Modelling environmentally-mediated infectious diseases of humans: transmission dynamics of schistosomiasis in China.

Macroparasites of humans are sensitive to a variety of environmental variables, including temperature, rainfall and hydrology, yet current comprehension of these relationships is limited. Given the incomplete mechanistic understanding of environment-disease interactions, mathematical models that describe them have seldom included the effects of time-varying environmental processes on transmission dynamics and where they have been included, simple generic, periodic functions are usually used. Few examples exist where seasonal forcing functions describe the actual processes underlying the environmental drivers of disease dynamics. Transmission of human schistosomes, which involves multiple environmental stages, offers a model for applying our understanding of the environmental determinants of the viability, longevity, infectivity and mobility of these stages to controlling disease in diverse environments. Here, a mathematical model of schistosomiasis transmission is presented which incorporates the effects of environmental variables on transmission. Model dynamics are explored and several key extensions to the model are proposed

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

Estimating the microbiological risks associated with inland flood events:bridging theory and models of pathogen transport

Flooding is known to facilitate infectious disease transmission, yet quantitative research on microbiological risks associated with floods has been limited. Pathogen fate and transport models provide a framework to examine interactions between landscape characteristics, hydrology, and waterborne disease risks, but have not been widely developed for flood conditions. We critically examine capabilities of current hydrological models to represent unusual flow paths, non-uniform flow depths, and unsteady flow velocities that accompany flooding. We investigate the theoretical linkages between hydrodynamic processes and spatio-temporally variable suspension and deposition of pathogens from soils and sediments; pathogen dispersion in flow; and concentrations of constituents influencing pathogen transport and persistence. Identifying gaps in knowledge and modeling practice, we propose a research agenda to strengthen microbial fate and transport modeling applied to inland floods: 1) development of models incorporating pathogen discharges from flooded sources (e.g., latrines), effects of transported constituents on pathogen persistence, and supply-limited pathogen transport; 2) studies assessing parameter identifiability and comparing model performance under varying degrees of process representation, in a range of settings; 3) development of remotely sensed datasets to support modeling of vulnerable, data-poor regions; and 4) collaboration between modelers and field-based researchers to expand the collection of useful data in situ

Polymorphic microsatellites in the human bloodfluke, Schistosoma japonicum, identified using a genomic resource

Re-emergence of schistosomiasis in regions of China where control programs have ceased requires development of molecular-genetic tools to track gene flow and assess genetic diversity of Schistosoma populations. We identified many microsatellite loci in the draft genome of Schistosoma japonicum using defined search criteria and selected a subset for further analysis. From an initial panel of 50 loci, 20 new microsatellites were selected for eventual optimization and application to a panel of worms from endemic areas. All but one of the selected microsatellites contain simple tri-nucleotide repeats. Moderate to high levels of polymorphism were detected. Numbers of alleles ranged from 6 to 14 and observed heterozygosity was always >0.6. The loci reported here will facilitate high resolution population-genetic studies on schistosomes in re-emergent foci

Spatially explicit modeling of schistosomiasis risk in Eastern China based on a synthesis of epidemiological, environmental and intermediate host genetic data

Schistosomiasis is considered the second most devastating parasitic disease after malaria. In China, it is transmitted to humans, cattle and other vertebrate hosts by a single intermediate snail host. It has long been suggested that the close co-evolutionary relationship between parasite and intermediate host makes the snail a major transmission bottleneck in the disease life cycle. Here, we use a novel approach to model the disease distribution in eastern China based on a combination of epidemiological, ecological, and genetic information. We found four major high risk areas for schistosomiasis occurrence in the large lakes and flood plain regions of the Yangtze River. These regions are interconnected, suggesting that the disease may be maintained in eastern China in part through the annual flooding of the Yangtze River, which drives snail transport and admixture of genotypes. The novel approach undertaken yielded improved prediction of schistosomiasis disease distribution in eastern China. Thus, it may also be of value for the predictive modeling of other host- or vector-borne diseases

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

Coccidioidomycosis seasonality in California: a longitudinal surveillance study of the climate determinants and spatiotemporal variability of seasonal dynamics, 2000–2021

BackgroundCoccidioidomycosis, an emerging fungal disease in the western USA, exhibits seasonal patterns that are poorly understood, including periods of strong cyclicity, aseasonal intervals, and variation in seasonal timing that have been minimally characterized, and unexplained as to their causal factors. Coccidioidomycosis incidence has increased markedly in recent years, and our limited understanding of intra- and inter-annual seasonality has hindered the identification of important drivers of disease transmission, including climate conditions. In this study, we aim to characterize coccidioidomycosis seasonality in endemic regions of California and to estimate the relationship between drought conditions and coccidioidomycosis seasonal periodicity and timing.MethodsWe analysed data on all reported incident cases of coccidioidomycosis in California from 2000 to 2021 to characterize seasonal patterns in incidence, and conducted wavelet analyses to assess the dominant periodicity, power, and timing of incidence for 17 counties with consistently high incidence rates. We assessed associations between seasonality parameters and measures of drought in California using a distributed lag nonlinear modelling framework.FindingsAll counties exhibited annual cyclicity in incidence (i.e., a dominant wavelet periodicity of 12 months), but there was considerable heterogeneity in seasonal strength and timing across regions and years. On average, 12-month periodicity was most pronounced in the Southern San Joaquin Valley and Central Coast. Further, the annual seasonal cycles in the Southern San Joaquin Valley and the Southern Inland regions occurred earlier than those in coastal and northern counties, yet the timing of annual cycles became more aligned among counties by the end of the study period. Drought conditions were associated with a strong attenuation of the annual seasonal cycle, and seasonal peaks became more pronounced in the 1-2 years after a drought ended.InterpretationWe conclude that drought conditions do not increase the risk of coccidioidomycosis onset uniformly across the year, but instead promote increased risk concentrated within a specific calendar period (September to December). The findings have important implications for public health preparedness, and for how future shifts in seasonal climate patterns and extreme events may impact spatial and temporal coccidioidomycosis risk.FundingNational Institutes of Health

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

Evidence for heterogeneity in China’s progress against pulmonary tuberculosis: uneven reductions in a major center of ongoing transmission, 2005–2017

Abstract Background China contributed 8.9% of all incident cases of tuberculosis globally in 2017, and understanding the spatiotemporal distribution of pulmonary tuberculosis (PTB) in major transmission foci in the country is critical to ongoing efforts to improve population health. Methods We estimated annual PTB notification rates and their spatiotemporal distributions in Sichuan province, a major center of ongoing transmission, from 2005 to 2017. Time series decomposition was used to obtain trend components from the monthly incidence rate time series. Spatiotemporal cluster analyses were conducted to detect spatiotemporal clusters of PTB at the county level. Results From 2005 to 2017, 976,873 cases of active PTB and 388,739 cases of smear-positive PTB were reported in Sichuan Province, China. During this period, the overall reported incidence rate of active PTB decreased steadily at a rate of decrease (3.77 cases per 100,000 per year, 95% confidence interval (CI): 3.28–4.31) that was slightly faster than the national average rate of decrease (3.14 cases per 100,000 per year, 95% CI: 2.61–3.67). Although reported PTB incidence decreased significantly in most regions of the province, incidence was observed to be increasing in some counties with high HIV incidence and ethnic minority populations. Active and smear-positive PTB case reports exhibited seasonality, peaking in March and April, with apparent links to social dynamics and climatological factors. Conclusions While PTB incidence rates decreased strikingly in the study area over the past decade, improvements have not been equally distributed. Additional surveillance and control efforts should be guided by the seasonal-trend and spatiotemporal cluster analyses presented here, focusing on areas with increasing incidence rates, and updated to reflect the latest information from real-time reporting.https://deepblue.lib.umich.edu/bitstream/2027.42/152198/1/12879_2019_Article_4262.pd