scholarly journals Understanding how temperature shifts could impact infectious disease

PLoS Biology ◽  
2020 ◽  
Vol 18 (11) ◽  
pp. e3000938
Author(s):  
Jason R. Rohr ◽  
Jeremy M. Cohen
Keyword(s):  
Climate Change ◽  
Infectious Disease ◽  
Disease Risk ◽  
Disease Models ◽  
Disease Dynamics ◽  
The Past ◽  
New Information ◽  
Infectious Disease Dynamics ◽  
Human Infectious Disease

Climate change is expected to have complex effects on infectious diseases, causing some to increase, others to decrease, and many to shift their distributions. There have been several important advances in understanding the role of climate and climate change on wildlife and human infectious disease dynamics over the past several years. This essay examines 3 major areas of advancement, which include improvements to mechanistic disease models, investigations into the importance of climate variability to disease dynamics, and understanding the consequences of thermal mismatches between host and parasites. Applying the new information derived from these advances to climate–disease models and addressing the pressing knowledge gaps that we identify should improve the capacity to predict how climate change will affect disease risk for both wildlife and humans.

scholarly journals Identifying climate drivers of infectious disease dynamics: recent advances and challenges ahead

2017 ◽  
Vol 284 (1860) ◽  
pp. 20170901 ◽  
Author(s):  
C. Jessica E. Metcalf ◽  
Katharine S. Walter ◽  
Amy Wesolowski ◽  
Caroline O. Buckee ◽  
Elena Shevliakova ◽  
...  
Keyword(s):  
Climate Change ◽  
Infectious Disease ◽  
Indirect Effects ◽  
Disease Incidence ◽  
Climate Science ◽  
Health Impacts ◽  
Disease Dynamics ◽  
Direct Effects ◽  
Disease Biology ◽  
Infectious Disease Dynamics

Climate change is likely to profoundly modulate the burden of infectious diseases. However, attributing health impacts to a changing climate requires being able to associate changes in infectious disease incidence with the potentially complex influences of climate. This aim is further complicated by nonlinear feedbacks inherent in the dynamics of many infections, driven by the processes of immunity and transmission. Here, we detail the mechanisms by which climate drivers can shape infectious disease incidence, from direct effects on vector life history to indirect effects on human susceptibility, and detail the scope of variation available with which to probe these mechanisms. We review approaches used to evaluate and quantify associations between climate and infectious disease incidence, discuss the array of data available to tackle this question, and detail remaining challenges in understanding the implications of climate change for infectious disease incidence. We point to areas where synthesis between approaches used in climate science and infectious disease biology provide potential for progress.

scholarly journals Modelling the influence of human behaviour on the spread of infectious diseases: a review

2010 ◽  
Vol 7 (50) ◽  
pp. 1247-1256 ◽  
Author(s):  
Sebastian Funk ◽  
Marcel Salathé ◽  
Vincent A. A. Jansen
Keyword(s):  
Infectious Disease ◽  
Experimental Study ◽  
Infectious Diseases ◽  
Systematic Investigation ◽  
Human Behaviour ◽  
Disease Models ◽  
Disease Dynamics ◽  
Behavioural Responses ◽  
Infectious Disease Dynamics ◽  
Source Of Information

Human behaviour plays an important role in the spread of infectious diseases, and understanding the influence of behaviour on the spread of diseases can be key to improving control efforts. While behavioural responses to the spread of a disease have often been reported anecdotally, there has been relatively little systematic investigation into how behavioural changes can affect disease dynamics. Mathematical models for the spread of infectious diseases are an important tool for investigating and quantifying such effects, not least because the spread of a disease among humans is not amenable to direct experimental study. Here, we review recent efforts to incorporate human behaviour into disease models, and propose that such models can be broadly classified according to the type and source of information which individuals are assumed to base their behaviour on, and according to the assumed effects of such behaviour. We highlight recent advances as well as gaps in our understanding of the interplay between infectious disease dynamics and human behaviour, and suggest what kind of data taking efforts would be helpful in filling these gaps.

scholarly journals Marine infectious disease dynamics and outbreak thresholds: contact transmission, pandemic infection, and the potential role of filter feeders

Ecosphere ◽  
2016 ◽  
Vol 7 (4) ◽  
Author(s):  
Gorka Bidegain ◽  
Eric N. Powell ◽  
John M. Klinck ◽  
Tal Ben‐Horin ◽  
Eileen E. Hofmann
Keyword(s):  
Infectious Disease ◽  
Potential Role ◽  
Disease Dynamics ◽  
Contact Transmission ◽  
Filter Feeders ◽  
Infectious Disease Dynamics

scholarly journals Real-time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model

Epidemics ◽  
2018 ◽  
Vol 22 ◽  
pp. 56-61 ◽  
Author(s):  
Sebastian Funk ◽  
Anton Camacho ◽  
Adam J. Kucharski ◽  
Rosalind M. Eggo ◽  
W. John Edmunds
Keyword(s):  
Infectious Disease ◽  
Real Time ◽  
Mechanistic Model ◽  
Disease Dynamics ◽  
Infectious Disease Dynamics

scholarly journals Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics

2019 ◽  
Vol 7 (8) ◽  
pp. 277
Author(s):  
Yong-jun Chen ◽  
Qing Liu ◽  
Cheng-peng Wan
Keyword(s):  
Infectious Disease ◽  
Risk Factors ◽  
Causal Model ◽  
Cloud Model ◽  
Rapid Development ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
Disease Dynamics ◽  
Transmission Process ◽  
Infectious Disease Dynamics

Accidents occur frequently in traffic-intensive waters, which restrict the safe and rapid development of the shipping industry. Due to the suddenness, randomness, and uncertainty of accidents in traffic-intensive waters, the probability of the risk factors causing traffic accidents is usually high. Thus, properly analyzing those key risk factors is of great significance to improve the safety of shipping. Based on the analysis of influencing factors of ship navigational risks in traffic-intensive waters, this paper proposes a cloud model to excavate the factors affecting navigational risk, which could accurately screen out the key risk factors. Furthermore, the risk causal model of ship navigation in traffic-intensive waters is constructed by using the infectious disease dynamics method in order to model the key risk causal transmission process. Moreover, an empirical study of the Yangtze River estuary is conducted to illustrate the feasibility of the proposed models. The research results show that the cloud model is useful in screening the key risk factors, and the constructed causal model of ship navigational risks in traffic-intensive waters is able to provide accurate analysis of the transmission process of key risk factors, which can be used to reduce the navigational risk of ships in traffic-intensive waters. This research provides both theoretical basis and practical reference for regulators in the risk management and control of ships in traffic-intensive waters.

scholarly journals Game theoretic modelling of infectious disease dynamics and intervention methods: a review

2020 ◽  
Vol 14 (1) ◽  
pp. 57-89 ◽  
Author(s):  
Sheryl L. Chang ◽  
Mahendra Piraveenan ◽  
Philippa Pattison ◽  
Mikhail Prokopenko
Keyword(s):  
Infectious Disease ◽  
Disease Dynamics ◽  
Game Theoretic ◽  
Infectious Disease Dynamics

scholarly journals Using GPS Technology to Quantify Human Mobility, Dynamic Contacts and Infectious Disease Dynamics in a Resource-Poor Urban Environment

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e58802 ◽  
Author(s):  
Gonzalo M. Vazquez-Prokopec ◽  
Donal Bisanzio ◽  
Steven T. Stoddard ◽  
Valerie Paz-Soldan ◽  
Amy C. Morrison ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Urban Environment ◽  
Human Mobility ◽  
Disease Dynamics ◽  
Gps Technology ◽  
Resource Poor ◽  
Infectious Disease Dynamics
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