Epidemic Surveillance Models for Containing the Spread of SARS-CoV-2 Variants: Taiwan Experience

ObjectivesTwo kinds of epidemic surveillance models are presented for containing the spread of SARS-CoV-2 variants so as to avert and stamp out a community-acquired outbreak (CAO) with non-pharmaceutical interventions (NPIs), tests, and vaccination. DesignThe surveillance of domestic cluster infections transmitted from imported cases with one-week time lag assessed by the Poisson model and the surveillance of whether, how and when NPIs and test contained the CAO with the SEIR model. SettingsBorder and Community of Taiwan. Main Outcome MeasurementsThe expected number and the upper bound of the 95% credible interval (CrI) of weekly covid-19 cases compared with the observed number for assessing the threshold of a CAO; effective reproductive number (Rt) and the effectiveness of NPIs for containing a CAO. ResultsFor the period of January-September 2020 when the wild type and the D614G period were prevailing, an increase in one imported case prior to one week would lead to 9.54% (95% CrI 6.44% to 12.59%) higher risk of domestic cluster infection that provides a one-week prior alert signal for more stringent NPIs and active testing locally. Accordingly, there was an absence of CAO until the Alpha VOC period of February 2021. However, given level one of NPI alert the risk of domestic cluster infections was gradually elevated to 14.14% (95% CrI 5.41% to 25.10%), leading to the Alpha VOC CAOs of six hotspots around mid-May 2021. It took two-and-half months for containing this CAO mainly with level three of NPI alert and rapid test and partially by the rolling out of vaccination. By applying the SEIR model, the Rt decreased from 4.0 at beginning to 0.7 on 31 July 2021 in parallel with the escalating NPIs from 30% to 90%. Containing a small outbreak of Delta VOC during this CAO period was also evaluated and demonstrated. After controlling the CAO, it again returned to imported-domestic transmission for Delta VOC from July until September 2021, giving an estimate of 10.16% (95% CrI: 7.01% to 13.59%) for the risk of several small cluster infections. However, there was an absence of CAO that resulted from the effectiveness of NPIs and tests, and the rapid expansion of vaccination. ConclusionsAverting and containing CAOs of SARS-CoV-2 variants are demonstrated by two kinds of epidemic surveillance models that have been applied to Taiwan scenario. These two models can be accommodated to monitor the epidemic of forthcoming emerging SARS-CoV-2 VOCs with various circumstances of vaccine coverage, NPIs, and tests in countries worldwide.

Bayesian approach for modelling the dynamic of COVID-19 outbreak on the Diamond Princess Cruise Ship

The outbreaks of acute respiratory infectious disease with high attack rates on cruise ships were rarely studied. The outbreak of COVID-19 on the Diamond Princess Cruise Ship provides an unprecedented opportunity to estimate its original transmissibility with basic reproductive number (R0) and the effectiveness of containment measures. The traditional deterministic approach for estimating R0 is based on the outbreak of a large population size rather than that a small cohort of cruise ship. The parameters are therefore fraught with uncertainty. To tackle this problem, we developed a Bayesian Susceptible-Exposed-Infected-Recovery (SEIR) model with ordinary differential equation (ODE) to estimate three parameters, including transmission coefficients, the latent period, and the recovery rate given the uncertainty implicated the outbreak of COVID-19 on cruise ship with modest population size. Based on the estimated results on these three parameters before the introduction of partial containment measures, the natural epidemic curve after intervention was predicted and compared with the observed curve in order to assess the efficacy of containment measures. With the application of the Bayesian model to the empirical data on COVID-19 outbreak on the Diamond Princess Cruise Ship, the R0 was estimated as high as 5.71(95% credible interval: 4.08-7.55) because of its aerosols and fomite transmission mode. The simulated trajectory shows the entire epidemic period without containment measurements was approximately 47 days and reached the peak one month later after the index case. The partial containment measure reduced 34% (95% credible interval: 31-36%) infected passengers. Such a discovery provides an insight into timely evacuation and early isolation and quarantine with decontamination for containing other cruise ships and warship outbreaks.

Easing social distancing index after COVID-19 pandemic

ContextEasing social distancing (ESD) is a global public health issue in post-pandemic period of COVID-19 and requires a simple index for real time assessment. ObjectiveWe aimed to develop a simple index for ESD to quantify the impacts of social distancing for reducing confirmed infected cases, optimal triage and care of patients for recovery, and critical care capacity for reducing death from COVID-19. Design, Setting, and ParticipantsData on the retrospective cohort of 185 countries with reported numbers on confirmed cases, recovery, and death from COVID-19 were retrieved from publicity available repository. Up to May 31, a total of 5,844,136 confirmed cases, 2,639,961 recovered, and 327,487 deaths were reported globally. Main Outcome MeasuresThe ESD index measured by cumulative number of COVID-19 cases and recovery and case-fatality rate. ResultsWe developed a simple index for the guidance of easing social distancing (ESD). If the ESD index is less than 1, ESD would be considered. The global ESD index declined from 3.87 at peak in March to 1.35 by the end of May, consisting of 56.76% countries/regions (105/185) with the ESD lower than one. Conclusion and RelevanceThis simple ESD index provides a quantitative assessment on whether and when to ease social distancing from local to global community.

Impacts of remdesivir on dynamics and efficacy stratified by the severity of COVID-19: a simulated two-arm controlled study

BackgroundThe impact of remdesivir on length of stay of hospitalization, high-risk state, and death stratified by the severity of COVID-19 at enrollment is controversial. MethodsWe applied a simulated two-arm controlled study design to the data on compassionate use of remdesivir as a secondary analysis. Dynamics of risk states and death from COVID-19 patients defined by the six-point disease severity recommended by the WHO R&D and the time to discharge from hospital were used to evaluate the efficacy of remdesivir treatment compared with standard care. ResultsStratified by the risk state at enrollment, low-risk patients exhibited the highest efficacy of remdesivir in reducing subsequent progression to high-risk state by 67% (relative risk (RR)=0.33,95% CI: 0.30-0.35) and further to death by 55% (RR=0.45, 95%CI: 0.39-0.50). For the medium-risk patients, less but still statistically significant efficacy results were noted in reducing progression to high-risk state by 52% (RR=0.48, 95% CI: 0.45-0.51) and further to death by 40% (RR=0.60, 95% CI:0.54-0.66). High-risk state patients treated with remdesivir led to a 25% statistically significant reduction in death (RR=0.75, 95% CI: 0.69-0.82). Regarding the outcome of discharge, remdesivir treatment was most effective for medium-risk patients at enrollment (RR: 1.41, 95% CI: 1.35-1.47) followed by high-(RR=1.34, 95% CI: 1.27-1.42) and low-risk patients (RR=1.28, 95% CI: 1.25-1.31). ConclusionOur results with a simulated two-arm controlled study have provided a new insight into the precision treatment of remdesivir for COVID-19 patients based on risk-stratified efficacy.

Efficacy of remdesivir in COVID-19 patients with a simulated two-arm controlled study

While the recent study on the compassionate use of remdesivir for COVID-19 patients has shown a 68% clinical improvement7 it is a one-arm study that renders the evaluation of the efficacy in reducing death and the length of stay of hospitalization intractable due to a lacking of the control group. We came up with a two-arm controlled study design to simulate the treated and the untreated (control group) group by applying two respective transition models to the empirical data on dynamics of the disease severity (Figure 2 of the original article7) that are classified into low- (no and low oxygen supplement), medium- (non-invasive ventilator and high oxygen supplement), and high-(ECMO and invasive ventilator) from enrolment until discharge, death or the end of follow-up. By using a simulated two-arm controlled study, the remdesivir treatment group as opposed to the control group led to a statistically significantly 29% (95% CI: 22-35%) reduction of death from COVID-19. The treated group also revealed a 33% (95% CI 28-38%) significantly higher odds of discharge than the control group. The median time to discharge for the treated group (5.5 days, 16.5 days, and 29.5 days for low-, medium-, and high-risk state, respectively) was around half of those of the control arm. Our results with a simulated two-arm controlled study have not only corroborated the efficacy of remdesivir but also made great contribution to designing a further large-scale randomized controlled trial. They have significant implications for reducing transmission probability and infectious time of COVID-19 patients when contacting with susceptible health care workers during hospitalization. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/20088559v1_fig2.gif" ALT="Figure 2"> View larger version (18K): org.highwire.dtl.DTLVardef@1c9a456org.highwire.dtl.DTLVardef@1442cdeorg.highwire.dtl.DTLVardef@ddd9d6org.highwire.dtl.DTLVardef@10895f9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Cumulative rate of discharge and death by treatments C_FIG Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the efficacy of remdesivir in reducing advanced disease state or death from COVID-19 and the length of stay of hospitalization? FindingsRemdesivir treatment results in a 33% significantly higher odds of discharge, a 29% significantly lower risk of death, and a 39% significantly lower risk for the combined endpoint of severe status and death. The median time to discharge for the remdesivir treated group was around half of the median time-to-discharge compared with the control arm. MeaningRemdesivir is effective in treating COVID-19 patients in terms of enhancing recovery and accelerating discharge.