> top > projects > LitCovid-sentences > docs > PMC:7449695 > annotations
LitCovid-sentences  

PMC:7449695 JSONTXT 20 Projects

Annnotations TAB TSV DIC JSON TextAE

Id Subject Object Predicate Lexical cue
T1 0-50 Sentence denotes Early analysis of the Australian COVID-19 epidemic
T2 52-60 Sentence denotes Abstract
T3 61-140 Sentence denotes As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia.
T4 141-180 Sentence denotes Of these, 98 had died from the disease.
T5 181-282 Sentence denotes The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April.
T6 283-481 Sentence denotes This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis – for now.
T7 482-688 Sentence denotes Analysing factors that contribute to individual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally.
T8 689-782 Sentence denotes We describe how the epidemic and public health response unfolded in Australia up to 13 April.
T9 783-1019 Sentence denotes We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April).
T10 1021-1033 Sentence denotes Introduction
T11 1034-1201 Sentence denotes A small cluster of cases of the disease now known as COVID-19 was first reported on December 29, 2019, in the Chinese city of Wuhan (World Health Organization, 2020a).
T12 1202-1330 Sentence denotes By early May 2020, the disease had spread to all global regions, and overwhelmed some the world’s most developed health systems.
T13 1331-1537 Sentence denotes More than 2.8 million cases and 260,000 deaths had been confirmed globally, and the vast majority of countries with confirmed cases were reporting escalating transmission (World Health Organization, 2020b).
T14 1538-1613 Sentence denotes As of 1 May 2020, there were 6808 confirmed cases of COVID-19 in Australia.
T15 1614-1653 Sentence denotes Of these, 98 had died from the disease.
T16 1654-1852 Sentence denotes Encouragingly, the daily count of new confirmed cases had been declining since late March 2020, with 308 cases reported nationally since 14 April (Australian Government Department of Health, 2020a).
T17 1853-2114 Sentence denotes This suggests that Australia has (to date) avoided a “worst-case” scenario — one where planning models estimated a peak daily demand for 35,000 ICU beds by around May 2020, far exceeding the health system’s capacity of around 2,200 ICU beds (Moss et al., 2020).
T18 2115-2238 Sentence denotes The first wave of COVID-19 epidemics, and the government and public responses to them, have varied vastly across the globe.
T19 2239-2416 Sentence denotes For example, many European countries and the United States are in the midst of explosive outbreaks with overwhelmed health systems (Remuzzi and Remuzzi, 2020; The Lancet, 2020).
T20 2417-2764 Sentence denotes Meanwhile, countries such as Singapore and South Korea had early success in containing the spread, partly attributed to their extensive surveillance efforts and case targeted interventions (Ng et al., 2020; COVID-19 National Emergency Response Center, Epidemiology and Case Management Team, Korea Centers for Disease Control and Prevention, 2020).
T21 2765-2973 Sentence denotes However, despite those early successes, Singapore has recently taken additional steps to further limit transmission in the face of increasing importations and community spread (Government of Singapore, 2020).
T22 2974-3185 Sentence denotes Other locations in the region, including Taiwan, Hong Kong and New Zealand, have had similar epidemic experiences, achieving control through a combination of border, case targeted and social distancing measures.
T23 3186-3427 Sentence denotes Analysing key epidemiological and response factors — such as the intensity and timing of public health interventions — that contribute to individual country experiences of COVID-19 will assist in the next stage of response planning globally.
T24 3428-3583 Sentence denotes Here we describe the course of the COVID-19 epidemic and public health response in Australia from 22 January up to mid-April 2020 (summarised in Figure 1).
T25 3584-3760 Sentence denotes We then quantify the impact of the public health response on disease transmission (Figure 2) and forecast the short-term health system demand from COVID-19 patients (Figure 3).
T26 3761-3770 Sentence denotes Figure 1.
T27 3772-3993 Sentence denotes Time series of new daily confirmed cases of COVID-19 in Australia by import status (purple = overseas acquired, blue = locally acquired, green = unknown origin) from 22 January 2020 (first case detected) to 13 April 2020.
T28 3994-4151 Sentence denotes Dates of selected key border and social distancing measures implemented by Australian authorities are indicated by annotations above the plotted case counts.
T29 4152-4462 Sentence denotes These measures were in addition to case targeted interventions (case isolation and contact quarantine) and further border measures, including enhanced testing and provision of advice, on arrivals from other selected countries, based on a risk-assessment tool developed in early February (Shearer et al., 2020).
T30 4463-4665 Sentence denotes Note that Australian citizens and residents (and their dependants) were exempt from travel restrictions, but upon returning to Australia were required to quarantine for 14 days from the date of arrival.
T31 4666-4767 Sentence denotes A full timeline of social distancing and border measures is provided in Figure 1—figure supplement 2.
T32 4768-4797 Sentence denotes Figure 1—figure supplement 1.
T33 4799-5042 Sentence denotes Time series of new daily confirmed cases of COVID-19 in each Australian state/territory by import status (purple = overseas acquired, blue = locally acquired, green = unknown origin) from 22 January 2020 (first case detected) to 13 April 2020.
T34 5043-5275 Sentence denotes Details on the epidemiological characteristics of locally and overseas acquired infections are available in the Australian Department of Health fortnightly epidemiological reports (Australian Government Department of Health, 2020e).
T35 5276-5305 Sentence denotes Figure 1—figure supplement 2.
T36 5307-5401 Sentence denotes Timeline of border and social distancing measures implemented in Australia up to 4 April 2020.
T37 5402-5527 Sentence denotes These measures were in addition to case targeted interventions, specifically case isolation and quarantine of their contacts.
T38 5528-5624 Sentence denotes Contact tracing was initiated from 29 January 2020 and was performed by public health officials.
T39 5625-5632 Sentence denotes Note 1:
T40 5633-5884 Sentence denotes Between 1 February and 15 March, further border measures were introduced, including enhanced testing and provision of advice on arrivals from other selected countries, based on a risk-assessment tool developed in early February (Shearer et al., 2020).
T41 5885-5892 Sentence denotes Note 2:
T42 5893-6084 Sentence denotes Australian citizens and residents (and their dependants) were exempt from travel restrictions but upon returning to Australia were required to quarantine for 14 days from the date of arrival.
T43 6085-6092 Sentence denotes Note 3:
T44 6093-6348 Sentence denotes School attendance is reported to have reduce substantially following government recommendations to keep children from school (National Centre for Immunisation Research and Surveillance, 2020), and in some cases, prior to these announcements (Carey, 2020).
T45 6349-6490 Sentence denotes It should also be noted that school holidays in some states/territories overlapped with the restriction periods (late March and early April).
T46 6491-6498 Sentence denotes Note 4:
T47 6499-6602 Sentence denotes The use of face masks by the general public was not recommended at any time during the analysis period.
T48 6603-6610 Sentence denotes Note 5:
T49 6611-6812 Sentence denotes Personal hygiene measures and the ‘1.5 m distancing rule’ were promoted to the general public through television, print, radio and social media campaigns commissioned by national and state governments.
T50 6813-6822 Sentence denotes Figure 2.
T51 6824-7086 Sentence denotes Time-varying estimate of the effective reproduction number (R𝑒𝑓𝑓) of COVID-19 by Australian state (light blue ribbon = 90% credible interval; dark blue ribbon = 50% credible interval) from 1 March to 5 April 2020, based on data up to and including 13 April 2020.
T52 7087-7203 Sentence denotes Confidence in the estimated values is indicated by shading with reduced shading corresponding to reduced confidence.
T53 7204-7322 Sentence denotes The horizontal dashed line indicates the target value of 1 for the effective reproduction number required for control.
T54 7323-7489 Sentence denotes Not presented are the Australian Capital Territory (ACT), Northern Territory (NT) and Tasmania (TAS), as these states/territories had insufficient local transmission.
T55 7490-7748 Sentence denotes The uncertainty in the R𝑒𝑓𝑓 estimates represent 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).
T56 7749-7778 Sentence denotes Figure 2—figure supplement 1.
T57 7780-7808 Sentence denotes Sensitivity analysis 1 of 3.
T58 7809-8071 Sentence denotes Time-varying estimate of the effective reproduction number (R𝑒𝑓𝑓) of COVID-19 by Australian state (light blue ribbon = 90% credible interval; dark blue ribbon = 50% credible interval) from 1 March to 5 April 2020, based on data up to and including 13 April 2020.
T59 8072-8189 Sentence denotes Confidence in the estimated values is indicated by shading, with reduced shading corresponding to reduced confidence.
T60 8190-8308 Sentence denotes The horizontal dashed line indicates the target value of 1 for the effective reproduction number required for control.
T61 8309-8552 Sentence denotes Results are produced assuming stepwise changes in the relative infectiousness of locally acquired to imported cases according to quarantine requirements for returning travellers introduced on 15 and 27 March (indicated by vertical grey lines).
T62 8553-8721 Sentence denotes We assumed that 90%, 50%, and 1% of imported cases contributed to transmission prior to 15 March, between 15 and 27 March (inclusive), and after 27 March, respectively.
T63 8722-8751 Sentence denotes Figure 2—figure supplement 2.
T64 8753-8781 Sentence denotes Sensitivity analysis 2 of 3.
T65 8782-9044 Sentence denotes Time-varying estimate of the effective reproduction number (R𝑒𝑓𝑓) of COVID-19 by Australian state (light blue ribbon = 90% credible interval; dark blue ribbon = 50% credible interval) from 1 March to 5 April 2020, based on data up to and including 13 April 2020.
T66 9045-9162 Sentence denotes Confidence in the estimated values is indicated by shading, with reduced shading corresponding to reduced confidence.
T67 9163-9281 Sentence denotes The horizontal dashed line indicates the target value of 1 for the effective reproduction number required for control.
T68 9282-9525 Sentence denotes Results are produced assuming stepwise changes in the relative infectiousness of locally acquired to imported cases according to quarantine requirements for returning travellers introduced on 15 and 27 March (indicated by vertical grey lines).
T69 9526-9694 Sentence denotes We assumed that 80%, 50%, and 1% of imported cases contributed to transmission prior to 15 March, between 15 and 27 March (inclusive), and after 27 March, respectively.
T70 9695-9724 Sentence denotes Figure 2—figure supplement 3.
T71 9726-9754 Sentence denotes Sensitivity analysis 3 of 3.
T72 9755-10017 Sentence denotes Time-varying estimate of the effective reproduction number (R𝑒𝑓𝑓) of COVID-19 by Australian state (light blue ribbon = 90% credible interval; dark blue ribbon = 50% credible interval) from 1 March to 5 April 2020, based on data up to and including 13 April 2020.
T73 10018-10135 Sentence denotes Confidence in the estimated values is indicated by shading, with reduced shading corresponding to reduced confidence.
T74 10136-10254 Sentence denotes The horizontal dashed line indicates the target value of 1 for the effective reproduction number required for control.
T75 10255-10498 Sentence denotes Results are produced assuming stepwise changes in the relative infectiousness of locally acquired to imported cases according to quarantine requirements for returning travellers introduced on 15 and 27 March (indicated by vertical grey lines).
T76 10499-10662 Sentence denotes We assumed 50%, 20%, and 1% of imported cases contributed to transmission prior to 15 March, between 15 and 27 March (inclusive), and after 27 March, respectively.
T77 10663-10672 Sentence denotes Figure 3.
T78 10674-10864 Sentence denotes Forecasted daily hospital ward (left) and intensive care unit (right) occupancy (dark ribbons = 50% confidence intervals; light ribbons = 95% confidence intervals) from 17 March to 28 April.
T79 10865-10941 Sentence denotes Occupancy = the number of beds occupied by COVID-19 patients on a given day.
T80 10942-11067 Sentence denotes Black dots indicate the reported ward and ICU occupancy available from the Australian national COVID-19 database at the time.
T81 11068-11157 Sentence denotes These data were retrospectively updated where complete data were available (red crosses).
T82 11158-11416 Sentence denotes Australian health system ward and ICU bed capacities are estimated to be over 25,000 and 1,100, respectively, under the assumption that 50% of total capacity could possibly be dedicated to COVID-19 patients (Australian Institute of Health and Welfare, 2019).
T83 11417-11492 Sentence denotes The forecasted daily case counts are shown in Figure 3—figure supplement 1.
T84 11493-11522 Sentence denotes Figure 3—figure supplement 1.
T85 11524-11766 Sentence denotes Time series of new daily confirmed cases of COVID-19 in Australia from 1 March to 13 April 2020 (grey bars) overlaid by daily case counts estimated from the forecasting model up to April 13 and projected forward from 14 to 28 April inclusive.
T86 11767-11808 Sentence denotes Inner shading = 50% confidence intervals.
T87 11809-11850 Sentence denotes Outer shading = 95% confidence intervals.
T88 11851-12046 Sentence denotes Note that forecasting model estimates prior to 13 April — the last recorded data point at the time of analysis (indicated by the dashed grey line) — use data up to and including the previous day.
T89 12047-12134 Sentence denotes Black dots show the number of new daily cases of COVID-19 reported from 14 to 28 April.
T90 12136-12171 Sentence denotes Timeline of the Australian epidemic
T91 12172-12235 Sentence denotes Australia took an early and precautionary approach to COVID-19.
T92 12236-12454 Sentence denotes On 1 February, when China was the only country reporting uncontained transmission, Australian authorities restricted all travel from mainland China to Australia, in order to reduce the risk of importation of the virus.
T93 12455-12566 Sentence denotes Only Australian citizens and residents (and their dependants) were permitted to travel from China to Australia.
T94 12567-12656 Sentence denotes These individuals were advised to self-quarantine for 14 days from their date of arrival.
T95 12657-12874 Sentence denotes Further border measures, including enhanced testing and provision of additional advice, were placed on arrivals from other countries, based on a risk-assessment tool developed in early February (Shearer et al., 2020).
T96 12875-13035 Sentence denotes The day before Australia imposed these restrictions (January 31), 9720 cases of COVID-19 had been reported in mainland China (World Health Organization, 2020c).
T97 13036-13229 Sentence denotes Australia had so far detected and managed nine imported cases, all with recent travel history from or a direct epidemiological link to Wuhan (Australian Government Department of Health, 2020b).
T98 13230-13408 Sentence denotes Before the restrictions, Australia was expecting to receive approximately 200,000 air passengers from mainland China during February 2020 (Australian Bureau of Statistics, 2019).
T99 13409-13484 Sentence denotes Travel numbers fell dramatically following the imposed travel restrictions.
T100 13485-13629 Sentence denotes These restrictions were not intended (and highly unlikely [Errett et al., 2020]) to prevent the ultimate importation of COVID-19 into Australia.
T101 13630-13755 Sentence denotes Their purpose was to delay the establishment of an epidemic, buying valuable time for health authorities to plan and prepare.
T102 13756-14005 Sentence denotes During the month of February, with extensive testing and case targeted interventions (case isolation and contact quarantine) initiated from 29 January (Australian Government Department of Health, 2020d), Australia detected and managed only 12 cases.
T103 14006-14181 Sentence denotes Meanwhile, globally, the geographic extent of transmission and daily counts of confirmed cases and deaths continued to increase drastically (World Health Organization, 2020d).
T104 14182-14518 Sentence denotes In early March, Australia extended travel restrictions to a number of countries with large uncontained outbreaks, namely Iran (as of 1 March) (Commonwealth Government of Australia, 2020a), South Korea (as of 5 March) (Commonwealth Government of Australia, 2020b) and Italy (as of 11 March) (Commonwealth Government of Australia, 2020c).
T105 14519-14622 Sentence denotes Despite these measures, the daily case counts rose sharply in Australia during the first half of March.
T106 14623-14877 Sentence denotes While the vast majority of these cases were connected to travellers returning to Australia from overseas, localised community transmission had been reported in areas of Sydney (NSW) and Melbourne (VIC) (Australian Government Department of Health, 2020c).
T107 14878-15165 Sentence denotes Crude plots of the cumulative number of cases by country showed Australia on an early trajectory similar to the outbreaks experienced in China, Europe and the United States, where health systems had become or were becoming overwhelmed (Australian Government Department of Health, 2020f).
T108 15166-15379 Sentence denotes From 16 March, the Australian Government progressively implemented a range of social distancing measures in order to reduce and prevent further community transmission (Commonwealth Government of Australia, 2020d).
T109 15380-15526 Sentence denotes The day before, authorities had imposed a self-quarantine requirement on all international arrivals (Commonwealth Government of Australia, 2020e).
T110 15527-15800 Sentence denotes On 19 March, Australia closed its borders to all non-citizens and non-residents (Commonwealth Government of Australia, 2020f), and on March 27, moved to a policy of mandatory quarantine for any returning citizens and residents (Commonwealth Government of Australia, 2020g).
T111 15801-16071 Sentence denotes By 29 March, social distancing measures had been escalated to the extent that all Australians were strongly advised to leave their homes only for limited essential activities and public gatherings were limited to two people (Commonwealth Government of Australia, 2020h).
T112 16072-16208 Sentence denotes By late March, daily counts of new cases appeared to be declining, suggesting that these measures had successfully reduced transmission.
T113 16210-16248 Sentence denotes Quantifying the impact of the response
T114 16249-16462 Sentence denotes Quantifying changes in the rate of spread of infection over the course of an epidemic is critical for monitoring the collective impact of public health interventions and forecasting the short-term clinical burden.
T115 16463-16734 Sentence denotes A key indicator of transmission in context is the effective reproduction number (R𝑒𝑓𝑓) — the average number of secondary infections caused by an infected individual in the presence of public health interventions and for which no assumption of 100% susceptibility is made.
T116 16735-16862 Sentence denotes If control efforts are able to bring R𝑒𝑓𝑓 below 1, then on average there will be a decline in the number of new cases reported.
T117 16863-17066 Sentence denotes The decline will become apparent after a delay of approximately one incubation period plus time to case detection and reporting following implementation of the control measure (i.e., at least two weeks).
T118 17067-17231 Sentence denotes Using case counts from the Australian national COVID-19 database, we estimated R𝑒𝑓𝑓 over time for each Australian state from 24 February to 5 April 2020 (Figure 2).
T119 17232-17632 Sentence denotes We used a statistical method that estimates time-varying R𝑒𝑓𝑓 by using an optimally selected moving average window (according to the continuous ranked probability score) to smooth the curve and reduce the impact of localised clusters and outbreaks that may cause large fluctuations (London School of Hygiene & Tropical Medicine Mathematical Modelling of Infectious Diseases nCoV working group, 2020).
T120 17633-17726 Sentence denotes Importantly, the method accounts for time delays between illness onset and case notification.
T121 17727-17939 Sentence denotes Incorporation of this lag is critical for accurate interpretation of the most recent data in the analysis, to be sure that an observed drop in the number of reported cases reflects an actual drop in case numbers.
T122 17940-18039 Sentence denotes Results show that R𝑒𝑓𝑓 has likely been below one in each Australian state since early-to-mid March.
T123 18040-18212 Sentence denotes These estimates are geographically averaged results over large areas and it is possible that R𝑒𝑓𝑓 was much higher than one in a number of localised settings (see Figure 2).
T124 18213-18395 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 only contribute to the force of infection.
T125 18396-18470 Sentence denotes Imported and locally acquired cases were assumed to be equally infectious.
T126 18471-18534 Sentence denotes The method for estimating R𝑒𝑓𝑓 is sensitive to this assumption.
T127 18535-18826 Sentence denotes Hence, we performed a sensitivity analysis to assess the impact of stepwise reductions in the infectiousness of imported cases on R𝑒𝑓𝑓 as a result of quarantine measures implemented over time (see Figure 2—figure supplement 1, Figure 2—figure supplement 2, and Figure 2—figure supplement 3).
T128 18827-18931 Sentence denotes The sensitivity analyses suggest that R𝑒𝑓𝑓 may well have dropped below one later than shown in Figure 2.
T129 18932-19291 Sentence denotes In Victoria and New South Wales, the two Australian states with a substantial number of local cases, the effective reproduction number likely dropped from marginally above one to well below one within a two week period (considering both our main result and those from the sensitivity analyses) coinciding with the implementation of social distancing measures.
T130 19292-19629 Sentence denotes A comparable trend was observed in New Zealand and many Western European countries, including France, Spain and Germany (London School of Hygiene & Tropical Medicine Mathematical Modelling of Infectious Diseases nCoV working group, 2020), where similar national, stage-wise social distancing policies were enacted (Flaxman et al., 2020).
T131 19630-19918 Sentence denotes However, most of these European countries experienced widespread community transmission prior to the implementation of social distancing measures, with R𝑒𝑓𝑓 estimates reaching between 1.5 and 2 in early March and declining over a longer period (three to four weeks) relative to Australia.
T132 19920-19951 Sentence denotes Forecasting the clinical burden
T133 19952-20056 Sentence denotes Next we used our estimates of time-varying R𝑒𝑓𝑓 to forecast the short-term clinical burden in Australia.
T134 20057-20172 Sentence denotes Estimates were input into a mathematical model of disease dynamics that was extended to account for imported cases.
T135 20173-20434 Sentence denotes A sequential Monte Carlo method was used to infer the model parameters and appropriately capture the uncertainty (Moss et al., 2019a), conditional on each of a number of sampled R𝑒𝑓𝑓 trajectories up to 5 April, from which point they were assumed to be constant.
T136 20435-20601 Sentence denotes The model was subsequently projected forward from April 14 to April 28, to forecast the number of reported cases, assuming a symptomatic detection probability of 80%.
T137 20602-20725 Sentence denotes The number of new daily hospitalisations and ICU admissions were estimated from recently observed and forecast case counts.
T138 20726-20988 Sentence denotes Specifically, the age distribution of projected cases, and age-specific probabilities of hospitalisation and ICU admission, were extracted from Australian age-specific data on confirmed cases, assuming that this distribution would remain unchanged (see Table 1).
T139 20989-21202 Sentence denotes In order to calculate the number of occupied ward/ICU beds per day, length-of-stay in a ward bed and ICU bed were assumed to be Gamma distributed with means (SD) of 11 (3.42) days and 14 (5.22) days, respectively.
T140 21203-21416 Sentence denotes Our results indicated that with the public health interventions in place as of 13 April, Australia’s hospital ward and ICU occupancy would remain well below capacity thresholds over the period from 14 to 28 April.
T141 21417-21425 Sentence denotes Table 1.
T142 21427-21631 Sentence denotes Age-specific proportions of confirmed cases extracted from the Australian national COVID-19 database and age-specific estimates of the probability of hospitalisation and ICU admission for confirmed cases.
T143 21632-21730 Sentence denotes Age Proportion of cases Pr(hospitalisation | confirmed case) Pr(ICU admission | confirmed case)
T144 21731-21758 Sentence denotes 0-9 0.0102 0.1475 0.0000
T145 21759-21788 Sentence denotes 10-18 0.0186 0.1081 0.0090
T146 21789-21818 Sentence denotes 19-29 0.2258 0.0504 0.0007
T147 21819-21848 Sentence denotes 30-39 0.1587 0.0865 0.0074
T148 21849-21878 Sentence denotes 40-49 0.1291 0.0947 0.0208
T149 21879-21908 Sentence denotes 50-59 0.1550 0.1112 0.0173
T150 21909-21938 Sentence denotes 60-69 0.1686 0.1529 0.0318
T151 21939-21968 Sentence denotes 70-79 0.1050 0.2440 0.0558
T152 21969-21996 Sentence denotes 80+ 0.0290 0.3815 0.0462
T153 21998-22009 Sentence denotes Conclusions
T154 22010-22327 Sentence denotes Our analysis suggests that Australia’s combined strategy of early, targeted management of the risk of importation, case targeted interventions, and broad-scale social distancing measures applied prior to the onset of (detected) widespread community transmission has substantially mitigated the first wave of COVID-19.
T155 22328-22502 Sentence denotes More detailed analyses are required to assess the relative impact of specific response measures, and this information will be crucial for the next phase of response planning.
T156 22503-22635 Sentence denotes Other factors, such as temperature, humidity and population density may influence transmission of SARS-CoV-2 (Kissler et al., 2020).
T157 22636-22759 Sentence denotes Whether these factors have played a role in the relative control of SARS-CoV-2 in some countries, remains an open question.
T158 22760-23003 Sentence denotes Noting that epidemics are established in both the northern and southern hemispheres, it may be possible to gain insight into such factors over the next six months, via for example a comparative analysis of transmission in Australia and Europe.
T159 23004-23172 Sentence denotes We further anticipated that the Australian health care system was well positioned to manage the projected COVID-19 case loads over the forecast period (up to 28 April).
T160 23173-23352 Sentence denotes Ongoing situational assessment and monitoring of forecast hospital and ICU demand will be essential for managing possible future relaxation of broad-scale community interventions.
T161 23353-23585 Sentence denotes Vigilance for localised increases in epidemic activity and in particular for outbreaks in vulnerable populations such as residential aged care facilities, where a high proportion of cases are likely to be severe, must be maintained.
T162 23586-23710 Sentence denotes One largely unknown factor at present is the proportion of SARS-CoV-2 infections that are asymptomatic, mild or undiagnosed.
T163 23711-23814 Sentence denotes Even if this number is high, the Australian population would still be largely susceptible to infection.
T164 23815-23933 Sentence denotes Accordingly, complete relaxation of the measures currently in place would see a rapid resurgence in epidemic activity.
T165 23934-23974 Sentence denotes This problem is not unique to Australia.
T166 23975-24166 Sentence denotes Many countries with intensive social distancing measures in place are starting to grapple with their options and time frames for a gradual return to relative normalcy (Gottlieb et al., 2020).
T167 24167-24375 Sentence denotes There are difficult decisions ahead for governments, and for now Australia is one of the few countries fortunate enough to be able to plan the next steps from a position of relative calm as opposed to crisis.
T168 24377-24398 Sentence denotes Materials and methods
T169 24400-24457 Sentence denotes Estimating the time-varying effective reproduction number
T170 24459-24467 Sentence denotes Overview
T171 24468-24598 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 24599-24879 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 24880-25001 Sentence denotes Full details of their statistical analysis and code base is available via their website (https://epiforecasts.io/covid/).
T174 25002-25321 Sentence denotes The uncertainty in the R𝑒𝑓𝑓 estimates (shown in Figure 2; Figure 2—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 25322-25534 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 25535-25681 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 25683-25687 Sentence denotes Data
T178 25688-25807 Sentence denotes We used line-lists of reported cases for each Australian state/territory extracted from the national COVID-19 database.
T179 25808-26036 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 26038-26074 Sentence denotes Reporting delays and under-reporting
T181 26075-26358 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 26359-26429 Sentence denotes The estimated reporting delay is assumed to remain constant over time.
T183 26430-26607 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 26608-26725 Sentence denotes Adjusting for reporting delays is critical for inferring when a drop in observed cases reflects a true drop in cases.
T185 26726-26824 Sentence denotes Trends identified using this approach are robust to under-reporting, assuming that it is constant.
T186 26825-26891 Sentence denotes However, absolute values of R𝑒𝑓𝑓 may be biased by reporting rates.
T187 26892-26968 Sentence denotes Pronounced changes in reporting rates may also impact the trends identified.
T188 26969-27109 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 27110-27338 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 27339-27631 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 27632-27689 Sentence denotes The converse would be true when overestimating the delay.
T192 27690-27876 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 27878-27932 Sentence denotes Estimating the effective reproduction number over time
T194 27933-28116 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 28117-28275 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 28276-28332 Sentence denotes 3.7, 6.0) and a standard deviation of 2.9 days (95% CrI:
T197 28333-28422 Sentence denotes 1.9, 4.9), as estimated from early outbreak data in Wuhan, China (Nishiura et al., 2020).
T198 28423-28546 Sentence denotes Combining the incidence over time with the uncertain distribution of serial intervals allows us to estimate R𝑒𝑓𝑓 over time.
T199 28547-28643 Sentence denotes A different choice of serial interval distribution would affect the estimated time varying R𝑒𝑓𝑓.
T200 28644-28765 Sentence denotes This sensitivity is explored in detail in Flaxman et al., 2020, though we provide a brief description of the impact here.
T201 28766-28929 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 28930-29033 Sentence denotes This effect can be understood intuitively by considering the epidemic dynamics in these two situations.
T203 29034-29092 Sentence denotes When R𝑒𝑓𝑓>1 , daily case counts are increasing on average.
T204 29093-29293 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 29294-29384 Sentence denotes In order to generate the same number of observed cases in the present, R𝑒𝑓𝑓 must increase.
T206 29385-29430 Sentence denotes A similar observation can be made for R𝑒𝑓𝑓<1.
T207 29431-29773 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 29774-29879 Sentence denotes When the estimated R𝑒𝑓𝑓 is below 1, a higher mean serial interval would further decrease those estimates.
T209 29880-29975 Sentence denotes Qualitatively, this does not impact on the time series of R𝑒𝑓𝑓 in each Australian jurisdiction.
T210 29976-30145 Sentence denotes A 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 30146-30393 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 30394-30529 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 30530-30647 Sentence denotes Conservatively, we assumed that all cases with an unknown or unconfirmed source of acquisition were locally acquired.
T214 30649-30678 Sentence denotes Accounting for imported cases
T215 30679-30780 Sentence denotes A large proportion of cases reported in Australia from January until now were imported from overseas.
T216 30781-30989 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 30990-31186 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 31187-31285 Sentence denotes Specifically, the method assumes that local and imported cases contribute equally to transmission.
T219 31286-31346 Sentence denotes The results under this assumption are presented in Figure 2.
T220 31347-31578 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 1—figure supplement 2).
T221 31579-31818 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 31819-32007 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 32008-32146 Sentence denotes Prior to 15 March, returning Australian residents and citizens (and their dependents) from mainland China were advised to self-quarantine.
T224 32147-32388 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 32389-32583 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 32584-33025 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 33026-33135 Sentence denotes We further assumed that the relative infectiousness of imported cases decreased with each intervention phase.
T228 33136-33439 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 33440-33674 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 33675-33811 Sentence denotes We then varied the percentage of imported cases contributing to transmission over the three intervention phases, as detailed in Table 2.
T231 33812-33820 Sentence denotes Table 2.
T232 33822-33955 Sentence denotes Percentage of imported cases assumed to be contributing to transmission over three intervention phases for each sensitivity analysis.
T233 33956-34308 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 34309-34352 Sentence denotes Imported cases contributing to transmission
T235 34353-34416 Sentence denotes Sensitivity analysis Prior to 15 March 15–27 March 27 March–
T236 34417-34432 Sentence denotes 1 90% 50% 1%
T237 34433-34448 Sentence denotes 2 80% 50% 1%
T238 34449-34464 Sentence denotes 3 50% 20% 1%
T239 34465-34567 Sentence denotes The results of these three analyses are shown in Figure 2—figure supplements 1, 2 and 3, respectively.
T240 34569-34618 Sentence denotes Forecasting short-term ward and ICU bed occupancy
T241 34619-34742 Sentence denotes We used the estimates of time-varying R𝑒𝑓𝑓 to forecast the national short-term ward/ICU occupancy due to COVID-19 patients.
T242 34744-34767 Sentence denotes Forecasting case counts
T243 34768-35003 Sentence denotes The forecasting method combines an SEEIIR (susceptible-exposed-infectious-recovered) population model of infection with daily COVID-19 case notification counts, through the use of a bootstrap particle filter (Arulampalam et al., 2002).
T244 35004-35169 Sentence denotes This approach is similar to that implemented and described in Moss et al., 2019b, in the context of seasonal influenza forecasts for several major Australian cities.
T245 35170-35309 Sentence denotes Briefly, the particle filter method uses post-regularisation (Doucet et al., 2001), with a deterministic resampling stage (Kitagawa, 1996).
T246 35310-35390 Sentence denotes Code and documentation are available at https://epifx.readthedocs.io/en/latest/.
T247 35391-35709 Sentence denotes The daily case counts by date of diagnosis were modelled using a negative binomial distribution with a fixed dispersion parameter k, and the expected number of cases was proportional to the daily incidence of symptomatic infections in the SEEIIR model; this proportion was characterised by the observation probability.
T248 35710-36044 Sentence denotes Natural disease history parameters were sampled from narrow uniform priors, based on values reported in the literature for COVID-19 (Table 3), and each particle was associated with an R𝑒𝑓𝑓 trajectory that was drawn from the state/territory R𝑒𝑓𝑓 trajectories in Figure 2 up to 5 April, from which point they are assumed to be constant.
T249 36045-36199 Sentence denotes The model was subsequently projected forward from April 14 to April 28, to forecast the number of reported cases, assuming a detection probability of 80%.
T250 36200-36208 Sentence denotes Table 3.
T251 36210-36246 Sentence denotes SEEIIR forecasting model parameters.
T252 36247-36294 Sentence denotes Parameter Definition Value/Prior distribution
T253 36295-36362 Sentence denotes σ Inverse of the mean incubation period U ⁢ ( 4 - 1 , 3 - 1 )
T254 36363-36431 Sentence denotes γ Inverse of the mean infectious period U ⁢ ( 10 - 1 , 9 - 1 )
T255 36432-36497 Sentence denotes τ Time of first exposure (days since 2020-01-01) U ⁢ ( 0 , 28 )
T256 36498-36541 Sentence denotes p 𝑜𝑏𝑠 Probability of observing a case 0.8
T257 36542-36591 Sentence denotes k Dispersion parameter on Negative-Binomial 100
T258 36592-36950 Sentence denotes observation model In order to account for imported cases, we used daily counts of imported cases to construct a time-series of the expected daily importation rate and, assuming that such cases were identified one week after initial exposure, introduced exposure events into each particle trajectory by adding an extra term to the force of infection equation.
T259 36951-37163 Sentence denotes Model equations below describe the flow of individuals in the population from the susceptible class (S), through two exposed classes (E1, E2), two infectious classes (I1, I2) and finally into a removed class (R).
T260 37164-37294 Sentence denotes The state variables S,E1,E2,I1,I2,R correspond to the proportion of individuals in the population (of size N) in each compartment.
T261 37295-37553 Sentence denotes Given the closed population and unidirectional flow of individuals through the compartments, we evaluate the daily incidence of symptomatic individuals (at time t) as the change in cumulative incidence (the bracketed term in the expression for 𝔼⁢[yt] below).
T262 37554-37694 Sentence denotes Two exposed and infectious classes are chosen such that the duration of time in the exposed or infectious period has an Erlang distribution.
T263 37695-37745 Sentence denotes The corresponding parameters are given in Table 2.
T264 37746-37859 Sentence denotes Model equations:dSdt=−β(t)⋅S(I1+I2)dE1dt=β(t)⋅S(I1+I2)−2σE1dE2dt=2σE1−2σE2dI1dt=2σE2−2γI1dI2dt=2γI1−2γI2dRdt=2γI2
T265 37860-37927 Sentence denotes With initial conditions:S(0)=N−10NE1(0)=10NE2(0)=I1(0)=I2(0)=R(0)=0
T266 37928-38062 Sentence denotes Observation model:E[yt]=N⋅pobs⋅[I2(t)+R(t)−(I2(t−1)+R(t−1))]xt=[S(t),E1(t),E2(t),I1(t),I2(t),R(t),βi(t),σ,γ,τ]ℒ(yt∣xt)∼NegBin(E[yt],k)
T267 38063-38183 Sentence denotes With time-varying transmission rate corresponding to R𝑒𝑓𝑓 trajectory i:βi(t)={0,ift<τReffi(t)⋅γ,ift≥τ,for i∈{1,2,...,10}
T268 38185-38263 Sentence denotes Forecasting ward and ICU bed occupancy from observed and projected case counts
T269 38264-38392 Sentence denotes The number of new daily hospitalisations and ICU admissions were estimated from recently observed and forecasted case counts by:
T270 38393-38547 Sentence denotes Estimating the age distribution of projected case counts using data from the national COVID-19 database on the age-specific proportion of confirmed cases;
T271 38548-38663 Sentence denotes Estimating the age-specific hospitalisation and ICU admission rates using data from the national COVID-19 database.
T272 38664-38868 Sentence denotes We assumed that all hospitalisations and ICU admissions were either recorded or were missing at random (31% and 58% of cases had no information recorded under hospitalisation or ICU status, respectively);
T273 38869-39223 Sentence denotes Randomly drawing the number of hospitalisations/ICU admissions in each age-group (for both the observed and projected case counts) from a binomial distribution with number of trials given by the expected number of cases in each age group (from 1), and probability given by the observed proportion of hospitalisations/ICU admissions by age group (from 2).
T274 39224-39446 Sentence denotes Finally, in order to calculate the number of occupied ward/ICU beds per day, length-of-stay in a ward bed and ICU bed were assumed to be Gamma distributed with means (SD) of 11 (3.42) days and 14 (5.22) days, respectively.
T275 39447-39582 Sentence denotes We assumed ICU admissions required a ward bed prior to, and following, ICU stay for a Poisson distributed number of days with mean 2.5.
T276 39583-39736 Sentence denotes Relevant Australian data were not available to parameterise a model that captures the dynamics of patient flow within the hospital system in more detail.
T277 39737-39880 Sentence denotes Instead, these distributions were informed by a large study of clinical characteristics of 1099 COVID-19 patients in China (Guan et al., 2020).
T278 39881-40081 Sentence denotes This model provides a useful indication of hospital bed occupancy based on limited available data and may be updated as more specific data (e.g., on COVID-19 patient length-of-stay) becomes available.
T279 40083-40102 Sentence denotes Funding Information
T280 40103-40151 Sentence denotes This paper was supported by the following grant:
T281 40152-40252 Sentence denotes http://dx.doi.org/10.13039/501100003921Department of Health, Australian Government to James M McCaw.
T282 40254-40270 Sentence denotes Acknowledgements
T283 40271-40438 Sentence denotes This study represents surveillance data reported through the Communicable Diseases Network Australia (CDNA) as part of the nationally coordinated response to COVID-19.
T284 40439-40664 Sentence denotes We thank public health staff from incident emergency operations centres in state and territory health departments, and the Australian Government Department of Health, along with state and territory public health laboratories.
T285 40665-40747 Sentence denotes We thank members of CDNA for their feedback and perspectives on the study results.
T286 40748-40872 Sentence denotes We thank Dr Jonathan Tuke for helping to assemble Australian national and state announcements of COVID-19 response measures.
T287 40874-40896 Sentence denotes Additional information
T288 40897-40916 Sentence denotes Competing interests
T289 40917-41130 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T290 41131-41344 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T291 41345-41558 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T292 41559-41772 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T293 41773-41986 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T294 41987-42200 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T295 42201-42414 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T296 42415-42628 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T297 42629-42842 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T298 42843-43056 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T299 43057-43270 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T300 43271-43484 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T301 43485-43698 Sentence denotes This work was undertaken with direct funding support from the Australian Government Department of Health, Office of Health Protection and has assisted the Australian Government in its epidemic response activities.
T302 43699-43719 Sentence denotes Author contributions
T303 43720-43876 Sentence denotes Conceptualization, Data curation, Software, Formal analysis, Validation, Visualization, Methodology, Writing - original draft, Writing - review and editing.
T304 43877-43981 Sentence denotes Conceptualization, Data curation, Formal analysis, Visualization, Methodology, Writing - original draft.
T305 43982-44024 Sentence denotes Methodology, Writing - review and editing.
T306 44025-44067 Sentence denotes Methodology, Writing - review and editing.
T307 44068-44160 Sentence denotes Data curation, Software, Formal analysis, Validation, Methodology, Writing - original draft.
T308 44161-44203 Sentence denotes Methodology, Writing - review and editing.
T309 44204-44250 Sentence denotes Formal analysis, Writing - review and editing.
T310 44251-44293 Sentence denotes Methodology, Writing - review and editing.
T311 44294-44336 Sentence denotes Methodology, Writing - review and editing.
T312 44337-44379 Sentence denotes Methodology, Writing - review and editing.
T313 44380-44422 Sentence denotes Methodology, Writing - review and editing.
T314 44423-44465 Sentence denotes Supervision, Writing - review and editing.
T315 44466-44593 Sentence denotes Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Writing - review and editing.
T316 44595-44611 Sentence denotes Additional files
T317 44612-44626 Sentence denotes Source code 1.
T318 44628-44642 Sentence denotes Analysis code.
T319 44643-44669 Sentence denotes Transparent reporting form
T320 44671-44688 Sentence denotes Data availability
T321 44689-44746 Sentence denotes Analysis code is included in the supplementary materials.
T322 44747-44841 Sentence denotes Datasets analysed and generated during this study are included in the supplementary materials.
T323 44842-45024 Sentence denotes For estimates of the time-varying effective reproduction number (Figure 2), the complete line listed data within the Australian national COVID-19 database are not publicly available.
T324 45025-45393 Sentence denotes However, we provide the cases per day by notification date and state (as shown in Figure 1 and Figure 1–figure supplement 1) which, when supplemented with the estimated distribution of the delay from symptom onset to notification (samples from this distribution are provided as a data file), analyses of the time-varying effective reproduction number can be performed.