Microbial Risk Assessment Framework for Exposure to Amended Sludge Projects

BackgroundAlthough the U.S. Environmental Protection Agency has a long history of using risk-based approaches for regulatory purposes, pollutant limits for pathogens in biosolids are not currently based on quantitative risk assessments.ObjectivesWe developed and demonstrated a risk-based methodology for assessing the risk to human health from exposure to pathogens via biosolids.MaterialsFour models were developed, incorporating direct ingestion, groundwater, and aerosol exposure pathways. Three sources of environmental data were used to estimate risk: pathogen monitoring of sludge, efficacy of sludge treatment, and pathogen monitoring of biosolids.ResultsRisk estimates were obtainable even for Class A biosolids, where posttreatment monitoring data are below detectable levels, demonstrating that risk assessments for biosolids exposure are practical. Model analyses suggest that: a) a two-digester design decreases the probability of risks >10(-4) compared with one-digester designs, b) risks associated with exposures to groundwater and aerosol pathways were, in general, lower than exposures to the direct ingestion pathway, and c) secondary transmission can be an important factor in risk estimation.ConclusionsThe risk-based approach presented here provides a tool to a) help biosolids producers interpret the results of biosolids monitoring data in terms of its health implications, b) help treatment plant engineers evaluate the risk-based benefits of operational changes to existing or projected treatment processes, and c) help environmental managers evaluate potential capital improvements and/or land application site placement issues. Regulation of pathogens can now be based on human health risk in a manner parallel to other water-related risks

Serum immunoglobulin G, M and A response to Cryptosporidium parvum in Cryptosporidium-HIV co-infected patients

<p>Abstract</p> <p>Background</p> <p><it>Cryptosporidium parvum</it>, the protozoan parasite, causes a significant enteric disease in immunocompromised hosts such as HIV patients. The present study was aimed to compare serum IgG, IgM and IgA responses to crude soluble antigen of <it>C. parvum </it>in HIV seropositive and seronegative patients co-infected with <it>Cryptosporidium </it>and to correlate the responses with symptomatology.</p> <p>Methods</p> <p><it>Cryptosporidium parvum </it>specific serum antibody (IgG, IgM and IgA) responses were assessed by ELISA in 11 HIV seropositive <it>Cryptosporidium </it>positive (Group I), 20 HIV seropositive <it>Cryptosporidium </it>negative (Group II), 10 HIV seronegative <it>Cryptosporidium </it>positive (Group III), 20 HIV seronegative <it>Cryptosporidium </it>negative healthy individuals (Group IV) and 25 patients with other parasitic diseases (Group V).</p> <p>Results</p> <p>A positive IgG and IgA antibody response was observed in significantly higher number of <it>Cryptosporidium </it>infected individuals (Gp I and III) compared to <it>Cryptosporidium </it>un-infected individuals (Gp II, IV and V) irrespective of HIV/immune status. Sensitivity of IgG ELISA in our study was found to be higher as compared to IgM and IgA ELISA. The number of patients with positive IgG, IgM and IgA response was not significantly different in HIV seropositive <it>Cryptosporidium </it>positive patients with diarrhoea when compared to patients without diarrhoea and in patients with CD4 counts <200 when compared to patients with CD4 counts >200 cells/μl.</p> <p>Conclusion</p> <p>The study showed specific serum IgG and IgA production in patients infected with <it>Cryptosporidium</it>, both HIV seropositive and seronegative as compared to uninfected subjects suggesting induction of <it>Cryptosporidium </it>specific humoral immune response in infected subjects. However, there was no difference in number of patients with positive response in HIV seropositive or seronegative groups indicating that HIV status may not be playing significant role in modulation of <it>Cryptosporidium </it>specific antibody responses. The number of patients with positive IgG, IgM and IgA response was not significantly different in patients with or without history of diarrhoea thereby indicating that <it>Cryptosporidium </it>specific antibody responses may not be necessarily associated with protection from symptomatology.</p

Using Dynamic Stochastic Modelling to Estimate Population Risk Factors in Infectious Disease: The Example of FIV in 15 Cat Populations

BACKGROUND:In natural cat populations, Feline Immunodeficiency Virus (FIV) is transmitted through bites between individuals. Factors such as the density of cats within the population or the sex-ratio can have potentially strong effects on the frequency of fight between individuals and hence appear as important population risk factors for FIV. METHODOLOGY/PRINCIPAL FINDINGS:To study such population risk factors, we present data on FIV prevalence in 15 cat populations in northeastern France. We investigate five key social factors of cat populations; the density of cats, the sex-ratio, the number of males and the mean age of males and females within the population. We overcome the problem of dependence in the infective status data using sexually-structured dynamic stochastic models. Only the age of males and females had an effect (p = 0.043 and p = 0.02, respectively) on the male-to-female transmission rate. Due to multiple tests, it is even likely that these effects are, in reality, not significant. Finally we show that, in our study area, the data can be explained by a very simple model that does not invoke any risk factor. CONCLUSION:Our conclusion is that, in host-parasite systems in general, fluctuations due to stochasticity in the transmission process are naturally very large and may alone explain a larger part of the variability in observed disease prevalence between populations than previously expected. Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease

Waterborne microbial risk assessment : a population-based dose-response function for Giardia spp. (E.MI.R.A study)

BACKGROUND: Dose-response parameters based on clinical challenges are frequently used to assess the health impact of protozoa in drinking water. We compare the risk estimates associated with Giardia in drinking water derived from the dose-response parameter published in the literature and the incidence of acute digestive conditions (ADC) measured in the framework of an epidemiological study in a general population. METHODS: The study combined a daily follow-up of digestive morbidity among a panel of 544 volunteers and a microbiological surveillance of tap water. The relationship between incidence of ADC and concentrations of Giardia cysts was modeled with Generalized Estimating Equations, adjusting on community, age, tap water intake, presence of bacterial indicators, and genetic markers of viruses. The quantitative estimate of Giardia dose was the product of the declared amount of drinking water intake (in L) by the logarithm of cysts concentrations. RESULTS: The Odds Ratio for one unit of dose [OR = 1.76 (95% CI: 1.21, 2.55)] showed a very good consistency with the risk assessment estimate computed after the literature dose-response, provided application of a 20 % abatement factor to the cysts counts that were measured in the epidemiological study. Doing so, a daily water intake of 2 L and a Giardia concentration of 10 cysts/100 L, would yield an estimated relative excess risk of 12 % according to the Rendtorff model, against 11 % when multiplying the baseline rate of ADC by the corresponding OR. This abatement parameter encompasses uncertainties associated with germ viability, infectivity and virulence in natural settings. CONCLUSION: The dose-response function for waterborne Giardia risk derived from clinical experiments is consistent with epidemiological data. However, much remains to be learned about key characteristics that may heavily influence quantitative risk assessment results

Logistics of community smallpox control through contact tracing and ring vaccination: a stochastic network model

BACKGROUND: Previous smallpox ring vaccination models based on contact tracing over a network suggest that ring vaccination would be effective, but have not explicitly included response logistics and limited numbers of vaccinators. METHODS: We developed a continuous-time stochastic simulation of smallpox transmission, including network structure, post-exposure vaccination, vaccination of contacts of contacts, limited response capacity, heterogeneity in symptoms and infectiousness, vaccination prior to the discontinuation of routine vaccination, more rapid diagnosis due to public awareness, surveillance of asymptomatic contacts, and isolation of cases. RESULTS: We found that even in cases of very rapidly spreading smallpox, ring vaccination (when coupled with surveillance) is sufficient in most cases to eliminate smallpox quickly, assuming that 95% of household contacts are traced, 80% of workplace or social contacts are traced, and no casual contacts are traced, and that in most cases the ability to trace 1–5 individuals per day per index case is sufficient. If smallpox is assumed to be transmitted very quickly to contacts, it may at times escape containment by ring vaccination, but could be controlled in these circumstances by mass vaccination. CONCLUSIONS: Small introductions of smallpox are likely to be easily contained by ring vaccination, provided contact tracing is feasible. Uncertainties in the nature of bioterrorist smallpox (infectiousness, vaccine efficacy) support continued planning for ring vaccination as well as mass vaccination. If initiated, ring vaccination should be conducted without delays in vaccination, should include contacts of contacts (whenever there is sufficient capacity) and should be accompanied by increased public awareness and surveillance

Seasonality in Human Zoonotic Enteric Diseases: A Systematic Review

BACKGROUND: Although seasonality is a defining characteristic of many infectious diseases, few studies have described and compared seasonal patterns across diseases globally, impeding our understanding of putative mechanisms. Here, we review seasonal patterns across five enteric zoonotic diseases: campylobacteriosis, salmonellosis, vero-cytotoxigenic Escherichia coli (VTEC), cryptosporidiosis and giardiasis in the context of two primary drivers of seasonality: (i) environmental effects on pathogen occurrence and pathogen-host associations and (ii) population characteristics/behaviour. METHODOLOGY/PRINCIPAL FINDINGS: We systematically reviewed published literature from 1960-2010, resulting in the review of 86 studies across the five diseases. The Gini coefficient compared temporal variations in incidence across diseases and the monthly seasonality index characterised timing of seasonal peaks. Consistent seasonal patterns across transnational boundaries, albeit with regional variations was observed. The bacterial diseases all had a distinct summer peak, with identical Gini values for campylobacteriosis and salmonellosis (0.22) and a higher index for VTEC (Gini  0.36). Cryptosporidiosis displayed a bi-modal peak with spring and summer highs and the most marked temporal variation (Gini = 0.39). Giardiasis showed a relatively small summer increase and was the least variable (Gini = 0.18). CONCLUSIONS/SIGNIFICANCE: Seasonal variation in enteric zoonotic diseases is ubiquitous, with regional variations highlighting complex environment-pathogen-host interactions. Results suggest that proximal environmental influences and host population dynamics, together with distal, longer-term climatic variability could have important direct and indirect consequences for future enteric disease risk. Additional understanding of the concerted influence of these factors on disease patterns may improve assessment and prediction of enteric disease burden in temperate, developed countries

Can learning health systems help organisations deliver personalised care?

There is increasing international policy and clinical interest in developing learning health systems and delivering precision medicine, which it is hoped will help reduce variation in the quality and safety of care, improve efficiency, and lead to increasing the personalisation of healthcare. Although reliant on similar policies, informatics tools, and data science and implementation research capabilities, these two major initiatives have thus far largely progressed in parallel. In this opinion piece, we argue that they should be considered as complementary, synergistic initiatives whereby the creation of learning health systems infrastructure can support and catalyse the delivery of precision medicine that maximises the benefits and minimises the risks associated with treatments for individual patients. We illustrate this synergy by considering the example of treatments for asthma, which is now recognised as an umbrella term for a heterogeneous group of related conditions

A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite's intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management

Impacts of small-scale chicken farming activity on antimicrobial-resistant Escherichia coli carriage in backyard chickens and children in rural Ecuador.

The emergence, spread, and persistence of antimicrobial resistance (AMR) remains a pressing global concern. Increased promotion of commercial small-scale agriculture within low-resource settings has facilitated an increased use in antimicrobials as growth promoters globally, creating antimicrobial-resistant animal reservoirs. We conducted a longitudinal field study in rural Ecuador to monitor the AMR of Escherichia coli populations from backyard chickens and children at three sample periods with approximately 2-month intervals (February, April, and June 2017). We assessed AMR to 12 antibiotics using generalized linear mixed effects models (GLMM). We also sampled and assessed AMR to the same 12 antibiotics in one-day-old broiler chickens purchased from local venders. One-day-old broiler chickens showed lower AMR at sample period 1 compared to sample period 2 (for 9 of the 12 antibiotics tested); increases in AMR between sample periods 2 and 3 were minimal. Two months prior to the first sample period (December 2016) there was no broiler farming activity due to a regional collapse followed by a peak in annual farming in February 2017. Between sample periods 1 and 2, we observed significant increases in AMR to 6 of the 12 antibiotics in children and to 4 of the 12 antibiotics in backyard chickens. These findings suggest that the recent increase in farming, and the observed increase of AMR in the one-day old broilers, may have caused the increase in AMR in backyard chickens and children. Small-scale farming dynamics could play an important role in the spread of AMR in low- and middle-income countries