The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 has started in December 2019 and it was declared pandemic by the World Health Organization (WHO) on March 11, 2020. As of October 28, 2020, over 44,00,000 new cases and over 11,65,000 deaths have been reported throughout the world. In addition to the human health policy, the COVID-19 pandemic has interrupted the global crisis and daily life on an unprecedented scale. COVID-19 has already break the previous histories of two coronavirus epidemics, namely Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV), posing a considerable menace to the word-wide public health and global economy after the Second World War.
To this date date, there is no specific licensed vaccine, antivirals or effective specific ctherapeutics to treat the coronavirus infected patients. Due to absence of coronavirus therapeutics, the Non-Pharmaceutical Interventions (NPIs) focused at minimizing transmission by reducing contact rates among individuals. For examples the measures adopted in this time incorporated social distancing, closing schools, universities, offices, churches, bars, avoid mass gatherings, use of masks, hand-sanitizers, other social places as well as contacts of cases (quarantine, surveillance, contact tracing), etc.
The scientific community globally have acted rapidly to fight against COVID-19 pandemic, working from different perspectives to better understand the epidemiological traits, such as modelling forecasting, imaging, genetic network analysis, systems biology, immunology, pattern formation, population health strategy and to identify the effective treatment and prevention strategies to mitigate the effects of COVID-19 and future pandemics.
Mathematical models have played a vital role in predicting the dynamics of the outbreaks, optimizing control strategies, understanding the immune responses, treatment policies, to reconstruct the evolutionary paths of COVID-19 by genetic network analysis, providing insights to virus transmission patterns and so on.
We hope that modelers can certainly make a significant contribution to understand the epidemiological traits, non-pharmaceutical intervention strategies and the transmission dynamics of the diseases and its causes.
We initiate this Research Topic to collect timely papers on modeling studies from the mathematical, computational, non-pharmaceutical, network, biological, epidemiological, immunological, social media, machine learning and virological aspects of COVID-19.
The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 has started in December 2019 and it was declared pandemic by the World Health Organization (WHO) on March 11, 2020. As of October 28, 2020, over 44,00,000 new cases and over 11,65,000 deaths have been reported throughout the world. In addition to the human health policy, the COVID-19 pandemic has interrupted the global crisis and daily life on an unprecedented scale. COVID-19 has already break the previous histories of two coronavirus epidemics, namely Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV), posing a considerable menace to the word-wide public health and global economy after the Second World War.
To this date date, there is no specific licensed vaccine, antivirals or effective specific ctherapeutics to treat the coronavirus infected patients. Due to absence of coronavirus therapeutics, the Non-Pharmaceutical Interventions (NPIs) focused at minimizing transmission by reducing contact rates among individuals. For examples the measures adopted in this time incorporated social distancing, closing schools, universities, offices, churches, bars, avoid mass gatherings, use of masks, hand-sanitizers, other social places as well as contacts of cases (quarantine, surveillance, contact tracing), etc.
The scientific community globally have acted rapidly to fight against COVID-19 pandemic, working from different perspectives to better understand the epidemiological traits, such as modelling forecasting, imaging, genetic network analysis, systems biology, immunology, pattern formation, population health strategy and to identify the effective treatment and prevention strategies to mitigate the effects of COVID-19 and future pandemics.
Mathematical models have played a vital role in predicting the dynamics of the outbreaks, optimizing control strategies, understanding the immune responses, treatment policies, to reconstruct the evolutionary paths of COVID-19 by genetic network analysis, providing insights to virus transmission patterns and so on.
We hope that modelers can certainly make a significant contribution to understand the epidemiological traits, non-pharmaceutical intervention strategies and the transmission dynamics of the diseases and its causes.
We initiate this Research Topic to collect timely papers on modeling studies from the mathematical, computational, non-pharmaceutical, network, biological, epidemiological, immunological, social media, machine learning and virological aspects of COVID-19.
