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.

Tracking deaths from hitherto undetected infections can be an indicator of latent sars-cov-2 cases

“…The Modified SEIRD model described in [9] uses two symmetric, parallel arms to represent the quarantined and free populations. The transition rates from one compartment to another are proportional to the extent of contact tracing and self-reporting in each of the respective compartments.…”

“…The transition rates from one compartment to another are proportional to the extent of contact tracing and self-reporting in each of the respective compartments. These transition rates are described in Figure 1 [9]. These transitions provide a metric called the intervention inefficiency that is interpreted as the ineffectiveness of interventions; or the fraction of infections that are undetected.…”

“…This metric is useful in gauging the risk of an epidemic [8] and when estimated in real time can determine the effectiveness of intervention strategies like lock downs and isolation that change the transmission dynamics [6,8]. Modified SEIRD model [9] uses the epidemic simulator as tool for administration and governance.…”

“…Using the epidemic simulator described in [9], we demonstrate the utility of such metrics in early detection of an epidemic wave that is hastened or exacerbated by inefficiency [9] on account of insufficient testing, tracing or containment measures. We use the symmetry in the two arms of the model [9] along with the fact that death of either kind is unmissable, to estimate the inefficiency (or latent spread) of an epidemic. We show here that recording the number of 'postmortem detection of infection' as a proportion of total deaths can be a good metric.…”

“…Modified SEIRD model [9] uses the epidemic simulator as tool for administration and governance. It uses compartments in two parallel tracks representing the quarantined and unquarantined population which makes it relevant in the days of COVID 19 pandemic.…”