Mumps vaccines have been widely used in recent years, but frequent mumps outbreaks and re-emergence around the world have not stopped. Mumps still remains a serious public health problem with a high incidence in China. The status of mumps epidemics in Chongqing, the largest city in China, is still unclear. This study aimed to investigate the epidemiological and spatiotemporal characteristics of mumps and to provide a scientific basis for formulating effective strategies for its prevention and control. Surveillance data of mumps in Chongqing from January 2004 to December 2018 were collected from the National Notifiable Diseases Reporting Information System. A descriptive analysis was conducted to understand the epidemiological characteristics. Hot spots and spatiotemporal patterns were identified by performing a spatial autocorrelation analysis, a purely spatial scan, and a spatiotemporal scan at the county level based on geographic information systems. A total of 895,429 mumps cases were reported in Chongqing, with an annual average incidence of 36.34 per 100,000. The yearly incidence of mumps decreased markedly from 2004 to 2007, increased sharply from 2007 to 2011, and then tapered with a two-year cyclical peak after 2011. The onset of mumps showed an obvious bimodal seasonal distribution, with a higher peak of mumps observed from April to July of each year. Children aged 5–9 years old, males, and students were the prime high-risk groups. The spatial distribution of mumps did not exhibit significant global autocorrelation in most years, but local indicators of spatial autocorrelation and scan statistics detected high-incidence clusters which were mainly located in the midwestern, western, northeastern, and southwestern parts of Chongqing. The aggregation time frame detected by the purely temporal scan was between March 2009 and July 2013. The incidence of mumps in Chongqing from 2004 to 2018 featured significant spatial heterogeneity and spatiotemporal clustering. The findings of this study might assist public health agencies to develop real-time space monitoring, especially in the clustering regions and at peak periods; to improve immunization strategies for long-term prevention; and to deploy health resources reasonably.

Acute haemorrhagic conjunctivitis is a highly contagious eye disease, the prediction of acute haemorrhagic conjunctivitis is very important to prevent and grasp its development trend. We use the exponential smoothing model and the seasonal autoregressive integrated moving average (SARIMA) model to analyse and predict. The monthly incidence data from 2004 to 2017 were used to fit two models, the actual incidence of acute haemorrhagic conjunctivitis in 2018 was used to validate the model. Finally, the prediction effect of exponential smoothing is best, the mean square error and the mean absolute percentage error were 0.0152 and 0.1871, respectively. In addition, the incidence of acute haemorrhagic conjunctivitis in Chongqing had a seasonal trend characteristic, with the peak period from June to September each year.

Chongqing is one of the five provinces in China that has the highest incidence of acute hemorrhagic conjunctivitis (AHC). Data of AHC cases from 2004 to 2018 were obtained from National Notifiable Diseases Reporting Information System (NNDRIS). Descriptive statistical methods were used to analyze the epidemiological characteristics; incidence maps were used to reflect incidence trends in each district; spatial autocorrelation was used to identify hotspot regions and spatiotemporal patterns of AHC outbreaks; spatiotemporal scan were conducted to identify AHC clusters. A total of 30,686 cases were reported with an annual incidence of 7.04 per 100,000. The incidence rates were high in 2007 and 2014, and large epidemics were observed in 2010 with the seasonal peak in September. Individuals aged 10-19 years, males, students and farmers were the prime high-risk groups. Except for 2012 and 2013, the spatial distribution of AHC did not exhibit significant global spatial autocorrelation. Local indicators of spatial association showed that the high-risk regions are Chengkou and Wuxi. The spatiotemporal scan indicated that all clusters occurred in September 2010, and the high-incidence clusters were mainly distributed in the northeast of Chongqing. The results could assist public health agencies to consider effective preventive measures based on epidemiological factors and spatiotemporal clusters in different regions. Acute hemorrhagic conjunctivitis (AHC) is a highly infectious viral disease caused by enterovirus 70 (EV70), coxsackievirus A24 variant (CA24v), or adenoviruses 1,2. It is characterized by rapid onset of symptoms, quick dissemination and short incubation period 3. The main manifestations of AHC are bilateral eye pain, eyelid swelling, conjunctival congestion, keratitis, foreign body sensation and increased ocular secretions 4. Generally, the majority of patients exhibit obvious symptoms but good prognosis. A small number of patients will rapidly develop systemic symptoms such as fever, fatigue and limb pain. A few patients develop serious complications and fatal infections 5. Since it was first reported in Ghana in 1969 6 , AHC has seen several periodic outbreaks around the world 7 , mainly in Asia, Africa and Latin America 4. The first outbreak of AHC in China was reported in Hong Kong in 1971 8. At present, it has spread to all provinces and cities, including some remote areas 9. From 2005 to 2012, the reported incidence of AHC in China was 4.12 per 100,000, and Guangxi, Guangdong, Chongqing, Sichuan and Hubei were ranked as the top 5 incidence provinces 10. Currently, AHC is still an important public health problem in China 11 , which is worth exploring and studying. Most of the previous studies on AHC focused on the epidemiological and etiological characteristics 12. However, the research on the spatial and temporal characteristics of AHC was still scarce. The geographical information system (GIS) has been widely used to analyze the spatiotemporal characteristics of diseases, helping to monitor and prevent...