Age-Period-Cohort Analysis of Influenza in Koreans: the National Health Insurance Research Database, 2009-2018

Incidence, Severity, and Mortality of Influenza During 2010-2020 in Korea: A Nationwide Study Based on the Population-Based National Health Insurance Service Database

BACKGROUND

The epidemiology of influenza is commonly used to understand and establish relevant health policies for emerging respiratory infections, including coronavirus disease 2019 (COVID-19). However, Korea has no confirmed nationwide data on influenza incidence, severity, and mortality rate.

METHODS

We conducted a cross-sectional study to obtain epidemic data on influenza at the national level using National Health Insurance claims data during 2010 to 2020. Influenza cases were defined as 90-day timeframe episodes based on all inpatient and outpatient claims data with disease code J09, J10, and J11. Influenza incidence, severity, and mortality rate were calculated, and logistic regressions were performed to assess the associations of demographic characteristics and comorbidity with influenza-related hospitalization, severe illness, and death.

RESULTS

There were 0.4-5.9% influenza cases in the population from 2010 to 2020, with 9.7-18.9%, 0.2-0.9%, and 0.03-0.08% hospitalized, used in the intensive care unit, and dead, respectively. Age-standardized incidence and mortality rates were 424.3-6847.4 and 0.2-1.9 per 100,000 population, respectively. While more than half of the influenza cases occurred in populations aged younger than 20 years, deaths in older than 60 years accounted for more than two-thirds of all deaths.

CONCLUSION

This study provided the simplest but most important statistics regarding Korean influenza epidemics as a reference. These can be used to understand and manage other new acute respiratory diseases, including COVID-19, and establish influenza-related policies.

Exploration of influenza incidence prediction model based on meteorological factors in Lanzhou, China, 2014-2017

Humans are susceptible to influenza. The influenza virus spreads quickly and behave seasonally. The seasonality and spread of influenza are often associated with meteorological factors and have spatio-temporal differences. Based on the influenza cases and daily average meteorological factors in Lanzhou from 2014 to 2017, this study firstly aimed to analyze the characteristics of influenza incidence in Lanzhou and the impact of meteorological factors on influenza activities. Then, SARIMA(X) models for the prediction were established. The influenza cases in Lanzhou from 2014 to 2017 was more male than female, and the younger the age, the higher the susceptibility; the epidemic characteristics showed that there is a peak in winter, a secondary peak in spring, and a trough in summer and autumn. The influenza cases in Lanzhou increased with increasing daily pressure, decreasing precipitation, average relative humidity, hours of sunshine, average daily temperature and average daily wind speed. Low temperature was a significant driving factor for the increase of transmission intensity of seasonal influenza. The SARIMAX (1,0,0)(1,0,1)[12] multivariable model with average temperature has better prediction performance than the university model. This model is helpful to establish an early warning system, and provide important evidence for the development of influenza control policies and public health interventions.

Forecasting Hospital Visits Due to Influenza Based on Emergency Department Visits for Fever: A Feasibility Study on Emergency Department-Based Syndromic Surveillance

This study evaluated the use of chief complaint data from emergency departments (EDs) to detect the increment of influenza cases identified from the nationwide medical service usage and developed a forecast model to predict the number of patients with influenza using the daily number of ED visits due to fever. The National Health Insurance Service (NHIS) and the National Emergency Department Information System (NEDIS) databases from 2015 to 2019 were used. The definition of fever included having an initial body temperature ≥ 38.0 °C at an ED department or having a report of fever as a patient's chief complaint. The moving average number of visits to the ED due to fever for the previous seven days was used. Patients in the NHIS with the International Classification of Diseases-10 codes of J09, J10, or J11 were classified as influenza cases, with a window duration of 100 days, assuming the claims were from the same season. We developed a forecast model according to an autoregressive integrated moving average (ARIMA) method using the data from 2015 to 2017 and validated it using the data from 2018 to 2019. Of the 29,142,229 ED visits from 2015 to 2019, 39.9% reported either a fever as a chief complaint or a ≥38.0 °C initial body temperature at the ED. ARIMA (1,1,1) (0,0,1)₇ was the most appropriate model for predicting ED visits due to fever. The mean absolute percentage error (MAPE) value showed the prediction accuracy of the model. The correlation coefficient between the number of ED visits and the number of patients with influenza in the NHIS up to 14 days before the forecast, with the exceptions of the eighth, ninth, and twelfth days, was higher than 0.70 (p-value = 0.001). ED-based syndromic surveillances of fever were feasible for the early detection of hospital visits due to influenza.

Recent Increases in Influenza-Related Hospitalizations, Critical Care Resource Use, and In-Hospital Mortality: A 10-Year Population-Based Study in South Korea

Background: Long-term trends in influenza-related hospitalizations, critical care resource use, and hospital outcomes since the 2009 H1N1 influenza pandemic season have been rarely studied for adult populations. Materials and Methods: Adult patients from the Korean Health Insurance Review and Assessment Service who were hospitalized with influenza over a 10-year period (2009−2019) were analyzed. The incidence rates of hospitalization, critical care resource use, and in-hospital death were calculated using mid-year population census data. Results: In total, 300,152 hospitalized patients with influenza were identified (men, 35.7%; admission to tertiary hospitals, 9.4%). Although the age-adjusted hospitalization rate initially decreased since the 2009 H1N1 pandemic (52.61/100,000 population in 2009/2010), it began to increase again in 2013/2014 and reached a peak of 169.86/100,000 population in 2017/2018 (p < 0.001). The in-hospital mortality rate showed a similar increasing trend as the hospitalization, with a peak of 1.44/100,000 population in 2017/2018 (vs. 0.35/100,000 population in 2009/2010; p < 0.001). The high incidence rates of both hospitalization and in-hospital mortality were mainly attributable to patients aged ≥60 years. The rate of intensive care unit admission and the use of mechanical ventilation, continuous renal replacement therapy and vasopressors have also increased from the 2013/2014 season. The incidence of heart failure was the most frequent complication investigated, with a three-fold increase in the last two seasons since 2009/2010. In multivariate analysis adjusted for covariates, among hospitalized patients, type of hospitals and 2009 H1N1 pandemic season were associated with in-hospital mortality. Conclusions: We confirmed that the rates of hospitalization, critical care resource use, and in-hospital mortality by influenza have increased again in recent years. Therefore, strategies are needed to reduce infections and optimize resource use with a greater focus on older people.

The impact of free vaccination policies under the Korean Influenza National Immunization Program: Trends in influenza vaccination rates in South Korea from 2010 to 2019

Background

Annual vaccination for influenza is recommended for high-risk populations for its high morbidity and mortality. South Korea provides free influenza vaccination to some target groups under the National Immunization Program (NIP), and discrepantly high vaccination rates are observed in such populations. In this study, we analyzed the trends in influenza vaccination rates and evaluated the impact of the recent expansion of financial coverage to children ≤12 years and pregnant women.

Methods

We conducted a cross-sectional study with nationwide survey data from Korea National Health and Nutrition Examination Survey (KNHANES). From 2010 to 2019, we evaluated the trends in influenza vaccination rates of the following four target groups: children ≤12 years, adults ≥65 years, pregnant women, and people with chronic diseases.

Results

In total, 80,861 individuals were analyzed. From 2017 to 2019, the vaccination coverage of children ≤12 years increased from 66.2% to 83.1%; pregnant women from 44.1% to 68.5% (comparing the mean of 2010–2017 and 2018–2019, P <0.001 for both). The elderly ≥65 years showed the highest rates (85.8% in 2019), while people with chronic diseases marked the lowest (41.9% in 2019). People with liver diseases showed the lowest vaccination rate of 27.8%, while that of other common diseases ranged between 31.7–44.1%.

Conclusion

The discrepancy between target groups corresponds to their financial coverage under NIP. The recent expansion of financial aids to children ≤12 years and pregnant women was followed by significant increases in vaccination rates in both groups. We suggest that free vaccination policy is one of the most effective strategies to enhance vaccination coverage, and we call for its expansion to other under-vaccinated target groups, especially people with chronic diseases.

Stagnation of life expectancy in Korea in 2018: A cause-specific decomposition analysis

According to the most recent annual report released by Korea Statistics, the life expectancy at birth (for both sexes) in 2018 was 82.7 years, an increase of 0.0 years over 2017, reflecting the first stagnation in life expectancy since 1960. In this study, a time-series analysis was conducted of trends in life expectancy from 2003 to 2018, and causes of death were analyzed using the Kannisto-Thatcher method and the Arriaga decomposition method. The time trend analysis of yearly life expectancy changes indicated that, in Korea, there was a tendency for the yearly increase in life expectancy between 2003 and 2018 to decrease by 0.0211 years per calendar year. The contribution of cardiovascular diseases, the most important contributor to the life expectancy increase in Korea, gradually decreased over this period. The contribution of cardiovascular diseases to the life expectancy increase was 0.506 years in 2003-2006, but this contribution decreased to 0.218 years in 2015-2018. The positive contributions of ill-defined causes and external causes to life expectancy increase detected in previous periods were not evident in 2015-2018. Diseases of the respiratory system made the largest negative contribution both between 2015 and 2018 and between 2017-2018. The life expectancy stagnation in 2018 could be understood as the combined effect of (a) decreasing momentum in the increase of life expectancy and (b) a chance event in 2018 involving life expectancy. Currently, it is difficult to judge whether the stagnation of life expectancy in 2018 is temporary, and further analyses of life expectancy and contributing causes of death in the future are needed.