About: Mathematical model study of a pandemic: Graded lockdown approach

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Mathematical model study of a pandemic: Graded lockdown approach
Creator	Chatterjee, S Banyal, Ravinder Vani, V
Source	MedRxiv
abstract	A kinetic approach is developed, in a %22tutorial style%22 to describe the evolution of an epidemic with spread taking place through contact. The %22infection-rate%22 is calculated from the rate at which an infected person approaches an uninfected susceptible individual, i.e. a potential recipient of the disease, up to a distance p, where the value of p may lie between pmin[≤]p[≤]pmax. We consider a situation with a total population of N individuals, living in an area A, x(t) amongst them being infected while xd(t) = {beta}'x(t) is the number that has died in the course of transmission and evolution of the epidemic. The evolution is developed under the conditions (1) a faction (t) of the [N-x(t)-xd(t)] uninfected individuals and (2) a {beta}(t) fraction of the x(t) infected population are quarantined, while the %22source-events%22 that spread the infection are considered to occur with frequency {upsilon}. The processes of contact and transmission are considered to be Markovian. Transmission is assumed to be inhibited by several processes like the use of %22masks%22, %22hand washing or use of sanitizers%22 while %22physical distancing%22 is described by p. The evolution equation for x(t) is a Riccati - type differential equation whose coefficients are time-dependent quantities, being determined by an interplay between the above parameters. A formal solution for x(t) is presented, for a %22graded lockdown%22 with the parameters, 0[≤](t), {beta}(t)[≤]1 reaching their respective saturation values in time scales, {tau}1, {tau}2 respectively, from their initial values (0)={beta}(0)=0. The growth is predicted for several BBMP wards in Bengaluru and in urban centers in Chikkaballapur district, as an illustrative case. The above selections serve as model cases for high, moderate and thin population densities. It is seen that the evolution of [x(t)/N] with time depends upon (a) the initial time scale of evolution, (b) the time scale of cure and (c) on the time dependence of the Lockdown function Q(t) = {[1-(t)]{middle dot}[1-{beta}(t)]}. The formulae are amenable to simple computations and show that in order to curb the spread one must ensure that Q({infty}) must be below a critical value and the vigilance has to be continued for a long time (at least 100 to 150 days) after the decay starts,to avoid all chances of the infection reappearing.
has issue date	2020-07-24(xsd:dateTime)
bibo:doi	10.1101/2020.07.22.20159962
has license	medrxiv
sha1sum (hex)	0136c436d466bf794d64ee60718b660cb1e5c3fc
schema:url	https://doi.org/10.1101/2020.07.22.20159962
resource representing a document's title	Mathematical model study of a pandemic: Graded lockdown approach
resource representing a document's body	covid:0136c436d466bf794d64ee60718b660cb1e5c3fc#body_text
is schema:about of	named entity 'Transmission' named entity 'population' named entity 'moderate' named entity 'living' named entity 'scales' named entity 'potential' named entity 'evolution' named entity 'faction' named entity 'initial' named entity 'area A' named entity 'pandemic' named entity 'BEING' named entity 'INFECTED' named entity '80%' named entity 'SUSCEPTIBLE' named entity 'SATURATION' named entity 'LIKE' named entity 'FUNCTION' named entity 'WASHING' named entity 'TRANSMISSION' named entity 'PRESENTED' named entity 'TIME DEPENDENCE' named entity 'STUDY' named entity 'BBMP' named entity 'infected' named entity 'masks' named entity 'contact' named entity 'number' named entity 'Chikkaballapur district' named entity 'developed' named entity 'quarantined' named entity 'events' named entity 'interplay' named entity 'evolution' named entity 'time' named entity 'population' named entity 'evolution' named entity 'high' named entity 'determined' named entity 'hand washing' named entity 'cases' named entity 'lockdown' named entity 'epidemic' named entity 'population densities' named entity 'infection' named entity 'Markovian' named entity 'infection' named entity 'differential equation' named entity 'Mathematical model' named entity 'died' named entity 'logistic equation' named entity 'CC-BY-ND' named entity 'impact parameter' named entity 'infection' named entity 'BBMP' named entity '8 days' named entity 'population density' named entity 'infection' named entity 'medRxiv' named entity 'doubling time' named entity 'CC-BY-ND' named entity 'infection' named entity 'exponential growth' named entity 'differential equation' named entity 'medRxiv' named entity 'infection' named entity 'BBMP' named entity 'infection' named entity 'peer review' named entity 'Bruhat Bengaluru Mahanagara Palike' named entity 'infection' named entity '8 days' named entity 'Covid-19 pandemic' named entity 'medRxiv' named entity 'infection' named entity 'CC-BY-ND' named entity 'public knowledge' named entity 'Riccati equation' named entity 'Chikkaballapur district' named entity 'Covid-19' named entity 'infection' named entity 'CC-BY-ND' named entity 'medRxiv'

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