scholarly journals Infectious diseases and social distancing in nature

Science ◽  
2021 ◽  
Vol 371 (6533) ◽  
pp. eabc8881 ◽  
Author(s):  
Sebastian Stockmaier ◽  
Nathalie Stroeymeyt ◽  
Eric C. Shattuck ◽  
Dana M. Hawley ◽  
Lauren Ancel Meyers ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Social Behavior ◽  
Infectious Diseases ◽  
Social Interactions ◽  
Disease Spread ◽  
Social Distancing ◽  
Nonhuman Animals ◽  
Underlying Mechanisms ◽  
Induced Changes

Spread of contagious pathogens critically depends on the number and types of contacts between infectious and susceptible hosts. Changes in social behavior by susceptible, exposed, or sick individuals thus have far-reaching downstream consequences for infectious disease spread. Although “social distancing” is now an all too familiar strategy for managing COVID-19, nonhuman animals also exhibit pathogen-induced changes in social interactions. Here, we synthesize the effects of infectious pathogens on social interactions in animals (including humans), review what is known about underlying mechanisms, and consider implications for evolution and epidemiology.

scholarly journals Drivers of Infectious Disease Seasonality: Potential Implications for COVID-19

2021 ◽  
pp. 074873042098732
Author(s):  
N. Kronfeld-Schor ◽  
T. J. Stevenson ◽  
S. Nickbakhsh ◽  
E. S. Schernhammer ◽  
X. C. Dopico ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Multidisciplinary Approach ◽  
Preliminary Assessment ◽  
Epidemiological Evidence ◽  
Wide Range ◽  
Human Coronaviruses ◽  
Induced Changes ◽  
And Behavior ◽  
Timing Phase

Not 1 year has passed since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). Since its emergence, great uncertainty has surrounded the potential for COVID-19 to establish as a seasonally recurrent disease. Many infectious diseases, including endemic human coronaviruses, vary across the year. They show a wide range of seasonal waveforms, timing (phase), and amplitudes, which differ depending on the geographical region. Drivers of such patterns are predominantly studied from an epidemiological perspective with a focus on weather and behavior, but complementary insights emerge from physiological studies of seasonality in animals, including humans. Thus, we take a multidisciplinary approach to integrate knowledge from usually distinct fields. First, we review epidemiological evidence of environmental and behavioral drivers of infectious disease seasonality. Subsequently, we take a chronobiological perspective and discuss within-host changes that may affect susceptibility, morbidity, and mortality from infectious diseases. Based on photoperiodic, circannual, and comparative human data, we not only identify promising future avenues but also highlight the need for further studies in animal models. Our preliminary assessment is that host immune seasonality warrants evaluation alongside weather and human behavior as factors that may contribute to COVID-19 seasonality, and that the relative importance of these drivers requires further investigation. A major challenge to predicting seasonality of infectious diseases are rapid, human-induced changes in the hitherto predictable seasonality of our planet, whose influence we review in a final outlook section. We conclude that a proactive multidisciplinary approach is warranted to predict, mitigate, and prevent seasonal infectious diseases in our complex, changing human-earth system.

scholarly journals Emerging infectious disease and the challenges of social distancing in human and non-human animals

2020 ◽  
Vol 287 (1932) ◽  
pp. 20201039 ◽  
Author(s):  
Andrea K. Townsend ◽  
Dana M. Hawley ◽  
Jessica F. Stephenson ◽  
Keelah E. G. Williams
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Social Behaviour ◽  
Emerging Infectious Diseases ◽  
Group Living ◽  
Emerging Diseases ◽  
Behavioural Plasticity ◽  
Social Distancing ◽  
The Social ◽  
Social Animals

The ‘social distancing’ that occurred in response to the COVID-19 pandemic in humans provides a powerful illustration of the intimate relationship between infectious disease and social behaviour in animals. Indeed, directly transmitted pathogens have long been considered a major cost of group living in humans and other social animals, as well as a driver of the evolution of group size and social behaviour. As the risk and frequency of emerging infectious diseases rise, the ability of social taxa to respond appropriately to changing infectious disease pressures could mean the difference between persistence and extinction. Here, we examine changes in the social behaviour of humans and wildlife in response to infectious diseases and compare these responses to theoretical expectations. We consider constraints on altering social behaviour in the face of emerging diseases, including the lack of behavioural plasticity, environmental limitations and conflicting pressures from the many benefits of group living. We also explore the ways that social animals can minimize the costs of disease-induced changes to sociality and the unique advantages that humans may have in maintaining the benefits of sociality despite social distancing.

scholarly journals Extended urbanisation and the spatialities of infectious disease: Demographic change, infrastructure and governance

Urban Studies ◽  
2020 ◽  
pp. 004209802091087 ◽  
Author(s):  
Creighton Connolly ◽  
Roger Keil ◽  
S. Harris Ali
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Political Ecology ◽  
Demographic Change ◽  
Disease Spread ◽  
Future Research ◽  
Suburban Areas ◽  
Urban Edge ◽  
Increased Risk ◽  
Health And Disease

This paper argues that contemporary processes of extended urbanisation, which include suburbanisation, post-suburbanisation and peri-urbanisation, may result in increased vulnerability to infectious disease spread. Through a review of existing literature at the nexus of urbanisation and infectious disease, we consider how this (potential) increased vulnerability to infectious diseases in peri- or suburban areas is in fact dialectically related to socio-material transformations on the metropolitan edge. In particular, we highlight three key factors influencing the spread of infectious disease that have been identified in the literature: demographic change, infrastructure and governance. These have been chosen given both the prominence of these themes and their role in shaping the spread of disease on the urban edge. Further, we suggest how a landscape political ecology framework can be useful for examining the role of socio-ecological transformations in generating increased risk of infectious disease in peri- and suburban areas. To illustrate our arguments we will draw upon examples from various re-emerging infectious disease events and outbreaks around the world to reveal how extended urbanisation in the broadest sense has amplified the conditions necessary for the spread of infectious diseases. We thus call for future research on the spatialities of health and disease to pay attention to how variegated patterns of extended urbanisation may influence possible outbreaks and the mechanisms through which such risks can be alleviated.

scholarly journals Brain games: Toward a neuroecology of social behavior

2013 ◽  
Vol 36 (4) ◽  
pp. 424-425 ◽  
Author(s):  
Jean-François Gariépy ◽  
Steve W. C. Chang ◽  
Michael L. Platt
Keyword(s):  
Social Cognition ◽  
Social Behavior ◽  
Social Interactions ◽  
Behavioral Ecology ◽  
Neural Basis ◽  
Second Person ◽  
Target Article ◽  
Nonhuman Animals

AbstractIn the target article, Schilbach et al. defend a “second-person neuroscience” perspective that focuses on the neural basis of social cognition during live, ongoing interactions between individuals. We argue that a second-person neuroscience would benefit from formal approaches borrowed from economics and behavioral ecology and that it should be extended to social interactions in nonhuman animals.

scholarly journals Impact of Social Distancing on COVID-19 and Other Related Infectious Disease Transmission: A Systematic Review

2021 ◽  
Vol 9 (F) ◽  
pp. 601-607
Author(s):  
Nor Rumaizah Mohd Nordin ◽  
Fadly Syah Arsad ◽  
Puteri Sofia Nadira Megat Kamaruddin ◽  
Muhammad Hilmi ◽  
Mohd Faizal Madrim ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
South Korea ◽  
Disease Transmission ◽  
Research Question ◽  
Control Measures ◽  
Physical Contact ◽  
Infectious Disease Transmission ◽  
Social Distancing ◽  
The Impact

Background   Similar to other coronaviruses, COVID-19 is transmitted mainly by droplets and is highly transmissible through close proximity or physical contact with an infected person. Countries across the globe have implemented public health control measures to prevent onwards transmission and reduce burden on health care settings. Social or physical distancing was found to be one of appropriate measure based on previous experience with epidemic and pandemic contagious diseases. This study aims to review the latest evidence of the impact of social or physical distancing implemented during COVID-19 pandemic towards COVID-19 and other related infectious disease transmission.   Methodology   The study uses PRISMA review protocol and formulation of research question was based on PICO. The selected databases include Ovid MEDLINE and Scopus. Thorough identification, screening and eligibility process were done, revealed selected 8 articles. The articles then ranked in quality through MMAT.   Results   A total of eight papers included in this analysis. Five studies (USA, Canada, South Korea and the United Kingdom) showed physical distancing had resulted in a reduction in Covid-19 transmission. In comparison, three other studies (Australia, South Korea and Finland) showed a similar decline on other infectious diseases (Human Immunodeficiency Virus (HIV), other sexually transmitted infections (STI), Influenza, Respiratory Syncytial Virus (RSV) and Vaccine-Preventive Disease (VPD). The degree of the distancing policy implemented differ between strict and lenient, with both result in effectiveness in reducing transmission of infectious disease.   Conclusion   Physical or social distancing may come in the form of extreme or lenient measure in effectively containing contagious disease like COVID-19, however the stricter the measure will give more proportionate impact towards the economy, education, mental health issues, morbidity and mortality of non-COVID-19 diseases. Since we need this measure to ensure the reduction of infectious diseases transmission in order to help flattening the curve which allow much needed time for healthcare system to prepare adequately to response, ‘Precision physical distancing” can be implemented which will have more benefit towards the survival of the community as a whole.

scholarly journals SOCIAL NETWORK ANALYSIS OF SPATIAL HUMAN MOBILITY BEHAVIOUR IN INFECTIOUS DISEASE INTERACTION: AN EXPLORATORY EVIDENCE OF TUBERCULOSIS IN MALAYSIA

2021 ◽  
Vol XLIII-B4-2021 ◽  
pp. 55-61
Author(s):  
I. Abdul Jalil ◽  
A. R. Abdul Rasam
Keyword(s):  
Infectious Disease ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Infectious Diseases ◽  
Network Structure ◽  
Human Mobility ◽  
Disease Spread ◽  
The Social ◽  
Mobility Behaviour

Abstract. The movement of individuals between specific locations and the different group contacts of people is essential to predict the future movement and interaction pattern of infectious diseases. Previous studies have shown major factor of infectious disease spread comes from human mobility because a complex and dynamic network of spatial interactions between locations such as the mobility formed by the daily activity of people from place to place. To better understand the such human mobility behaviour, innovative methods are required to depict and analyse their structures by using social network analysis (SNA). This paper aims to investigate the social network structure of selected tuberculosis (TB) case in Klang, Selangor as actors (nodes), and then human mobility (home-work place) data as edge generally used to investigate social network mobility structures and analyse relation among the nodes and study their edges in term of their network centrality. The main finding has revealed that the higher the centrality (degree and betweenness) of a node in the network structure, the higher the chance the node influencing the TB spread in the whole network, after comparing the network graph result with the geographic information system (GIS) mapping approach. Most of the result share the similar result where most of high infection of TB are located in urban and crowded areas. The SNA is a practical knowledge of the social system and contact structure of a community that can therefore provide crucial information to predict outbreaks of infectious diseases in a dynamic spatial phenomena.

Paleoepidemiological Considerations of Mobility and Population Interaction in the Spread of Infectious Diseases in the Prehistoric Past

2021 ◽  
Author(s):  
Melandri Vlok ◽  
Hallie Buckley
Keyword(s):  
Infectious Disease ◽  
Population Density ◽  
Infectious Diseases ◽  
Residential Mobility ◽  
Human Interaction ◽  
Disease Spread ◽  
Relative Risk Ratio ◽  
Disease Patterns ◽  
Population Interaction ◽  
The Impact

The processes of human mobility have been well demonstrated to influence the spread of infectious disease globally in the present and the past. However, to date, paleoepidemiological research has focused more on factors of residential mobility and population density as drivers for epidemiological shifts in prehistoric infectious disease patterns. A strong body of epidemiological literature exists for the dynamics of infectious disease spread through networks of mobility and interaction. We review the epidemiological theory of infectious disease spread and propose frameworks for application of this theory to bioarchaeology. We outline problems with current definitions of prehistoric mobility and propose a framework shift with focus on population interactions as nodes for disease transmission. To conceptualize this new framework, we produced a theoretical model that considers the interplay between climate suitability, population density, residential mobility, and human interaction levels to influence infectious disease patterns in prehistoric assemblages. We then tested observable effects of this model in paleoepidemiological data from Asia (n = 343). Relative risk ratio analysis and correlations were used to test the impact of population interaction, residential mobility, population density, climate, and subsistence on the prevalence and diversity of infectious diseases. Our statistical results showed higher levels of population interaction led to significantly higher prevalence of infectious disease in sedentary populations and a significant increase in pathogen diversity in mobile populations. We recommend that population interaction be included as an important component of infectious disease analysis of prehistoric population health alongside other biosocial factors, such as sedentism and population density.   Daar is goed gedemonstreer dat die prosesse van menslike mobiliteit die verspreiding van aansteeklike siektes wêreldwyd in die hede en in die verlede beïnvloed. Maar tot op hede het paleo-epidemiologiese navorsing egter meer gefokus op faktore van residensiële mobiliteit en bevolkingsdigtheid as dryfvere vir epidemiologiese verskuiwings in die prehistoriese infeksiesiektepatrone. Sterk epidemiologiese literatuur bestaan vir die dinamika van aansteeklike siektes wat versprei word deur netwerke van mobiliteit en interaksie. Ons ondersoek die epidemiologiese teorie van die verspreiding van aansteeklike siektes en stel raamwerke voor vir die toepassing van hierdie teorie op die bioargeologie. Ons skets probleme met huidige definisies van prehistoriese mobiliteit en stel ‘n raamwerk verskuiwing voor met die fokus op bevolkings-interaksies as nodusse vir oordrag van siektes. Om hierdie nuwe raamwerk te konseptualiseer, het ons ‘n teoretiese model vervaardig wat die wisselwerking tussen klimaatsgeskiktheid, bevolkingsdigtheid, residensiële mobiliteit en menslike interaksievlakke oorweeg om die infeksiesiektepatrone in prehistoriese samestellings te beïnvloed. Daarna het ons die waarneembare effekte van hierdie model getoets in paleo-epidemiologiese data uit Asië (n = 343). Relatiewe risiko-verhoudingsanalise en korrelasies is gebruik om die impak van bevolkings-interaksie, residensiële mobiliteit, bevolkingsdigtheid, klimaat en bestaan op die voorkoms en diversiteit van aansteeklike siektes te toets. Ons statistiese resultate het gedemonstreer dat hoër vlakke van bevolkings-interaksie gelei het tot aansienlik hoër voorkoms van aansteeklike siektes in sittende bevolkings en ‘n beduidende toename in patogeen diversiteit in mobiele bevolkings. Ons beveel aan dat bevolkings-interaksie ingesluit word as ‘n belangrike komponent van die aantstekingsiekte-ontleding van die prehistoriese bevolkingsgesondheid, tesame met ander biososiale faktore soos sedentisme en bevolkingsdigtheid.

scholarly journals A model for the co-evolution of dynamic social networks and infectious disease dynamics

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hendrik Nunner ◽  
Vincent Buskens ◽  
Mirjam Kretzschmar
Keyword(s):  
Infectious Disease ◽  
Social Networks ◽  
Social Network ◽  
Health Behavior ◽  
Infectious Diseases ◽  
Network Formation ◽  
Disease Spread ◽  
Disease Dynamics ◽  
Dynamic Social Networks ◽  
Infectious Disease Dynamics

AbstractRecent research shows an increasing interest in the interplay of social networks and infectious diseases. Many studies either neglect explicit changes in health behavior or consider networks to be static, despite empirical evidence that people seek to distance themselves from diseases in social networks. We propose an adaptable steppingstone model that integrates theories of social network formation from sociology, risk perception from health psychology, and infectious diseases from epidemiology. We argue that networking behavior in the context of infectious diseases can be described as a trade-off between the benefits, efforts, and potential harm a connection creates. Agent-based simulations of a specific model case show that: (i) high (perceived) health risks create strong social distancing, thus resulting in low epidemic sizes; (ii) small changes in health behavior can be decisive for whether the outbreak of a disease turns into an epidemic or not; (iii) high benefits for social connections create more ties per agent, providing large numbers of potential transmission routes and opportunities for the disease to travel faster, and (iv) higher costs of maintaining ties with infected others reduce final size of epidemics only when benefits of indirect ties are relatively low. These findings suggest a complex interplay between social network, health behavior, and infectious disease dynamics. Furthermore, they contribute to solving the issue that neglect of explicit health behavior in models of disease spread may create mismatches between observed transmissibility and epidemic sizes of model predictions.

scholarly journals Smart System to Monitor Social-Distancing During the Covid-19 Pandemic

2020 ◽  
Author(s):  
Omar Elharrouss ◽  
Noor Al-Maadeed ◽  
Khalid Abualsaud ◽  
Amr Mahmoud ◽  
Tamer Khattab ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Computer Vision ◽  
Real Time ◽  
Video Surveillance ◽  
Social Distance ◽  
Moving Objects ◽  
Physical Distance ◽  
Disease Spread ◽  
Smart System ◽  
Social Distancing

We introduce a smart system to track and maintain real-time physical distance between people and to warn people over any deviation from the prescribed distances. Social-distancing is an effective way of slowing infectious disease spread. People are advised to reduce their contacts with each other, thus reducing the chances of transmitting the disease through physical or near contact. We proposed a system to automate the task of tracking social distance using video surveillance and sensors. The system can be used to detect moving objects and measure distance between people. The system collected sensor environmental information for commercial, industrial and governmental purposes. Furthermore we are using drown to detect crowded area. The accuracy of detection using sensors can be helpful when it combined with the camera for computer vision task in terms of visualization using camera and rebuses of detection using sensor. Both camera and sensor gauge the environment to detect moving objects simultaneously.

scholarly journals SIM-D: An Agent-Based Simulator for Modeling Contagion in Population

2020 ◽  
Vol 10 (21) ◽  
pp. 7745
Author(s):  
Muhammad Waleed ◽  
Tai-Won Um ◽  
Tariq Kamal ◽  
Aftab Khan ◽  
Zaka Ullah Zahid
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Infectious Diseases ◽  
Close Contact ◽  
Disease Spread ◽  
Agent Based ◽  
Disease States ◽  
Simulation Engine ◽  
Health Authorities ◽  
Public Health Authorities

The spread of infectious diseases such as COVID-19, flu influenza, malaria, dengue, mumps, and rubella in a population is a big threat to public health. The infectious diseases spread from one person to another person through close contact. Without proper planning, an infectious disease can become an epidemic and can result in large human and financial losses. To better respond to the spread of infectious disease and take measures for its control, the public health authorities need models and simulations to study the spread of such diseases. In this paper, an agent-based simulation engine is presented that models the spread of infectious diseases in the population. The simulation takes as an input the human-to-human interactions, population dynamics, disease transmissibility and disease states and shows the spread of disease over time. The simulation engine supports non-pharmaceutical interventions and shows its impact on the disease spread across locations. A unique feature of this tool is that it is generic; therefore, it can simulate a wide variety of infectious disease models (SIR), susceptible-infectious-susceptible (SIS) and susceptible-infectious (SI). The proposed simulation engine will help the policy-makers and public health authorities study the behavior of disease spreading; thus, allowing for better planning.

Sign in / Sign up

Export Citation Format

Share Document