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.

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 Analysis of infectious disease transmission and prediction through SEIQR epidemic model

2021 ◽  
Vol 8 (1) ◽  
pp. 75-86
Author(s):  
Swati Tyagi ◽  
Shaifu Gupta ◽  
Syed Abbas ◽  
Krishna Pada Das ◽  
Baazaoui Riadh
Keyword(s):  
Mathematical Model ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Disease Spread ◽  
Infectious Disease Transmission ◽  
Control Measurement ◽  
Dynamics And Control ◽  
The Stability ◽  
And Control ◽  
Special Case

Abstract In literature, various mathematical models have been developed to have a better insight into the transmission dynamics and control the spread of infectious diseases. Aiming to explore more about various aspects of infectious diseases, in this work, we propose conceptual mathematical model through a SEIQR (Susceptible-Exposed-Infected-Quarantined-Recovered) mathematical model and its control measurement. We establish the positivity and boundedness of the solutions. We also compute the basic reproduction number and investigate the stability of equilibria for its epidemiological relevance. To validate the model and estimate the parameters to predict the disease spread, we consider the special case for COVID-19 to study the real cases of infected cases from [2] for Russia and India. For better insight, in addition to mathematical model, a history based LSTM model is trained to learn temporal patterns in COVID-19 time series and predict future trends. In the end, the future predictions from mathematical model and the LSTM based model are compared to generate reliable results.

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.

scholarly journals SEIR Mathematical Model of Convalescent Plasma Transfusion to Reduce COVID-19 Disease Transmission

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2857
Author(s):  
Hennie Husniah ◽  
Ruhanda Ruhanda ◽  
Asep K. Supriatna ◽  
Md. H. A. Biswas
Keyword(s):  
Mathematical Model ◽  
Disease Transmission ◽  
Patient Survival ◽  
Equilibrium Points ◽  
Population Level ◽  
Infectious Period ◽  
Plasma Transfusion ◽  
Standard Procedures ◽  
Reproduction Numbers ◽  
Trivial Equilibrium

In some diseases, due to the restrictive availability of vaccines on the market (e.g., during the early emergence of a new disease that may cause a pandemic such as COVID-19), the use of plasma transfusion is among the available options for handling such a disease. In this study, we developed an SEIR mathematical model of disease transmission dynamics, considering the use of convalescent plasma transfusion (CPT). In this model, we assumed that the effect of CPT increases patient survival or, equivalently, leads to a reduction in the length of stay during an infectious period. We attempted to answer the question of what the effects are of different rates of CPT applications in decreasing the number of infectives at the population level. Herein, we analyzed the model using standard procedures in mathematical epidemiology, i.e., finding the trivial and non-trivial equilibrium points of the system including their stability and their relation to basic and effective reproduction numbers. We showed that, in general, the effects of the application of CPT resulted in a lower peak of infection cases and other epidemiological measures. As a consequence, in the presence of CPT, lowering the height of an infective peak can be regarded as an increase in the number of remaining healthy individuals; thus, the use of CPT may decrease the burden of COVID-19 transmission.

scholarly journals An open-access database of infectious disease transmission trees to explore superspreader epidemiology

2021 ◽  
Author(s):  
Juliana C. Taube ◽  
Paige B. Miller ◽  
John M. Drake
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Emerging Infectious Diseases ◽  
Dispersion Parameter ◽  
Infectious Disease Transmission ◽  
Secondary Infections ◽  
Open Access Database ◽  
Outbreak Investigations ◽  
Outbreak Size

AbstractHistorically, emerging and re-emerging infectious diseases have caused large, deadly, and expensive multi-national outbreaks. Often outbreak investigations aim to identify who infected whom by reconstructing the outbreak transmission tree, which visualizes transmission between individuals as a network with nodes representing individuals and branches representing transmission from person to person. We compiled a database of 383 published, standardized transmission trees consisting of 16 directly-transmitted diseases ranging in size from 2 to 286 cases. For each tree and disease we calculated several key statistics, such as outbreak size, average number of secondary infections, the dispersion parameter, and the number of superspreaders. We demonstrated the potential utility of the database through short analyses addressing questions about superspreader epidemiology for a variety of diseases, including COVID-19. First, we compared the frequency and contribution of superspreaders to onward transmission across diseases. COVID-19 outbreaks had significantly fewer superspreaders than outbreaks of SARS and MERS and a dispersion parameter between that of SARS and MERS. Across diseases the presence of more superspreaders was associated with greater outbreak size. Second, we further examined how early spread impacts tree size. Generally, trees sparked by a superspreader had larger outbreak sizes than those trees not sparked by a superspreader, and this trend was significant for COVID-19 trees. Third, we investigated patterns in how superspreaders are infected. Across trees with more than one superspreader, we found support for the theory that superspreaders generate other superspreaders, even when controlling for number of secondary infections. In sum, our findings put the role of superspreading to COVID-19 transmission in perspective with that of SARS and MERS and suggest an avenue for further research on the generation of superspreaders. These data have been made openly available to encourage reuse and further scientific inquiry.Author SummaryPublic health investigations often aim to identify who infected whom, or the transmission tree, during outbreaks of infectious diseases. These investigations tend to be resource intensive but valuable as they contain epidemiological information, including the average number of infections caused by each individual and the variation in this number. To date, there remains no standardized format nor comprehensive database of infectious disease transmission trees. To fill this gap, we standardized and compiled more than 350 published transmission trees for 16 directly-transmitted diseases into a database that is publicly available. In this paper, we give an overview of the database construction process, as well as a demonstration of the types of questions that the database can be used to answer related to superspreader epidemiology. For example, we show that COVID-19 outbreaks have fewer superspreaders than outbreaks of SARS and MERS. We also find support for the theory that superspreaders generate other superspreaders. In the future, this database can be used to answer other outstanding questions in the field of epidemiology.

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.

scholarly journals Review of digital PCR potential for surveillance of emerging disease from wastewater

2021 ◽  
Vol 926 (1) ◽  
pp. 012065
Author(s):  
A Dewantoro ◽  
W C Anggundari ◽  
B Prasetya ◽  
Yopi
Keyword(s):  
Nucleic Acid ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Emerging Infectious Diseases ◽  
Digital Pcr ◽  
Absolute Quantification ◽  
Emerging Disease ◽  
Environmental Surveillance ◽  
The World

Abstract Emerging infectious diseases (EID) such as COVID-19 had been widely caused massive impact for all countries in the world. The spreading of pathogens became uncontrolled and unpredictable to overcome this pandemic disease. Some non-waterborne EID also was discovered in wastewater in many countries of the world. Studies showed that digital PCR could become a powerful tool for environmental surveillance. It enables the performance of absolute quantification for nucleic acid with a high inhibitory sample, like wastewater, and potentially possibly detected a tiny quantity of pathogen residue and tracked the infectious diseases that originated from human excretions into sewage. Hopefully, with the development of this method and support of measurement and standardization, it is possible to become an effective method to overcome the digital PCR (dPCR) method challenge for surveillance of disease transmission from wastewater.

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