Increasing Number of Scarlet Fever Cases, South Korea, 2011-2016

Pertussis epidemic in Korea and implications for epidemic control

The pertussis epidemic in Korea is ongoing, with a record-high incidence rate. Although pertussis incidence is high worldwide in 2024, the scale of the increase observed in Korea is unprecedented and incomparable to that in other countries. The high proportion of cases among children aged 5 to 14 years is the distinctive characteristics of the 2024 pertussis epidemic in Korea. To accurately interpret the epidemiological trend in pertussis incidence in Korea, validating the surveillance system and evaluating vaccine efficacy and effectiveness are essential.

Trends (2007-2019) of major atopic diseases throughout the life span in a large Mexican population

Background

Major atopic diseases such as atopic dermatitis (AD), allergic rhinitis (AR), and asthma share the same atopic background, but they often show differences in their epidemiological behavior.

Objective

We aimed to report the profile of these atopic diseases in a large Mexican population, including their age-related incidences, male:female (M:F) ratios, recent time trends, and association with altitude.

Methods

Registries from the largest, nationwide health institution in Mexico (more than 34 million insured subjects), were reviewed. New cases of AD, AR, and asthma diagnosed each year by family physicians from 2007 to 2019 were adjusted by the corresponding insured population to estimate incidence rates.

Results

Incidences of the 3 atopic diseases were highest in the 0-4 years age-group and progressively decreased thereafter until adolescence. Asthma and AR, but not AD, were more frequent in males during childhood (M:F ratios of 1.5, 1.3, and 0.95, respectively), but predominated in females during adulthood (M:F ratios of 0.52, 0.68, and 0.73, respectively). Time trends showed an initial increasing trend of annual incidences, with a peak around 2009-2011, and a downward trend afterward. This decreasing trend was seen in all age-groups and was more evident for AD (∼50% drop) and asthma (∼40% drop) than for AR (∼20% drop). Geographical distribution suggested that incidences of asthma and AR, but not of AD, had an inverse association with altitude.

Conclusion

Annual incidences of the 3 major atopic diseases have declined in recent years in almost all age groups, and their epidemiological profile during the life span showed contrasting differences according to age, sex, and ecological association with altitude, mainly regarding AD.

Forecasting the monthly incidence of scarlet fever in Chongqing, China using the SARIMA model

The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R²) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)₁₂. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.

Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China

OBJECTIVE

We aim to examine the adequacy of an innovation state-space modeling framework (called TBATS) in forecasting the long-term epidemic seasonality and trends of hemorrhagic fever with renal syndrome (HFRS).

METHODS

The HFRS morbidity data from January 1995 to December 2020 were taken, and subsequently, the data were split into six different training and testing segments (including 12, 24, 36, 60, 84, and 108 holdout monthly data) to investigate its predictive ability of the TBATS method, and its forecasting performance was compared with the seasonal autoregressive integrated moving average (SARIMA).

RESULTS

The TBATS (0.27, {0,0}, -, {<12,4>}) and SARIMA (0,1,(1,3))(0,1,1)12 were selected as the best TBATS and SARIMA methods, respectively, for the 12-step ahead prediction. The mean absolute deviation, root mean square error, mean absolute percentage error, mean error rate, and root mean square percentage error were 91.799, 14.772, 123.653, 0.129, and 0.193, respectively, for the preferred TBATS method and were 144.734, 25.049, 161.671, 0.203, and 0.296, respectively, for the preferred SARIMA method. Likewise, for the 24-, 36-, 60-, 84-, and 108-step ahead predictions, the preferred TBATS methods produced smaller forecasting errors over the best SARIMA methods. Further validations also suggested that the TBATS model outperformed the Error-Trend-Seasonal framework, with little exception. HFRS had dual seasonal behaviors, peaking in May-June and November-December. Overall a notable decrease in the HFRS morbidity was seen during the study period (average annual percentage change=-6.767, 95% confidence intervals: -10.592 to -2.778), and yet different stages had different variation trends. Besides, the TBATS model predicted a plateau in the HFRS morbidity in the next ten years.

CONCLUSION

The TBATS approach outperforms the SARIMA approach in estimating the long-term epidemic seasonality and trends of HFRS, which is capable of being deemed as a promising alternative to help stakeholders to inform future preventive policy or practical solutions to tackle the evolving scenarios.

Spatiotemporal clustering and meteorological factors affected scarlet fever incidence in mainland China from 2004 to 2017

OBJECTIVE

To analyze the spatiotemporal dynamic distribution and detect the related meteorological factors of scarlet fever from an ecological perspective, which could provide scientific information for effective prevention and control of this disease.

METHODS

The data on scarlet fever cases in mainland China were downloaded from the Data Center of the China Public Health Science, while monthly meteorological data were extracted from the official website of the National Bureau of Statistics. Global Moran's I, local Getis-Ord G_i^⁎ hotspot statistics, and Kulldorff's retrospective space-time scan statistical analysis were used to detect the spatial and spatiotemporal clusters of scarlet fever across all settings. A spatial panel data model was conducted to estimate the impact of meteorological factors on scarlet fever incidence.

RESULTS

Scarlet fever in China had obvious spatial, temporal, and spatiotemporal clustering, high-incidence spatial clusters were located mainly in the north and northeast of China. Nine spatiotemporal clusters were identified. A spatial lag fixed effects panel data model was the best fit for regression analysis. After adjusting for spatial individual effects and spatial autocorrelation (ρ = 0.5623), scarlet fever incidence was positively associated with a one-month lag of average temperature, precipitation, and total sunshine hours (all P-values < 0.05). Each 10 °C, 2 cm, and 10 h increase in temperature, precipitation, and sunshine hours, respectively, was associated with a 6.41% increment and 1.04% and 1.41% decrement in scarlet fever incidence, respectively.

CONCLUSION

The incidence of scarlet fever in China showed an upward trend in recent years. It had obvious spatiotemporal clustering, with the high-risk areas mainly concentrated in the north and northeast of China. Areas with high temperature and with low precipitation and sunshine hours tended to have a higher scarlet fever incidence, and we should pay more attention to prevention and control in these places.

Incidence and Effects of Acquisition of the Phage-Encoded ssa Superantigen Gene in Invasive Group A Streptococcus

The acquisition of the phage-encoded superantigen ssa by scarlet fever-associated group A Streptococcus (Streptococcus pyogenes, GAS) is found in North Asia. Nonetheless, the impact of acquiring ssa by GAS in invasive infections is unclear. This study initially analyzed the prevalence of ssa+ GAS among isolates from sterile tissues and blood. Among 220 isolates in northern Taiwan, the prevalence of ssa+ isolates increased from 1.5% in 2008–2010 to 40% in 2017–2019. Spontaneous mutations in covR/covS, which result in the functional loss of capacity to phosphorylate CovR, are frequently recovered from GAS invasive infection cases. Consistent with this, Phostag western blot results indicated that among the invasive infection isolates studied, 10% of the ssa+ isolates lacked detectable phosphorylated CovR. Transcription of ssa is upregulated in the covS mutant. Furthermore, in emm1 and emm12 covS mutants, ssa deletion significantly reduced their capacity to grow in human whole blood. Finally, this study showed that the ssa gene could be transferred from emm12-type isolates to the emm1-type wild-type strain and covS mutants through phage infection and lysogenic conversion. As the prevalence of ssa+ isolates increased significantly, the role of streptococcal superantigen in GAS pathogenesis, particularly in invasive covR/covS mutants, should be further analyzed.

Use of meteorological parameters for forecasting scarlet fever morbidity in Tianjin, Northern China

The scarlet fever incidence has increased drastically in recent years in China. However, the long-term relationship between climate variation and scarlet fever remains contradictory, and an early detection system is lacking. In this study, we aim to explore the potential long-term effects of variations in monthly climatic parameters on scarlet fever and to develop an early scarlet-fever detection tool. Data comprising monthly scarlet fever cases and monthly average climatic variables from 2004 to 2017 were retrieved from the Notifiable Infectious Disease Surveillance System and National Meteorological Science Center, respectively. We used a negative binomial multivariable regression to assess the long-term impacts of weather parameters on scarlet fever and then built a novel forecasting technique by integrating an autoregressive distributed lag (ARDL) method with a nonlinear autoregressive neural network (NARNN) based on the significant meteorological drivers. Scarlet fever was a seasonal disease that predominantly peaked in spring and winter. The regression results indicated that a 1 °C increment in the monthly average temperature and a 1-h increment in the monthly aggregate sunshine hours were associated with 17.578% (95% CI 7.674 to 28.393%) and 0.529% (95% CI 0.035 to 1.025%) increases in scarlet fever cases, respectively; a 1-hPa increase in the average atmospheric pressure at a 1-month lag was associated with 12.996% (95% CI 9.972 to 15.919%) decrements in scarlet fever cases. Based on the model evaluation criteria, the best-performing basic and combined approaches were ARDL(1,0,0,1) and ARDL(1,0,0,1)-NARNN(5, 22), respectively, and this hybrid approach comprised smaller performance measures in both the training and testing stages than those of the basic model. Climate variability has a significant long-term influence on scarlet fever. The ARDL-NARNN technique with the incorporation of meteorological drivers can be used to forecast the future epidemic trends of scarlet fever. These findings may be of great help for the prevention and control of scarlet fever.

Exposure to air pollution and scarlet fever resurgence in China: a six-year surveillance study

Scarlet fever has resurged in China starting in 2011, and the environment is one of the potential reasons. Nationwide data on 655,039 scarlet fever cases and six air pollutants were retrieved. Exposure risks were evaluated by multivariate distributed lag nonlinear models and a meta-regression model. We show that the average incidence in 2011-2018 was twice that in 2004-2010 [RR = 2.30 (4.40 vs. 1.91), 95% CI: 2.29-2.31; p < 0.001] and generally lower in the summer and winter holiday (p = 0.005). A low to moderate correlation was seen between scarlet fever and monthly NO₂ (r = 0.21) and O₃ (r = 0.11). A 10 μg/m³ increase of NO₂ and O₃ was significantly associated with scarlet fever, with a cumulative RR of 1.06 (95% CI: 1.02-1.10) and 1.04 (95% CI: 1.01-1.07), respectively, at a lag of 0 to 15 months. In conclusion, long-term exposure to ambient NO₂ and O₃ may be associated with an increased risk of scarlet fever incidence, but direct causality is not established.

The association between ambient particulate matters, nitrogen dioxide, and childhood scarlet fever in Hangzhou, Eastern China, 2014-2018

BACKGROUND

The emerging cases of childhood scarlet fever (SF) and worsening air pollution problems in Chinese cities suggests a potential linkage between them. However, few studies had explored this association in a large childhood population.

METHODS

We conducted a time-series analysis using the daily count of SF and the daily concentrations of particulate matters with an aerodynamic diameter of 2.5 (PM_2.5) and 10 (PM₁₀), as well as nitrogen dioxide (NO₂) in Hangzhou, China from 2014 to 2018. Distributed lag nonlinear models were used to estimate the lag effects of PM_2.5, PM₁₀ and NO₂ for a maximum lag of 10 days, which were quantified using relative risk (RR) comparing the adjusted risks at the 2.5th (extremely low effect) and 97.5th (extremely high effect) percentiles of concentration of the three air pollutants to that at the median. Stratified RRs by sex were also reported.

RESULTS

Using the median concentration as reference, for extremely high effect, the RR was the highest on lag days 5, 6, and 3 for PM_2.5, PM₁₀, and NO₂ respectively. While on lag day 0, the RR of PM_2.5, PM₁₀, and NO₂ were 1.04 (95%CI: 0.90-1.20), 1.07 (95%CI: 0.92-1.24), and 1.08 (95%CI: 0.92-1.26) respectively, the RRs increased constantly and cumulatively to the maximum values of 1.88 (95%CI: 1.33-2.66), 1.82 (95%CI: 1.29-2.55), and 2.19 (95%CI: 1.47-3.27) for PM_2.5, PM₁₀, and NO₂ respectively on lag day 10. Subgroup analyses showed that females appeared to be more vulnerable to the three pollutants than males.

CONCLUSION

Our study provides evidence that PM_2.5, PM₁₀, and NO₂ exert delayed effects on SF infection.

Epidemiological study of scarlet fever in Shenyang, China

Background

Since 2011, there has been an increase in the incidence of scarlet fever across China. The main objective of this study was to depict the spatiotemporal epidemiological characteristics of the incidence of scarlet fever in Shenyang, China, in 2018 so as to provide the scientific basis for effective strategies of scarlet control and prevention.

Methods

Excel 2010 was used to demonstrate the temporal distribution at the month level and ArcGIS10.3 was used to demonstrate the spatial distribution at the district/county level. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation and the Getis-Ord statistic was used to determine the hot-spot areas of scarlet fever.

Results

A total of 2314 scarlet fever cases were reported in Shenyang in 2018 with an annual incidence of 31.24 per 100,000. The incidence among males was higher than that among females(p<0.001). A vast majority of the cases (96.89%) were among children aged 3 to 11 years. The highest incidence was 625.34/100,000 in children aged 5–9 years. In 2018 there were two seasonal peaks of scarlet fever in June (summer-peak) and December (winter-peak). The incidence of scarlet fever in urban areas was significantly higher than that in rural areas(p<0.001). The incidence of scarlet fever was randomly distributed in Shenyang. There are hotspot areas located in seven districts.

Conclusions

Urban areas are the hot spots of scarlet fever and joint prevention and control measures between districts should be applied. Children aged 3–11 are the main source of scarlet fever and therefore the introduction of prevention and control into kindergarten and primary schools may be key to the control of scarlet fever epidemics.

Increased Incidence of Scarlet Fever - China, 1999-2018

What is already known about this topic?

Scarlet fever had high incidence between the 1950s and 1980s, but during the 1980s and 1990s, the incidence of scarlet fever dropped to a relatively low and stable levels in China.

What is added by this report?

Starting in 2011, scarlet fever incidence significantly increased in China. In the eight years between 2011 and 2018, 479,555 cases were reported, which exceeded the total number of 241,365 cases reported in the previous twelve years 1999-2010.

What are the implications for public health practice? Both patient and pathogen epidemiological surveillance need to be heightened to monitor serious cases of scarlet fever and to implement timely control measures.

Emergence of dominant toxigenic M1T1 Streptococcus pyogenes clone during increased scarlet fever activity in England: a population-based molecular epidemiological study

BACKGROUND

Since 2014, England has seen increased scarlet fever activity unprecedented in modern times. In 2016, England's scarlet fever seasonal rise coincided with an unexpected elevation in invasive Streptococcus pyogenes infections. We describe the molecular epidemiological investigation of these events.

METHODS

We analysed changes in S pyogenes emm genotypes, and notifications of scarlet fever and invasive disease in 2014-16 using regional (northwest London) and national (England and Wales) data. Genomes of 135 non-invasive and 552 invasive emm1 isolates from 2009-16 were analysed and compared with 2800 global emm1 sequences. Transcript and protein expression of streptococcal pyrogenic exotoxin A (SpeA; also known as scarlet fever or erythrogenic toxin A) in sequenced, non-invasive emm1 isolates was quantified by real-time PCR and western blot analyses.

FINDINGS

Coincident with national increases in scarlet fever and invasive disease notifications, emm1 S pyogenes upper respiratory tract isolates increased significantly in northwest London in the March to May period, from five (5%) of 96 isolates in 2014, to 28 (19%) of 147 isolates in 2015 (p=0·0021 vs 2014 values), to 47 (33%) of 144 in 2016 (p=0·0080 vs 2015 values). Similarly, invasive emm1 isolates collected nationally in the same period increased from 183 (31%) of 587 in 2015 to 267 (42%) of 637 in 2016 (p<0·0001). Sequences of emm1 isolates from 2009-16 showed emergence of a new emm1 lineage (designated M1UK)-with overlap of pharyngitis, scarlet fever, and invasive M1UK strains-which could be genotypically distinguished from pandemic emm1 isolates (M1global) by 27 single-nucleotide polymorphisms. Median SpeA protein concentration in supernatant was nine-times higher among M1UK isolates (190·2 ng/mL [IQR 168·9-200·4]; n=10) than M1global isolates (20·9 ng/mL [0·0-27·3]; n=10; p<0·0001). M1UK expanded nationally to represent 252 (84%) of all 299 emm1 genomes in 2016. Phylogenetic analysis of published datasets identified single M1UK isolates in Denmark and the USA.

INTERPRETATION

A dominant new emm1 S pyogenes lineage characterised by increased SpeA production has emerged during increased S pyogenes activity in England. The expanded reservoir of M1UK and recognised invasive potential of emm1 S pyogenes provide plausible explanation for the increased incidence of invasive disease, and rationale for global surveillance.

FUNDING

UK Medical Research Council, UK National Institute for Health Research, Wellcome Trust, Rosetrees Trust, Stoneygate Trust.

Analysis of Epidemiological Characteristics of Scarlet Fever in Zhejiang Province, China, 2004-2018

Objective: The aim of this study was to analyze the trends and epidemiological characteristics of scarlet fever in Zhejiang Province in 2004–2018, intending to provide a basis for targeted prevention and control of this disease. Method: We collated the epidemiological data for cases of scarlet fever from the China Information System for Disease Control and Prevention (CISDCP) in Zhejiang province between 1 January 2004 and 31 December 2018. Descriptive statistical analysis was used to analyze epidemiological characteristics of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Results: In 2004–2018, a total of 22,194 cases of scarlet fever were reported in Zhejiang Province, with no death reports. The annual average of scarlet fever incidence was 2.82/100,000 (range,1.12 to 6.34/100,000). The male incidence was higher than that among female (χ² = 999.834, p < 0.05), and a majority of the cases (86.42%) occurred in children aged 3–9 years. Each year, the incidence of scarlet fever in Zhejiang Province appeared two seasonal peaks: the first peak occurred from March to June (the constituent ratio was 49.06%), the second peak was lower than the first one during November and the following January (the constituent ratio was 28.67%). The two peaks were almost in accordance with the school spring semester and autumn–winter semester, respectively. The incidence in the northern regions of the province was generally higher than that in the southern regions. High-value clusters were detected in the central and northern regions, while low-value clusters occurred in the southern regions via the Getis-Ord Gi* statistical analysis. Conclusions: The prevalence of scarlet fever in Zhejiang Province showed a marked seasonality variation and mainly clustered in the central and northern regions in 2004–2018. Children under 15 years of age were most susceptible to scarlet fever. Kindergartens and primary schools should be the focus of prevention and control, and targeted strategies and measures should be taken to reduce the incidence.

Complementing conventional infectious disease surveillance with national health insurance claims data in the Republic of Korea

Surveillance remains an important tool for timely outbreak detection and response. Many countries, including Korea, have established national infectious disease surveillance systems with clinical notification. We aimed to evaluate the National Health Insurance Claims-based Surveillance (NHICS) compared to conventional passive report-based National Infectious Diseases Surveillance (NIDS). Reported to claimed cases ratios (R/C ratio) were evaluated from monthly notifiable disease cases captured by NIDS and NHICS. The relationships between 26 infectious diseases and each surveillance system were analysed using Pearson's correlation analysis and linear regression. There was an overall increase in R/C ratio from 2010-2017 (0.37 to 0.78). In 22 infectious diseases, there was a correlation between NIDS and NHICS. Moreover, claim-based surveillance showed less fluctuating disease incidence rates than report-based surveillance for specific infectious diseases, such as varicella, mumps, and scarlet fever. However, for infectious diseases with episodic outbreaks or low incidence, it was difficult to assess NHICS usefulness. Claim-based surveillance is less affected by limitations of conventional report-based surveillance systems, such as reporting rate. Given delays in claim systems, a claim-based surveillance is expected to be complementary to conventional systems for the detection of various infectious diseases with the advancement of bio-information technology.

Incidence of Scarlet Fever in Children in Jeju Province, Korea, 2002-2016: An Age-period-cohort Analysis

Objectives:

Outbreaks of scarlet fever in Mexico in 1999, Hong Kong and mainland China in 2011, and England in 2014-2016 have received global attention, and the number of notified cases in Korean children, including in Jeju Province, has also increased since 2010. To identify relevant hypotheses regarding this emerging outbreak, an age-period-cohort (APC) analysis of scarlet fever incidence was conducted among children in Jeju Province, Korea.

Methods:

This study analyzed data from the nationwide insurance claims database administered by the Korean National Health Insurance Service. The inclusion criteria were children aged ≤14 years residing in Jeju Province, Korea who received any form of healthcare for scarlet fever from 2002 to 2016. The age and year variables were categorized into 5 groups, respectively. After calculating the crude incidence rate (CIR) for age and calendar year groups, the intrinsic estimator (IE) method was applied to conduct the APC analysis.

Results:

In total, 2345 cases were identified from 2002 to 2016. Scarlet fever was most common in the 0-2 age group, and boys presented more cases than girls. Since the CIR decreased with age between 2002 and 2016, the age and period effect decreased in all observed years. The IE coefficients suggesting a cohort effect shifted from negative to positive in 2009.

Conclusions:

The results suggest that the recent outbreak of scarlet fever among children in Jeju Province might be explained through the cohort effect. As children born after 2009 showed a higher risk of scarlet fever, further descriptive epidemiological studies are needed.

Effect of meteorological factors on scarlet fever incidence in Guangzhou City, Southern China, 2006-2017

OBJECTIVE

To explore the relationship between meteorological factors and scarlet fever incidence from 2006 to 2017 in Guangzhou, the largest subtropical city of Southern China, and assist public health prevention and control measures.

METHODS

Data for weekly scarlet fever incidence and meteorological variables from 2006 to 2017 in Guangzhou were collected from the National Notifiable Disease Report System (NNDRS) and the Guangzhou Meteorological Bureau (GZMB). Distributed lag nonlinear models (DLNMs) were conducted to estimate the effect of meteorological factors on weekly scarlet fever incidence in Guangzhou.

RESULTS

We observed nonlinear effects of temperature, relative humidity, and wind velocity. The risk was the highest when the weekly mean temperature was 31 °C during lag week 14, yielding a relative risk (RR) of 1.48 (95% CI: 1.01-2.17). When relative humidity was 43.5% during lag week 0, the RR was 1.49 (95% CI: 1.04-2.12); the highest RR (1.55, 95% CI: 1.20-1.99) was reached when relative humidity was 93.5% during lag week 20. When wind velocity was 4.4 m/s during lag week 13, the RR was highest at 3.41 (95% CI: 1.57-7.44). Positive correlations were observed among weekly temperature ranges and atmospheric pressure with scarlet fever incidence, while a negative correlation was detected with aggregate rainfall. The cumulative extreme effect of meteorological variables on scarlet fever incidence was statistically significant, except for the high effect of wind velocity.

CONCLUSION

Weekly mean temperature, relative humidity, and wind velocity had double-trough effects on scarlet fever incidence; high weekly temperature range, high atmospheric pressure, and low aggregate rainfall were risk factors for scarlet fever morbidity. Our findings provided preliminary, but fundamental, information that may be useful for a better understanding of epidemic trends of scarlet fever and for developing an early warning system. Laboratory surveillance for scarlet fever should be strengthened in the future.

Detecting spatio-temporal hotspots of scarlet fever in Taiwan with spatio-temporal Gi* statistic

A resurgence of scarlet fever has caused many pediatric infections in East Asia and the United Kingdom. Although scarlet fever in Taiwan has not been a notifiable infectious disease since 2007, the comprehensive national health insurance data can still track its trend. Here, we used data from the open data portal of the Taiwan Centers for Disease Control. The scarlet fever trend was measured by outpatient and hospitalization rates from 2009 to 2017. In order to elucidate the spatio-temporal hotspots, we developed a new method named the spatio-temporal Gi* statistic, and applied Joinpoint regression to compute the annual percentage change (APC). The overall APCs in outpatient and hospitalization were 15.1% (95% CI: 10.3%-20.2%) and 7.7% (95%CI: 4.5% -10.9%). The major two infected groups were children aged 5-9 (outpatient: 0.138 scarlet fever diagnoses per 1,000 visits; inpatient: 2.579 per 1,000 visits) and aged 3-4 (outpatient: 0.084 per 1,000 visits; inpatient: 1.469 per 1,000 visits). We found the counties in eastern Taiwan and offshore counties had the most hotspots in the outpatient setting. In terms of hospitalization, the hotspots mostly occurred in offshore counties close to China. With the help of the spatio-temporal statistic, health workers can set up enhanced laboratory surveillance in those hotspots.

Epidemiological Impact of the Korean National Immunization Program on Varicella Incidence

The number of reported varicella cases is continuously increasing in Korea; however, associated medical utilization is declining. The ratio between varicella insurance claims and reports of passive infectious disease surveillance has gradually increased to > 80% since the second half of 2017. The recent increase in reported varicella cases is influenced by improved reporting. We calculated the varicella incidence and cumulative incidence in each birth cohort according to age. The cumulative incidence rate among children aged < 6 years in the birth cohort born after the National Immunization Program introduced the varicella vaccine was about 60% lower than among children born before.

Seasonality and trend prediction of scarlet fever incidence in mainland China from 2004 to 2018 using a hybrid SARIMA-NARX model

Background

Scarlet fever is recognized as being a major public health issue owing to its increase in notifications in mainland China, and an advanced response based on forecasting techniques is being adopted to tackle this. Here, we construct a new hybrid method incorporating seasonal autoregressive integrated moving average (SARIMA) with a nonlinear autoregressive with external input(NARX) to analyze its seasonality and trend in order to efficiently prevent and control this re-emerging disease.

Methods

Four statistical models, including a basic SARIMA, basic nonlinear autoregressive (NAR) method, traditional SARIMA-NAR and new SARIMA-NARX hybrid approaches, were developed based on scarlet fever incidence data between January 2004 and July 2018 to evaluate its temporal patterns, and their mimic and predictive capacities were compared to discover the optimal using the mean absolute percentage error, root mean square error, mean error rate, and root mean square percentage error.

Results

The four preferred models identified were comprised of the SARIMA(0,1,0)(0,1,1)₁₂, NAR with 14 hidden neurons and five delays, SARIMA-NAR with 33 hidden neurons and five delays, and SARIMA-NARX with 16 hidden neurons and 4 delays. Among which presenting the lowest values of the aforementioned indices in both simulation and prediction horizons is the SARIMA-NARX method. Analyses from the data suggested that scarlet fever was a seasonal disease with predominant peaks of summer and winter and a substantial rising trend in the scarlet fever notifications was observed with an acceleration of 9.641% annually, particularly since 2011 with 12.869%, and moreover such a trend will be projected to continue in the coming year.

Conclusions

The SARIMA-NARX technique has the promising ability to better consider both linearity and non-linearity behind scarlet fever data than the others, which significantly facilitates its prevention and intervention of scarlet fever. Besides, under current trend of ongoing resurgence, specific strategies and countermeasures should be formulated to target scarlet fever.

Analysis of Epidemiological Characteristics of Notifiable Diseases Reported in Children Aged 0⁻14 Years from 2008 to 2017 in Zhejiang Province, China

This study aims to learn the characteristics of morbidity and mortality of notifiable diseases reported in children aged 0⁻14 years in Zhejiang Province in 2008⁻2017. We collated data from the China Information System for Disease Control and Prevention in Zhejiang province between 1 January 2008 and 31 December 2017 of children aged 0⁻14 years. From 2008 to 2017, a total of 32 types and 1,994,740 cases of notifiable diseases were reported in children aged 0⁻14 years, including 266 deaths in Zhejiang Province. The annual average morbidity was 2502.87/100,000, and the annual average mortality was 0.33/100,000. Male morbidity was 2886.98/100,000, and female morbidity was 2072.16/100,000, with the male morbidity rate higher than the female morbidity rate (χ² = 54,033.12, p < 0.01). No Class A infectious diseases were reported. The morbidity of Class B infectious diseases showed a downward trend, but that of Class C infectious diseases showed an upward trend. There were 72,041 cases in 22 kinds of Class B infectious disease and 138 death cases, with a morbidity rate of 90.39/100,000, and a mortality rate of 0.17/100,000. There were 1,922,699 cases in 10 kinds of Class C infectious disease and 128 death cases, with a morbidity rate of 2412.47/100,000, and a mortality rate of 0.16/100,000. The main high-prevalence diseases included hand-foot-and-mouth disease (1430.38/100,000), other infectious diarrheal diseases (721.40/100,000), mumps (168.83/100,000), and influenza (47.40/100,000). We should focus on the prevention and control of hand-foot and mouth disease, other infectious diarrheal diseases, mumps and influenza in children aged 0⁻14 years in Zhejiang Province. It is recommended to strengthen epidemic surveillance and undertake early prevention and control measures in order to reduce the younger children incidence rate of infectious diseases. Immunization planning vaccines can help achieve a significant preventive decline of infectious diseases.

Increasing varicella incidence rates among children in the Republic of Korea: an age-period-cohort analysis

In the Republic of Korea, despite the introduction of one-dose universal varicella vaccination in 2005 and achieving a high coverage rate of 98.9% in 2012, the incidence rate has been increased sevenfold. This study aimed to investigate time trends of varicella incidence rate, assessing the age, period and birth cohort effects. We used national data on the annual number of reported cases from 2006 to 2017. A log-linear Poisson regression model was used to estimate age-period-cohort effects on varicella incidence rate. From 2006 to 2017, the incidence of varicella increased from 22.5 cases to more than 154.8 cases per 100 000. Peak incidence has shifted from 4 to 6 years old. The estimated period and cohort effects showed significant upward patterns, with a linear increasing trend by net drift. There has been an increase in the incidence among the Korean population regarding period and cohort despite the universal vaccination of varicella vaccine. Our data suggest the need for additional studies to address the current gap in herd immunity.

Cytotoxicity and Survival Fitness of Invasive covS Mutant of Group A Streptococcus in Phagocytic Cells

Group A streptococci (GAS) with spontaneous mutations in the CovR/CovS regulatory system are more invasive and related to severe manifestations. GAS can replicate inside phagocytic cells; therefore, phagocytic cells could serve as the niche to select invasive covS mutants. Nonetheless, the encapsulated covS mutant is resistant to phagocytosis. The fate of intracellular covS mutant in phagocytic cells and whether the intracellular covS mutant contributes to invasive infections are unclear. In this study, capsule-deficient (cap^-) strains were utilized to study how intracellular bacteria interacted with phagocytic cells. Results from the competitive infection model showed that the cap^-covS mutant had better survival fitness than the cap^- wild-type strain in the PMA-activated U937 cells. In addition, the cap^-covS mutant caused more cell damages than the cap^- wild-type strain and encapsulated covS mutant. Furthermore, treatments with infected cells with clindamycin to inhibit the intracellular bacteria growth was more effective to reduce bacterial toxicity than utilized penicillin to kill the extracellular bacteria. These results not only suggest that the covS mutant could be selected from the intracellular niche of phagocytic cells but also indicating that inactivating or killing intracellular GAS may be critical to prevent invasive infection.