LitCovid-sentences  

PMC:7551987 / 18718-25807 JSONTXT 3 Projects

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Id Subject Object Predicate Lexical cue
T121 0-2 Sentence denotes 3.
T122 3-10 Sentence denotes Results
T123 12-16 Sentence denotes 3.1.
T124 17-43 Sentence denotes Model Sensitivity Analysis
T125 44-153 Sentence denotes Figure 2 depicts a tornado plot that communicates the sensitivity of the model to permutations in parameters.
T126 154-341 Sentence denotes Across features, the model is most sensitive to parameters that are considered virulence-associated (Table 3) and is relatively less sensitive to survival-associated parameters (Table 4).
T127 342-446 Sentence denotes Similar to other features, R0 (Figure 2D) of the model is most sensitive to the parameters ⍵, βA, and ν.
T128 447-578 Sentence denotes The sensitivity of R0 to changes in ⍵ reflects the importance of the rate of conversion to the symptomatic state on model dynamics.
T129 579-778 Sentence denotes In addition, βA has a very important influence on the model, consistent with other findings for COVID-19 that have emphasized the importance of asymptomatic transmission in disease spread [25,26,27].
T130 780-784 Sentence denotes 3.2.
T131 785-822 Sentence denotes Illustrative Dynamics of Model System
T132 823-1041 Sentence denotes Based on the parameter values in Table 2, Figure 3A demonstrates the base dynamics of the model playing out over the first 100 days while Figure 3B shows the dynamics within the environment over the course of 250 days.
T133 1042-1117 Sentence denotes In these dynamics, the population begins to be fixed for susceptible hosts.
T134 1118-1244 Sentence denotes The disease dynamics manifest in the shapes of the curves corresponding to exposed, asymptomatic, and symptomatic individuals.
T135 1245-1327 Sentence denotes Note the long tail of the curve corresponding to contamination by the environment.
T136 1328-1423 Sentence denotes The environment remains infectious even after the infected populations have declined in number.
T137 1424-1514 Sentence denotes The length and shape of this tail are influenced by the free-living survival of the virus.
T138 1516-1520 Sentence denotes 3.3.
T139 1521-1580 Sentence denotes The Epidemic Consequences of Varying Virulence and Survival
T140 1581-1697 Sentence denotes In the next analysis, we examine the epidemic consequences of varying traits associated with survival and virulence.
T141 1698-1950 Sentence denotes One can consider this as a scenario where we compare the endpoints of evolution of different virus populations (corresponding to combinations of values of survival and virulence) and calculating how these evolved populations manifest in epidemic terms.
T142 1951-2241 Sentence denotes In Figure 4, we observe how dynamics of the outbreak are influenced across a space of combinations of traits altering virulence (see Table 3 for a list of virulence-associated parameters) and survival (see Table 4 for a list of survival-associated parameters), changed by ±5% (10% overall).
T143 2242-2417 Sentence denotes In Figure 4D, we demonstrate how changes in virulence and free-living survival traits influence R0, with variation in virulence-related traits having the largest effect on R0.
T144 2418-2539 Sentence denotes Of note is how the range in R0 values varies widely across virulence–survival values, from nearly 2.0 to 3.7 (Figure 4D).
T145 2541-2545 Sentence denotes 3.4.
T146 2546-2621 Sentence denotes Implications of Virulence–Survival Relationships at Their Relative Extremes
T147 2622-2861 Sentence denotes Having observed how outbreak dynamics are influenced by variation in traits that alter virulence–survival phenotypes, we then examined how each outbreak metric is influenced by the extreme (±5%) values of the trait combinations considered.
T148 2862-3021 Sentence denotes Specifically, we assess how a change in pathogen survival affects outbreak dynamics, based on two expected relationships between survival and virulence traits.
T149 3023-3027 Sentence denotes 3.5.
T150 3028-3079 Sentence denotes Positive Correlation Between Survival and Virulence
T151 3080-3199 Sentence denotes In a positive correlation scenario, high values for survival would be associated with high values for virulence [4,13].
T152 3200-3361 Sentence denotes Because the correlations we observe are often not exactly linear, we utilize quadrants to express a trend, allowing for some variance around the expected “line”.
T153 3362-3502 Sentence denotes In Figure 5, the positive correlation scenario can be represented by combinations of virulence and survival residing in quadrants I and III.
T154 3503-3681 Sentence denotes If host–pathogen evolution proceeds according to a positive correlation scenario, all outbreak metrics would show an increase in severity as both survival and virulence increase.
T155 3682-4086 Sentence denotes Across the range of variation in virulence and survival traits considered (5% above and below the nominal value), the peak number of infected individuals increases by approximately 35%, the rate at which the peak is reached increases by approximately 16%, the total number of infected individuals after 30 days increases by approximately 98%, and R0 increases by approximately 94% (Figure 6 and Table 5).
T156 4088-4092 Sentence denotes 3.6.
T157 4093-4144 Sentence denotes Negative Correlation Between Survival and Virulence
T158 4145-4309 Sentence denotes In a negative correlation scenario, high values for survival would be associated with low values for virulence [2,9,15] and a low peak in total infected population.
T159 4310-4450 Sentence denotes Pathogens with a life history that exhibits negative virulence–survival associations would likely appear in quadrants II and IV in Figure 5.
T160 4451-4529 Sentence denotes Under negative correlation, outbreak severity decreases as survival increases.
T161 4530-4857 Sentence denotes Across the measured range of variation in virulence–survival traits, the peak number of infected individuals decreases by approximately 23%, the rate at which the epidemic peak is reached decreases by 0.15%, the total number of infected individuals decreases by 3%, and R0 decreases by approximately 84% (Figure 6 and Table 6).
T162 4858-5048 Sentence denotes Across all metrics considered, the effects of increased viral survival on outbreak dynamics is more extreme under the positive correlation than the negative correlation scenarios (Figure 6).
T163 5050-5054 Sentence denotes 3.7.
T164 5055-5125 Sentence denotes Dynamics of Epidemics at Extreme Values for Virus Free-Living Survival
T165 5126-5311 Sentence denotes In Figure 7, we observe the disease dynamics at extreme values for survival and the dynamics corresponding to the fraction of the environment that is contaminated with infectious virus.
T166 5312-5547 Sentence denotes Consistent with the data represented in Figure 6, we observe that minimum and maximum simulations differ more substantially for extreme survival scenarios in the positive correlation scenario than for the negative correlation scenario.
T167 5548-5713 Sentence denotes The feature of different outbreaks that varies most ostensibly between the correlation scenarios is the time needed to reach the peak number of infected individuals.
T168 5714-5889 Sentence denotes In positive correlation simulations, one can observe that the low virulence, low survival scenario (Figure 7A,B) takes longer to reach the peak number of infected individuals.
T169 5890-6094 Sentence denotes Most notably, however, the low virulence, low survival setting has a far smaller peak of environmental contamination and shorter tail relative to its high virulence, high survival counterpart (Figure 7D).
T170 6095-6254 Sentence denotes Similarly, intriguing findings exist in the comparison between the simulation sets corresponding to extremes in the negative correlation setting (Figure 7E–H).
T171 6255-6482 Sentence denotes Especially notable is the difference in the length of the tail of the environmental contamination for the high virulence, low survival combination (Figure 7F) vs. the low virulence, low survival combination variant (Figure 7H).
T172 6483-6693 Sentence denotes The explanation is that, in this model, higher virulence influences (among many other things) the rate at which the virus is shed into the environment from either the asymptomatic (𝜎A) or symptomatic (𝜎I) host.
T173 6694-6889 Sentence denotes We observe how the high virulence, low survival simulation (Figure 7E) features a symptomatic peak that is larger in size and is prolonged relative to the lower virulence counterpart (Figure 7G).
T174 6890-7089 Sentence denotes This relatively large symptomatic population sheds infectious virus into the environment for a longer period of time, contributing to the long tail of contaminated environments observed in Figure 5F.