scholarly journals The temporal association of introducing and lifting non-pharmaceutical interventions with the time-varying reproduction number (R) of SARS-CoV-2: a modelling study across 131 countries

2020 ◽  
Author(s):  
You Li ◽  
Harry Campbell ◽  
Durga Kulkarni ◽  
Alice Harpur ◽  
Madhurima Nundy ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Temporal Association ◽  
Time Varying ◽  
Pharmaceutical Interventions ◽  
Modelling Study

scholarly journals The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang Liu ◽  
◽  
Christian Morgenstern ◽  
James Kelly ◽  
Rachel Lowe ◽  
...  
Keyword(s):  
Empirical Evidence ◽  
Strong Evidence ◽  
International Travel ◽  
School Closure ◽  
Contact Tracing ◽  
Temporal Association ◽  
Time Varying ◽  
Temporal Clustering ◽  
The Impact ◽  
Pharmaceutical Interventions

Abstract Background Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. Methods We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission using data from January to June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect, and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support, and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g. restrictions on 1000+ people gathering were not effective, restrictions on < 10 people gathering were). Evidence about the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Effect sizes varied depending on whether or not we included data after peak NPI intensity. Conclusion Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects, and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many, although not all, actions policy-makers are taking to respond to the COVID-19 pandemic.

scholarly journals Tracking R of COVID-19: A new real-time estimation using the Kalman filter

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244474 ◽  
Author(s):  
Francisco Arroyo-Marioli ◽  
Francisco Bullano ◽  
Simas Kucinskas ◽  
Carlos Rondón-Moreno
Keyword(s):  
Growth Rate ◽  
Kalman Filter ◽  
Reproduction Number ◽  
Time Estimation ◽  
Sir Model ◽  
Time Varying ◽  
The World ◽  
Real Time Estimation ◽  
Image Position ◽  
Pharmaceutical Interventions

We develop a new method for estimating the effective reproduction number of an infectious disease (R) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, R is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of R for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.

scholarly journals The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

2020 ◽  
Author(s):  
Yang Liu ◽  
Christian Morgenstern ◽  
James Kelly ◽  
Rachel Lowe ◽  
Mark Jit ◽  
...  
Keyword(s):  
Empirical Evidence ◽  
Strong Evidence ◽  
International Travel ◽  
School Closure ◽  
Contact Tracing ◽  
Temporal Association ◽  
Time Varying ◽  
Temporal Clustering ◽  
The Impact ◽  
Pharmaceutical Interventions

Introduction: Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. Methods: We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission with data from January - June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g., restrictions on 1000+ people gathering were not effective, restrictions on <10 people gathering was). Evidence supporting the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Conclusion: Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications taking into account these effects, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many although not all the actions policy-makers are taking to respond to the COVID-19 pandemic.

scholarly journals Despite vaccination, China needs non-pharmaceutical interventions to prevent widespread outbreaks of COVID-19 in 2021

2021 ◽  
Author(s):  
Juan Yang ◽  
Valentina Marziano ◽  
Xiaowei Deng ◽  
Giorgio Guzzetta ◽  
Juanjuan Zhang ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Synergetic Effect ◽  
Data Driven ◽  
Natural Immunity ◽  
Epidemic Threshold ◽  
Policy Makers ◽  
Large Populations ◽  
One Year ◽  
Pharmaceutical Interventions

AbstractCOVID-19 vaccination is being conducted in over 200 countries and regions to control SARS-CoV-2 transmission and return to a pre-pandemic lifestyle. However, understanding when non-pharmaceutical interventions (NPIs) can be lifted as immunity builds up remains a key question for policy makers. To address this, we built a data-driven model of SARS-CoV-2 transmission for China. We estimated that, to prevent the escalation of local outbreaks to widespread epidemics, stringent NPIs need to remain in place at least one year after the start of vaccination. Should NPIs alone be capable of keeping the reproduction number (Rt) around 1.3, the synergetic effect of NPIs and vaccination could reduce the COVID-19 burden by up to 99% and bring Rt below the epidemic threshold in about 9 months. Maintaining strict NPIs throughout 2021 is of paramount importance to reduce COVID-19 burden while vaccines are distributed to the population, especially in large populations with little natural immunity.

scholarly journals Heterogeneity and effectiveness analysis of COVID-19 prevention and control in major cities in China through time-varying reproduction number estimation

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qing Cheng ◽  
Zeyi Liu ◽  
Guangquan Cheng ◽  
Jincai Huang
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Reproduction Number ◽  
Correlation Method ◽  
Control Measures ◽  
Time Varying ◽  
Short Period ◽  
Significant Difference ◽  
Prevention And Control Measures ◽  
And Control

AbstractBeginning on December 31, 2019, the large-scale novel coronavirus disease 2019 (COVID-19) emerged in China. Tracking and analysing the heterogeneity and effectiveness of cities’ prevention and control of the COVID-19 epidemic is essential to design and adjust epidemic prevention and control measures. The number of newly confirmed cases in 25 of China’s most-affected cities for the COVID-19 epidemic from January 11 to February 10 was collected. The heterogeneity and effectiveness of these 25 cities’ prevention and control measures for COVID-19 were analysed by using an estimated time-varying reproduction number method and a serial correlation method. The results showed that the effective reproduction number (R) in 25 cities showed a downward trend overall, but there was a significant difference in the R change trends among cities, indicating that there was heterogeneity in the spread and control of COVID-19 in cities. Moreover, the COVID-19 control in 21 of 25 cities was effective, and the risk of infection decreased because their R had dropped below 1 by February 10, 2020. In contrast, the cities of Wuhan, Tianmen, Ezhou and Enshi still had difficulty effectively controlling the COVID-19 epidemic in a short period of time because their R was greater than 1.

scholarly journals The effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in different socioeconomic populations in Kuwait: a modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fatima Khadadah ◽  
Abdullah A. Al-Shammari ◽  
Ahmad Alhashemi ◽  
Dari Alhuwail ◽  
Bader Al-Saif ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Transmission Model ◽  
Socioeconomic Groups ◽  
Before And After ◽  
Cross Transmission ◽  
Community Transmission ◽  
The Impact ◽  
Pharmaceutical Interventions ◽  
The Basic Reproduction Number

Abstract Background Aggressive non-pharmaceutical interventions (NPIs) may reduce transmission of SARS-CoV-2. The extent to which these interventions are successful in stopping the spread have not been characterized in countries with distinct socioeconomic groups. We compared the effects of a partial lockdown on disease transmission among Kuwaitis (P1) and non-Kuwaitis (P2) living in Kuwait. Methods We fit a modified metapopulation SEIR transmission model to reported cases stratified by two groups to estimate the impact of a partial lockdown on the effective reproduction number ($$ {\mathcal{R}}_e $$ R e ). We estimated the basic reproduction number ($$ {\mathcal{R}}_0 $$ R 0 ) for the transmission in each group and simulated the potential trajectories of an outbreak from the first recorded case of community transmission until 12 days after the partial lockdown. We estimated $$ {\mathcal{R}}_e $$ R e values of both groups before and after the partial curfew, simulated the effect of these values on the epidemic curves and explored a range of cross-transmission scenarios. Results We estimate $$ {\mathcal{R}}_e $$ R e at 1·08 (95% CI: 1·00–1·26) for P1 and 2·36 (2·03–2·71) for P2. On March 22nd, $$ {\mathcal{R}}_e $$ R e for P1 and P2 are estimated at 1·19 (1·04–1·34) and 1·75 (1·26–2·11) respectively. After the partial curfew had taken effect, $$ {\mathcal{R}}_e $$ R e for P1 dropped modestly to 1·05 (0·82–1·26) but almost doubled for P2 to 2·89 (2·30–3·70). Our simulated epidemic trajectories show that the partial curfew measure greatly reduced and delayed the height of the peak in P1, yet significantly elevated and hastened the peak in P2. Modest cross-transmission between P1 and P2 greatly elevated the height of the peak in P1 and brought it forward in time closer to the peak of P2. Conclusion Our results indicate and quantify how the same lockdown intervention can accentuate disease transmission in some subpopulations while potentially controlling it in others. Any such control may further become compromised in the presence of cross-transmission between subpopulations. Future interventions and policies need to be sensitive to socioeconomic and health disparities.

scholarly journals Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study

2021 ◽  
Author(s):  
Sam Moore ◽  
Edward M Hill ◽  
Michael J Tildesley ◽  
Louise Dyson ◽  
Matt J Keeling
Keyword(s):  
Mathematical Modelling ◽  
Pharmaceutical Interventions ◽  
Modelling Study
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