Urbanisation and health in China.

China has seen the largest human migration in history, and the country's rapid urbanisation has important consequences for public health. A provincial analysis of its urbanisation trends shows shifting and accelerating rural-to-urban migration across the country and accompanying rapid increases in city size and population. The growing disease burden in urban areas attributable to nutrition and lifestyle choices is a major public health challenge, as are troubling disparities in health-care access, vaccination coverage, and accidents and injuries in China's rural-to-urban migrant population. Urban environmental quality, including air and water pollution, contributes to disease both in urban and in rural areas, and traffic-related accidents pose a major public health threat as the country becomes increasingly motorised. To address the health challenges and maximise the benefits that accompany this rapid urbanisation, innovative health policies focused on the needs of migrants and research that could close knowledge gaps on urban population exposures are needed

Stirred, not shaken: genetic structure of the intermediate snail host Oncomelania hupensis robertsoni in an historically endemic schistosomiasis area

<p>Abstract</p> <p>Background</p> <p><it>Oncomelania hupensis robertsoni </it>is the sole intermediate host for <it>Schistosoma japonicum </it>in western China. Given the close co-evolutionary relationships between snail host and parasite, there is interest in understanding the distribution of distinct snail phylogroups as well as regional population structures. Therefore, this study focuses on these aspects in a re-emergent schistosomiasis area known to harbour representatives of two phylogroups - the Deyang-Mianyang area in Sichuan Province, China. Based on a combination of mitochondrial and nuclear DNA, the following questions were addressed: 1) the phylogeography of the two <it>O. h. robertsoni </it>phylogroups, 2) regional and local population structure in space and time, and 3) patterns of local dispersal under different isolation-by-distance scenarios.</p> <p>Results</p> <p>The phylogenetic analyses confirmed the existence of two distinct phylogroups within <it>O. h. robertsoni</it>. In the study area, phylogroups appear to be separated by a mountain range. Local specimens belonging to the respective phylogroups form monophyletic clades, indicating a high degree of lineage endemicity. Molecular clock estimations reveal that local lineages are at least 0.69-1.58 million years (My) old and phylogeographical analyses demonstrate that local, watershed and regional effects contribute to population structure. For example, Analyses of Molecular Variances (AMOVAs) show that medium-scale watersheds are well reflected in population structures and Mantel tests indicate isolation-by-distance effects along waterways.</p> <p>Conclusions</p> <p>The analyses revealed a deep, complex and hierarchical structure in <it>O. h. robertsoni</it>, likely reflecting a long and diverse evolutionary history. The findings have implications for understanding disease transmission. From a co-evolutionary standpoint, the divergence of the two phylogroups raises species level questions in <it>O. h. robertsoni </it>and also argues for future studies relative to the distinctness of the respective parasites. The endemicity of snail lineages at the regional level supports the concept of endemic schistosomiasis areas and calls for future geospatial analyses for a better understanding of respective boundaries. Finally, local snail dispersal mainly occurs along waterways and can be best described by using cost distance, thus potentially enabling a more precise modelling of snail, and therefore, parasite dispersal.</p

Disinfection of Ebola Virus in Sterilized Municipal Wastewater

Concerns have been raised regarding handling of Ebola virus contaminated wastewater, as well as the adequacy of proposed disinfection approaches. In the current study, we investigate the inactivation of Ebola virus in sterilized domestic wastewater utilizing sodium hypochlorite addition and pH adjustment. No viral inactivation was observed in the one-hour tests without sodium hypochlorite addition or pH adjustment. No virus was recovered after 20 seconds (i.e. 4.2 log10 unit inactivation to detection limit) following the addition of 5 and 10 mg L-1 sodium hypochlorite, which resulted in immediate free chlorine residuals of 0.52 and 1.11 mg L-1, respectively. The addition of 1 mg L-1 sodium hypochlorite resulted in an immediate free chlorine residual of 0.16 mg L-1, which inactivated 3.5 log10 units of Ebola virus in 20 seconds. Further inactivation was not evident due to the rapid consumption of the chlorine residual. Elevating the pH to 11.2 was found to significantly increase viral decay over ambient conditions. These results indicate the high susceptibility of the enveloped Ebola virus to disinfection in the presence of free chlorine in municipal wastewater; however, we caution that extension to more complex matrices (e.g. bodily fluids) will require additional verification

Reframing Optimal Control Problems for Infectious Disease Management in Low-Income Countries

Optimal control theory can be a useful tool to identify the best strategies for the management of infectious diseases. In most of the applications to disease control with ordinary differential equations, the objective functional to be optimized is formulated in monetary terms as the sum of intervention costs and the cost associated with the burden of disease. We present alternate formulations that express epidemiological outcomes via health metrics and reframe the problem to include features such as budget constraints and epidemiological targets. These alternate formulations are illustrated with a compartmental cholera model. The alternate formulations permit us to better explore the sensitivity of the optimal control solutions to changes in available budget or the desired epidemiological target. We also discuss some limitations of comprehensive cost assessment in epidemiology

Estimating the health effects of greenhouse gas mitigation strategies: addressing parametric, model, and valuation challenges.

BACKGROUND: Policy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Studies of such co-benefits and co-harms involve modeling approaches requiring a range of analytic decisions that affect the model output. OBJECTIVE: Our objective was to assess analytic decisions regarding model framework, structure, choice of parameters, and handling of uncertainty when modeling health co-benefits, and to make recommendations for improvements that could increase policy uptake. METHODS: We describe the assumptions and analytic decisions underlying models of mitigation co-benefits, examining their effects on modeling outputs, and consider tools for quantifying uncertainty. DISCUSSION: There is considerable variation in approaches to valuation metrics, discounting methods, uncertainty characterization and propagation, and assessment of low-probability/high-impact events. There is also variable inclusion of adverse impacts of mitigation policies, and limited extension of modeling domains to include implementation considerations. Going forward, co-benefits modeling efforts should be carried out in collaboration with policy makers; these efforts should include the full range of positive and negative impacts and critical uncertainties, as well as a range of discount rates, and should explicitly characterize uncertainty. We make recommendations to improve the rigor and consistency of modeling of health co-benefits. CONCLUSION: Modeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. Increased attention to these and other analytic decisions has the potential to increase the policy relevance and application of co-benefits modeling studies, potentially helping policy makers to maximize mitigation potential while simultaneously improving health

Genetic Assignment Methods for Gaining Insight into the Management of Infectious Disease by Understanding Pathogen, Vector, and Host Movement

For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease

Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach

Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data

Toward Sustainable and Comprehensive Control of Schistosomiasis in China: Lessons from Sichuan

Triggered by a fascinating publication in the New England Journal of Medicine detailing China's new multi-pronged strategy to control and eventually interrupt the transmission of Schistosoma japonicum, this PLoS Neglected Tropical Diseases Debate critically examines the generalizability and financial costs of the studies presented from the marshlands of the lake region. Edmund Seto from the University of California and colleagues emphasize that the epidemiology and control of schistosomiasis varies according to the social-ecological context. They conjecture that the successful intervention packages piloted in the lake region is not fully fit for the hilly and mountainous environments in Sichuan and Yunnan provinces, and hence call for more flexible, setting-specific, and less expensive control strategies. In response, Xiao-Nong Zhou from the National Institute of Parasitic Diseases at the Chinese Center of Disease Control and Prevention and colleagues explain the steps from designing pilot studies to the articulation and implementation of a new national control strategy through a careful process of scaling-up and adaptations. Finally, the two opponents converge. The need for integrated, intersectoral, and setting-specific control measures is stressed, supported by rigorous surveillance and continuous research. Experiences and lessons from China are important for shaping the schistosomiasis elimination agenda

Leveraging Rural Energy Investment for Parasitic Disease Control: Schistosome Ova Inactivation and Energy Co-Benefits of Anaerobic Digesters in Rural China

Cooking and heating remain the most energy intensive activities among the world's poor, and thus improved access to clean energies for these tasks has been highlighted as a key requirement of attaining the major objectives of the UN Millennium Development Goals. A move towards clean energy technologies such as biogas systems (which produce methane from human and animal waste) has the potential to provide immediate benefits for the control of neglected tropical diseases. Here, an assessment of the parasitic disease and energy benefits of biogas systems in Sichuan Province, China, is presented, highlighting how the public health sector can leverage the proliferation of rural energy projects for infectious disease control. ova) counted at the influent of two biogas systems were removed in the systems when adjusted for system residence time, an approximate 1-log removal attributable to sedimentation. Combined, these inactivation/removal processes underscore the promise of biogas infrastructure for reducing parasite contamination resulting from nightsoil use. When interviewed an average of 4 years after construction, villagers attributed large changes in fuel usage to the installation of biogas systems. Household coal usage decreased by 68%, wood by 74%, and crop waste by 6%. With reported energy savings valued at roughly 600 CNY per year, 2–3 years were required to recoup the capital costs of biogas systems. In villages without subsidies, no new biogas systems were implemented.Sustainable strategies that integrate rural energy needs and sanitation offer tremendous promise for long-term control of parasitic diseases, while simultaneously reducing energy costs and improving quality of life. Government policies can enhance the financial viability of such strategies by introducing fiscal incentives for joint sanitation/sustainable energy projects, along with their associated public outreach and education programs

Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally