Leptospirosis is a water-borne and widespread spirochetal zoonosis caused by pathogenic bacteria called leptospires. Human leptospirosis is an important zoonotic infectious disease with frequent outbreaks in recent years in China. Leptospirosis’s emergence has been linked to many environmental and ecological drivers of disease transmission. In this paper, we identified the environmental and socioeconomic factors associated with leptospirosis in China, and predict potential risk area of leptospirosis using predictive models. Leptospirosis incidence data were derived from the database of China’s web-based infectious disease reporting system, a national surveillance network maintained by Chinese Center for Disease Control and Prevention. We built statistical relationship between occurrence of leptospirosis and nine environmental and socioeconomic risk factors using logistic regression model and Maxent model. Both logistic regression model and Maxent model have high performance in predicting the occurrence of leptospirosis, with AUC value of 0.95 and 0.96, respectively. Annual mean temperature (Bio1) and annual total precipitation (Bio12) are two most important variables governing the geographic distribution of leptospirosis in China. The geographic distributions of areas at risk of leptospirosis predicted from both models show high agreement. The risk areas are located mainly in seven provinces of China: Sichuan Province, Chongqing Municipality, Hunan Province, Jiangxi Province, Guangdong Province, Guangxi Province, and Hainan Province, where surveillance and control programs are urgently needed. Logistic regression model and Maxent model predicted that 403 and 464 counties are at very high risk of leptospirosis, respectively. Our results highlight the importance of socioeconomic and environmental variables and predictive models in identifying risk areas for leptospirosis in China. The values of Geographic Information System and predictive models were demonstrated for investigating the geographic distribution, estimating socioeconomic and environmental risk factors, and enhancing our understanding of leptospirosis in China.

H7N9 human cases were first detected in mainland China in March 2013. Circulation of this virus has continued each year shifting to typical winter months. We compared the clinical and epidemiologic characteristics for the first three waves of virus circulation. The first wave was defined as reported cases with onset dates between March 31-September 30, 2013, the second wave was defined as October 1, 2013-September 30, 2014 and the third wave was defined as October 1, 2014-September 30, 2015. We used simple descriptive statistics to compare characteristics of the three distinct waves of virus circulation. In mainland China, 134 cases, 306 cases and 219 cases were detected and reported in first three waves, respectively. The median age of cases was statistically significantly older in the first wave (61 years vs. 56 years, 56 years, p < 0.001) compared to the following two waves. Most reported cases were among men in all three waves. There was no statistically significant difference between case fatality proportions (33, 42 and 45%, respectively, p = 0.08). There were no significant statistical differences for time from illness onset to first seeking healthcare, hospitalization, lab confirmation, initiation antiviral treatment and death between the three waves. A similar percentage of cases in all waves reported exposure to poultry or live poultry markets (87%, 88%, 90%, respectively). There was no statistically significant difference in the occurrence of severe disease between the each of the first three waves of virus circulation. Twenty-one clusters were reported during these three waves (4, 11 and 6 clusters, respectively), of which, 14 were considered to be possible human-to-human transmission. Though our case investigation for the first three waves found few differences between the epidemiologic and clinical characteristics, there is continued international concern about the pandemic potential of this virus. Since the virus continues to circulate, causes more severe disease, has the ability to mutate and become transmissible from human-to-human, and there is limited natural protection from infection in communities, it is critical that surveillance systems in China and elsewhere are alert to the influenza H7N9 virus.

Qinghai-Tibetan Plateau of China is known to be the plague endemic region where marmot (Marmota himalayana) is the primary host. Human plague cases are relatively low incidence but high mortality, which presents unique surveillance and public health challenges, because early detection through surveillance may not always be feasible and infrequent clinical cases may be misdiagnosed.

Background: Earthquakes causing significant damage have occurred frequently in China, producing enormous health losses, damage to the environment and public health issues. Timely public health response is crucial to reduce mortality and morbidity and promote overall effectiveness of rescue efforts after a major earthquake. Methods: A rapid assessment framework was established based on GIS technology and high-resolution remote sensing images. A two-step casualties and injures estimation method was developed to evaluate health loss with great rapidity. Historical data and health resources information was reviewed to evaluate the damage condition of medical resources and public health issues. Results: The casualties and injures are estimated within a few hours after an earthquake. For the Wenchuan earthquake, which killed about 96,000 people and injured about 288,000, the estimation accuracy is about 77%. 242/294 (82.3%) of the medical existing institutions were severely damaged. About 40,000 tons of safe drinking water was needed every day to ensure basic living needs. The risk of water-borne and foodborne disease, respiratory and close contact transmission disease is high. For natural foci diseases, the high-risk area of schistosomiasis was mapped in Lushan County as an example. Finally, temporary settlements for victims of earthquake were mapped. Conclusions: High resolution Earth observation technology can provide a scientific basis for public health emergency management in the major disasters field, which will be of great significance in helping policy makers effectively improve health service ability and public health emergency management in prevention and control of infectious diseases and risk assessment.