Abstract
(1) Background: Evidence regarding scarlet fever and its relationship with meteorological, including air pollution factors, is not very available. This study aimed to examine the relationship between ambient air pollutants and meteorological factors with scarlet fever occurrence in Beijing, China. (2) Methods: A retrospective ecological study was carried out to distinguish the epidemic characteristics of scarlet fever incidence in Beijing districts from 2013 to 2014. Daily incidence and corresponding air pollutant and meteorological data were used to develop the model. Global Moran’s I statistic and Anselin’s local Moran’s I (LISA) were applied to detect the spatial autocorrelation (spatial dependency) and clusters of scarlet fever incidence. The spatial lag model (SLM) and spatial error model (SEM) including ordinary least squares (OLS) models were then applied to probe the association between scarlet fever incidence and meteorological including air pollution factors. (3) Results: Among the 5491 cases, more than half (62%) were male, and more than one-third (37.8%) were female, with the annual average incidence rate 14.64 per 100,000 population. Spatial autocorrelation analysis exhibited the existence of spatial dependence; therefore, we applied spatial regression models. After comparing the values of R-square, log-likelihood and the Akaike information criterion (AIC) among the three models, the OLS model (R2 = 0.0741, log likelihood = −1819.69, AIC = 3665.38), SLM (R2 = 0.0786, log likelihood = −1819.04, AIC = 3665.08) and SEM (R2 = 0.0743, log likelihood = −1819.67, AIC = 3665.36), identified that the spatial lag model (SLM) was best for model fit for the regression model. There was a positive significant association between nitrogen oxide (p = 0.027), rainfall (p = 0.036) and sunshine hour (p = 0.048), while the relative humidity (p = 0.034) had an adverse association with scarlet fever incidence in SLM. (4) Conclusions: Our findings indicated that meteorological, as well as air pollutant factors may increase the incidence of scarlet fever; these findings may help to guide scarlet fever control programs and targeting the intervention.
Highlights
It has been well known that scarlet fever is a seasonal infectious childhood illness caused by Group A Streptococcus bacteria (Group A beta haemolytic streptococci (GABHS))
Most of the scarlet fever patients were 3–8-year-old children (83%) followed by 9–15 years (14%), and the other age group accounted for only 3% during the study period
Our study found a positive significant relationship between average monthly rainfall (5.498, p = 0.036) and average sunshine hours (3.8136, p = 0.048) with scarlet fever incidence, which was consistent with the findings of other studies [12,13,15]
Summary
It has been well known that scarlet fever is a seasonal infectious childhood illness caused by Group A Streptococcus bacteria (Group A beta haemolytic streptococci (GABHS)). Scarlet fever predominately occurs in school children aged between 2 and 10 years It spreads by the aerosol route (inhalation), but may be able to spread through skin contact or by fomites [1,2,3,4]. It is not normally considered as a food- or milk-borne illness, as an outbreak noted in China due to infected chicken meat [5,6]. The trend of scarlet fever outbreaks has been increasing among the school children in mainland China and other countries, as well [7,8,9,10]. It is still regarded as an important public health problem in China [11]
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