LitCovid-sentences  

PMC:7060038 / 46304-52280 JSONTXT 12 Projects

Annnotations TAB TSV DIC JSON TextAE

Id Subject Object Predicate Lexical cue
T281 0-21 Sentence denotes Materials and methods
T282 23-40 Sentence denotes Modeling strategy
T283 41-169 Sentence denotes The model’s structure is summarized above (Figure 1), and detailed methods have been described previously (Gostic et al., 2015).
T284 170-243 Sentence denotes Here, we summarize relevant extensions, assumptions and parameter inputs.
T285 245-255 Sentence denotes Extensions
T286 256-416 Sentence denotes Our previous model tracked all the ways in which infected travellers can be detected by screening (fever screen, or risk factor screen at arrival or departure).
T287 417-637 Sentence denotes Here, we additionally keep track of the many ways in which infected travellers can be missed (i.e. missed given fever present, missed given exposure risk present, missed given both present, or missed given undetectable).
T288 638-798 Sentence denotes Cases who have not yet passed the incubation period are considered undetectable by fever screening, even if they will eventually develop symptoms in the future.
T289 799-945 Sentence denotes In other words, no traveller is considered ‘missed given fever present’ until they have passed the incubation period and show detectable symptoms.
T290 946-1100 Sentence denotes Infected travellers who progress to symptoms during their journey are considered undetectable by departure screening, but detectable by arrival screening.
T291 1101-1254 Sentence denotes Additionally, we now provide a supplementary user interface, which allows stakeholders to test input parameters of interest using up-to-date information.
T292 1255-1416 Sentence denotes Here, in addition to the analyses presented in this study, we implemented the possibility that some fraction of infected travellers deliberately evade screening.
T293 1418-1447 Sentence denotes Basic reproduction number, R0
T294 1448-1554 Sentence denotes Existing point estimates for R0 span a wide range (2.2–6.47), but most fall between 2.0 and 4.0 (Table 1).
T295 1555-1693 Sentence denotes The vast majority of these estimates are informed by data collected very early in the outbreak, before any control measures were in place.
T296 1694-1903 Sentence denotes However, several studies already demostrate decreases in the reproductive number over time, as a consequence of social distancing behaviors, and containment measures (Kucharski et al., 2020; Liu et al., 2020).
T297 1904-2059 Sentence denotes Realistically, R0 will vary considerably over time, and across locations, depending on the social context, resource availability, and containment policies.
T298 2060-2362 Sentence denotes Our analysis considers a plausible range of R0 values spanning 1.5–4.0, with 4.0 representing a plausible maximum in the absence of any behavioral changes or containment efforts, and 1.5 reflecting a plausible lower bound, given containment measures may already be in place at the time of introduction.
T299 2364-2393 Sentence denotes Fraction of subclinical cases
T300 2394-2599 Sentence denotes To estimate the upper-bound fraction of subclinical cases, we draw on data from active surveillance of passengers quarantined on a cruise ship off the coast of Japan, or passengers of repatriation flights.
T301 2600-2765 Sentence denotes These data show that 50–70% of cases are asymptomatic at the time of diagnosis (Dorigatti et al., 2020; Nishiura et al., 2020; Schnirring, 2020c; Schnirring, 2020b).
T302 2766-3031 Sentence denotes We estimate that 50% subclinical cases is a reasonable upper bound: due to intensive monitoring, cases in repatriated individuals or in cruise ship passengers will be detected earlier than usual in the course of infection--and possibly before the onset of symptoms.
T303 3032-3380 Sentence denotes From clinical data (where severe cases are likely overrepresented), we estimate a lower bound of 5%: even among clinically attended cases, 2–15% lack fever or cough, and would be undetectable in symptom screening (Chan et al., 2020; Chen et al., 2020; The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team, 2020; Huang et al., 2020).
T304 3381-3516 Sentence denotes In addition to the upper and lower bound scenarios, we consider a plausible middle-case scenario in which 25% of cases are subclinical.
T305 3517-3758 Sentence denotes A very recent delay-adjusted estimate indicates 30-40% of infections on the cruise ship quarantined off the coast of Japan are asymptomatic, so the truth may fall somewhere between our middle and worst-case scenarios (Mizumoto et al., 2020).
T306 3760-3790 Sentence denotes Incubation period distribution
T307 3791-3856 Sentence denotes We use a gamma distribution to model individual incubation times.
T308 3857-4040 Sentence denotes We choose this form over the Weibull and lognormal distribution for ease of interpretation (gamma shape and scale parameters can be transformed easily to mean and standard deviation).
T309 4041-4225 Sentence denotes So far, best-fit gamma distributions to COVID-19 data have had mean 6.5 and standard deviation 2.6 (Backer et al., 2020), or mean 5.46 and standard deviation 1.94 (Lauer et al., 2020).
T310 4226-4463 Sentence denotes Here, to model uncertainty around the true mean incubation time, we fix the standard deviation to 2.25 (intermediate between the two existing estimates), and allow the mean to vary between 4.5 and 6.5 days (Figure 2—figure supplement 2).
T311 4464-4714 Sentence denotes The 95th percentile of the distributions we consider fall between 8.7 and 10.6 days, slightly below the officially accepted maximum incubation time of 14 days, and consistent with existing estimates (Table 1; Backer et al., 2020; Lauer et al., 2020).
T312 4716-4761 Sentence denotes Effectiveness of exposure risk questionnaires
T313 4762-4953 Sentence denotes The probability that an infected traveller is detectable using questionnaire-based screening for exposure risk will be highest if risk factors with high sensitivity and specificity are known.
T314 4954-5206 Sentence denotes Currently, official guidance recommends asking whether travellers have visited a country with epidemic transmission, a healthcare facility with confirmed cases, or had close contact with a confirmed or suspected case (World Health Organization, 2020c).
T315 5207-5423 Sentence denotes Given the relative anonymity of respiratory transmission, we assume that a minority of infected travellers would realize that they have been exposed before symptoms develop (20% in Figure 2, range 5–40% in Figure 3).
T316 5424-5600 Sentence denotes Further, relying on a previous upper-bound estimate (Gostic et al., 2015) we assume that only 25% of travellers would self-report truthfully if aware of elevated exposure risk.
T317 5601-5696 Sentence denotes Table 1 summarizes the state of knowledge about additional parameters, as of February 20, 2020.
T318 5698-5724 Sentence denotes Code and data availability
T319 5725-5976 Sentence denotes All code and source data used to perform analyses and generate figures is archived at https://github.com/kgostic/traveller_screening/releases/tag/v2.1. (Gostic, 2020; copy archived at https://github.com/elifesciences-publications/traveller_screening).