PMC:7014668 / 1849-6884
Annnotations
{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/7014668","sourcedb":"PMC","sourceid":"7014668","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7014668","text":"Simulation of travellers at each stage of infection with 2019-nCoV\nWe simulated 100 2019-nCoV infected travellers planning to board a flight who would pose a risk for seeding transmission in a new region. The duration of travel was considered as the flight time plus a small amount of additional travel time (ca 1 hour) for airport procedures. We assumed that infected individuals will develop symptoms, including fever, at the end of their incubation period (mean 5.2 days (Table)) [8] and progress to more severe symptoms after a few days, resulting in hospitalisation and isolation. We also took into account that individuals may have asymptomatic (subclinical) infection that would not be detected by thermal scanning or cause them to seek medical care, although these individuals may be infectious, and that infected travellers may exhibit severe symptoms during their travel and be hospitalised upon arrival without undergoing entry screening. We then estimated the proportion of infected travellers who would be detected by exit and entry screening, develop severe symptoms during travel, or go undetected, under varying assumptions of: (i) the duration of travel; (ii) the sensitivity of exit and entry screening; (iii) the proportion of asymptomatic infections; (iv) the incubation period and (v) the time from symptom onset to hospitalisation (Table).\nTable Parameter values and assumptions for the baseline scenario estimating effectiveness of exit and entry screening at airports for detecting passengers infected with novel coronavirus (2019-nCoV)\nParameter Value (baseline scenario) Source\nDuration of travel 12 hours Beijing – London [18]\nSensitivity of exit screening 86% Sensitivity of infrared thermal image scanners [19]\nSensitivity of entry screening 86% Sensitivity of infrared thermal image scanners [19]\nProportion of asymptomatic infections undetectable by typical screening procedures 17% 1 of 6 reported asymptomatic in a 2019-nCoV family cluster [11]\nIncubation period Mean 5.2 days, variance 4.1 days Reported Gamma distributed mean, variance estimated from uncertainty interval of mean [8]\nTime from symptom onset to hospitalisation Mean 9.1 days, variance 14.7 days Reported Gamma distributed mean, variance estimated from uncertainty interval of mean [8] We assume that the time of starting travel is randomly and uniformly distributed between the time of infection and twice the expected time to severe disease, ensuring that simulated travellers are travelling during their incubation period. However, we only consider those travellers who depart before their symptoms progress to being so severe that they would require hospital care [8]. We simulate travellers with individual incubation period, time from onset to severe disease, flight start times and detection success at exit and entry screening according to the screening sensitivities (Figure 1). An individual will be detected at exit screening if their infection is symptomatic i.e. has detectable fever, their departure time exceeds their incubation period, and their stochastic exit screening success indicates detection. An individual will be detected at entry screening if their infection is symptomatic, their incubation period ends after their departure but before their arrival, they have not been detected at exit screening, and their entry screening result is positive despite imperfect sensitivity. Entry screening detections are further divided into detection due to severe symptoms and detection of mild symptoms via equipment such as thermal scanners. We used 10,000 bootstrap samples to calculate 95% confidence intervals (CI).\nFigure 1 Simulated infection histories of travellers infected with novel coronavirus (2019-nCoV)\nThe incubation period begins on infection and travellers then progress to being symptomatic and having severe symptoms. Travellers may fly at any point within the incubation or symptomatic phases; any would-be travellers who show (severe) symptoms and are hospitalised before exit. Vertical lines represent the exit screening at start of travel (solid) and entry screening at end of travel (dashed) 12 hours later. The model code is available via GitHub [9] and the results can be further explored in a Shiny app [10] at https://cmmid-lshtm.shinyapps.io/traveller_screening/ (Figure 2).\nFigure 2 Screenshot of Shiny appa displaying the number of travellers infected with novel coronavirus (2019-nCoV) detected at airport exit and entry screening with baseline assumptionsb, 95% bootstrap confidence intervals, time distributions for incubation period and time to severe disease*\na Source [9].\nb Baseline assumptions according to the Table.\nResults are from stochastic simulation, and so there may be small variations in the number of travellers in each group when the same parameters are used twice. Sliders are provided to modify the duration of travel, the sensitivity of both exit and entry screening, the proportion symptomatic, and the natural history parameters for the 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