Appraisal of the present and future impact of climate change and climate variability on the transmission of infectious diseases is a complex but pressing public health issue. We developed a biology-driven model to assess the potential impact of rising temperature on the transmission of schistosomiasis in China. We found a temperature threshold of 15.4 degrees C for development of Schistosoma japonicum within the intermediate host snail (i.e., Oncomelania hupensis), and a temperature of 5.8 degrees C at which half the snail sample investigated was in hibernation. Historical data suggest that the occurrence of O. hupensis is restricted to areas where the mean January temperature is above 0 degrees C. The combination of these temperature thresholds, together with our own predicted temperature increases in China of 0.9 degrees C in 2030 and 1.6 degrees C in 2050 facilitated predictive risk mapping. We forecast an expansion of schistosomiasis transmission into currently non-endemic areas in the north, with an additional risk area of 783,883 km(2) by 2050, translating to 8.1% of the surface area of China. Our results call for rigorous monitoring and surveillance of schistosomiasis in a future warmer China.

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BackgroundEosinophilic meningitis (angiostrongyliasis) caused by Angiostrongylus cantonensis is emerging in mainland China. However, the distribution of A. cantonensis and its intermediate host snails, and the role of two invasive snail species in the emergence of angiostrongyliasis, are not well understood.Methodology/Principal FindingsA national survey pertaining to A. cantonensis was carried out using a grid sampling approach (spatial resolution: 40×40 km). One village per grid cell was randomly selected from a 5% random sample of grid cells located in areas where the presence of the intermediate host snail Pomacea canaliculata had been predicted based on a degree-day model. Potential intermediate hosts of A. cantonensis were collected in the field, restaurants, markets and snail farms, and examined for infection. The infection prevalence among intermediate host snails was estimated, and the prevalence of A. cantonensis within P. canaliculata was displayed on a map, and predicted for non-sampled locations. It was confirmed that P. canaliculata and Achatina fulica were the predominant intermediate hosts of A. cantonensis in China, and these snails were found to be well established in 11 and six provinces, respectively. Infected snails of either species were found in seven provinces, closely matching the endemic area of A. cantonensis. Infected snails were also found in markets and restaurants. Two clusters of A. cantonensis–infected P. canaliculata were predicted in Fujian and Guangxi provinces.Conclusions/SignificanceThe first national survey in China revealed a wide distribution of A. cantonensis and two invasive snail species, indicating that a considerable number of people are at risk of angiostrongyliasis. Health education, rigorous food inspection and surveillance are all needed to prevent recurrent angiostrongyliasis outbreaks.

Hand, foot and mouth disease (HFMD) is an important public health issue in mainland China, including Jiangsu Province. The main purpose of this study was to depict the epidemiological characteristics of HFMD and evaluate the effects of meteorological variables on its dynamics via spatiotemporal analytic methods, which is essential for formulating scientific and effective prevention and control strategies and measures. In total, 497,910 cases of HFMD occurred in the 2009-2013 period, with an average annual incidence of 126.3 per 100,000 in Jiangsu. Out of these, 87.7% were under 5 years old with a male-to-female incidence ratio of 1.4. The dominant pathogens of the laboratory-confirmed cases were EV71 and CoxA16, accounting for 44.8% and 30.6% of all cases, respectively. Two incidence peaks were observed in each year, the higher occurring between April and June, the lower between November and December. The incidence ranged between 16.8 and 233.5 per 100,000 at the county level. The incidence in the South of the province was generally higher than that in the northern regions. The most likely spatiotemporal cluster detected by space–time scan analysis occurred in May-June of 2012 in the southern region. Average temperature and rainfall were positively correlated with HFMD incidence, while the number of days with rainfall ≥ 0.1mm, low temperature, high temperature and hours of sunshine were negatively related. Particularly, relative humidity had no relationship. In conclusion, the prevalence of HFMD in Jiangsu Province has an obvious feature of seasonality. The etiological composition changed dynamically and might be a latent driving force for the temporal variation of the incidence of HFMD. A moderately warm environment promotes the transmission of the HFMD viruses, while particularly cold and hot climate conditions restrain their transmission.

BackgroundWater plays an important role in the transmission of many infectious diseases, which pose a great burden on global public health. However, the global distribution of these water-associated infectious diseases and underlying factors remain largely unexplored.Methods and FindingsBased on the Global Infectious Disease and Epidemiology Network (GIDEON), a global database including water-associated pathogens and diseases was developed. In this study, reported outbreak events associated with corresponding water-associated infectious diseases from 1991 to 2008 were extracted from the database. The location of each reported outbreak event was identified and geocoded into a GIS database. Also collected in the GIS database included geo-referenced socio-environmental information including population density (2000), annual accumulated temperature, surface water area, and average annual precipitation. Poisson models with Bayesian inference were developed to explore the association between these socio-environmental factors and distribution of the reported outbreak events. Based on model predictions a global relative risk map was generated. A total of 1,428 reported outbreak events were retrieved from the database. The analysis suggested that outbreaks of water-associated diseases are significantly correlated with socio-environmental factors. Population density is a significant risk factor for all categories of reported outbreaks of water-associated diseases; water-related diseases (e.g., vector-borne diseases) are associated with accumulated temperature; water-washed diseases (e.g., conjunctivitis) are inversely related to surface water area; both water-borne and water-related diseases are inversely related to average annual rainfall. Based on the model predictions, “hotspots” of risks for all categories of water-associated diseases were explored.ConclusionsAt the global scale, water-associated infectious diseases are significantly correlated with socio-environmental factors, impacting all regions which are affected disproportionately by different categories of water-associated infectious diseases.

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AB STRACT: Nursing stud ies have shown that nurs ing care deliv ery changes affect staff and orga ni za tional out comes, but the effects on cli ent out comes have not been stud ied suf fi ciently. The pur pose of this study was thus to exam ine the effect of nurse staff ing vari ables-daily aver age hours of care, ratio of RNs to aver age patient cen sus, work load, and skill mix-on patient out comes as mea sured by five adverse occur rences. The adverse patient occur rences included unit rates of patient falls, pres s ure ulcers, respi ra tory and uri nary tract infec tions, and patient/fam ily com plaints. Vari ables were mea sured ret ro spec tively using con sis tently avail able data from each month of fis cal year 2000 from 21 med i cal-surgical nurs ing care units in a 1394-bed med i cal cen ter in Tai wan. Data were ana lyzed by descrip tive and multivariate infer en tial sta tis tics while con trol ling for patient acu ity level. Results showed that work load of nurses is the most pow er ful pre dic tor of nosocomial infec tions and hours of care best pre dicted the five adverse patient out come indi ces. Lower adverse out come rates were more con sis tently related to a higher pro por tion of N3 level of RNs. Patients could fare better when N3s play a sig nif i cant role in the staff ing mix. The find ings pro vide fur ther empir i cal sup port for the con text of impli ca tions that patient out comes are cor re lated to orga ni za tional struc ture. It obviously illus trates the rela tion ships between nurse staff ing and the qual ity of nurs ing prac tice.

Summary 1. Only few freshwater snail species transmit the rat lungworm Angiostrongylus cantonensis, which is partially explained by the low likelihood of contact between snails and infected rat faeces. The snail Pomacea canaliculata was introduced into China in 1981 and has become the key intermediate host for A. cantonensis. Thus far, the snail has been recorded in 13 provinces of southern China. 2. We developed a biological model and assessed potential impacts of climate change on the distribution of P. canaliculata and hence the transmission of A. cantonensis. Mean January temperature and snail generation intensity (generation number) were identified as the key factors determining P. canaliculata distribution. Our models predict an increase of 56.9% for the ‘spread’ and a decrease of 40.9% for the ‘establishment’ regions (‘spread’ and ‘establishment’ defined according to a national sampling survey) by the 2030s relative to the present day. 3. Key determinants of A. cantonensis transmission were identified as the generation intensity in the intermediate host, the longevity of A. cantonensis‐infected rats and the dormant period of P. canaliculata. Transmission of A. cantonensis occurs only in areas where the snail’s dormant period is <173.2 days. The potential endemic area of A. cantonensis is predicted to double by the 2030s relative to the present day. 4. The tight fit of our model predictions with data derived from a national sampling survey suggests that biological models hold promise for assessing potential impacts of climate change on infectious diseases once key determinants have been established. Geographical variation analysis may offer an approach to identify areas prone to the spread of vectors, intermediate hosts and parasites in a future warmer China and elsewhere.