LitCovid-sentences  

PMC:7449695 / 24400-34567 JSONTXT 9 Projects

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Id Subject Object Predicate Lexical cue
T169 0-57 Sentence denotes Estimating the time-varying effective reproduction number
T170 59-67 Sentence denotes Overview
T171 68-198 Sentence denotes The method used to estimate R𝑒𝑓𝑓 is described in Cori et al., 2013, as implemented in the R package, EpiNow (Abbott et al., 2020).
T172 199-479 Sentence denotes This method is currently in development by the Centre for the Mathematical Modelling of Infectious Diseases at the London School of Hygiene and Tropical Medicine (London School of Hygiene & Tropical Medicine Mathematical Modelling of Infectious Diseases nCoV working group, 2020).
T173 480-601 Sentence denotes Full details of their statistical analysis and code base is available via their website (https://epiforecasts.io/covid/).
T174 602-921 Sentence denotes The uncertainty in the R𝑒𝑓𝑓 estimates (shown in Figure 2; Figure 2β€”figure supplements 1, 2 and 3) represents variability in a population-level average as a result of imperfect data, rather than individual-level heterogeneity in transmission (i.e., the variation in the number of secondary cases generated by each case).
T175 922-1134 Sentence denotes This is akin to the variation represented by a confidence interval (i.e., variation in the estimate resulting from a finite sample), rather than a prediction interval (i.e., variation in individual observations).
T176 1135-1281 Sentence denotes We provide a brief overview of the method and sources of imperfect data below, focusing on how the analysis was adapted to the Australian context.
T177 1283-1287 Sentence denotes Data
T178 1288-1407 Sentence denotes We used line-lists of reported cases for each Australian state/territory extracted from the national COVID-19 database.
T179 1408-1636 Sentence denotes The line-lists contain the date when the individual first exhibited symptoms, date when the case notification was received by the jurisdictional health department and where the infection was acquired (i.e., overseas or locally).
T180 1638-1674 Sentence denotes Reporting delays and under-reporting
T181 1675-1958 Sentence denotes A pre-hoc statistical analysis was conducted in order to estimate a distribution of the reporting delays from the line-lists of cases, using the code base provided by London School of Hygiene & Tropical Medicine Mathematical Modelling of Infectious Diseases nCoV working group, 2020.
T182 1959-2029 Sentence denotes The estimated reporting delay is assumed to remain constant over time.
T183 2030-2207 Sentence denotes These reporting delays are used to: (i) infer the time of symptom onset for those without this information, and; (ii) infer how many cases in recent days are yet to be recorded.
T184 2208-2325 Sentence denotes Adjusting for reporting delays is critical for inferring when a drop in observed cases reflects a true drop in cases.
T185 2326-2424 Sentence denotes Trends identified using this approach are robust to under-reporting, assuming that it is constant.
T186 2425-2491 Sentence denotes However, absolute values of R𝑒𝑓𝑓 may be biased by reporting rates.
T187 2492-2568 Sentence denotes Pronounced changes in reporting rates may also impact the trends identified.
T188 2569-2709 Sentence denotes The delay from symptom onset to reporting is likely to decrease over the course of the epidemic, due to improved surveillance and reporting.
T189 2710-2938 Sentence denotes We used a delay distribution estimated from observed reporting delays from the analysis period, which is therefore likely to underestimate reporting delays early in the epidemic, and overestimate them as the epidemic progressed.
T190 2939-3231 Sentence denotes Underestimating the delay would result in an overestimate of R𝑒𝑓𝑓, as the inferred onset dates (for those that were unknown) and adjustment for right-truncation, would result in more concentrated inferred daily cases (i.e., the inferred cases would be more clustered in time than in reality).
T191 3232-3289 Sentence denotes The converse would be true when overestimating the delay.
T192 3290-3476 Sentence denotes The impact of this misspecified distribution will be greatest on the most recent estimates of R𝑒𝑓𝑓, where inference for both right-truncation and missing symptom onset dates is required.
T193 3478-3532 Sentence denotes Estimating the effective reproduction number over time
T194 3533-3716 Sentence denotes Briefly, the R𝑒𝑓𝑓 was estimated for each day from 24 February 2020 up to 5 April 2020 using line list data – date of symptom onset, date of report, and import status – for each state.
T195 3717-3875 Sentence denotes The method assumes that the serial interval (i.e., time between symptom onset for an index and secondary case) is uncertain, with a mean of 4.7 days (95% CrI:
T196 3876-3932 Sentence denotes 3.7, 6.0) and a standard deviation of 2.9 days (95% CrI:
T197 3933-4022 Sentence denotes 1.9, 4.9), as estimated from early outbreak data in Wuhan, China (Nishiura et al., 2020).
T198 4023-4146 Sentence denotes Combining the incidence over time with the uncertain distribution of serial intervals allows us to estimate R𝑒𝑓𝑓 over time.
T199 4147-4243 Sentence denotes A different choice of serial interval distribution would affect the estimated time varying R𝑒𝑓𝑓.
T200 4244-4365 Sentence denotes This sensitivity is explored in detail in Flaxman et al., 2020, though we provide a brief description of the impact here.
T201 4366-4529 Sentence denotes For the same daily case data, a longer average serial interval would correspond to an increased estimate of R𝑒𝑓𝑓 when R𝑒𝑓𝑓>1, and a decreased estimate when R𝑒𝑓𝑓<1.
T202 4530-4633 Sentence denotes This effect can be understood intuitively by considering the epidemic dynamics in these two situations.
T203 4634-4692 Sentence denotes When R𝑒𝑓𝑓>1 , daily case counts are increasing on average.
T204 4693-4893 Sentence denotes The weighted average case counts (weighted by the serial interval distribution), decrease as the mean of the serial interval increases (i.e., as the support is shifted to older/lower daily case data).
T205 4894-4984 Sentence denotes In order to generate the same number of observed cases in the present, R𝑒𝑓𝑓 must increase.
T206 4985-5030 Sentence denotes A similar observation can be made for R𝑒𝑓𝑓<1.
T207 5031-5373 Sentence denotes In the context of our analyses (Figure 2), when the estimated R𝑒𝑓𝑓 is above 1, assuming a longer mean serial interval would further increase the R𝑒𝑓𝑓 estimates in each jurisdiction (i.e., the upper 75% of the Victorian posterior distribution for approximately the first 7–10 days, while stretching the upper tails in the other jurisdictions).
T208 5374-5479 Sentence denotes When the estimated R𝑒𝑓𝑓 is below 1, a higher mean serial interval would further decrease those estimates.
T209 5480-5575 Sentence denotes Qualitatively, this does not impact on the time series of R𝑒𝑓𝑓 in each Australian jurisdiction.
T210 5576-5745 Sentence denotes AΒ prior distribution was specified for R𝑒𝑓𝑓, with mean 2.6 (informed by Imai et al., 2020) and a broad standard deviation of 2 so as to allow for a range of R𝑒𝑓𝑓 values.
T211 5746-5993 Sentence denotes Finally, R𝑒𝑓𝑓 is estimated with a moving average window, selected to optimise the continuous ranked probability score, in order to smooth the curve and reduce the impact of localised events (i.e., cases clustered in time) causing large variations.
T212 5994-6129 Sentence denotes Note that up to 20% of reported cases in the Australian national COVID-19 database do not have a reported import status (see Figure 1).
T213 6130-6247 Sentence denotes Conservatively, we assumed that all cases with an unknown or unconfirmed source of acquisition were locally acquired.
T214 6249-6278 Sentence denotes Accounting for imported cases
T215 6279-6380 Sentence denotes A large proportion of cases reported in Australia from January until now were imported from overseas.
T216 6381-6589 Sentence denotes It is critical to account for two distinct populations in the case notification data – imported and locally acquired – in order to perform robust analyses of transmission in the early stages of this outbreak.
T217 6590-6786 Sentence denotes The estimated time-varying R𝑒𝑓𝑓 value is based on cases that have been identified as a result of local transmission, whereas imported cases contribute to transmission only (Thompson et al., 2019).
T218 6787-6885 Sentence denotes Specifically, the method assumes that local and imported cases contribute equally to transmission.
T219 6886-6946 Sentence denotes The results under this assumption are presented in Figure 2.
T220 6947-7178 Sentence denotes However, it is likely that imported cases contributed relatively less to transmission than locally acquired cases, as a result of quarantine and other border measures which targeted these individuals (Figure 1β€”figure supplement 2).
T221 7179-7418 Sentence denotes In the absence of data on whether the infector of local cases was themselves an imported or local case (from which we could robustly estimate the contribution of imported cases to transmission), we explored this via a sensitivity analysis.
T222 7419-7607 Sentence denotes We aimed to explore the impact of a number of plausible scenarios, based on our knowledge of the timing, extent and level of enforcement of different quarantine policies enacted over time.
T223 7608-7746 Sentence denotes Prior to 15 March, returning Australian residents and citizens (and their dependents) from mainland China were advised to self-quarantine.
T224 7747-7988 Sentence denotes Note that further border measures were implemented during this period, including enhanced testing and provision of advice on arrivals from selected countries based on a risk assessment tool developed in early February (Shearer et al., 2020).
T225 7989-8183 Sentence denotes On 15 March, Australian authorities imposed a self-quarantine requirement on all international arrivals, and from 27 March, moved to a mandatory quarantine policy for all international arrivals.
T226 8184-8625 Sentence denotes Hence for the sensitivity analysis, we assumed two step changes in the effectiveness of quarantine of overseas arrivals (timed to coincide with the two key policy changes), resulting in three intervention phases: prior to 15 March (self-quarantine of arrivals from selected countries); 15–27 March inclusive (self-quarantine of arrivals from all countries); and 27 March onward (mandatory quarantine of overseas arrivals from all countries).
T227 8626-8735 Sentence denotes We further assumed that the relative infectiousness of imported cases decreased with each intervention phase.
T228 8736-9039 Sentence denotes The first two intervention phases correspond to self-quarantine policies, so we assume that they resulted in a relatively small reduction in the relative infectiousness of imported cases (the first smaller than the second, since the pre-15 March policy only applied to arrivals from selected countries).
T229 9040-9274 Sentence denotes The third intervention phase corresponds to mandatory quarantine of overseas arrivals in hotels which we assume is highly effective at reducing onward transmission from imported cases, but allows for the occasional transmission event.
T230 9275-9411 Sentence denotes We then varied the percentage of imported cases contributing to transmission over the three intervention phases, as detailed in Table 2.
T231 9412-9420 Sentence denotes Table 2.
T232 9422-9555 Sentence denotes Percentage of imported cases assumed to be contributing to transmission over three intervention phases for each sensitivity analysis.
T233 9556-9908 Sentence denotes We assume two step changes in the effectiveness of quarantine of overseas arrivals, resulting in three intervention phases: prior to 15 March (self-quarantine of arrivals from selected countries); 15–27 March inclusive (self-quarantine of arrivals from all countries); and 27 March onward (mandatory quarantine of overseas arrivals from all countries).
T234 9909-9952 Sentence denotes Imported cases contributing to transmission
T235 9953-10016 Sentence denotes Sensitivity analysis Prior to 15 March 15–27 March 27 March–
T236 10017-10032 Sentence denotes 1 90% 50% 1%
T237 10033-10048 Sentence denotes 2 80% 50% 1%
T238 10049-10064 Sentence denotes 3 50% 20% 1%
T239 10065-10167 Sentence denotes The results of these three analyses are shown in Figure 2β€”figure supplements 1, 2 and 3, respectively.