scholarly journals Behavioural phenotypes predict disease susceptibility and infectiousness

2016 ◽  
Vol 12 (8) ◽  
pp. 20160480 ◽  
Author(s):  
Alessandra Araujo ◽  
Lucas Kirschman ◽  
Robin W. Warne
Keyword(s):  
Inverse Relationship ◽  
Disease Susceptibility ◽  
Disease Outbreaks ◽  
Disease Spread ◽  
Viral Shedding ◽  
Larval Amphibians ◽  
Behavioural Phenotypes ◽  
Experimental Trials ◽  
Conspecific Interactions ◽  
Pathogenic Infection

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans.

scholarly journals A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China

10.2196/21685 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e21685
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  
Keyword(s):  
Public Health ◽  
Information And Communication Technologies ◽  
Ethical Issues ◽  
Rapid Development ◽  
Disease Outbreaks ◽  
Face Mask ◽  
Digital Data ◽  
Disease Spread ◽  
Health Measures ◽  
Digital Epidemiology

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

scholarly journals Host size and proximity to diseased neighbours drive the spread of a coral disease outbreak in Hawai‘i

2018 ◽  
Vol 285 (1870) ◽  
pp. 20172265 ◽  
Author(s):  
Jamie M. Caldwell ◽  
Megan J. Donahue ◽  
C. Drew Harvell
Keyword(s):  
Disease Risk ◽  
Coral Disease ◽  
Disease Outbreaks ◽  
Disease Outbreak ◽  
Host Size ◽  
Disease Spread ◽  
Wildlife Diseases ◽  
Infectious Individual ◽  
Force Of Infection ◽  
Affected Tissue

Understanding how disease risk varies over time and across heterogeneous populations is critical for managing disease outbreaks, but this information is rarely known for wildlife diseases. Here, we demonstrate that variation in host and pathogen factors drive the direction, duration and intensity of a coral disease outbreak. We collected longitudinal health data for 200 coral colonies, and found that disease risk increased with host size and severity of diseased neighbours, and disease spread was highest among individuals between 5 and 20 m apart. Disease risk increased by 2% with every 10 cm increase in host size. Healthy colonies with severely diseased neighbours (greater than 75% affected tissue) were 1.6 times more likely to develop disease signs compared with colonies with moderately diseased neighbours (25–75% affected tissue). Force of infection ranged from 7 to 20 disease cases per 1000 colonies (mean = 15 cases per 1000 colonies). The effective reproductive ratio, or average number of secondary infections per infectious individual, ranged from 0.16 to 1.22. Probability of transmission depended strongly on proximity to diseased neighbours, which demonstrates that marine disease spread can be highly constrained within patch reefs.

scholarly journals African swine fever virus – the possible role of flies and other insects in virus transmission

2020 ◽  
Vol 64 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Mateusz Fila ◽  
Grzegorz Woźniakowski
Keyword(s):  
African Swine Fever Virus ◽  
Animal Health ◽  
Virus Transmission ◽  
Disease Outbreaks ◽  
African Swine Fever ◽  
Disease Spread ◽  
The Baltic ◽  
Haemorrhagic Disease ◽  
And Control

AbstractAfrican swine fever (ASF) is an acute viral haemorrhagic disease of pigs and wild boars. It presents a serious threat to pig production worldwide, and since 2007, ASF outbreaks have been recorded in the Caucasus, Eastern Europe, and the Baltic States. In 2014, the disease was detected in Poland. ASF is on the list of notifiable diseases of the World Organisation for Animal Health (OIE). Due to the lack of an available vaccine and treatment, the countermeasures against the disease consist in early detection of the virus in the pig population and control of its spread through the elimination of herds affected by disease outbreaks. Knowledge of the potential vectors of the virus and its persistence in the environment is crucial to prevent further disease spread and to understand the new epidemiology for how it compares to the previous experience in Spain gathered in the 1970s and 1980s.

scholarly journals The impact of community containment implementation timing on the spread of COVID-19: A simulation study

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 452 ◽  
Author(s):  
Attayeb Mohsen ◽  
Ahmed Alarabi
Keyword(s):  
Simulation Model ◽  
Disease Outbreaks ◽  
Simulation Method ◽  
Final Outcome ◽  
Disease Spread ◽  
Network Graph ◽  
Real World Data ◽  
Infectious Disease Outbreaks ◽  
Spread Parameters ◽  
The Impact

Background: Community containment is one of the common methods used to mitigate infectious disease outbreaks. The effectiveness of such a method depends on how strictly it is applied and the timing of its implementation. An early start and being strict is very effective; however, at the same time, it impacts freedom and economic opportunity. Here we created a simulation model to understand the effect of the starting day of community containment on the final outcome, that is, the number of those infected, hospitalized and those that died, as we followed the dynamics of COVID-19 pandemic. Methods: We used a stochastic recursive simulation method to apply disease outbreak dynamics measures of COVID-19 as an example to simulate disease spread. Parameters are allowed to be randomly assigned between higher and lower values obtained from published COVID-19 literature. Results: We simulated the dynamics of COVID-19 spread, calculated the number of active infections, hospitalizations and deaths as the outcome of our simulation and compared these results with real world data. We also represented the details of the spread in a network graph structure, and shared the code for the simulation model to be used for examining other variables. Conclusions: Early implementation of community containment has a big impact on the final outcome of an outbreak.

scholarly journals A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China (Preprint)

2020 ◽  
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  
Keyword(s):  
Public Health ◽  
Information And Communication Technologies ◽  
Ethical Issues ◽  
Rapid Development ◽  
Disease Outbreaks ◽  
Face Mask ◽  
Digital Data ◽  
Disease Spread ◽  
Health Measures ◽  
Digital Epidemiology

UNSTRUCTURED A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

scholarly journals Towards a quantitative model of epidemics during conflicts

2019 ◽  
Author(s):  
Soumya Banerjee
Keyword(s):  
Public Health ◽  
Disease Outbreaks ◽  
Integrated Approach ◽  
Quantitative Model ◽  
Disease Spread ◽  
Mathematical Framework ◽  
Health Measures ◽  
Conflict Zone ◽  
Socio Economic Development

Epidemics may both contribute to and arise as a result of conflict. The effects of conflict on infectious diseases are complex and there have been confounding observations of both increase and decrease in disease outbreaks during and after conflicts. However there is no unified mathematical model that explains all these counter-intuitive observations. There is an urgent need for a quantitative framework for modelling conflicts and epidemics. We introduce a set of mathematical models to understand the role of conflicts in epidemics. Our mathematical framework has the potential to explain the counterintuitive observations and the complex role of human conflicts in epidemics. Our work suggests that aid and peacekeeping organizations should take an integrated approach that combines public health measures, socio-economic development, and peacekeeping in the conflict zone. Our approach exemplifies the role of non-linear thinking in complex systems like human societies. We view our work as a step towards a quantitative model of disease spread in conflicts.

scholarly journals SARS-COV-2 and Ocular Surface: From Physiology to Pathology, a Route to Understand Transmission and Disease

2021 ◽  
Vol 12 ◽  
Author(s):  
Dalton de Freitas Santoro ◽  
Luciene Barbosa de Sousa ◽  
Niels O. S. Câmara ◽  
Denise de Freitas ◽  
Lauro Augusto de Oliveira
Keyword(s):  
Ocular Surface ◽  
Middle Eastern ◽  
Tear Film ◽  
Disease Spread ◽  
Secretory Iga ◽  
Public Attention ◽  
Level Of Evidence ◽  
Viral Shedding ◽  
Human Contact ◽  
Protective Environment

Coronaviruses gained public attention during the severe acute respiratory syndrome (SARS) outbreak in East Asia in 2003 and spread of Middle Eastern respiratory syndrome (MERS) in 2012. Direct human-to-human contact and droplet are the main methods of transmission. Viral stability in aerosols on different surfaces supports evidence on indirect viral acquisition from fomites through the mucous membranes of the mouth, nose, and eyes. Given the pandemic circumstances, the level of evidence in COVID-19 and ophthalmology regarding eye infection, conjunctival transmission, and viral shedding through tears is insufficient. Presently, conjunctival transmission of coronaviruses has not been confirmed and remains controversial. Considering the physiology of the lacrimal system and ocular surface, the eyes are considered an immunoprotective site, with several antiviral molecules and anti-inflammatory proteins. Nevertheless, they represent an interface with the exterior world and face daily putative aggressors. Understanding the host’s ocular surface immunological and protective environment is crucial to clarify the potential of the conjunctiva as an entry route for SARS-CoV-2 and as part of this viral infection. We will discuss hypothetical ocular surface transmission mechanisms and related counterarguments addressed to both angiotensin-converting enzyme 2 receptors found on the conjunctival and corneal epithelia and lactoferrin, lysozyme, lipocalin and secretory IgA levels in the tear film. Hopefully, we will promote better understanding of this organ in COVID-19 infection and the potential transmission route that can be helpful in setting recommendations on best practices and protective guidelines to mitigate the disease spread.

Active Surveillance for COVID-19 through artificial intelligence using concept of real-time speech-recognition mobile application to analyse cough sound.

2020 ◽  
Author(s):  
MOHAMMAD ZAFAR IQBAL
Keyword(s):  
Artificial Intelligence ◽  
Speech Recognition ◽  
Real Time ◽  
Active Surveillance ◽  
Mobile Application ◽  
Disease Outbreaks ◽  
Viral Disease ◽  
Disease Spread ◽  
Healthcare Facilities ◽  
Routine Basis

In view of recent coronavirus (SARS-CoV2) outbreak, we propose a novel model of active surveillance for COVID-19 through artificial intelligence. Both past and recent events of viral disease outbreaks have shown us that we do not have effective methods to screen the whole population and efforts are failing to stop the pandemics. Moreover, at this stage, social distancing and home quarantine are only measures to stop the spread of COVID-19 infection. The purpose of our project is to introduce a robust method of using speech-recognition techniques through a mobile application in analysing cough sounds of suspected people, who previously were healthy, suffering from a respiratory ailment and actively monitor the progress of their symptoms in real-time. The mobile application will give feedback to the app users on a routine basis and advise to take medication and necessary precautions to avoid spreading of the infection. The app will also notify the local healthcare facilities about sick users or vice-versa if their symptoms deteriorates. A feedback will be sent to an app-centre notifying the number of both new and old sick users appeared in a particular region. With the data compiled at the app-centre, we will also be able to trace the disease spread patterns, categorise the regions in three levels- mild, moderate and severe based on the number of sick users and deploy the resources accordingly to stop the transmission hence, preventing unnecessary use of both human and medical resources to stop the infection in redundant regions.

scholarly journals Microbial dysbiosis reflects disease resistance in diverse coral species

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Nicholas J. MacKnight ◽  
Kathryn Cobleigh ◽  
Danielle Lasseigne ◽  
Andia Chaves-Fonnegra ◽  
Alexandra Gutting ◽  
...  
Keyword(s):  
Disease Susceptibility ◽  
Coral Species ◽  
Disease Incidence ◽  
Disease Outbreaks ◽  
Life History Strategies ◽  
Microbial Dysbiosis ◽  
White Plague ◽  
Caribbean Coral ◽  
Microbial Responses ◽  
Coral Communities

AbstractDisease outbreaks have caused significant declines of keystone coral species. While forecasting disease outbreaks based on environmental factors has progressed, we still lack a comparative understanding of susceptibility among coral species that would help predict disease impacts on coral communities. The present study compared the phenotypic and microbial responses of seven Caribbean coral species with diverse life-history strategies after exposure to white plague disease. Disease incidence and lesion progression rates were evaluated over a seven-day exposure. Coral microbiomes were sampled after lesion appearance or at the end of the experiment if no disease signs appeared. A spectrum of disease susceptibility was observed among the coral species that corresponded to microbial dysbiosis. This dysbiosis promotes greater disease susceptiblity in coral perhaps through different tolerant thresholds for change in the microbiome. The different disease susceptibility can affect coral’s ecological function and ultimately shape reef ecosystems.

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