Clustering and link prediction for mesoscopic COVID-19 transmission networks in Republic of Korea.

We analyze the dataset of confirmed cases of severe acute respiratory syndrome coronavirus 2 (COVID-19) in the Republic of Korea, which contains transmission information on who infected whom as well as temporal information regarding when the infection possibly occurred. We derive time series of mesoscopic transmission networks using the location and age of each individual in the dataset to see how the structure of these networks changes over time in terms of clustering and link prediction. We find that the networks are clustered to a large extent, while those without weak links could be seen as having a tree structure. It is also found that triad-based link predictability using the network structure could be improved when combined with additional information on mobility and age-stratified contact patterns. Abundant triangles in the networks can help us better understand mixing patterns of people with different locations and age groups, hence the spreading dynamics of infectious disease.

Evidence of the importance of contact tracing in fighting COVID-19.

OBJECTIVES: We analyzed data to determine whether there are distinguishing characteristics depending on the success or failure of control for coronavirus disease 2019 (COVID-19) by country in the trend of the daily number of confirmed cases and the number of tests. METHODS: We obtained the number of confirmed cases and tests per day for almost every country in the world from Our World in Data. The Pearson correlation between the two time series was calculated according to the time delay to analyze the relationship between the number of tests and the number of cases with a lag. RESULTS: For each country, we obtained the time lag that makes the maximum correlation between the number of confirmed cases and the number of tests for COVID-19. It can be seen that countries whose time lag making maximum correlation lies in a special section between about 15 days and 20 days are generally been successful in controlling COVID-19. That section looks like a trench on the battlefield. CONCLUSIONS: We have seen the possibility that the success in mitigating COVID-19 can be expressed as a simple indicator of the time lag of the correlation between confirmed cases and tests. This time lag indicator is presumably reflected by efforts to actively trace the infected persons.

Early detection of influenza outbreak using time derivative of incidence.

For mitigation strategies of an influenza outbreak, it can be helpful to understand the characteristics of regional and age-group-specific spread. In South Korea, however, there has been no official statistic related to it. In this study, we extract the time series of influenza incidence from National Health Insurance Service claims database, which consists of all medical and prescription drug-claim records for all South Korean population. The extracted time series contains the number of new patients by region (250 city-county-districts) and age-group (0-4, 5-19, 20-64, 65+) within a week. The number of cases of influenza (2009-2017) is 12,282,356. For computing an onset of influenza outbreak by region and age-group, we propose a novel method for early outbreak detection, in which the onset of outbreak is detected as a sudden change in the time derivative of incidence. The advantage of it over the cumulative sum and the exponentially weighted moving average control charts, which have been widely used for the early outbreak detection of infectious diseases, is that information on the previous non-epidemic periods are not necessary. Then, we show that the metro area and 5-19 age-group are earlier than the rural area and other age-groups for the start of the influenza outbreak. Also, the metro area and 5-19 age-group peak earlier than the rural area and other age-groups. These results would be helpful to design a surveillance system for timely early warning of an influenza outbreak in South Korea.

Intervention effects in the transmission of COVID-19 depending on the detection rate and extent of isolation.

OBJECTIVE: In 2020, the coronavirus disease 2019 (COVID-19) respiratory infection is spreading in Korea. In order to prevent the spread of an infectious disease, infected people must be quickly identified and isolated, and contact with the infected must be blocked early. This study attempted to verify the intervention effects on the spread of an infectious disease by using these measures in a mathematical model. METHODS: We used the susceptible-infectious-recovery (SIR) model for a virtual population group connected by a special structured network. In the model, the infected state (I) was divided into I in which the infection is undetected and Ix in which the infection is detected. The probability of transitioning from an I state to Ix can be viewed as the rate at which an infected person is found. We assumed that only those connected to each other in the network can cause infection. In addition, this study attempted to evaluate the effects of isolation by temporarily removing the connection among these people. RESULTS: In Scenario 1, only the infected are isolated; in Scenario 2, those who are connected to an infected person and are also found to be infected are isolated as well. In Scenario 3, everyone connected to an infected person are isolated. In Scenario 3, it was possible to effectively suppress the infectious disease even with a relatively slow rate of diagnosis and relatively high infection rate. CONCLUSION: During the epidemic, quick identification of the infected is helpful. In addition, it was possible to quantitatively show through a simulation evaluation that the management of infected individuals as well as those who are connected greatly helped to suppress the spread of infectious diseases.

Effects of temperature, humidity, and diurnal temperature range on influenza incidence in a temperate region.

BACKGROUND: The effect of temperature and humidity on the incidence of influenza may differ by climate region. In addition, the effect of diurnal temperature range on influenza incidence is unclear, according to previous study findings. OBJECTIVES: The aim of this study was to analyze the effects of temperature, humidity, and diurnal temperature range on the incidence of influenza in Seoul, Republic of Korea, which is located in a temperate region. METHODS: We used Korean National Health insurance data to assess the weekly influenza incidence between 2010 and 2016, and used meteorological data from Seoul. To investigate the effect of temperature, relative humidity, and diurnal temperature range levels on influenza incidence, we used a distributed lag non-linear model. RESULTS: The risk of influenza incidence was significantly increased with low daily temperatures of 0-5°C and low (30%-40%) or high (70%) relative humidity. We found a positive significant association between diurnal temperature range and influenza incidence in this study. CONCLUSIONS: Influenza incidence increased with low temperature and low/high humidity in a temperate region. Influenza incidence also increased with high diurnal temperature range, after considering temperature and humidity.

Effect of spatially correlated noise on coherence resonance in a network of excitable cells.

We study the effect of spatially correlated noise on coherence resonance (CR) in a Watts-Strogatz small-world network of Fitz Hugh-Nagumo neurons, where the noise correlation decays exponentially with distance between neurons. It is found that CR is considerably improved just by a small fraction of long-range connections for an intermediate coupling strength. For other coupling strengths, an abrupt change in CR occurs following the drastic fracture of the clustered structures in the network. Our study shows that spatially correlated noise plays a significant role in the phenomenon of CR reinforcing the role of the clustered structure of the system.

Effects of periodic stimulation on an overly activated neuronal circuit.

Motivated by therapeutic deep brain stimulation, we carried out a model study on the effects of periodic stimulation on an overly activated neuronal circuit. Our neuronal circuit, modeled as a small-world network of noisy Hodgkin-Huxley neurons, is controlled to undergo the mechanism of coherence resonance to exhibit spontaneous synchronization of neuronal firing. This state of energy burst is then directly modulated by a chain of electric pulses. Our study shows that (i) the stimulation blocks the synchronization by generating traveling waves, (ii) only the pulse with proper frequency can block the synchronization, and (iii) the effects of stimulation are completely reversible. It is also found that the stimulation is effective only when the network maintains fairly good structural regularity.

Period-2 spiral waves supported by nonmonotonic wave dispersion.

Rotating spiral waves appear ubiquitously in a wide range of nonlinear systems, and they play important roles in many biological phenomena. Recently, unusual spiral waves, which support period-2 dynamics, have been found in several different systems including cardiac tissues as well as nonlinear chemical reaction-diffusion systems. They are potentially significant as an intermediate dynamic state linking regularly rotating period-1 spiral waves to complex dynamic states such as cardiac fibrillations; for example, it is intrinsic of period-2 spiral waves to have "line defects" and their instability can lead to a spatiotemporal chaos. Previous mathematical models regarding period-2 spiral waves are mostly based on a coupled system of period-2 oscillators, but these are inappropriate for the description of a large class of systems that are composed of (nonoscillatory) excitable elements--a good example being the heart. In this paper we hypothesize that excitable media, which support a nonmonotonic conduction velocity dispersion relation, can sustain period-2 oscillatory spiral waves. We explicitly demonstrate that the new mechanism can create period-2 spirals by computer simulations on a simple mathematical model describing spiral wave front dynamics.

Nucleation, drift, and decay of phase bubbles in period-2 oscillatory wave trains in a reaction-diffusion system.

This is a report on experimental observations of phase bubbles, simply closed boundaries between domains oscillating 2pi out of phase, associated with period-2 oscillatory traveling waves in a Belousov-Zhabotinsky reaction-diffusion system. The bubbles nucleate spontaneously through a fast localized phase slip, drift radially away from a neighboring spiral wave core in an oscillatory fashion, and gradually shrink to disappear. Their oscillatory drift along the radial direction is a consequence of "period adaptation," while their lateral shrinkage is an attribute of local curvature. Similar dynamic structures can be reproduced in a simple, three-species reaction-diffusion model that supports period-2 oscillatory wave trains.