Establishment and evaluation of a theater influenza monitoring platform.

BACKGROUND: Influenza is an acute respiratory infectious disease with a high incidence rate in the Chinese army, which directly disturbs military training and affects soldiers' health. Influenza surveillance systems are widely used around the world and play an important role in influenza epidemic prevention and control. METHODS: As a theater centers for disease prevention and control, we established an influenza monitoring platform (IMP) in 2014 to strengthen the monitoring of influenza-like illness and influenza virus infection. In this study, we introduced the constitution, influenza virus detection, and quality control for an IMP. The monitoring effect was also evaluated by comparing the monitoring data with data from national influenza surveillance systems. The experiences and problems associated with the platform also were summarized. RESULTS: A theater IMP was established based on 3 levels of medical units, including monitoring sites, testing laboratories and a checking laboratory. A series of measures were taken to guarantee the quality of monitoring, such as technical training, a unified process, sufficient supervision and timely communication. The platform has run smoothly for 3 monitoring years to date. In the 2014-2015 and 2016-2017 monitoring years, sample amount coincided with that obtained from the National Influenza Surveillance program. In the 2015-2016 monitoring year, due to the strict prevention and control measures, an influenza epidemic peak was avoided in monitoring units, and the monitoring data did not coincide with that of the National Influenza Surveillance program. Several problems, including insufficient attention, unreasonable administrative intervention or subordination relationships, and the necessity of detection in monitoring sites were still observed. CONCLUSIONS: A theater IMP was established rationally and played a deserved role in the prevention and control of influenza. However, several problems remain to be solved.

Time-specific ecologic niche models forecast the risk of hemorrhagic fever with renal syndrome in Dongting Lake district, China, 2005-2010.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne infectious disease, is one of the most serious public health threats in China. Increasing our understanding of the spatial and temporal patterns of HFRS infections could guide local prevention and control strategies. METHODOLOGY/PRINCIPAL FINDINGS: We employed statistical models to analyze HFRS case data together with environmental data from the Dongting Lake district during 2005-2010. Specifically, time-specific ecologic niche models (ENMs) were used to quantify and identify risk factors associated with HFRS transmission as well as forecast seasonal variation in risk across geographic areas. Results showed that the Maximum Entropy model provided the best predictive ability (AUC = 0.755). Time-specific Maximum Entropy models showed that the potential risk areas of HFRS significantly varied across seasons. High-risk areas were mainly found in the southeastern and southwestern areas of the Dongting Lake district. Our findings based on models focused on the spring and winter seasons showed particularly good performance. The potential risk areas were smaller in March, May and August compared with those identified for June, July and October to December. Both normalized difference vegetation index (NDVI) and land use types were found to be the dominant risk factors. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that time-specific ENMs provide a useful tool to forecast the spatial and temporal risk of HFRS.

Animal reservoir, natural and socioeconomic variations and the transmission of hemorrhagic fever with renal syndrome in Chenzhou, China, 2006-2010.

BACKGROUND: China has the highest incidence of hemorrhagic fever with renal syndrome (HFRS) worldwide. Reported cases account for 90% of the total number of global cases. By 2010, approximately 1.4 million HFRS cases had been reported in China. This study aimed to explore the effect of the rodent reservoir, and natural and socioeconomic variables, on the transmission pattern of HFRS. METHODOLOGY/PRINCIPAL FINDINGS: Data on monthly HFRS cases were collected from 2006 to 2010. Dynamic rodent monitoring data, normalized difference vegetation index (NDVI) data, climate data, and socioeconomic data were also obtained. Principal component analysis was performed, and the time-lag relationships between the extracted principal components and HFRS cases were analyzed. Polynomial distributed lag (PDL) models were used to fit and forecast HFRS transmission. Four principal components were extracted. Component 1 (F1) represented rodent density, the NDVI, and monthly average temperature. Component 2 (F2) represented monthly average rainfall and monthly average relative humidity. Component 3 (F3) represented rodent density and monthly average relative humidity. The last component (F4) represented gross domestic product and the urbanization rate. F2, F3, and F4 were significantly correlated, with the monthly HFRS incidence with lags of 4 months (r = -0.289, P<0.05), 5 months (r = -0.523, P<0.001), and 0 months (r = -0.376, P<0.01), respectively. F1 was correlated with the monthly HFRS incidence, with a lag of 4 months (r = 0.179, P = 0.192). Multivariate PDL modeling revealed that the four principal components were significantly associated with the transmission of HFRS. CONCLUSIONS: The monthly trend in HFRS cases was significantly associated with the local rodent reservoir, climatic factors, the NDVI, and socioeconomic conditions present during the previous months. The findings of this study may facilitate the development of early warning systems for the control and prevention of HFRS and similar diseases.