Influences of habitat and arthropod density on parasitism in two co-occurring host taxa

2017 ◽  
Vol 95 (8) ◽  
pp. 589-597 ◽  
Author(s):  
J. Koprivnikar ◽  
T.M.Y. Urichuk ◽  
D. Szuroczki
Keyword(s):  
Infectious Diseases ◽  
Dilution Effect ◽  
Agricultural Activity ◽  
Disease Dynamics ◽  
Future Studies ◽  
Larval Amphibians ◽  
General Importance ◽  
Single Host ◽  
Lower Infection ◽  
Road Distance

Habitat attributes are known to influence infectious diseases such as those caused by parasites, but most studies have only considered single host and (or) parasite taxa, making it difficult to assess which features may be of general importance and to predict how alterations could affect disease dynamics. We examined infection with trematode (flatworm) parasites in two commonly co-occurring host taxa (larval amphibians and larval odonates (dragonflies and damselflies)) to investigate links with landscape-level features, including agricultural activity. We also assessed pond community composition with respect to the abundance and richness of aquatic arthropods known to prey upon tadpoles and (or) free-swimming trematode infectious stages. Larval amphibians from agricultural sites were most likely to be parasitized but had lower infection intensities, and infected hosts were positively associated with increasing distance to the nearest forest habitat, but negatively with road distance. The opposite was observed for larval odonate infection status; however, probability and intensity of parasitism in both host taxa was negatively associated with greater predatory arthropod abundance, consistent with the “dilution effect” of biodiversity on infectious diseases. Our approach demonstrates the importance of considering multiple host taxa when studying habitat links to diseases, and future studies incorporating even greater diversity will be needed.

Dilution effect of plant diversity on infectious diseases: latitudinal trend and biological context dependence

Oikos ◽  
2020 ◽  
Vol 129 (4) ◽  
pp. 457-465 ◽  
Author(s):  
Xiang Liu ◽  
Lifan Chen ◽  
Mu Liu ◽  
Graciela García‐Guzmán ◽  
Gregory S. Gilbert ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Plant Diversity ◽  
Dilution Effect ◽  
Context Dependence ◽  
Latitudinal Trend ◽  
Biological Context

scholarly journals Human infectious disease burdens decrease with urbanization but not with biodiversity

2017 ◽  
Vol 372 (1722) ◽  
pp. 20160122 ◽  
Author(s):  
Chelsea L. Wood ◽  
Alex McInturff ◽  
Hillary S. Young ◽  
DoHyung Kim ◽  
Kevin D. Lafferty
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Disease Transmission ◽  
Scientific Evidence ◽  
Dilution Effect ◽  
Policy Implications ◽  
Global Public Health ◽  
Country Level ◽  
Life Years ◽  
Over Time

Infectious disease burdens vary from country to country and year to year due to ecological and economic drivers. Recently, Murray et al. (Murray CJ et al . 2012 Lancet 380 , 2197–2223. ( doi:10.1016/S0140-6736(12)61689-4 )) estimated country-level morbidity and mortality associated with a variety of factors, including infectious diseases, for the years 1990 and 2010. Unlike other databases that report disease prevalence or count outbreaks per country, Murray et al. report health impacts in per-person disability-adjusted life years (DALYs), allowing comparison across diseases with lethal and sublethal health effects. We investigated the spatial and temporal relationships between DALYs lost to infectious disease and potential demographic, economic, environmental and biotic drivers, for the 60 intermediate-sized countries where data were available and comparable. Most drivers had unique associations with each disease. For example, temperature was positively associated with some diseases and negatively associated with others, perhaps due to differences in disease agent thermal optima, transmission modes and host species identities. Biodiverse countries tended to have high disease burdens, consistent with the expectation that high diversity of potential hosts should support high disease transmission. Contrary to the dilution effect hypothesis, increases in biodiversity over time were not correlated with improvements in human health, and increases in forestation over time were actually associated with increased disease burden. Urbanization and wealth were associated with lower burdens for many diseases, a pattern that could arise from increased access to sanitation and healthcare in cities and increased investment in healthcare. The importance of urbanization and wealth helps to explain why most infectious diseases have become less burdensome over the past three decades, and points to possible levers for further progress in improving global public health. This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications’.

Editor's choice: Disease dynamics in marine metapopulations: modelling infectious diseases on coral reefs

2009 ◽  
Vol 46 (3) ◽  
pp. 621-631 ◽  
Author(s):  
Susanne H. Sokolow ◽  
Patrick Foley ◽  
Janet E. Foley ◽  
Alan Hastings ◽  
Laurie L. Richardson
Keyword(s):  
Coral Reefs ◽  
Infectious Diseases ◽  
Disease Dynamics

scholarly journals THE DYNAMICS OF THE RISK OF THE MORBIDITY AND THE ADAPTATION PROCESS AS INDICES OF THE IMPACT OF LOCAL ENVIRONMENTAL FACTORS ON THE POPULATION

2018 ◽  
Vol 97 (2) ◽  
pp. 124-131 ◽  
Author(s):  
V. M. Prusakov ◽  
Aleksandra V. Prusakova
Keyword(s):  
High Risk ◽  
Environmental Factors ◽  
Infectious Diseases ◽  
Absolute Magnitude ◽  
The Body ◽  
Adaptation Process ◽  
Disease Dynamics ◽  
Local Factors ◽  
The Impact

There were studied: The role of the disease dynamics at the background area in the formation of the risk for childhood morbidity in the study area; the value of indices of the long-term wavelike risk dynamics and the corresponding adaptation process for the identification and classification of mass non-infectious diseases. The waviness dynamics of the children morbidity risk is caused by the wave-like nature of the disease dynamics in the study and background areas. The disease risk level is formed not only by differences in the incidence rates of the background and study areas but also from differences in phases of high and low non-specific resistance of children contingent in these territories. The different character of the dynamics of the risk for the disease and related waviness of the adaptation process among children reflects the existence of differences in exposure to characteristics of local environmental factors in each territory. The average risk of disease, around which there are carried out annual fluctuations risks and phase states of the adaptation process, and the corresponding levels of reactivity and resistance of the body are the result of the absolute magnitude of the impact of local factors on the study area. The average relative risk of the morbidity, around which there are carried out annual fluctuations risks and phase states of the adaptation process is an integral index of the level of mass non-infectious diseases and the degree of severity of the medical and environmental situation, the level of reactivity and work mismatch of the body subsystems of children and the degree of their intensity. This is the measure of the absolute magnitude of the impact of local factors. The waviness to the development of states of high and low resistance is both always an index of antistress activation responses (or non-specifically high resistance state) and relative to the average force of impact factors (for the observed reactivity level). On the basis of the accounting for the level of the risk, there is suggested the classification of infectious diseases, including 1) the background or relatively satisfactory morbidity, 2) mass morbidity with the increased risk, 3) mass incidence of the high-risk, and 4) a mass incidence of the very high risk.

scholarly journals Stochastic dynamics of an epidemics with recurrent spillovers from an endemic reservoir

2017 ◽  
Author(s):  
Marina Voinson ◽  
Alexandra Alvergne ◽  
Sylvain Billiard ◽  
Charline Smadi
Keyword(s):  
Infectious Diseases ◽  
Stochastic Dynamics ◽  
Emerging Infectious Diseases ◽  
Recurrent Infection ◽  
Zoonotic Diseases ◽  
Animal Origin ◽  
Direct Transmission ◽  
Modes Of Transmission ◽  
Single Host ◽  
Incidental Host

AbstractMost emerging human infectious diseases have an animal origin. Yet, while zoonotic diseases originate from a primary reservoir, most theoretical studies have principally focused on single-host processes, either exclusively humans or exclusively animals, without considering the importance of animal to human transmission for understanding the dynamics of emerging infectious diseases. Here we aim to investigate the importance of spillover transmission for explaining the number and the size of outbreaks. We propose a simple stochastic Susceptible-Infected-Recovered model with a recurrent infection of an incidental host from a reservoir (e.g. humans by a zoonotic species), considering two modes of transmission, (1) animal-to-human and (2) human-to-human. The model assumes that (i) epidemiological processes are faster than other processes such as demographics or pathogen evolution and (ii) that an epidemic occurs until there are no susceptible individuals left. The results show that during an epidemic, even when the pathogens are barely contagious, multiple outbreaks are observed due to spillover transmission. Overall, the findings demonstrate that the only consideration of direct transmission between individuals is not sufficient to explain the dynamics of zoonotic pathogens in an incidental host.

scholarly journals Comparing metapopulation dynamics of infectious diseases under different models of human movement

2021 ◽  
Vol 118 (18) ◽  
pp. e2007488118
Author(s):  
Daniel T. Citron ◽  
Carlos A. Guerra ◽  
Andrew J. Dolgert ◽  
Sean L. Wu ◽  
John M. Henry ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Human Movement ◽  
Global Scale ◽  
Disease Dynamics ◽  
Movement Model ◽  
Bioko Island ◽  
Geographical Distances ◽  
Infectious Disease Dynamics ◽  
Human Population Movement

Newly available datasets present exciting opportunities to investigate how human population movement contributes to the spread of infectious diseases across large geographical distances. It is now possible to construct realistic models of infectious disease dynamics for the purposes of understanding global-scale epidemics. Nevertheless, a remaining unanswered question is how best to leverage the new data to parameterize models of movement, and whether one’s choice of movement model impacts modeled disease outcomes. We adapt three well-studied models of infectious disease dynamics, the susceptible–infected–recovered model, the susceptible–infected–susceptible model, and the Ross–Macdonald model, to incorporate either of two candidate movement models. We describe the effect that the choice of movement model has on each disease model’s results, finding that in all cases, there are parameter regimes where choosing one movement model instead of another has a profound impact on epidemiological outcomes. We further demonstrate the importance of choosing an appropriate movement model using the applied case of malaria transmission and importation on Bioko Island, Equatorial Guinea, finding that one model produces intelligible predictions of R0, whereas the other produces nonsensical results.

Timing and order of exposure to two echinostome species affect patterns of infection in larval amphibians

Parasitology ◽  
2020 ◽  
Vol 147 (13) ◽  
pp. 1515-1523
Author(s):  
Logan S. Billet ◽  
Vanessa P. Wuerthner ◽  
Jessica Hua ◽  
Rick A. Relyea ◽  
Jason T. Hoverman
Keyword(s):  
Rana Pipiens ◽  
Parasite Species ◽  
Priority Effects ◽  
Ecological Studies ◽  
Field Surveys ◽  
Larval Amphibians ◽  
Lower Infection ◽  
Multiple Species ◽  
Echinostoma Trivolvis ◽  
Timing Of Exposure

AbstractThe study of priority effects with respect to coinfections is still in its infancy. Moreover, existing coinfection studies typically focus on infection outcomes associated with exposure to distinct sets of parasite species, despite that functionally and morphologically similar parasite species commonly coexist in nature. Therefore, it is important to understand how interactions between similar parasites influence infection outcomes. Surveys at seven ponds in northwest Pennsylvania found that multiple species of echinostomes commonly co-occur. Using a larval anuran host (Rana pipiens) and the two most commonly identified echinostome species from our field surveys (Echinostoma trivolvis and Echinoparyphium lineage 3), we examined how species composition and timing of exposure affect patterns of infection. When tadpoles were exposed to both parasites simultaneously, infection loads were higher than when exposed to Echinoparyphium alone but similar to being exposed to Echinostoma alone. When tadpoles were sequentially exposed to the parasite species, tadpoles first exposed to Echinoparyphium had 23% lower infection loads than tadpoles first exposed to Echinostoma. These findings demonstrate that exposure timing and order, even with similar parasites, can influence coinfection outcomes, and emphasize the importance of using molecular methods to identify parasites for ecological studies.

scholarly journals The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases

2014 ◽  
Vol 281 (1780) ◽  
pp. 20133172 ◽  
Author(s):  
Tamer Oraby ◽  
Vivek Thampi ◽  
Chris T. Bauch
Keyword(s):  
Infectious Diseases ◽  
Social Norms ◽  
Perceived Risk ◽  
Initial Conditions ◽  
Vaccine Coverage ◽  
Vaccine Uptake ◽  
Disease Dynamics ◽  
Small Communities ◽  
Low Incidence ◽  
The Uk

Mathematical models that couple disease dynamics and vaccinating behaviour often assume that the incentive to vaccinate disappears if disease prevalence is zero. Hence, they predict that vaccine refusal should be the rule, and elimination should be difficult or impossible. In reality, countries with non-mandatory vaccination policies have usually been able to maintain elimination or very low incidence of paediatric infectious diseases for long periods of time. Here, we show that including injunctive social norms can reconcile such behaviour-incidence models to observations. Adding social norms to a coupled behaviour-incidence model enables the model to better explain pertussis vaccine uptake and disease dynamics in the UK from 1967 to 2010, in both the vaccine-scare years and the years of high vaccine coverage. The model also illustrates how a vaccine scare can perpetuate suboptimal vaccine coverage long after perceived risk has returned to baseline, pre-vaccine-scare levels. However, at other model parameter values, social norms can perpetuate depressed vaccine coverage during a vaccine scare well beyond the time when the population's baseline vaccine risk perception returns to pre-scare levels. Social norms can strongly suppress vaccine uptake despite frequent outbreaks, as observed in some small communities. Significant portions of the parameter space also exhibit bistability, meaning long-term outcomes depend on the initial conditions. Depending on the context, social norms can either support or hinder immunization goals.

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 Comparing Metapopulation Dynamics of Infectious Diseases under Different Models of Human Movement

2020 ◽  
Author(s):  
Daniel T. Citron ◽  
Carlos A. Guerra ◽  
Andrew J. Dolgert ◽  
Sean L. Wu ◽  
John M. Henry ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Human Movement ◽  
Global Scale ◽  
Disease Dynamics ◽  
Movement Model ◽  
Sis Model ◽  
Bioko Island ◽  
Geographical Distances ◽  
Infectious Disease Dynamics

Newly available data sets present an exciting opportunity to investigate how human population movement contributes to the spread of infectious diseases across large geographical distances. It is now possible to construct realistic models of infectious disease dynamics for the purposes of understanding global-scale epidemics. Nevertheless, a remaining unanswered question is how best to leverage the new data to parameterize models of movement, and whether one’s choice of movement model impacts modeled disease outcomes. We adapt three well-studied models of infectious disease dynamics, the SIR model; the SIS model; and the Ross-Macdonald model, to incorporate either of two candidate movement models. We describe the effect that the choice of movement model has on each disease model’s results, finding that in all cases there are parameter regimes where choosing one movement model instead of another has a profound impact on epidemiological outcomes. We further demonstrate the importance of choosing an appropriate movement model using the applied case of malaria transmission and importation on Bioko Island, Equatorial Guinea, finding that one model produces intelligible predictions of R0 while the other produces nonsensical results.

Sign in / Sign up

Export Citation Format

Share Document