Anticipating the Novel Coronavirus Disease (Covid-19) Pandemic

Bibliographic Data

ID22085778
AuthorsTaranjot Kaur (0000-0001-8152-6925, Indian Institute of Technology Ropar), Sukanta Sarkar (0000-0001-5304-5550, Indian Institute of Technology Ropar), Sourangsu Chowdhury (0000-0002-4600-2226, Max Planck Institute for Chemistry), Sudipta Kumar Sinha (0000-0002-9568-5676, Indian Institute of Technology Ropar), Mohit Kumar Jolly (0000-0002-6631-2109, Indian Institute of Science Bangalore), Partha Sharathi Dutta (0000-0001-6067-1023, Indian Institute of Technology Ropar, corresponding author)
Year2020
Volume8
Pages569669-569669
Publication date2020-09-03
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2020.569669
PMID33014985
OpenAlexW3082341314
LanguageEN
Citations received3
References cited41

The COVID-19 outbreak was first declared an international public health, and it was later deemed a pandemic. In most countries, the COVID-19 incidence curve rises sharply over a short period of time, suggesting a transition from a disease-free (or low-burden disease) equilibrium state to a sustained infected (or high-burden disease) state. Such a transition is often known to exhibit characteristics of "critical slowing down." Critical slowing down can be, in general, successfully detected using many statistical measures, such as variance, lag-1 autocorrelation, density ratio, and skewness. Here, we report an empirical test of this phenomena on the COVID-19 datasets of nine countries, including India, China, and the United States. For most of the datasets, increases in variance and autocorrelation predict the onset of a critical transition. Our analysis suggests two key features in predicting the COVID-19 incidence curve for a specific country: (a) the timing of strict social distancing and/or lockdown interventions implemented and (b) the fraction of a nation's population being affected by COVID-19 at that time. Furthermore, using satellite data of nitrogen dioxide as an indicator of lockdown efficacy, we found that countries where lockdown was implemented early and firmly have been successful in reducing COVID-19 spread. These results are essential for designing effective strategies to control the spread/resurgence of infectious pandemics

Development economics · Disease · Econometrics · Economics · Environmental health · Geography · Outbreak · Pandemic · Population · Public health · Social distance · COVID-19 epidemiological studies · Demography · Ecosystem dynamics and resilience · Medicine · Mental Health Research Topics · Virology

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