scholarly journals 'Resistance is futile': Weaker selection for resistance during larger epidemics further increases prevalence and depresses host density

2021 ◽  
Author(s):  
Jason Cosens Walsman ◽  
Meghan A Duffy ◽  
Carla E Cáceres ◽  
Spencer R Hall
Keyword(s):  
Transmission Rate ◽  
Host Density ◽  
Evolutionary Model ◽  
Bimodal Distribution ◽  
Infection Prevalence ◽  
Opposite Pattern ◽  
Lower Resistance ◽  
Epidemic Size ◽  
Experimental Mesocosms ◽  
Field Approaches

What determines how much resistance hosts evolve? One might intuit that hosts evolve higher resistance when parasites are more abundant. However, the opposite pattern can arise due to costs of resistance. Here we illustrate with mathematical, experimental, and field approaches how ecological context can increase parasite abundance and select for lower resistance. "Resistance is futile" when all host genotypes become sufficiently infected. To make this argument, we first analyzed an eco-evolutionary model of parasites, hosts, and resources of hosts. We determined eco-evolutionary outcomes for resistance (mathematically, transmission rate) and densities along gradients that drive epidemic size. When epidemic drivers are high, hosts evolve lower resistance, amplifying epidemics and decreasing host density. Experimental mesocosms qualitatively agreed. In the experiment, higher supply of nutrients drove larger epidemics of survival-reducing fungal parasites. Evolving zooplankton hosts were less resistant at high nutrients than at low. Less resistance, in turn, was associated with higher infection prevalence and lower host density. We also analyzed the size of naturally occurring epidemics, finding a broad, bimodal distribution of epidemic sizes consistent with the eco-evolutionary model. Together, our three approaches supported predictions that high epidemic drivers lead to evolution of lower resistance which drives higher prevalence and lower host density.

Risk factors associated with Enteromyxum scophthalmi (Myxozoa) infection in cultured turbot, Scophthalmus maximus (L.)

Parasitology ◽  
2006 ◽  
Vol 133 (4) ◽  
pp. 433-442 ◽  
Author(s):  
M. I. QUIROGA ◽  
M. J. REDONDO ◽  
A. SITJÀ-BOBADILLA ◽  
O. PALENZUELA ◽  
A. RIAZA ◽  
...  
Keyword(s):  
Risk Factors ◽  
Distribution Pattern ◽  
Control Strategies ◽  
Host Density ◽  
Scophthalmus Maximus ◽  
Fish Distribution ◽  
Fish Mortality ◽  
Infection Prevalence ◽  
Western Spain ◽  
Turbot Scophthalmus Maximus

An epidemiological cohort study of Enteromyxum scophthalmi in cultured turbot was performed on a farm in North Western Spain. Four different ongrowing stocks (A, B, C, D) were monitored monthly until market size. Fish from stocks C and D were divided into 2 subgroups, receiving filtered (CF and DF) or unfiltered (CUF and DUF) water. The lack of water filtration was positively associated with infection prevalence, as all fish kept in filtered water remained uninfected. Parasite abundance varied seasonally (P<0·05) in stock B and subgroup CUF. Infection was also associated (P<0·05) with host weight, and the highest prevalences and intensities were detected in 101–200 g and 201–300 g fish. Distribution pattern of E. scophthalmi in subgroups CUF and DUF had a variance higher than the mean, indicating overdispersion. The minimum period necessary for the first detection of the parasite and for the appearance of disease symptoms and mortality, varied depending on the stock and introduction date, although a long pre-patent period was always observed. Several factors, such as host density, parasite recruitment and parasite-induced fish mortality can contribute to the observed distribution pattern. Risk factors found to be associated with E. scophthalmi infection, including water quality and accumulation of infective stages in the culture tanks, should be considered when designing control strategies to prevent the introduction and spread of infective stages in the facilities.

EXACT ANALYTICAL EXPRESSIONS FOR THE FINAL EPIDEMIC SIZE OF AN SIR MODEL ON SMALL NETWORKS

2016 ◽  
Vol 57 (4) ◽  
pp. 429-444 ◽  
Author(s):  
K. MCCULLOCH ◽  
M. G. ROBERTS ◽  
C. R. LAING
Keyword(s):  
Initial Conditions ◽  
Transmission Rate ◽  
Sir Model ◽  
Contact Network ◽  
Sir Epidemic Model ◽  
Node Number ◽  
Sir Epidemic ◽  
Epidemic Size ◽  
Final Epidemic Size ◽  
Analytical Expressions

We investigate the dynamics of a susceptible infected recovered (SIR) epidemic model on small networks with different topologies, as a stepping stone to determining how the structure of a contact network impacts the transmission of infection through a population. For an SIR model on a network of$N$nodes, there are$3^{N}$configurations that the network can be in. To simplify the analysis, we group the states together based on the number of nodes in each infection state and the symmetries of the network. We derive analytical expressions for the final epidemic size of an SIR model on small networks composed of three or four nodes with different topological structures. Differential equations which describe the transition of the network between states are also derived and solved numerically to confirm our analysis. A stochastic SIR model is numerically simulated on each of the small networks with the same initial conditions and infection parameters to confirm our results independently. We show that the structure of the network, degree of the initial infectious node, number of initial infectious nodes and the transmission rate all significantly impact the final epidemic size of an SIR model on small networks.

scholarly journals Disease control across urban–rural gradients

2020 ◽  
Vol 17 (173) ◽  
pp. 20200775
Author(s):  
Konstans Wells ◽  
Miguel Lurgi ◽  
Brendan Collins ◽  
Biagio Lucini ◽  
Rowland R. Kao ◽  
...  
Keyword(s):  
Urban Areas ◽  
Transmission Rate ◽  
Control Strategies ◽  
Control Measure ◽  
Personal Contact ◽  
Metapopulation Model ◽  
Transmission Rates ◽  
Epidemic Size ◽  
Limited Efficacy ◽  
Urban Rural

Controlling the regional re-emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban–rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases or regional lockdowns in response to local outbreaks have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test-and-trace strategies, is pivotal to reducing the overall epidemic size over a wider range of transmission scenarios. We define an ‘urban–rural gradient in epidemic size' as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban–rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatic individuals only. Our results emphasize the importance of test-and-trace strategies and maintaining low transmission rates for efficiently controlling SARS-CoV-2 spread, both at landscape scale and in urban areas.

scholarly journals COVID-19 control across urban-rural gradients

2020 ◽  
Author(s):  
Konstans Wells ◽  
Miguel Lurgi ◽  
Brendan Collins ◽  
Biagio Lucini ◽  
Rowland Raymond Kao ◽  
...  
Keyword(s):  
Urban Areas ◽  
Transmission Rate ◽  
Control Strategies ◽  
Control Measure ◽  
Personal Contact ◽  
Metapopulation Model ◽  
Transmission Rates ◽  
Epidemic Size ◽  
Limited Efficacy ◽  
Urban Rural

Controlling the regional re-emergence of SARS-CoV-2 after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban-rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases, or regional lockdowns in response to local outbreaks, have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test and trace strategies, is pivotal to reduce the overall epidemic size over a wider range of transmission scenarios. We define an urban-rural gradient in epidemic size as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban-rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatics only. Our results emphasise the importance of test-and-tracing strategies and maintaining low transmission rates for efficiently controlling COVID19 spread, both at landscape scale and in urban areas.

scholarly journals Why are most COVID-19 infection curves linear?

2020 ◽  
Author(s):  
Stefan Thurner ◽  
Peter Klimek ◽  
Rudolf Hanel
Keyword(s):  
Linear Growth ◽  
Transmission Rate ◽  
Herd Immunity ◽  
Fine Tuning ◽  
Infection Prevalence ◽  
Epidemiological Models ◽  
Contact Networks ◽  
Empirical Estimates ◽  
The Us ◽  
New Phase

Many countries have passed their first COVID-19 epidemic peak. Traditional epidemiological models describe this as a result of non-pharmaceutical interventions that pushed the growth rate below the recovery rate. In this new phase of the pandemic many countries show an almost linear growth of confirmed cases for extended time-periods. This new containment regime is hard to explain by traditional models where infection numbers either grow explosively until herd immunity is reached, or the epidemic is completely suppressed (zero new cases). Here we offer an explanation of this puzzling observation based on the structure of contact networks. We show that for any given transmission rate there exists a critical number of social contacts, Dc, below which linear growth and low infection prevalence must occur. Above Dc traditional epidemiological dynamics takes place, as e.g. in SIR-type models. When calibrating our corresponding model to empirical estimates of the transmission rate and the number of days being contagious, we find Dc ~ 7.2. Assuming realistic contact networks with a degree of about 5, and assuming that lockdown measures would reduce that to household-size (about 2.5), we reproduce actual infection curves with a remarkable precision, without fitting or fine-tuning of parameters. In particular we compare the US and Austria, as examples for one country that initially did not impose measures and one that responded with a severe lockdown early on. Our findings question the applicability of standard compartmental models to describe the COVID-19 containment phase. The probability to observe linear growth in these is practically zero.

scholarly journals Parasite-driven cascades or hydra effects: susceptibility and foraging depression shape parasite-host-resource interactions

2021 ◽  
Author(s):  
Jason Cosens Walsman ◽  
Alexander T Strauss ◽  
Spencer R Hall
Keyword(s):  
Carrying Capacity ◽  
Host Density ◽  
Infection Prevalence ◽  
Test Model ◽  
Susceptibility To Infection ◽  
Mediated Effects ◽  
Resource Interactions ◽  
Hydra Effect ◽  
Clonal Lines ◽  
Host Parasite

When epidemics kill hosts and increase their resources, should the density of hosts decrease (with a resource increase, this constitutes a trophic cascade) or increase (a hydra effect)? Seeking answers, we integrate trait measurements, a resource-host-parasite model, and experimental epidemics with plankton. This combination reveals how a spectrum from cascades to hydra effects can arise. It reflects tension between parasite-driven mortality (a density-mediated effect) and foraging depression upon contact with parasite propagules (a trait-mediated one). In the model, mortality rises when higher susceptibility to infection increases infection prevalence. Epidemics release resources while suppressing hosts (creating a cascade). In contrast, when hosts are less susceptible and parasites depress their foraging, a resource feedback can elevate host density during epidemics (creating a hydra effect), particularly at higher carrying capacity of resources. This combination elevates primary production relative to per-host consumption of resources (two key determinants of host density). We test these predictions of the qualitative effects of host traits and resource carrying capacity with trait measurements and a mesocosm experiment. Trait measurements show clonal lines of zooplankton hosts differ in their foraging depression and susceptibility. We seeded resource-host-parasite mesocosms with different host genotypes and provided different nutrient supplies to test model predictions. Hydra effects and trophic cascades arose under different conditions, as predicted by the model. Hence, tension between trait-mediated and density-mediated effects of parasites governs the fate of host density during epidemics, from cascades to hydra effects, via feedbacks with resources.

scholarly journals Environmental persistence but not per capita transmission rates of a chytrid fungus determines infection prevalence

2021 ◽  
Author(s):  
Samantha L Rumschlag ◽  
Sadie A. Roth ◽  
Taegan A. McMahon ◽  
Jason R. Rohr ◽  
David J. Civitello
Keyword(s):  
Transmission Rate ◽  
Life Stage ◽  
Pond Water ◽  
Mortality Rates ◽  
Water Sources ◽  
Infection Prevalence ◽  
Chytrid Fungus ◽  
Transmission Rates ◽  
Per Capita ◽  
Mechanistic Understanding

Understanding local-scale variability in disease dynamics can be important for informing strategies for surveillance and management. For example, the amphibian chytrid fungus (Batrachochytrium dendrobatidis; Bd), which is implicated in population declines and species extinctions of amphibians, causes spatially variable epizootics and extirpations of its hosts. Outbreak heterogeneity could be driven by differential survival of zoospores, the free-living infectious life stage of Bd, or the persistence of dead zoospores and/or its metabolites in water, which could induce resistance among hosts. To gain a mechanistic understanding of the potential for variation in local transmission dynamics of Bd, we conducted Bd survival and infection experiments and then fit models to discern how Bd mortality, decomposition, and per-capita transmission rate vary among water sources. We found that infection prevalence differed among water sources, which was driven by differences in mortality rates of Bd zoospores, rather than differences in per-capita transmission rates. Specifically, zoospore mortality rates varied significantly among pond water treatments and were lower in artificial spring water compared to pond water sources. These results suggest that variation in Bd infection dynamics could be a function of differences in exposure of hosts to live Bd. In contrast to the persistence of live zoospores, we found that rates of decomposition of dead zoospores did not vary among water sources. These results may suggest that exposure of hosts to dead Bd or its metabolites, which have been shown to induce acquired resistance, might not commonly vary among nearby sites. Ultimately, a mechanistic understanding of the drivers of variable epizootics of Bd could lead to increases in the effectiveness of surveillance and management strategies.

scholarly journals A field test of the dilution effect hypothesis in four avian multi-host pathogens

2021 ◽  
Vol 17 (6) ◽  
pp. e1009637
Author(s):  
Martina Ferraguti ◽  
Josué Martínez-de la Puente ◽  
Miguel Ángel Jiménez–Clavero ◽  
Francisco Llorente ◽  
David Roiz ◽  
...  
Keyword(s):  
Species Richness ◽  
Species Diversity ◽  
Passer Domesticus ◽  
Host Density ◽  
Dilution Effect ◽  
Pathogen Transmission ◽  
Opposite Pattern ◽  
Vector Borne ◽  
Effect Hypothesis ◽  
Community Variables

The Dilution Effect Hypothesis (DEH) argues that greater biodiversity lowers the risk of disease and reduces the rates of pathogen transmission since more diverse communities harbour fewer competent hosts for any given pathogen, thereby reducing host exposure to the pathogen. DEH is expected to operate most intensely in vector-borne pathogens and when species-rich communities are not associated with increased host density. Overall, dilution will occur if greater species diversity leads to a lower contact rate between infected vectors and susceptible hosts, and between infected hosts and susceptible vectors. Field-based tests simultaneously analysing the prevalence of several multi-host pathogens in relation to host and vector diversity are required to validate DEH. We tested the relationship between the prevalence in house sparrows (Passer domesticus) of four vector-borne pathogens–three avian haemosporidians (including the avian malaria parasite Plasmodium and the malaria-like parasites Haemoproteus and Leucocytozoon) and West Nile virus (WNV)–and vertebrate diversity. Birds were sampled at 45 localities in SW Spain for which extensive data on vector (mosquitoes) and vertebrate communities exist. Vertebrate censuses were conducted to quantify avian and mammal density, species richness and evenness. Contrary to the predictions of DEH, WNV seroprevalence and haemosporidian prevalence were not negatively associated with either vertebrate species richness or evenness. Indeed, the opposite pattern was found, with positive relationships between avian species richness and WNV seroprevalence, and Leucocytozoon prevalence being detected. When vector (mosquito) richness and evenness were incorporated into the models, all the previous associations between WNV prevalence and the vertebrate community variables remained unchanged. No significant association was found for Plasmodium prevalence and vertebrate community variables in any of the models tested. Despite the studied system having several characteristics that should favour the dilution effect (i.e., vector-borne pathogens, an area where vector and host densities are unrelated, and where host richness is not associated with an increase in host density), none of the relationships between host species diversity and species richness, and pathogen prevalence supported DEH and, in fact, amplification was found for three of the four pathogens tested. Consequently, the range of pathogens and communities studied needs to be broadened if we are to understand the ecological factors that favour dilution and how often these conditions occur in nature.

scholarly journals Prediction on Covid-19 epidemic for different countries: Focusing on South Asia under various precautionary measures

2020 ◽  
Author(s):  
Abhijit Paul ◽  
Samrat Chatterjee ◽  
Nandadulal Bairagi
Keyword(s):  
Disease Burden ◽  
Transmission Rate ◽  
Research Community ◽  
Model Parameters ◽  
Epidemic Size ◽  
Estimated Parameters ◽  
The Social ◽  
Precautionary Measures ◽  
Pharmaceutical Interventions ◽  
Epidemiological Parameters

ABSTRACTThe coronavirus disease 2019 (COVID-19), which emerged from Wuhan, China, is now a pandemic, affecting across the globe. Government of different countries have developed and adopted various policies to contain this epidemic and the most common were the social distancing and lockdown. We proposed a SEIR epidemic model that accommodates the effects of lockdown and individual based precautionary measures and used it to estimate model parameters from the epidemic data up to 2nd April, 2020, freely available in GitHub repository for COVID-19, for nine developed and developing countries. We used the estimated parameters to predict the disease burden in these countries with special emphasis on India, Bangladesh and Pakistan. Our analysis revealed that the lockdown and recommended individual hygiene can slow down the outbreak but unable to eradicate the disease from the society. With the current human-to-human transmission rate and existing level of personal precautionary, the number of infected individuals in India will be increasing at least for the next 3 months and the peak will come in 5 months. We can, however, reduce the epidemic size and prolong the time to arrive epidemic peak by seriously following the measures suggested by the authorities. We need to wait for another one month to obtain more data and epidemiological parameters for giving a better prediction about the pandemic. It is to be mentioned that research community is working for drugs and/ or vaccines against COVID19 and the presence of such pharmaceutical interventions will significantly alter the results.

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