A Novel Tool for Real-time Estimation of Epidemiological Parameters of Communicable Diseases Using Contact-Tracing Data: Development and Deployment.

BACKGROUND: The Surveillance Outbreak Response Management and Analysis System (SORMAS) contains a management module to support countries in their epidemic response. It consists of the documentation, linkage, and follow-up of cases, contacts, and events. To allow SORMAS users to visualize data, compute essential surveillance indicators, and estimate epidemiological parameters from such network data in real-time, we developed the SORMAS Statistics (SORMAS-Stats) application. OBJECTIVE: This study aims to describe the essential visualizations, surveillance indicators, and epidemiological parameters implemented in the SORMAS-Stats application and illustrate the application of SORMAS-Stats in response to the COVID-19 outbreak. METHODS: Based on findings from a rapid review and SORMAS user requests, we included the following visualization and estimation of parameters in SORMAS-Stats: transmission network diagram, serial interval (SI), time-varying reproduction number R(t), dispersion parameter k, and additional surveillance indicators presented in graphs and tables. We estimated SI by fitting lognormal, gamma, and Weibull distributions to the observed distribution of the number of days between symptom onset dates of infector-infectee pairs. We estimated k by fitting a negative binomial distribution to the observed number of infectees per infector. Furthermore, we applied the Markov Chain Monte Carlo approach and estimated R(t) using the incidence data and the observed SI computed from the transmission network data. RESULTS: Using COVID-19 contact-tracing data of confirmed cases reported between July 31 and October 29, 2021, in the Bourgogne-Franche-Comté region of France, we constructed a network diagram containing 63,570 nodes. The network comprises 1.75% (1115/63,570) events, 19.59% (12,452/63,570) case persons, and 78.66% (50,003/63,570) exposed persons, including 1238 infector-infectee pairs and 3860 transmission chains with 24.69% (953/3860) having events as the index infector. The distribution with the best fit to the observed SI data was a lognormal distribution with a mean of 4.30 (95% CI 4.09-4.51) days. We estimated a dispersion parameter k of 21.11 (95% CI 7.57-34.66) and an effective reproduction number R of 0.9 (95% CI 0.58-0.60). The weekly estimated R(t) values ranged from 0.80 to 1.61. CONCLUSIONS: We provide an application for real-time estimation of epidemiological parameters, which is essential for informing outbreak response strategies. The estimates are commensurate with findings from previous studies. The SORMAS-Stats application could greatly assist public health authorities in the regions using SORMAS or similar tools by providing extensive visualizations and computation of surveillance indicators.

[Logic model of the Franche-Comté Regional Health Project: advantages and limitations for the evaluation process]. / Cadre logique du Projet régional de santé de Franche-Comté : intérêts et limites pour la démarche d'évaluation.

The French "Hospitals, patients, health and territories" law of July 2009 created the Regional Health Project (PRS) to support regional health policy, and requires evaluation of these projects. The construction of these projects, which includes prevention planning, care planning, and medical and social welfare planning, presents an unprecedented complexity in France, where evaluation programmes are still in their infancy. To support future evaluations, the Franche-Comté Regional Health Agency (ARS FC), assisted by the expertise of EFECT Consultants, decided to reconstruct the PRS logic model. This article analyzes the advantages and limitations of this approach. The resulting logic model allows visualization of the strategy adopted to achieve the Franche-Comté PRS ambitions and expected results. The model highlights four main aspects of structural change to the health system, often poorly visible in PRS presentation documents. This model also establishes links with the usual public policy evaluation issues and facilitates their prioritization. This approach also provides a better understanding of the importance of analysis of the programme construction in order to be effective rather than direct analysis of the effects, which constitutes the natural tendency of current practice. The main controversial limit concerns the retrospective design of the PRS framework, both in terms of the reliability of interpretation and adoption by actors not directly involved in this initiative.

Haber's rule duration adjustments should not be used systematically for risk assessment in public health decision-making.

Human health risk assessment can be used to support decisions for public health regulations and actions. Characterizing the hazards of inhaled toxicants generally includes extrapolation from observations on experimental animals, subjected to intermittent or subchronic exposures, to a human environmental context with exposure that is usually continuous and long-term. The extrapolation is usually based on a simple linear relationship derived from Haber's rule which assumes that, for a given chemical compound, multiplying the same concentration by the same duration of exposure will yield the same biological response. This study assessed the reliability of this assumption. The p-power in the equation C×t(p)=k was calculated for 21 chemicals, based on a comparison of LOAELs for subacute, subchronic and chronic durations. A bibliographic survey was then carried out to study the reliability of the intermittent-to-continuous exposure adjustment factors currently used in risk assessment. The results showed that the value of p, assumed to be 1 in risk assessment methodology, was not in fact equal to 1 for any of the selected chemicals. Moreover, in the case of respiratory tract irritation, the value of p varied from 0 to 0.44, as confirmed by experimental studies. These results suggest that a more in-depth and case-by-case approach is required for regulatory toxicology, based on toxicokinetics and toxicodynamic data analysis for each toxicant before applying a temporal-adjustment factor.

The French approach to deriving toxicity reference values: an example using reprotoxic effects.

Following the French health and environment action plan, the French Agency for Environmental and Occupational Health and Safety set up a workgroup to standardise a method of deriving toxicity reference values (TRVs). Over the last few decades, there has been increasing concern about the effect of exposure to chemicals on reproductive function, leading the group to take an interest in reprotoxic effects. This article presents the recommendations of the workgroup regarding specific reprotoxic effects. Abnormal development of foetuses and infants, together with impairment of reproduction were considered to be critical effects. Where critical windows of exposure were concerned, quantitative analysis suggested the need for several types of toxicity reference value, as a function of exposure duration: reprotoxic effects may result from acute or chronic exposure at any time of life, whilst developmental effects may occur after exposure during the pregnancy or during the lactation period. The choice of a critical study is based on epidemiological or toxicological quality criteria. The working group recommends the use of the benchmark dose approach in estimating the critical dose. Finally, the working group considered the application of uncertainty factors typically used to take into account the variability between animal and human, between different individuals, and the availability of the data.

Risk of cancer in the vicinity of municipal solid waste incinerators: importance of using a flexible modelling strategy.

BACKGROUND: We conducted an ecological study in four French administrative departments and highlighted an excess risk in cancer morbidity for residents around municipal solid waste incinerators. The aim of this paper is to show how important are advanced tools and statistical techniques to better assess weak associations between the risk of cancer and past environmental exposures. METHODS: The steps to evaluate the association between the risk of cancer and the exposure to incinerators, from the assessment of exposure to the definition of the confounding variables and the statistical analysis carried out are detailed and discussed. Dispersion modelling was used to assess exposure to sixteen incinerators. A geographical information system was developed to define an index of exposure at the IRIS level that is the geographical unit we considered. Population density, rural/urban status, socio-economic deprivation, exposure to air pollution from traffic and from other industries were considered as potential confounding factors and defined at the IRIS level. Generalized additive models and Bayesian hierarchical models were used to estimate the association between the risk of cancer and the index of exposure to incinerators accounting for the confounding factors. RESULTS: Modelling to assess the exposure to municipal solid waste incinerators allowed accounting for factors known to influence the exposure (meteorological data, point source characteristics, topography). The statistical models defined allowed modelling extra-Poisson variability and also non-linear relationships between the risk of cancer and the exposure to incinerators and the confounders. CONCLUSION: In most epidemiological studies distance is still used as a proxy for exposure. This can lead to significant exposure misclassification. Additionally, in geographical correlation studies the non-linear relationships are usually not accounted for in the statistical analysis. In studies of weak associations it is important to use advanced methods to better assess dose-response relationships with disease risk.

Acute-to-chronic species sensitivity distribution extrapolation.

Seeking to make greater use of available data for risk assessment of substances, we constructed, for the situation in which chronic data are limited or even nonexistent but acute data are relatively large, an acute to chronic transformation (ACT) methodology based on the concept of species sensitivity distributions (SSDs). This ACT methodology uses a comparison of acute and chronic SSDs, separately for vertebrate data (with 22 substances) and for invertebrate data (with 15 substances). Rather than comparing an acute toxicity value with a chronic value, as when calculating an acute to chronic ratio (ACR), samples of acute and chronic data corresponding to the same category of species were compared. Starting from a sample of acute data, the ACT methodology showed relationships that enable the creation of a sample of predicted chronic values. This sample can then be used to calculate a predicted chronic hazardous concentration potentially affecting 5% of species (HC5%), just as with a sample of real chronic toxicity values. This ACT approach was tested on 11 substances. For each substance, the real chronic HC5% and the predicted chronic HC5% were calculated and compared. The ratio between chronic HC5% and ACT HC5% was, on average, 1.6 and did not exceed 4.4 for the 11 substances studied.

Effects of data manipulation and statistical methods on species sensitivity distributions.

Species sensitivity distribution (SSD) methodology currently is used in environmental risk assessment to determine the predicted no-effect concentration (PNEC) of a substance in cases where a sufficient number of chronic ecotoxicological tests have been carried out on the substance, covering, for the aquatic environment with which we are concerned, three taxonomic groups: algae, invertebrates, and vertebrates. In particular, SSD methodology enables calculation of a hazardous concentration that is assumed to protect 95% of species (HC5). This approach is based on the hypothesis that the species for which results of ecotoxicological tests are known are representative, in terms of sensitivity, of the totality of the species in the environment, which raises a number of questions, both theoretical and practical. In this study, we compared various methods of constructing a species sensitivity-weighted distribution (SSWD). Each method is characterized by a different way of taking into account intraspecies variation and proportions of taxonomic groups (vertebrates, invertebrates, and algae), as well as by the statistical method of calculation of the HC5 and its confidence interval. Those methods are tested on 15 substances by using chronic no-observed-effect concentration data available in the literature. The choice of data (intraspecies variation and proportions between taxonomic groups) was found to have more effect on the value of the HC5 than the statistical method used to construct the distribution. The weight of each taxonomic group is the most important parameter for the result of the SSWD and letting literature references decide which proportions of data are used to construct it is not satisfactory.

Modeling explicitly and mechanistically median lethal concentration as a function of time for risk assessment.

A mechanistic model that explains how toxic effects depend on the duration of exposure has been developed. Derived from the dynamic energy budget (DEB)tox model, it expresses the hazard rate as a function of the toxic concentration in the organism. Using linear approximations in accordance with the general simplifications made in DEBtox, the concentration that induces x% of lethality (LCx) and in particular the lethal concentration 50% (LC50) are expressed explicitly as functions of time. Only three parameters are required: an asymptotic effect concentration, a time constant, and an effect velocity. More sophisticated (but still analytic) models are possible, describing more complex toxicity patterns such as an increase of sensitivity with time or, conversely, an adaptation. These models can be fitted to the common and widespread LC50 endpoints available from the literature for various aquatic species and chemicals. The interpretation of the values assigned to the parameters will help explain the toxicity processes and standardize toxicity values from different sources for comparisons.