Background
Scarlet fever is caused by erythogenic toxins produced by group A Streptococcus (GAS) which is mainly transmitted through direct contact with saliva and nasal fluids from infected persons [
1]. The disease is characterized by a sorethroat, fever, and a sandpaper-like rash on reddened skin and most commonly occurs in winter and spring and most commonly affects children [
2].
In 2011, an outbreak of scarlet fever hit Hong Kong (China) and over 600 cases were reported by the end of June 2011 [
3], with two deaths. The same year in April to July, Shanghai witnessed an unprecedented outbreak of scarlet fever among children. In recent years, the number of scarlet fever cases have been increasing in China [
4]. In 2017, a total of 74,369 cases of scarlet fever was reported, compared with 34,207 in 2013 and 54,247 in 2014 and 68,249 in 2015 and 59,282 in 2016 respectively [
5].
As a useful tool, geographic information system (GIS) has been widely applied in infectious diseases surveillance [
6‐
8]. However, few studies [
9,
10] have focused on the spatiotemporal characteristics of scarlet fever. In Shenyang, some researchers described the epidemiology of scarlet fever [
11‐
14], but none explored the spatiotemporal patterns.
In our study, we used Excel 2010 and ArcGIS 10.3 to depict the spatiotemporal characteristics of scarlet fever in Shenyang followed the methods of Qi Zhang et al., 2017 [
9]. The objective of our study was to describe the temporal and spatial epidemic characteristics of scarlet fever in Shenyang and explore the socio-demographic and geographic risk factors affecting the epidemic of scarlet fever in order to provide scientific basis for the prevention and control measures of scarlet fever in Shenyang.
Discussion
Over the past decade, an exceptional upturn in the morbidity of scarlet fever has occurred in some Asian and European countries and areas, containing mainland China [
20], Vietnam [
21], Hong Kong [
22], South Korea [
23], Germany [
24] and England [
25] and the reasons remain unknown [
26‐
29]. This is a worsening trend, especially in China where the ongoing resurgence in disease morbidity has exerted a marked influence on Chinese population since 2011 [
20,
30]. To tackle this, understanding the epidemic characteristics of this disease may play a significant role in the allocation of limited health resource and the formulation of prevention and control strategies [
31].
In this study, We found that the incidence of scarlet fever in Shenyang in 2018 is higher than that in Beijing [
10] during 2005–2014 (14.25 per 100,000) and Jiangsu [
9] during 2005–2015 (1.87 per 100,000),and is higher than the average annual incidence of the whole country [
32] during 2003–2010 (1.58 per 100,000) and during 2011–2016 (4.14 per 100,000). We also found that the incidence of scarlet fever in 2018 was the highest since the outbreak of scarlet fever in 2011 in Shenyang [
13,
14].
According to our study, the incidence of scarlet fever was higher among males than among females, which is consistent with other findings [
9,
10,
33,
34]. The number of scarlet fever cases was the highest among children aged 3–11 years and accounted for 96.89%.The WHO and Public Health UK stated that a high-risk group of scarlet fever was among children 5–15 years old [
35,
36] . In China, kindergarten education is at the age of 3–5 years and primary education is at the age of 6–11 years, so our study suggests that children in the kindergartens and the primary schools may be at high risk for scarlet fever.
Scarlet fever could occur throughout all the year, yet case notifications had a distinct seasonal distribution and showed double peak pattern in the year. There were fewer cases in February, and the number of cases increased sharply from March to June, the first peak occurred in June. The number of cases decreased from July to August and increased again between September and December, the second peak appeared in December, which is consistent with the findings of previous studies [
9,
10,
31,
32]. In China, March–June and September–December are school days, and January–February and July–August are school holidays. It can be seen that the month in which the number of scarlet fever cases increases is the time when the children in the kindergartens and the primary school students are in school. The month in which the number of scarlet fever cases decrease is the time when the children in the kindergartens and the primary school students are on vacation. Prompting us that scarlet fever has obvious aggregation in kindergartens and primary schools. Since there is no scarlet fever vaccine at present, it may be helpful to suggest kindergartens and primary schools to implement the morning check system, epidemic reporting system and isolation measures. In addition, teachers and parents need to teach children to wash their hands frequently. Although previous studies have not consistently demonstrated direct transmission of GAS from fomites, proper maintenance of environmental hygiene remains a prudent measure to take [
37]. Therefore, it is also suggested that kindergartens and schools improve environmental hygiene by disinfecting toys, railings and tables.
In our study, the disease mapping, spatial autocorrelation analysis and hot spot analysis were applied to depict the geographic distribution of scarlet fever incidence. The spatial distribution showed that scarlet fever cases were concentrated in urban areas with high population density, and the incidence of scarlet fever in urban areas was significantly higher than that in rural areas, consistent with the findings of Gehendra et al. [
10] and this may suggest that the incidence of scarlet fever is related to population density. The autocorrelation analysis of Global Moran’s I value demonstrated that the spatial distribution of scarlet fever was randomly distributed in Shenyang in 2018. This meant that there was no autocorrelation of the spatial distribution of scarlet fever between districts in Shenyang. It indicated that there was neither positive correlation nor negative correlation between adjacent districts in the incidence, but a random distribution of high and low values with no rule to follow in Shenyang. However, hotspot analysis of Getis-Ord (Gi*) Z values revealed that the hotspot area with a high-high positive spatial association of scarlet fever incidence was located around the urban districts (Heping, Shenhe, Dadong, Huanggu, Sujiatun, Hunnan and Yuhong) and the coldspot area with a low-low positive spatial association of scarlet fever incidence was not found, which is consistent with the findings of Gehendra et al. [
10] Prompting us that scarlet fever is easily to form aggregation in urban areas with high population density and convenient transportation which increased the risk of scarlet fever exposure [
10]. These results remind us that prevention and control measures for scarlet fever should focus more on the hotspot areas.
In spite of the above findings, the limitations in our study should be considered. First, not all children aged 3–11 are enrolled in kindergarten or primary school and so further work is required to explore whether children in kindergarten or primary school are at higher risk of scarlet fever than children who are not in enrolled in school. Secondly, we did not analyze the reasons that the incidence is higher in Shenyang than in the rest of China, we will also conduct more studies to analyze the reasons for the higher incidence in Shenyang compared with other places in the future. Thirdly, our study confirmed once again that scarlet fever was more likely to occur in children, and once again emphasized the importance of strengthening prevention and control measures in kindergartens and primary schools, but our study provided no new information on risk factors, we will also do further work to study the risk factors of scarlet fever and provide more scientific evidence for the prevention and control of scarlet fever in the future.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.