Re-examination of the impact of some non-pharmaceutical interventions and media coverage on the COVID-19 outbreak in Wuhan

Abstract

In this paper, based on the classic Kermack-McKendrick SIR model, we propose an ordinary differential equation model to re-examine the COVID-19 epidemics in Wuhan where this disease initially broke out. The focus is on the impact of all those major non-pharmaceutical interventions (NPIs) implemented by the local public healthy authorities and government during the epidemics. We use the data publicly available and the nonlinear least-squares solver lsqnonlin built in MATLAB to estimate the model parameters. Then we explore the impact of those NPIs, particularly the timings of these interventions, on the epidemics. The results can help people review the responses to the outbreak of the COVID-19 in Wuhan, while the proposed model also offers a framework for studying epidemics of COVID-19 and/or other similar diseases in other places, and accordingly helping people better prepare for possible future outbreaks of similar diseases.

Testing the Role of Socioeconomic Levels and Government Policies in Spreading Coronavirus Disease 2019 (COVID-19) in ASEAN

“…The worldwide respiratory disease outbreak was first identified in November 2019 [18] at a popular seafood market in Wuhan, China [1], where many people came to buy and sell seafood and wildlife. Coronavirus disease 2019 (COVID- 19), formerly referred to as 2019 novel coronavirus or 2019-nCoV [25] by the World Health Organization (WHO) on January 10, 2020 [2], declared as Public Health Emergency of International Concern (PHEIC) [13] since it is inconvertibly not merely represents a delineate global shock, spreading its consequence under numerous respect in comprising health, political, institutional, social and economic aspects [9] but also has become a terrible disease caused by a virus that infects wildlife and can be transmitted to humans [10]. Transmission through humans can occur through direct physical contacts such as a handshake between an infected person and a person susceptible to infection or through indirect contacts [14] such as droplets or aerosol transmission and contaminated objects [14].…”

Modeling SARS-CoV-2 spread with dynamic isolation

“…Models help to understand the dynamics of infectious diseases under the given circumstances and provide valuable information about how to control the disease. The impact of nonpharmaceutical interventions against the spread of SARS-CoV-2 can be seen in numerous studies [19,23,26]. Some studies showed that mitigation, plans and preparedness should be organized and deployed globally to prevent the progression of transmission rate, otherwise the basic reproduction number could reach up higher [16,34,43,44].…”

Effect of quarantine and vaccination in a pandemic situation: a mathematical modelling approach

“…Media awareness can also help preventing the spread of COVID-19 [15]. Media coverage along with non pharmaceutical interventions applied at right timings can stop the outbreak of COVID-19 [16] whereas delay in diagnosis can not eliminate the disease [17]. Environment can also work as a reservoir of COVID-19 and is able to spread the virus [18].…”