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Using epidemic simulators for monitoring an ongoing epidemic.

Abstract：

:Prediction of infection trends, estimating the efficacy of contact tracing, testing or impact of influx of infected are of vital importance for administration during an ongoing epidemic. Most effective methods currently are empirical in nature and their relation to parameters of interest to administrators are not evident. We thus propose a modified SEIRD model that is capable of modeling effect of interventions and inward migrations on the progress of an epidemic. The tunable parameters of this model bear relevance to monitoring of an epidemic. This model was used to show that some of the commonly seen features of cumulative infections in real data can be explained by piecewise constant changes in interventions and population influx. We also show that the data of cumulative infections from twelve Indian states between mid March and mid April 2020 can be generated from the model by applying interventions according to a set of heuristic rules. Prediction for the next ten days based on this model, reproduced real data very well. In addition, our model also reproduced the time series of recoveries and deaths. Our work constitutes an important first step towards an effective dashboard for the monitoring of epidemic by the administration, especially in an Indian context.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Raghavan M,Sridharan KS,Mandayam Rangayyan Y

doi

10.1038/s41598-020-73308-5

subject

Has Abstract

pub_date

2020-10-06 00:00:00

pages

16571

issue

1

issn

2045-2322

pii

10.1038/s41598-020-73308-5

journal_volume

10

pub_type

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