scholarly journals Evaluating Apple Inc. mobility trend data related to the COVID-19 outbreak in Japan (Preprint)

2020 ◽  
Author(s):  
Junko Kurita ◽  
Yoshiyuki Sugishita ◽  
Tamie Sugawara ◽  
Yasushi Ohkusa
Keyword(s):  
Normal Level ◽  
North American ◽  
Local Governments ◽  
Critical Level ◽  
Polynomial Function ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Complete Cessation ◽  
Normal Number ◽  
Trend Data

BACKGROUND In Japan, as a countermeasure against the COVID-19 outbreak, voluntary restrictions against going out (VRG) from a residence were announced from the end of March by national and local governments in preference to lockdowns like those instituted in European and North American countries. OBJECTIVE We examined some associations among going out information provided by Apple Inc. and estimated an effective reproduction number R(t). METHODS We regressed R(t) on a polynomial function of daily Apple Inc. data. From estimation using the whole period, the sub-periods delimited by March 10 were analyzed. RESULTS Estimation results indicate R(t) as 1.72 if VRG ceases and mobility reverts to a normal level. However, the critical level of R(t)<1 was achieved at a 89.3% of the normal level of mobility. CONCLUSIONS Results indicate that a 10% reduction from the normal number of trips will be necessary until herd immunity is achieved. Complete cessation of VRG might not be necessary to avoid re-emergence of the outbreak.

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.

A Comparative View of Citizen Engagement in Social Media of Local Governments From North American Countries

2019 ◽  
pp. 40-57
Author(s):  
María del Mar Gálvez-Rodríhuez ◽  
Arturo Haro-de-Rosario ◽  
María del Carmen Caba-Pérez
Keyword(s):  
United States ◽  
Social Media ◽  
North American ◽  
Local Governments ◽  
The United States ◽  
Communication Strategy ◽  
Three Dimensions ◽  
Citizen Engagement ◽  
General Terms ◽  
Facebook Pages

Taking into consideration the growing popularity of social media in North American countries, this chapter aims to perform a comparative analysis of the use of Facebook as a communication strategy for encouraging citizen engagement among local governments in The United States, Canada and Mexico. With regards to the three dimensions used in all regions to measure online citizen engagement, in general terms, the “popularity” and “virality” dimensions are the most common, while the “commitment” dimension is still underutilized. With respect to the significant differences found, Mexican citizens are those that make the best use of the tool “like” to express their support of the information supplied by local governments. Furthermore, in relation to the citizens that are fans of the Facebook pages of local governments, we can observe that Canadian citizens show a greater interest in participating more actively in dialogue building while U.S. citizens are the most willing to disseminate information from their local governments.

13. The application of reproduction number concepts to tuberculosis Vynnycky E, Fine PEM. Epidemiol Infect 1998; 121: 309–324

2005 ◽  
Vol 133 (S1) ◽  
pp. S45-S47 ◽  
Author(s):  
EMILIA VYNNYCKY
Keyword(s):  
Critical Level ◽  
Reproduction Number ◽  
Developed Countries ◽  
Varicella Zoster ◽  
Vaccination Strategies ◽  
The United Kingdom ◽  
Age Dependent ◽  
Mathematical Literature ◽  
Epidemiol Infect ◽  
Effect Of Age

Epidemiology & Infection probably attracts more papers on mathematical modelling of infectious diseases than does any other epidemiology journal. The most important modelling papers published in the journal were probably those of Anderson and May during the 1980s, which laid the foundations for much of the subsequent modelling work carried out by themselves and their colleagues. Since the start of their partnership, they authored 17 articles between them in the journal, including work quantifying the effect of different vaccination strategies against measles and rubella [1, 2], on the epidemiology of rubella in the United Kingdom [3], and on the effect of age-dependent contact between individuals on the critical level of vaccination coverage required for control [4]. The latter work, published in 1985, was particularly important, since it described methods for incorporating realistic assumptions about (heterogeneous) mixing between individuals into models, an issue which was beginning to be addressed in the mathematical literature but which had not yet reached many epidemiological journals. Other important modelling work published in Epidemiology and Infection includes that of McLean et al. (reproduced in this edition) on the control of measles in developing countries [5, 6], and by Garnett and Grenfell on the epidemiology of varicella zoster in developed countries [7, 8].

scholarly journals Covid 19: Need of vaccine induced herd immunity in India

2020 ◽  
Vol 2 (4) ◽  
pp. 82-84
Author(s):  
D. Pragathi ◽  
Dinesh Kumar Kukunuri ◽  
Venkatesh Paturu
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Traditional Concept ◽  
Contagious Diseases ◽  
Research Article ◽  
Past Data ◽  
The Mean ◽  
Novel Coronavirus ◽  
Indirect Protection

Introduction: Herd immunity is a traditional concept nothing but a form of indirect protection from contagious diseases. In a mass community, there is no need to be everyone immune. If a high proportion of members in the community are immune, spreading of the disease is reduced even to non-immunized patients. This study offers an overview of vaccine-induced herd immunity importance in this pandemic and how it will be achieved. Methodology: The data of basic reproduction number Ro values for COVID 19 of 10 weeks in India which were estimated by Ro package in R software are extracted from a research article (reference no.4) and taken the mean Ro value due to fluctuations as well as to avoid great errors by using MS Excel. Herd immunity is calculated by using a standard equation stated as R=(1-Pc )(1-P1)Ro   Results:  The mean basic reproduction number Ro for COVID 19 in India was calculated as 1.671 by using MS excel and the herd 3 determines that only 40.16% proportion of individuals need to immunized through a vaccine to achieve herd immunity towards COVID 19 in India. Conclusion: This study estimates mean base reproduction Ro as 1.671 and Herd Immunity Threshold (HIT) as 40.16% by using past data. This study concludes that vaccine-induced herd immunity helps us by playing a key role to eliminate novel coronavirus.

scholarly journals Pandemic spread in communities via random graphs

2021 ◽  
Vol 2021 (11) ◽  
pp. 113501
Author(s):  
Dor Minzer ◽  
Yaron Oz ◽  
Muli Safra ◽  
Lior Wainstain
Keyword(s):  
Branching Process ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Connected Component ◽  
Natural Evolution ◽  
Contact Graph ◽  
Process Framework ◽  
The Difference ◽  
Number Of Individuals ◽  
The Basic Reproduction Number

Abstract Working in the multi-type Galton–Watson branching-process framework we analyse the spread of a pandemic via a general multi-type random contact graph. Our model consists of several communities, and takes, as input, parameters that outline the contacts between individuals in distinct communities. Given these parameters, we determine whether there will be an outbreak and if yes, we calculate the size of the giant-connected-component of the graph, thereby, determining the fraction of the population of each type that would be infected before it ends. We show that the pandemic spread has a natural evolution direction given by the Perron–Frobenius eigenvector of a matrix whose entries encode the average number of individuals of one type expected to be infected by an individual of another type. The corresponding eigenvalue is the basic reproduction number of the pandemic. We perform numerical simulations that compare homogeneous and heterogeneous spread graphs and quantify the difference between them. We elaborate on the difference between herd immunity and the end of the pandemic and the effect of countermeasures on the fraction of infected population.

scholarly journals Herd Immunity in India: A Review

2021 ◽  
Vol 3 (1) ◽  
pp. 18-21
Author(s):  
Sheema Fatima Khan
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Natural Infection ◽  
Herd Immunity ◽  
Herd Effect ◽  
Susceptible Population ◽  
Herd Protection ◽  
Cdc Guidelines ◽  
And Control

Herd Immunity is a brilliant solution to tackle and control global pandemics, if taken proper route for immunization such as through vaccination. It is defined as the number of immune individuals against a transmissible virus in a completely susceptible population. The term herd protection or herd effect is the protection to the whole population due to herd immunity. Herd immunity threshold is the minimum proportion of immune population required for herd effect or herd protection. To calculate the threshold, we use basic reproduction number (R0) to measure the rate of transmission of pathogen, in this case SARS-CoV-2. However, a better measure is effective reproduction number (Re). India is major example of herd immunity. Despite strict lockdown and other Covid measure, due to already crowded area the virus could spread fast and to vast majority of people if one of them were to catch it. This explains the steady decline in the number of coronavirus cases in India. At the end, until an approved effective vaccination available, public will still need to follow all the CDC guidelines in order to avoid the large deaths along with natural infection.

scholarly journals Flattening the curve is not enough, we need to squash it: An explainer using a simple model

2020 ◽  
Author(s):  
ES McBryde ◽  
MT Meehan ◽  
JM Trauer
Keyword(s):  
Deterministic Model ◽  
Reproduction Number ◽  
Herd Immunity ◽  
International Travel ◽  
Effective Control ◽  
Curve Versus ◽  
Successful Control ◽  
The Difference ◽  
The Uk ◽  
Local Transmission

AbstractBackgroundAround the world there are examples of both effective control (e.g., South Korea, Japan) and less successful control (e.g., Italy, Spain, United States) of COVID-19 with dramatic differences in the consequent epidemic curves. Models agree that flattening the curve without controlling the epidemic completely is insufficient and will lead to an overwhelmed health service. A recent model, calibrated for the UK and US, demonstrated this starkly.MethodsWe used a simple compartmental deterministic model of COVID-19 transmission in Australia, to illustrate the dynamics resulting from shifting or flattening the curve versus completely squashing it.ResultsWe find that when the reproduction number is close to one, a small decrease in transmission leads to a large reduction in burden (i.e., cases, deaths and hospitalisations), but achieving this early in the epidemic through social distancing interventions also implies that the community will not reach herd immunity.ConclusionsAustralia needs not just to shift and flatten the curve, but to squash it by getting the reproduction number below one. This will require Australia to achieve transmission rates at least two thirds lower than those seen in the most severely affected countries.The knownCOVID-19 has been diagnosed in over 4,000 Australians. Up until mid-March, most were from international travel, but now we are seeing a rise in locally acquired cases.The newThis study uses a simple transmission dynamic model to demonstrate the difference between moderate changes to the reproduction number and forcing the reproduction number below one.The implicationsLowering local transmission is becoming important in reducing the transmission of COVID-19. To maintain control of the epidemic, the focus should be on those in the community who do not regard themselves as at risk.

scholarly journals The risk for a new COVID-19 wave – and how it depends on R0, the current immunity level and current restrictions

2020 ◽  
Author(s):  
Tom Britton ◽  
Pieter Trapman ◽  
Frank Ball
Keyword(s):  
Preventive Measures ◽  
Reproduction Number ◽  
Social Activity ◽  
Herd Immunity ◽  
Time Varying ◽  
The World ◽  
Two Factors ◽  
Second Wave ◽  
Different Parts ◽  
Future Outbreak

AbstractThe COVID-19 pandemic has hit different parts of the world differently: some regions are still in the rise of the first wave, other regions are now facing a decline after a first wave, and yet other regions have started to see a second wave. The current immunity level î in a region is closely related to the cumulative fraction infected, which primarily depends on two factors: a) the initial potential for COVID-19 in the region (often quantified by the basic reproduction number R0), and b) the timing, amount and effectiveness of preventive measures put in place. By means of a mathematical model including heterogeneities owing to age, social activity and susceptibility, and allowing for time-varying preventive measures, the risk for a new epidemic wave and its doubling time, and how they depend on R0, î and the overall effect of the current preventive measures, are investigated. Focus lies on quantifying the minimal overall effect of preventive measures pMin needed to prevent a future outbreak. The first result shows that the current immunity level î plays a more influential roll than when immunity is obtained from vaccination. Secondly, by comparing regions with different R0 and î it is shown that regions with lower R0 and low î may now need higher preventive measures (pMin) compared with other regions having higher R0 but also higher î, even when such immunity levels are far from herd immunity.

scholarly journals Recent updates in the therapeutic management of patients with co-infection of COVID-19 with other seasonal epidemics prone disease

2020 ◽  
Vol 7 (5) ◽  
pp. 35-37
Author(s):  
D. Sharad Gedam ◽  
◽  
Mrs. Mamta Verma ◽  
Keyword(s):  
North American ◽  
Herd Immunity ◽  
Therapeutic Management ◽  
Seasonal Epidemics ◽  
Significant Disease

COVID 19 Pandemic is most significant disease in last 100 years. It is now becoming challenging tocontrol the Pandemic in different part of world. Some countries are facing 2nd & 3rd wave of severedisease with no evidences of herd immunity in most of European and North American countries. Itbecome more challenging to treat the already co-existing morbidities, seasonal diseases along withCOVID 19.

scholarly journals A new design of an adaptive model of infectious diseases based on artificial intelligence approach: monitoring and forecasting of COVID-19 epidemic cases

2020 ◽  
Author(s):  
Bachir Nail ◽  
Abdelaziz Rabehi ◽  
Belkacem Bekhiti ◽  
Taha Arbaoui
Keyword(s):  
Artificial Intelligence ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Adaptive Model ◽  
Comparison Study ◽  
Adaptive Parameters ◽  
Monitoring And Forecasting ◽  
Intelligent Model ◽  
Intelligence Approach ◽  
Artificial Intelligence Approach

AbstractBackgroundMathematical infectious disease models available in literature, mostly take in their design that the parameters of basic reproduction number R0 and interval serial SI as constant values during tracking the outbreak cases. In this report a new intelligent model called HH-COVID-19 is proposed, with simple design and adaptive parameters.MethodsThe parameters R0 and SI are adapted by adding three new weighting factors α, β and γ and two free parameters σ1 and σ2 in function of time t, thus the HH-COVID-19 become time-variant model. The parameters R0, SI, α, β, γ, σ1 and σ2 are estimated optimally based on a recent algorithm of artificial intelligence (AI), inspired from nature called Harris Hawks Optimizer (HHO), using the data of the confirmed infected cases in Algeria country in the first t = 55 days.ResultsParameters estimated optimally: R0 = 1.341, SI = 5.991, α = 2.987, β = 1.566, γ = 4.998, σ1 = −0.133 and σ2 = 0.0324. R0 starts on 1.341 and ends to 2.677, and SI starts on 5.991 and ends to 6.692. The estimated results are identically to the actual infected incidence in Algeria, HH-COVID-19 proved its superiority in comparison study. HH-COVID-19 predicts that in 1 May, the infected cases exceed 50 000, during May, to reach quickly the herd immunity stage at beginning of July.ConclusionHH-COVID-19 can be used for tracking any COVID-19 outbreak cases around the world, just should updating its new parameters to fitting the area to be studied, especially when the population is directly vulnerable to COVID-19 infection.

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