Detecting spatial-temporal cluster of hand foot and mouth disease in Beijing, China, 2009-2014

Spatiotemporally comparative analysis of three common infectious diseases in China during 2013-2015

BACKGROUND

Dengue fever (DF), influenza, and hand, foot, and mouth disease (HFMD) have had several various degrees of outbreaks in China since the 1900s, posing a serious threat to public health. Previous studies have found that these infectious diseases were often prevalent in the same areas and during the same periods in China.

METHODS

This study combined traditional descriptive statistics and spatial scan statistic methods to analyze the spatiotemporal features of the epidemics of DF, influenza, and HFMD during 2013-2015 in mainland China at the provincial level.

RESULTS

DF got an intensive outbreak in 2014, while influenza and HFMD were stable from 2013 to 2015. DF mostly occurred during August-November, influenza appeared during November-next March, and HFMD happened during April-November. The peaks of these diseases form a year-round sequence; Spatially, HFMD generally has a much higher incidence than influenza and DF and covers larger high-risk areas. The hotspots of influenza tend to move from North China to the southeast coast. The southeastern coastal regions are the high-incidence areas and the most significant hotspots of all three diseases.

CONCLUSIONS

This study suggested that the three diseases can form a year-round sequence in southern China, and the southeast coast of China is a particularly high-risk area for these diseases. These findings may have important implications for the local public health agency to allocate the prevention and control resources.

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.

Spatiotemporal analysis of hand, foot and mouth disease data using time-lag geographically-weighted regression

Hand, Foot, and Mouth Disease (HFMD) is a common and widespread infectious disease. Previous studies have presented evidence that climate factors, including the monthly averages of temperature, relative humidity, air pressure, wind speed and Cumulative Risk (CR) all have a strong influence on the transmission of HFMD. In this paper, the monthly time-lag geographically- weighted regression model was constructed to investigate the spatiotemporal variations of effect of climate factors on HFMD occurrence in Inner Mongolia Autonomous Region, China. From the spatial and temporal perspectives, the spatial and temporal variations of effect of climate factors on HFMD incidence are described respectively. The results indicate that the effect of climate factors on HFMD incidence shows very different spatial patterns and time trends. The findings may provide not only an indepth understanding of spatiotemporal variation patterns of the effect of climate factors on HFMD occurrence, but also provide helpful evidence for making measures of HFMD prevention and control and implementing appropriate public health interventions at the county level in different seasons.

Transmission dynamics of brucellosis: Mathematical modelling and applications in China

Brucellosis, the most common zoonotic disease worldwide, represents a great threat to animal husbandry with the potential to cause enormous economic losses. Meanwhile, brucellosis is one of the major public-health problems in China, and the number of human brucellosis cases has increased dramatically in recent years. In order to show the main features of brucellosis transmission in China, we give a systematic review on the transmission dynamics of brucellosis including a series of mathematical models and their applications in China. For different situations, dynamical models of brucellosis transmission in single population and multiple populations are devised based on ordinary differential equations. Furthermore, we revealed the spatial-temporal characteristics and effective control measures of brucellosis transmission. The results may provide new perspectives for the prevention and control of other types of zoonoses.

Spatiotemporal analyses of foot and mouth disease outbreaks in cattle farms in Chiang Mai and Lamphun, Thailand

Background

Foot and mouth disease (FMD) is a highly infectious and contagious febrile vesicular disease of cloven-hoofed livestock with high socio-economic consequences globally. In Thailand, FMD is endemic with 183 and 262 outbreaks occurring in the years 2015 and 2016, respectively. In this study, we aimed to assess the spatiotemporal distribution of FMD outbreaks among cattle in Chiang Mai and Lamphun provinces in the northern part of Thailand during the period of 2015–2016. A retrospective space-time scan statistic including a space-time permutation (STP) and the Poisson and Bernoulli models were applied in order to detect areas of high incidence of FMD.

Results

Results have shown that 9 and 8 clusters were identified by the STP model in 2015 and 2016, respectively, whereas 1 and 3 clusters were identified by the Poisson model, and 3 and 4 clusters were detected when the Bernoulli model was applied for the same time period. In 2015, the most likely clusters were observed in Chiang Mai and these had a minimum radius of 1.49 km and a maximum radius of 20 km. Outbreaks were clustered in the period between the months of May and October of 2015. The most likely clusters in 2016 were observed in central Lamphun based on the STP model and in the eastern area of Chiang Mai by the Poisson and Bernoulli models. The cluster size of the STP model (8.51 km) was smaller than those of the Poisson and Bernoulli models (> 20 km). The cluster periods in 2016 were approximately 7 months, while 4 months and 1 month were identified by the Poisson, Bernoulli and STP models respectively.

Conclusions

The application of three models provided more information for FMD outbreak epidemiology. The findings from this study suggest the use of three different space-time scan models for the investigation process of outbreaks along with the follow-up process to identify FMD outbreak clusters. Therefore, active prevention and control strategies should be implemented in the areas that are most susceptible to FMD outbreaks.

Epidemiological and aetiological characteristics of hand, foot, and mouth disease in Sichuan Province, China, 2011-2017

Hand, foot, and mouth disease (HFMD) remains a threat to the Asia-Pacific region. The epidemiological characteristics and pathogen spectrum of HFMD vary with space and time. These variations are crucial for HFMD interventions but poorly understood in Sichuan Province, China, particularly after the introduction of the EV-A71 vaccine. Using descriptive methods, regression analyses, spatial autocorrelation analysis, and space-time scan statistics, we analysed the epidemiological and aetiological characteristics of HFMD surveillance data in Sichuan Province between 2011 and 2017 to identify spatio-temporal variations. The dominant serotypes of HFMD have changed from enterovirus 71 and coxsackievirus A16 to other enteroviruses since 2013. The seasonal pattern of HFMD showed two peaks generally occurring from April to July and November to December; however, the seasonal pattern varied by prefecture and enterovirus serotype. From 2011 to 2017, spatio-temporal clusters were increasingly concentrated in Chengdu, with several small clusters in northeast Sichuan. The clusters observed in southern Sichuan from 2011 to 2015 disappeared in 2016–2017. These findings highlight the importance of pathogen surveillance and vaccination strategies for HFMD interventions; future prevention and control of HFMD should focus on Chengdu and its vicinity.

Transmission center and driving factors of hand, foot, and mouth disease in China: A combined analysis

Hand, foot, and mouth disease (HFMD) has become a major public health issue in China. The disease incidence varies substantially over time and across space. To understand the heterogeneity of HFMD transmission, we compare the spatiotemporal dynamics of HFMD in Qinghai and Shanghai by conducting combined analysis of epidemiological, wavelet time series, and mathematical methods to county-level data from 2009 to 2016. We observe hierarchical epidemic waves in Qinghai, emanating from Huangzhong and in Shanghai from Fengxian. Besides population, we also find that the traveling waves are significantly associated with socio-economic and geographical factors. The population mobility also varies between the two regions: long-distance movement in Qinghai and between-neighbor commuting in Shanghai. Our findings provide important evidence for characterizing the heterogeneity of HFMD transmission and for the design and implementation of interventions, such as deploying optimal vaccine and changing local driving factors in the transmission center, to prevent or limit disease spread in these areas.

Epidemiological study on hand, foot and mouth disease in Tongzhou District, Beijing, 2013-2017

Objective

To study the epidemiological characteristics of hand, foot and mouth disease (HFMD) in Tongzhou District, Beijing between 2013 and 2017.

Methods

Data on HFMD infections from 1 January 2013 to 31 December 2017 were collected from the Notifiable Infectious Diseases Reporting Information System and analysed. Serotyping of enteroviruses from samples from patients with HFMD was undertaken using reverse transcription–polymerase chain reaction.

Results

A total of 15 341 patients with HFMD were reported and 32 patients (0.2%) were classified as having severe HFMD. The annual mean incidence rate of HFMD was 219.3/100 000 of the general population. The incidence and case-severity rates of HFMD generally decreased between 2013 and 2017. In the floating migrant population, the incidence and cases-severity rates of HFMD were significantly higher than in the local population. The peak incidence and severity-case rates were at 2 years of age and > 90% of patients were ≤5 years. Enterovirus A71 and Coxsackievirus A16 were the predominant pathogens in 2013–2017.

Conclusions

During the 5-year period 2013–2017, the incidence rate and case-severity rate of HFMD generally decreased in Tongzhou District, Beijing. The floating migrant population and children ≤5 years of age were at the highest risk of HFMD.

Predicting the outbreak of hand, foot, and mouth disease in Nanjing, China: a time-series model based on weather variability

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China and an accurate prediction of epidemic can improve the effectiveness of HFMD control. This study aims to develop a weather-based forecasting model for HFMD using the information on climatic variables and HFMD surveillance in Nanjing, China. Daily data on HFMD cases and meteorological variables between 2010 and 2015 were acquired from the Nanjing Center for Disease Control and Prevention, and China Meteorological Data Sharing Service System, respectively. A multivariate seasonal autoregressive integrated moving average (SARIMA) model was developed and validated by dividing HFMD infection data into two datasets: the data from 2010 to 2013 were used to construct a model and those from 2014 to 2015 were used to validate it. Moreover, we used weekly prediction for the data between 1 January 2014 and 31 December 2015 and leave-1-week-out prediction was used to validate the performance of model prediction. SARIMA (2,0,0)₅₂ associated with the average temperature at lag of 1 week appeared to be the best model (R ² = 0.936, BIC = 8.465), which also showed non-significant autocorrelations in the residuals of the model. In the validation of the constructed model, the predicted values matched the observed values reasonably well between 2014 and 2015. There was a high agreement rate between the predicted values and the observed values (sensitivity 80%, specificity 96.63%). This study suggests that the SARIMA model with average temperature could be used as an important tool for early detection and prediction of HFMD outbreaks in Nanjing, China.

Using the Kulldorff's scan statistical analysis to detect spatio-temporal clusters of tuberculosis in Qinghai Province, China, 2009-2016

BACKGROUND

Although the incidence of tuberculosis (TB) in most parts of China are well under control now, in less developed areas such as Qinghai, TB still remains a major public health problem. This study aims to reveal the spatio-temporal patterns of TB in the Qinghai province, which could be helpful in the planning and implementing key preventative measures.

METHODS

We extracted data of reported TB cases in the Qinghai province from the China Information System for Disease Control and Prevention (CISDCP) during January 2009 to December 2016. The Kulldorff's retrospective space-time scan statistics, calculated by using the discrete Poisson probability model, was used to identify the temporal, spatial, and spatio-temporal clusters of TB at the county level in Qinghai.

RESULTS

A total of 48,274 TB cases were reported from 2009 to 2016 in Qinghai. Results of the Kulldorff's scan revealed that the TB cases in Qinghai were significantly clustered in spatial, temporal, and spatio-temporal distribution. The most likely spatio-temporal cluster (LLR = 2547.64, RR = 4.21, P < 0.001) was mainly concentrated in the southwest of Qinghai, covering seven counties and clustered in the time frame from September 2014 to December 2016.

CONCLUSION

This study identified eight significant space-time clusters of TB in Qinghai from 2009 to 2016, which could be helpful in prioritizing resource assignment in high-risk areas for TB control and elimination in the future.