Abstract
The coronavirus epidemic (COVID-19) is a public health challenge due to its rapid global spread. Its unprecedented speed and pervasiveness have led many governments to implement a series of countermeasures, such as lock-downs, stopping/restricting travels, and mandating social distancing. To control and prevent the spread of COVID-19, it is essential to understand the latent dynamics of the disease’s evolution and the effectiveness of the intervention policies. Hidden Markov models (HMMs) capture both randomnesses in spatio-temporal dynamics and uncertainty in observations. In this paper, we apply an overall HMM that, based on multiple nations’ COVID-19 data including the USA, several European countries, and countries that have strict control policies, explore different types of observations, and we use it to infer the severity state on small geographical states or regions in the USA and Italy as test cases. Further, we aggregate the severity level of each region over a fixed time period to visualize the time evolution and propagation across regions. Such an analysis and visualization provide suggestions for interventions and responses in a calibrated manner. Results from HMM modeling are consistent with what is observed in Italy and the USA and these models can serve as visualization and proactive decision support tools to policymakers.
Highlights
The coronavirus epidemic (COVID-19) is arguably one of the most life-threatening and economic disasters of the 21st century, as, in addition to deep economic suffering, it has caused more than 198 million cases worldwide and over 4 million deaths, as of July 31, 2021
ON THE NORMALIZATION OF OBSERVATION SEQUENCES In the experiments, the vector observation for learning the parameters of the Hidden Markov models (HMMs) is composed by normalized daily positive cases and normalized daily deaths
The learned HMM models based on data from multiple countries, including the USA, several European countries and countries with strict control policies, are used to study the distributions of the spread of COVID-19 in small geographic regions, and were applied to the United States and Italy
Summary
The coronavirus epidemic (COVID-19) is arguably one of the most life-threatening and economic disasters of the 21st century, as, in addition to deep economic suffering, it has caused more than 198 million cases worldwide and over 4 million deaths, as of July 31, 2021. It spreads rapidly due (for example) to its long incubation period (median of 5.2 days) and asymptomatic spreading, and it impacts the respiratory tract, possibly leading to pneumonia and acute. It is salient to extract the spatio-temporal evolution of the disease from the observed
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