital to decrease the risk of zoonotic disease transmission. While some programs are already in place, expanding current and implementing new programs across the globe is pertinent. We propose enhancing international collaboration and communication efforts through intergovernmental organizations such as the United Nations (UN) and the World Health Organization (WHO), to better research, monitor, and mitigate the risk of tick-borne zoonotic disease. By focusing international efforts on ticks, subsequent zoonotic disease-climate change research and monitoring efforts can be done across species.

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