Epidemiological study of scarlet fever in Shenyang, China

Abstract

BackgroundSince 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.MethodsExcel 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.ResultsA 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.ConclusionsUrban 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.

Spatiotemporal dynamics and potential ecological drivers of acute respiratory infectious diseases: an example of scarlet fever in Sichuan Province

“…In our study, males outnumbered females in all patients, according to statistics, which is consistent with previous studies [ 20 , 39 ]. This can be explained by the risk of exposure, for example, men have more outdoor activities and unhygienic behaviors than women [ 21 ].…”

“…As for the spatiotemporal study of scarlet fever, most studies concentrated on dynamics of the epidemic part (e.g, epidemic from temporal aspect and epidemic from spatial aspect) [ 17 – 20 ], ignoring the endemic part (e.g, indirect transmission from the environment). And also they did not qualify the effect of covariates in different dimensions (i.e, time, space, and endemic).…”

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

“…Over the past decade, the incidence of scarlet fever has an anomalous increase in some Asian and European countries and regions, and this trend had exerted a marked influence on Chinese population since 2011 [ 19 ]. It is necessary to fully understand the epidemiological characteristics and predict the incidence of scarlet fever to provide information and evidence for its prevention and control.…”

Study on geographical characteristics and influencing factors of scarlet fever based on Bayesian hierarchical spatio-temporal model and geodetector

“…The study of scarlet fever in the direction of geography mainly starts from the study of the disease time of scarlet fever. Studies have shown that the incidence rate is higher between March-July and November-January each year [1][2][3][4][5][6] . With the deepening of the research, some studies combined spatial on the basis of time, and the researches show that scarlet fever showed spatial characteristics that urban areas were more prone to disease than rural areas [2,5] .…”