scholarly journals Mobility data can explain the entire COVID-19 outbreak course in Japan

2020 ◽  
Author(s):  
Junko Kurita ◽  
Tamie Sugawara ◽  
Yasushi Ohkusa
Keyword(s):  
Confidence Interval ◽  
Polynomial Function ◽  
Reproduction Number ◽  
Sir Model ◽  
Control Measures ◽  
Recovery Model ◽  
Mobility Data

AbstractBackgroundIn Japan, as a countermeasure against the COVID-19 outbreak, voluntary restrictions against going out (VRG) have been applied.ObjectWe examined mobility information provided by Apple Inc. to a susceptible–infected–recovery model.MethodWhen applying a polynomial function to daily Apple data with the SIR model, we presumed the function up to a cubic term as in our earlier study.ResultsEstimation results demonstrated R0 as 1.507 and its 95% confidence interval was [1.502, 1.509].. The estimated coefficients of Apple data was 1.748 and its 95% confidence interval was [1.731, 1.788].Discussion and ConclusionResults show that mobility data from Apple Inc. can explain the entire course of the outbreak in COVID-19 in Japan. Therefore, monitoring Apple data might be sufficient to adjust control measures to maintain an effective reproduction number of less than one.

scholarly journals The first 100 days of SARS-CoV-2 control in Vietnam

2020 ◽  
Author(s):  
Thai Quang Pham ◽  
Maia Rabaa ◽  
Luong Huy Duong ◽  
Tan Quang Dang ◽  
Quang Dai Tran ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Severe Disease ◽  
Steering Committee ◽  
International Travel ◽  
Control Measures ◽  
Contact Tracing ◽  
Population Mobility ◽  
Early Introduction ◽  
Mobility Data ◽  
Travel Restrictions

Background: One hundred days after SARS-CoV-2 was first reported in Vietnam on January 23rd, 270 cases have been confirmed, with no deaths. We describe the control measures used and their relationship with imported and domestically-acquired case numbers. Methods: Data on the first 270 SARS-CoV-2 infected cases and the timing and nature of control measures were captured by Vietnam's National Steering Committee for COVID-19 response. Apple and Google mobility data provided population movement proxies. Serial intervals were calculated from 33 infector-infectee pairs and used to estimate the proportion of pre-symptomatic transmission events and time-varying reproduction numbers. Results: After the first confirmed case on January 23rd, the Vietnamese Government initiated mass communications measures, contact tracing, mandatory 14-day quarantine, school and university closures, and progressive flight restrictions. A national lockdown was implemented between April 1st and 22nd. Around 200,000 people were quarantined and 266,122 RT-PCR tests conducted. Population mobility decreased progressively before lockdown. 60% (163/270) of cases were imported; 43% (89/208) of resolved infections were asymptomatic. 21 developed severe disease, with no deaths. The serial interval was 3.24 days, and 27.5% (95% confidence interval, 15.7%-40.0%) of transmissions occurred pre-symptomatically. Limited transmission amounted to a maximum reproduction number of 1.15 (95% confidence interval, 0.37-2.36). No community transmission has been detected since April 15th. Conclusions: Vietnam has controlled SARS-CoV-2 spread through the early introduction of communication, contact-tracing, quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic cases and imported cases, and evidence for substantial pre-symptomatic transmission.

scholarly journals Evaluating Apple Inc Mobility Trend Data Related to the COVID-19 Outbreak in Japan: Statistical Analysis

10.2196/20335 ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e20335
Author(s):  
Junko Kurita ◽  
Yoshiyuki Sugishita ◽  
Tamie Sugawara ◽  
Yasushi Ohkusa
Keyword(s):  
Statistical Analysis ◽  
Local Governments ◽  
Critical Level ◽  
Polynomial Function ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Short Term ◽  
Mobility Data ◽  
Trend Data ◽  
Short Term Prediction

Background In Japan, as a countermeasure against the COVID-19 outbreak, both the national and local governments issued voluntary restrictions against going out from residences at the end of March 2020 in preference to the lockdowns instituted in European and North American countries. The effect of such measures can be studied with mobility data, such as data which is generated by counting the number of requests made to Apple Maps for directions in select countries/regions, sub-regions, and cities. Objective We investigate the associations of mobility data provided by Apple Inc and an estimate an an effective reproduction number R(t). Methods We regressed R(t) on a polynomial function of daily Apple data, estimated using the whole period, and analyzed subperiods delimited by March 10, 2020. Results In the estimation results, R(t) was 1.72 when voluntary restrictions against going out ceased and mobility reverted to a normal level. However, the critical level of reducing R(t) to <1 was obtained at 89.3% of normal mobility. Conclusions We demonstrated that Apple mobility data are useful for short-term prediction of R(t). The results indicate that the number of trips should decrease by 10% until herd immunity is achieved and that higher voluntary restrictions against going out might not be necessary for avoiding a re-emergence of the outbreak.

scholarly journals Forecast of the COVID-19 outbreak, collapse of medical facilities, and lockdown effects in Tokyo, Japan

2020 ◽  
Author(s):  
Junko Kurita ◽  
Tamie Sugawara ◽  
Yasushi Ohkusa
Keyword(s):  
Confidence Interval ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Sir Model ◽  
Age Classes ◽  
Number Of Patients ◽  
Medical Facilities ◽  
China And Japan ◽  
The Basic Reproduction Number

AbstractBackgroundThe number of patients of COVID-19 in Tokyo has been increasing gradually through the end of March, 2020.ObjectSupport for policymaking requires forecasting of the entire course and outcome of the outbreak including the date of collapse of medical facilities if a lockdown is not initiated. Moreover, the effects of a lockdown must be considered when choosing to initiate one.MethodData of Tokyo patients with symptoms during January 14 – March 28, 2020 were used to formulate a susceptible–infected–recovered (SIR) model using three age classes and to estimate the basic reproduction number (R0). Based on the estimated R0, We inferred outbreak outcomes including the date of collapse of medical facilities if a lockdown were not enacted. Then we estimate the lockdown effects.ResultsResults suggest R0 as 2.86, with a 95% confidence interval of [2.73, 2.97]. Collapse of medical facilities can be expected to occur on April 26 if no lockdown occurs. The total number of deaths can be expected to be half a million people. If a lockdown were enacted from April 6, and if more than 60% of trips outside the home were restricted voluntarily, then a collapse of medical facilities could be avoided.Discussion and ConclusionThe estimated R0 was similar to that found from other studies conducted in China and Japan. Results demonstrate that a lockdown with reasonable cooperation of residents can avoid a collapse of medical facilities and save 0.25 million mortality cases.

scholarly journals Preliminary evaluation of voluntary event cancellation as a countermeasure against the COVID-19 outbreak in Japan as of 11 March, 2020

2020 ◽  
Author(s):  
Yoshiyuki Sugishita ◽  
Junko Kurita ◽  
Tamie Sugawara ◽  
Yasushi Ohkusa
Keyword(s):  
Confidence Interval ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Preliminary Evaluation ◽  
Recovery Model ◽  
Reporting Delay ◽  
The Basic Reproduction Number

AbstractBackgroundTo control COVID-19 outbreak in Japan, sports and entertainment events were canceled in Japan for two weeks from 26 February to 11 March. It has been designated as voluntary event cancellation (VEC).ObjectThis study predicts the effectiveness of VEC enduring and after its implementation.MethodWe applied a simple susceptible–infected–recovery model to data of patients with symptoms in Japan during 14 January to VEC introduction and after VEC introduction to 8 March. We adjusted the reporting delay in the latest few days.ResultsResults suggest that the basic reproduction number, R0, before VEC introduced as 2.50 with a 95% confidence interval (CI) was [2.43, 2.55] and the effective reproduction number, Rv, after VEC introduced as 1. 88; its 95% CI was [1.68,2.02].Discussion and ConclusionResults demonstrated that VEC can reduce COVID-19 infectiousness by 35%, but R0 remains higher than one.

scholarly journals COVID-19 Outbreak Forecasting and Effects of Self-Restraint Against Excursions in Tokyo, Japan, as of the End of March, 2020, Before the Emergency Declaration on April 7, 2020

2021 ◽  
Vol 16 (1) ◽  
pp. 6-11
Author(s):  
Yoshiyuki Sugishita ◽  
Junko Kurita ◽  
Tamie Sugawara ◽  
Yasushi Ohkusa ◽  
◽  
...  
Keyword(s):  
Confidence Interval ◽  
Medical Care ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Sir Model ◽  
Age Classes ◽  
Medical Resources ◽  
Care Services ◽  
The Basic Reproduction Number

In Tokyo, Japan, coronavirus disease 2019 (COVID-19) cases have been increasing gradually since late March 2020. This study was aimed to predict the effects of self-restraint against excursions in Tokyo before the emergency declaration of April 7, 2020. Data of symptomatic patients collected between January 14 and March 28, 2020, in Tokyo, were used to formulate a susceptible–infected–recovered (SIR) model using three age classes and estimate the basic reproduction number (R0). Based on the estimated R0, we inferred outbreak outcomes and medical burdens if self-restraint against excursions had not been enacted. Thereafter, we estimated the effects of self-restraint against excursions. The results suggested an R0 value of 2.86, with a 95% confidence interval of 2.73–2.97. It is likely that the exhaustion of medical resources could have occurred on April 28, 2020, if no self-restraint against excursions had occurred. If self-restraint against excursions had been enacted from April 6, 2020, and more than 60% of trips outside the home had been restricted voluntarily, medical care services would then have been predicted to be maintained. Our suggestion might have contributed to countermeasures against COVID-19 in Tokyo.

scholarly journals Analysis of Intervention Effectiveness Using Early Outbreak Transmission Dynamics to Guide Future Pandemic Management and Decision-Making in Kuwait

2021 ◽  
Author(s):  
Michael G. Tyshenko ◽  
Tamer Oraby ◽  
Joseph Craig Longenecker ◽  
Harri Vainio ◽  
Janvier Gasana ◽  
...  
Keyword(s):  
Decision Making ◽  
Reproduction Number ◽  
Control Measures ◽  
World Health ◽  
Transmission Model ◽  
Mobility Data ◽  
Imported Cases ◽  
Community Transmission ◽  
Health Organization ◽  
Case Data

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a World Health Organization designated pandemic that can result in severe symptoms and death that disproportionately affects older patients or those with comorbidities. Kuwait reported its first imported cases of COVID-19 on February 24, 2020. Analysis of data from the first three months of community transmission of the COVID-19 outbreak in Kuwait can provide important guidance for decision-making when dealing with future SARS-CoV-2 epidemic wave management. The analysis of intervention scenarios can help to evaluate the possible impacts of various outbreak control measures going forward which aim to reduce the effective reproduction number during the initial outbreak wave. Herein we use a modified susceptible-exposed-asymptomatic-infectious-removed (SEAIR) transmission model to estimate the outbreak dynamics of SARS-CoV-2 transmission in Kuwait. We fit case data from the first 96 days in the model to estimate the basic reproduction number and used Google mobility data to refine community contact matrices. The SEAIR modelled scenarios allow for the analysis of various interventions to determine their effectiveness. The model can help inform future pandemic wave management, not only in Kuwait but for other countries as well.

SIR model for propagation of COVID-19 in the Paraíba's State (Brazil)

2021 ◽  
Vol 2 (2) ◽  
pp. 39-48
Author(s):  
Célia Maria Rufino Franco ◽  
Renato Ferreira Dutra
Keyword(s):  
Compartmental Model ◽  
Reproduction Number ◽  
Health Department ◽  
Sir Model ◽  
Euler Method ◽  
Control Measures ◽  
System Of Differential Equations ◽  
Infection Transmission ◽  
Epidemic Dynamics ◽  
The Town

This work aims to apply the SIR-type compartmental model (Susceptible - Infected - Removed) in the evolution of Covid-19 in Paraíba's State and Campina Grande City. For that, the parameters of the model were considered to be variable during time evolution, within an appropriate range. The system of differential equations was solved numerically using the Euler method. The parameters were obtained by adjusting the model to the infected data provided by the Paraíba Health Department. According to the results obtained, the model describes the infected population well. There was a reduction in the effective reproduction number in Paraíba and the town of Campina Grande. It is noteworthy that understanding the dynamics of infection transmission and evaluating the effectiveness of control measures is crucial to assess the potential for sustained transmission to occur in new areas. The model can also be applied to describe epidemic dynamics in other regions and countries. 

scholarly journals Fractional SIR-Model for Estimating Transmission Dynamics of COVID-19 in India

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 86-100
Author(s):  
Nita H. Shah ◽  
Ankush H. Suthar ◽  
Ekta N. Jayswal ◽  
Ankit Sikarwar
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Sir Model ◽  
Time Dependent ◽  
Contact Rate ◽  
Distribution Maps ◽  
Fundamental Parameters ◽  
Different Order ◽  
The Basic Reproduction Number

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model's transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.

scholarly journals Reduction in mobility and COVID-19 transmission

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Pierre Nouvellet ◽  
Sangeeta Bhatia ◽  
Anne Cori ◽  
Kylie E. C. Ainslie ◽  
Marc Baguelin ◽  
...  
Keyword(s):  
Predictive Ability ◽  
Control Measures ◽  
Social Distancing ◽  
Beneficial Effects ◽  
Mobility Data ◽  
Strict Control ◽  
Before And After ◽  
Proxy Measure ◽  
Lower Transmission ◽  
The Relationship

AbstractIn response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27–77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49–91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12–48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.

scholarly journals Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zuiyuan Guo ◽  
Dan Xiao
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Cumulative Number ◽  
Individual Based Model ◽  
Whole Process ◽  
Coordinate Descent Algorithm ◽  
Initial Stage ◽  
The Government ◽  
Prevention And Control Measures ◽  
And Control

AbstractWe established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82–5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982–2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.

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