The benefits and logic of intersectoral collaboration have been reiterated at regular intervals and substantial experience has been gained in what works and what doesn't. One of the iterations was the joint WHO/FAO/UNEP/UNCHS Panel of Experts on Environmental Management for Vector Control. This chapter starts by summarising that experience. We learned that successful intersectoral collaboration depends on vested interests, external pressures, strong institutional arrangements and suitable instruments. Health impact assessment (HIA) has proved one of the most successful instruments and we describe its procedures and methods in some detail. Although HIA is completely general, it includes the management of vector-borne diseases (VBD). In countries where VBD are of major public health importance, they make up a large part of the fraction of the increased disease burden attributable to development projects. HIA assists planners and decision-makers in non-health sectors, such as water resource development, energy, transport, mining or agriculture, to anticipate the health impacts and opportunities of their plans and projects. A set of recommendations can then be formulated to protect and promote health. These recommendations can be arranged in a hierarchy and this includes healthy engineering design. We identify different types of intersectoral collaboration and suggest where intervention points lie during development project planning. Reference is made to the health and safety performance standards of the lending institutions, and national planning and environmental regulations. There is still a global lack of capacity to carry out HIA to an acceptable standard and we summarise some of the causes and consequences. We provide two recent examples of intersectoral collaboration. The first example is a recently completed programme of the Asian Development Bank that focused on malaria and other communicable disease threats. The second example concerns the procedures used by multinational corporations and often referred to as environmental, social and health impact assessment (ESHIA). We conclude with a brief summary of future directions.

BackgroundIn countries of high endemicity of the soil-transmitted helminth parasites Ascaris lumbricoides, Trichuris trichiura, and hookworm, preventive chemotherapy (i.e., repeated administration of anthelmintic drugs to at-risk populations) is the main strategy to control morbidity. However, rapid reinfection of humans occurs after successful deworming, and therefore effective preventive measures are required to achieve public health goals with optimal efficiency and sustainability.Methods and findingsWe conducted a systematic review and meta-analysis to assess the effect of sanitation (i.e., access and use of facilities for the safe disposal of human urine and feces) on infection with soil-transmitted helminths. PubMed, Embase, ISI Web of Science, and the World Health Organization Library Database were searched without language restrictions and year of publication (search performed until December 31, 2010). Bibliographies of identified articles were hand-searched. All types of studies reporting data on sanitation availability (i.e., having access at own household or living in close proximity to sanitation facility), or usage, and soil-transmitted helminth infections at the individual level were considered. Reported odds ratios (ORs) of the protective effect of sanitation on soil-transmitted helminth infections were extracted from the papers or calculated from reported numbers. The quality of published studies was assessed with a panel of criteria developed by the authors. Random effects meta-analyses were used to account for observed heterogeneity. Thirty-six publications, consisting of 39 datasets, met our inclusion criteria. Availability of sanitation facilities was associated with significant protection against infection with soil-transmitted helminths (OR = 0.46 to 0.58). Regarding the use of sanitation, ORs of 0.54 (95% confidence interval [CI] 0.28-1.02), 0.63 (95% CI 0.37-1.05), and 0.78 (95% CI 0.60-1.00) were determined for T. trichiura, hookworm, and A. lumbricoides, respectively. The overall ORs, combining sanitation availability and use, were 0.51 (95% CI 0.44-0.61) for the three soil-transmitted helminths combined, 0.54 (95% CI 0.43-0.69) for A. lumbricoides, 0.58 (95% CI 0.45-0.75) for T. trichiura, and 0.60 (95% CI 0.48-0.75) for hookworm.ConclusionsDespite a number of limitations (e.g., most studies used a cross-sectional design and were of low quality, with potential biases and considerable heterogeneity), our results reveal that sanitation is associated with a reduced risk of transmission of helminthiases to humans. Access to improved sanitation should be prioritized alongside preventive chemotherapy and health education to achieve a durable reduction of the burden of helminthiases.

Water is stored to facilitate access, and at all scales from huge reservoirs to small pots within the household. But there are health hazards as well as benefits from water storage; these are explored here within the frameworks of geometry, process and functional classification of risk. Hazards depend upon ease of access of people and other biota and pathogens to the water. Insect vectors of disease may breed in the water. Risk tends to decrease in larger water bodies. Methods to reduce the health hazards of large dams are well studied, even if often ignored, but those for small dams are less clear, requiring a choice appropriate to the locally relevant pathogens, and further research attention. Measures against specific diseases will depend on the preexisting levels of endemicity, and on how far alternative methods of treatment and prevention are available.

First principles models are commonly obtained using finite element or finite difference methods. One of the advantages of these models is that the states in the model have a clear physical interpretation. This makes of them perfect candidates for the monitoring of the states of the system. Unfortunately, the CPU time associated with each evaluation of these complex models is often far too large for these models to be used for online monitoring purposes. This paper introduces a general method to approximate a computationally expensive first principles model with a quasi-linear parameter varying (q-LPV) model. Besides approximating the original model accurately and conserving the physical interpretation of the states, the resulting q-LPV model has generally a much simpler structure than the original model. This in turn implies that the CPU time associated with each model evaluation is generally considerably reduced, allowing the use of these models for online monitoring. Unlike other q-LPV identification techniques, the proposed method extensively uses the availability of the original first principles model.

Functional magnetic resonance imaging (fMRI) data that are corrupted by temporally colored noise are generally preprocessed (i.e., prewhitened or precolored) prior to functional activation detection. In this paper, we propose likelihood-based hypothesis tests that account for colored noise directly within the framework of functional activation detection. Three likelihood-based tests are proposed: the generalized likelihood ratio (GLR) test, the Wald test, and the Rao test. The fMRI time series is modeled as a linear regression model, where one regressor describes the task-related hemodynamic response, one regressor accounts for a constant baseline and one regressor describes potential drift. The temporal correlation structure of the noise is modeled as an autoregressive (AR) model. The order of the AR model is determined from practical null data sets using Akaike's information criterion (with penalty factor 3) as order selection criterion. The tests proposed are based on exact expressions for the likelihood function of the data. Using Monte Carlo simulation experiments, the performance of the proposed tests is evaluated in terms of detection rate and false alarm rate properties and compared to the current general linear model (GLM) test, which estimates the coloring of the noise in a separate step. Results show that theoretical asymptotic distributions of the GLM, GLR, and Wald test statistics cannot be reliably used for computing thresholds for activation detection from finite length time series. Furthermore, it is shown that, for a fixed false alarm rate, the detection rate of the proposed GLR test statistic is slightly, but (statistically) significantly improved compared to that of the common GLM-based tests. Finally, simulations results reveal that all tests considered show seriously inferior performance if the order of the AR model is not chosen sufficiently high to give an adequate description of the correlation structure of the noise, whereas the effects of (slightly) overmodeling are observed to be less harmful.

A shallow, vertically shaken granular bed in a quasi-two-dimensional container is explored experimentally yielding a wider variety of phenomena than in any previous study: (1) bouncing bed, (2) undulations, (3) granular Leidenfrost effect, (4) convection rolls, and (5) granular gas. These phenomena and the transitions among them are characterized by dimensionless control parameters and combined in a full experimental phase diagram.

An estimated 779 million people are at risk of schistosomiasis, of whom 106 million (13.6%) live in irrigation schemes or in close proximity to large dam reservoirs. We identified 58 studies that examined the relation between water resources development projects and schistosomiasis, primarily in African settings. We present a systematic literature review and meta-analysis with the following objectives: (1) to update at-risk populations of schistosomiasis and number of people infected in endemic countries, and (2) to quantify the risk of water resources development and management on schistosomiasis. Using 35 datasets from 24 African studies, our meta-analysis showed pooled random risk ratios of 2(.)4 and 2(.)6 for urinary and intestinal schistosomiasis, respectively, among people living adjacent to dam reservoirs. The risk ratio estimate for studies evaluating the effect of irrigation on urinary schistosomiasis was in the range 0(.)02-7(.)3 (summary estimate 1(.)1) and that on intestinal schistosomiasis in the range 0(.)49-23(.)0 (summary estimate 4(.)7). Geographic stratification showed important spatial differences, idiosyncratic to the type of water resources development. We conclude that the development and management of water resources is an important risk factor for schistosomiasis, and hence strategies to mitigate negative effects should become integral parts in the planning, implementation, and operation of future water projects.

A shallow, vertically shaken granular bed in a quasi 2-D container is studied experimentally yielding a wider variety of phenomena than in any previous study: (1) bouncing bed, (2) undulations, (3) granular Leidenfrost effect, (4) convection rolls, and (5) granular gas. These phenomena and the transitions between them are characterized by dimensionless control parameters and combined in a full experimental phase diagram.

Maximum-likelihood estimation of the parameters of a continuous-time model for irregularly sampled data is very sensitive to initial conditions. Simulations may converge to a good solution if the true parameters are used as starting values for the nonlinear search of the minimum of the negative log likelihood. From realizable starting values, the convergence to a continuous-time model with an accurate spectrum is rare if more than three parameters have to be estimated. A discrete-time spectral estimator that applies a new algorithm for automatic equidistant missing-data analysis,to irregularly spaced data is introduced. This requires equidistant resampling of the data. A slotted nearest neighbor (NN) resampling method replaces a true irregular observation time instant by the nearest equidistant resampling time point if and only if the distance to the true time is within half the slot width. It will be shown that this new resampling algorithm with the slotting principle has favorable properties over existing schemes such as NN resampling. A further improvement is obtained by using a slot width that is only a fraction of the resampling time.

In the literature, many methods are available for estimation of the variance of the noise in magnetic resonance (MR) images. A commonly used method, based on the maximum of the background mode of the histogram, is revisited and a new, robust, and easy to use method is presented based on maximum likelihood (ML) estimation. Both methods are evaluated in terms of accuracy and precision using simulated MR data. It is shown that the newly proposed method outperforms the commonly used method in terms of mean-squared error (MSE).

Maximum-likelihood (ML) theory presents an elegant asymptotic solution for the estimation of the parameters of time-series models. Unfortunately, the performance of ML algorithms in finite samples is often disappointing, especially in missing-data problems. The likelihood function is symmetric with respect to the unit circle for the estimated zeros of time-series models. As a consequence, the unit circle is either a local maximum or a local minimum in the likelihood of moving-average (MA) models. This is a trap for nonlinear optimization algorithms that often converge to poor models, with estimated zeros precisely on the unit circle. With ML estimation, it is much easier to estimate a long autoregressive (AR) model with only poles. The parameters of that long AR model can then be used to estimate MA and autoregressive moving-average (ARMA) models for different model orders. The accuracy of the estimated AR, MA, and ARMA spectra is very good. The robustness is excellent as long as the AR order is less than 10 or 15. For still-higher AR orders until about 60, the possible convergence to a useful model will depend on the missing fraction and on the specific properties of the data at hand.

The Bangkok Charter on Health Promo-tion in a Globalized World, adopted at the Sixth Global Conference on Health Promotion in August 2005 (http://www.who.int/healthpromotion/conferences/6gchp/bangkok_charter/en/), highlights the role of health impact assessment (HIA) as a key decision-making tool in development planning.HIA is a combination of procedures, methods and tools by which a policy, programme or project may be judged with regard to its potential effects on the health of a population and the distribution of those effects within the population.

In the literature, many methods are available for estimation of the variance of the noise in magnetic resonance (MR) images. A commonly used method, based on the maximum of the background mode of the histogram, is revisited and a new, robust and easy to use method is presented based on maximum likelihood (ML) estimation. Both methods are evaluated in terms of accuracy and precision using simulated MR data. It is shown that the newly proposed method outperforms the commonly used method in terms of mean-squared-error.

Lymphatic filariasis (LF) is a debilitating disease overwhelmingly caused by Wuchereria bancrofti, which is transmitted by various mosquito species. Here, we present a systematic literature review with the following objectives: (i) to establish global and regional estimates of populations at risk of LF with particular consideration of water resource development projects, and (ii) to assess the effects of water resource development and management on the frequency and transmission dynamics of the disease. We estimate that globally, 2 billion people are at risk of LF. Among them, there are 394.5 million urban dwellers without access to improved sanitation and 213 million rural dwellers living in close proximity to irrigation. Environmental changes due to water resource development and management consistently led to a shift in vector species composition and generally to a strong proliferation of vector populations. For example, in World Health Organization (WHO) subregions 1 and 2, mosquito densities of the Anopheles gambiae complex and Anopheles funestus were up to 25-fold higher in irrigated areas when compared with irrigation-free sites. Although the infection prevalence of LF often increased after the implementation of a water project, there was no clear association with clinical symptoms. Concluding, there is a need to assess and quantify changes of LF transmission parameters and clinical manifestations over the entire course of water resource developments. Where resources allow, integrated vector management should complement mass drug administration, and broad-based monitoring and surveillance of the disease should become an integral part of large-scale waste management and sanitation programs, whose basic rationale lies in a systemic approach to city, district, and regional level health services and disease prevention.

Functional magnetic resonance (fMRI) data are often corrupted with colored noise. To account for this type of noise, many pre-whitening and pre-coloring strategies have been proposed to process the fMRI time series prior to statistical inference. In this paper, a generalized likelihood ratio test for brain activation detection is proposed in which the temporal correlation structure of the noise is modelled as an autoregressive (AR) model. The order of the AR model is determined from experimental null data sets. Simulation tests reveal that, for a fixed false alarm rate, the proposed test is slightly (2-3%) better than current tests incorporating colored noise in terms of detection rate.

Over the past decades, the picture of water-related human health issues has become increasingly comprehensive, with a greater recognition of the complex nature of these links, the emergence of new water-related infectious diseases and a re-emergence of ones already known, and with a greater awareness and insight of the detrimental impact of water-related diseases on social and economic development. Today, we have strong evidence that water-, sanitationand hygiene-related diseases (i.e. the classical safe drinking water and sanitation, or water-borne and water-washed diseases) account for some 2 213 000 deaths annually and an annual loss of 82 196 000 Disability Adjusted Life Years (DALYs). This does not take into account water-related diseases such as malaria, schistosomiasis and other vector-borne diseases, or the more modern infections such as legionellosis. For these diseases, the analyses remain to be done, and, in many cases, the detailed attribution to aquatic environments is not yet completed. The most recent of emerging water-related diseases is that caused by the SARS CoV infections, with a number of well-documented cases of aerosol transmission in specific sanitary domestic or hospital situations. The global picture of water and health has a strong local dimension with some 1.1 billion people still lacking access to improved drinking water sources (and

First principles models of complex industrial processes are often derived using finite element or finite difference methods. One of the advantages of these models is that the states in the model have a clear physical interpretation. Using such models we can attempt to monitor or control selected physical quantities, even though they may not be directly measurable. Unfortunately the CPU time associated with each model evaluation of these complex models is often far too large for use in modern online monitoring or control algorithms. This paper introduces a general purpose method to approximate the computationally expensive first principles models with a quasi-Linear Parameter Varying (qLPV) model structure. The CPU time associated with the resulting qLPV models is generally considerably less than the original first principles model. The identification algorithm is such that the physical interpretation of the state vector is retained in the identified model. In contrary to other qLPV identification algorithms, the proposed algorithm extensively utilizes the availability of the original first principles model.

Japanese encephalitis (JE) is a disease caused by an arbovirus that is spread by marsh birds, amplified by pigs, and mainly transmitted by the bite of infected Culex tritaeniorhynchus mosquitoes. The estimated annual incidence and mortality rates are 30,000--50,000 and 10,000, respectively, and the estimated global burden of JE in 2002 was 709,000 disability-adjusted life years lost. Here, we discuss the contextual determinants of JE, and systematically examine studies assessing the relationship between irrigated rice agriculture and clinical parameters of JE. Estimates of the sizes of the rural population and population in irrigated areas are presented, and trends of the rural population, the rice-irrigated area, and the rice production are analyzed from 1963 to 2003. We find that approximately 1.9 billion people currently live in rural JE-prone areas of the world. Among them 220 million people live in proximity to rice-irrigation schemes. In 2003, the total rice harvested area of all JE-endemic countries (excluding the Russian Federation and Australia) was 1,345,000 km(2). This is an increase of 22% over the past 40 years. Meanwhile, the total rice production in these countries has risen from 226 millions of tonnes to 529 millions of tonnes (+134%). Finally, we evaluate the effect of different vector control interventions in rice fields, including environmental measures (i.e. alternate wet and dry irrigation (AWDI)), and biological control approaches (i.e. bacteria, nematodes, invertebrate predators, larvivorous fish, fungi and other natural products). We conclude that in JE-endemic rural settings, where vaccination rates are often low, an integrated vector management approach with AWDI and the use of larvivorous fish as its main components can reduce vector populations, and hence has the potential to reduce the transmission level and the burden of JE.