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

Heterogeneous Host Susceptibility Enhances Prevalence of Mixed-Genotype Micro-Parasite Infections

Dose response in micro-parasite infections is usually shallower than predicted by the independent action model, which assumes that each infectious unit has a probability of infection that is independent of the presence of other infectious units. Moreover, the prevalence of mixed-genotype infections was greater than predicted by this model. No probabilistic infection model has been proposed to account for the higher prevalence of mixed-genotype infections. We use model selection within a set of four alternative models to explain high prevalence of mixed-genotype infections in combination with a shallow dose response. These models contrast dependent versus independent action of micro-parasite infectious units, and homogeneous versus heterogeneous host susceptibility. We specifically consider a situation in which genome differences between genotypes are minimal, and highly unlikely to result in genotype-genotype interactions. Data on dose response and mixed-genotype infection prevalence were collected by challenging fifth instar Spodoptera exigua larvae with two genotypes of Autographa californica multicapsid nucleopolyhedrovirus (AcMNPV), differing only in a 100 bp PCR marker sequence. We show that an independent action model that includes heterogeneity in host susceptibility can explain both the shallow dose response and the high prevalence of mixed-genotype infections. Theoretical results indicate that variation in host susceptibility is inextricably linked to increased prevalence of mixed-genotype infections. We have shown, to our knowledge for the first time, how heterogeneity in host susceptibility affects mixed-genotype infection prevalence. No evidence was found that virions operate dependently. While it has been recognized that heterogeneity in host susceptibility must be included in models of micro-parasite transmission and epidemiology to account for dose response, here we show that heterogeneity in susceptibility is also a fundamental principle explaining patterns of pathogen genetic diversity among hosts in a population. This principle has potentially wide implications for the monitoring, modeling and management of infectious diseases

Effective detection of human adenovirus in hawaiian waters using enhanced pcr methods

<p>Abstract</p> <p>Background</p> <p>The current criteria for recreational water quality evaluation are primarily based on measurements of fecal indicator bacteria growth. However, these criteria often fail to predict the presence of waterborne human pathogenic viruses. To explore the possibility of direct use of human enteric viruses as improved human fecal contamination indicators, human adenovirus (HAdV) was tested as a model in this study.</p> <p>Findings</p> <p>In order to establish a highly sensitive protocol for effective detection of HAdV in aquatic environments, sixteen published PCR primer sets were re-optimized and comparatively evaluated. Primer sets nehex3deg/nehex4deg, ADV-F/ADV-R, and nested PCR primer sets hex1deg/hex2deg and nehex3deg/nehex4deg were identified to be the most sensitive ones, with up to 1,000 fold higher detection sensitivity compared to other published assays. These three PCR protocols were successfully employed to detect HAdV in both treated and untreated urban wastewaters, and also in 6 of 16 recreational water samples collected around the island of Oahu, Hawaii.</p> <p>Conclusions</p> <p>Findings from this study support the possible use of enteric viruses for aquatic environmental monitoring, specifically for the essential routine monitoring of Hawaiian beach waters using the optimized PCR protocol to detect HAdV at certain water sites to ensure a safe use of recreational waters.</p

Immune Boosting Explains Regime-Shifts in Prevaccine-Era Pertussis Dynamics

Understanding the biological mechanisms underlying episodic outbreaks of infectious diseases is one of mathematical epidemiology’s major goals. Historic records are an invaluable source of information in this enterprise. Pertussis (whooping cough) is a re-emerging infection whose intermittent bouts of large multiannual epidemics interspersed between periods of smaller-amplitude cycles remain an enigma. It has been suggested that recent increases in pertussis incidence and shifts in the age-distribution of cases may be due to diminished natural immune boosting. Here we show that a model that incorporates this mechanism can account for a unique set of pre-vaccine-era data from Copenhagen. Under this model, immune boosting induces transient bursts of large amplitude outbreaks. In the face of mass vaccination, the boosting model predicts larger and more frequent outbreaks than do models with permanent or passively-waning immunity. Our results emphasize the importance of understanding the mechanisms responsible for maintaining immune memory fo

A Methodological Framework for the Evaluation of Syndromic Surveillance Systems: A Case Study of England

Background: Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect. Methods: We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis. Results: Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different types outbreaks with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings. Conclusions: The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden

Acknowledgements: We thank colleagues within the Modelling, Evidence and Policy Research Group for useful feedback on this manuscript. Competing interests: The authors declare that they have no competing interests. Availability of data and materials: The R code used in this research is available at https://gitlab.com/rasanderson/campylobacter-microsimulation; it is platform independent, R version 3.3.0 and above. Funding: This research was funded by Medical Research Council Grant, Natural Environment Research Council, Economic and Social Research Council, Biotechnology and Biological Sciences Research Council, and the Food Standards Agency through the Environmental and Social Ecology of Human Infectious Diseases Initiative (Sources, seasonality, transmission and control: Campylobacter and human behaviour in a changing environment (ENIGMA); Grant Reference G1100799-1). PRH, SJO’B, and IRL are funded in part by the NIHR Health Protection Research Unit in Gastrointestinal Infection, at the University of Liverpool. PRH and IRL are also funded in part by the NIHR Health Protection Research Unit in Emergency Preparedness and Response, at King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or Public Health England.Peer reviewedPublisher PD

Infectieuze gastro-enteritis - mogelijkheden voor dosis-responsmodellering

Pathogene micro-organismen die het menselijk lichaam binnendringen via voeding of door het drinken van besmet water, krijgen te maken met een door de gastheer opgeworpen systeem van barrieres. Teneinde delen van het spijsverteringskanaal te bereiken die geschikt zijn voor groei en hechting, moet elk van de tussenliggende barrieres overwonnen worden. De gangbare visie op infectie gaat ervan uit dat minstens een van de ingeslikte pathogenen moet overleven om te kunnen koloniseren. Dit is de basis voor dosis-responsmodellen zoals toegepast bij de microbiologische risico-analyse. Afweermechanismen tegen infectie en invasie door micro-organismen kunnen immunologisch zijn of non-immunologisch. In dit rapport wordt de geldigheid van het Beta-Poissonmodel voor meer dan een barriere gedemonstreerd en wordt enige aandacht besteed aan het 'single-hit' principe. Ook besproken wordt een benadering in de afleiding van het Beta-Poissonmodel, en aangetoond wordt dat deze benadering voor bepaalde parameterwaarden resultaten oplevert die verschillen van de exacte formule. Tenslotte worden enkele aanzetten gedaan tot modellen, waarbij extra informatie over infectie en ziekte kan worden gebruikt.When pathogenic microorganisms enter the human body via ingestion of food or drinking water, they encounter a system of barriers mounted by the host. Defense mechanisms against microbial infection and invasion may be immunological or non-immunological. To reach parts of the intestinal tract that are suitable for growth and attachment, they must overcome each of the barriers successfully. According to the present view on infection, at least one of the ingested pathogens must survive if colonization is to start. This is the basis for dose response models used for quantitative risk assessment. The validity of such a model, the Beta Poisson model, was demonstrated for multiple barriers, with some attention being given to the single-hit principle. Also discussed was an approach to the derivation of the Beta Poisson model, an aspect which is usually neglected. This approach was shown here to produce results for certain parameter values that were different from the exact formula. Finally, several initiatives for new models are presented in which extra information on infection and illness is incorporated.IGBV

Infectieuze gastro-enteritis - mogelijkheden voor dosis-responsmodellering

When pathogenic microorganisms enter the human body via ingestion of food or drinking water, they encounter a system of barriers mounted by the host. Defense mechanisms against microbial infection and invasion may be immunological or non-immunological. To reach parts of the intestinal tract that are suitable for growth and attachment, they must overcome each of the barriers successfully. According to the present view on infection, at least one of the ingested pathogens must survive if colonization is to start. This is the basis for dose response models used for quantitative risk assessment. The validity of such a model, the Beta Poisson model, was demonstrated for multiple barriers, with some attention being given to the single-hit principle. Also discussed was an approach to the derivation of the Beta Poisson model, an aspect which is usually neglected. This approach was shown here to produce results for certain parameter values that were different from the exact formula. Finally, several initiatives for new models are presented in which extra information on infection and illness is incorporated.Pathogene micro-organismen die het menselijk lichaam binnendringen via voeding of door het drinken van besmet water, krijgen te maken met een door de gastheer opgeworpen systeem van barrieres. Teneinde delen van het spijsverteringskanaal te bereiken die geschikt zijn voor groei en hechting, moet elk van de tussenliggende barrieres overwonnen worden. De gangbare visie op infectie gaat ervan uit dat minstens een van de ingeslikte pathogenen moet overleven om te kunnen koloniseren. Dit is de basis voor dosis-responsmodellen zoals toegepast bij de microbiologische risico-analyse. Afweermechanismen tegen infectie en invasie door micro-organismen kunnen immunologisch zijn of non-immunologisch. In dit rapport wordt de geldigheid van het Beta-Poissonmodel voor meer dan een barriere gedemonstreerd en wordt enige aandacht besteed aan het 'single-hit' principe. Ook besproken wordt een benadering in de afleiding van het Beta-Poissonmodel, en aangetoond wordt dat deze benadering voor bepaalde parameterwaarden resultaten oplevert die verschillen van de exacte formule. Tenslotte worden enkele aanzetten gedaan tot modellen, waarbij extra informatie over infectie en ziekte kan worden gebruikt