European Centre for Disease Prevention and Control, Bill and Melinda Gates Foundation.

Summary Background Listeriosis, caused by Listeria monocytogenes, is an important foodborne disease that can be difficult to control and commonly results in severe clinical outcomes. We aimed to provide the first estimates of global numbers of illnesses, deaths, and disability-adjusted life-years (DALYs) due to listeriosis, by synthesising information and knowledge through a systematic review. Methods We retrieved data on listeriosis through a systematic review of peer-reviewed and grey literature (published in 1990–2012). We excluded incidence data from before 1990 from the analysis. We reviewed national surveillance data where available. We did a multilevel meta-analysis to impute missing country-specific listeriosis incidence rates. We used a meta-regression to calculate the proportions of health states, and a Monte Carlo simulation to generate DALYs by WHO subregion. Findings We screened 11 722 references and identified 87 eligible studies containing listeriosis data for inclusion in the meta-analyses. We estimated that, in 2010, listeriosis resulted in 23 150 illnesses (95% credible interval 6061–91 247), 5463 deaths (1401–21 497), and 172 823 DALYs (44 079–676 465). The proportion of perinatal cases was 20·7% (SD 1·7). Interpretation Our quantification of the global burden of listeriosis will enable international prioritisation exercises. The number of DALYs due to listeriosis was lower than those due to congenital toxoplasmosis but accords with those due to echinococcosis. Urgent efforts are needed to fill the missing data in developing countries. We were unable to identify incidence data for the AFRO, EMRO, and SEARO WHO regions. Funding WHO Foodborne Diseases Epidemiology Reference Group and the Université catholique de Louvain.

BackgroundIn calculations of burden of disease using disability-adjusted life years, disability weights are needed to quantify health losses relating to non-fatal outcomes, expressed as years lived with disability. In 2012 a new set of global disability weights was published for the Global Burden of Disease 2010 (GBD 2010) study. That study suggested that comparative assessments of different health outcomes are broadly similar across settings, but the significance of this conclusion has been debated. The aim of the present study was to estimate disability weights for Europe for a set of 255 health states, including 43 new health states, by replicating the GBD 2010 Disability Weights Measurement study among representative population samples from four European countries.MethodsFor the assessment of disability weights for Europe we applied the GBD 2010 disability weights measurement approach in web-based sample surveys in Hungary, Italy, Netherlands, and Sweden. The survey included paired comparisons (PC) and population health equivalence questions (PHE) formulated as discrete choices. Probit regression analysis was used to estimate cardinal values from PC responses. To locate results onto the 0-to-1 disability weight scale, we assessed the feasibility of using the GBD 2010 scaling approach based on PHE questions, as well as an alternative approach using non-parametric regression.ResultsIn total, 30,660 respondents participated in the survey. Comparison of the probit regression results from the PC responses for each country indicated high linear correlations between countries. The PHE data had high levels of measurement error in these general population samples, which compromises the ability to infer ratio-scaled values from discrete choice responses. Using the non-parametric regression approach as an alternative rescaling procedure, the set of disability weights were bounded by distance vision mild impairment and anemia with the lowest weight (0.004) and severe multiple sclerosis with the highest weight (0.677).ConclusionsPC assessments of health outcomes in this study resulted in estimates that were highly correlated across four European countries. Assessment of the feasibility of rescaling based on a discrete choice formulation of the PHE question indicated that this approach may not be suitable for use in a web-based survey of the general population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12963-015-0042-4) contains supplementary material, which is available to authorized users.

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BackgroundThe Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates.Methods and FindingsThe global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process.ConclusionsWe developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level.

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BackgroundParasitic zoonoses (PZs) pose a significant but often neglected threat to public health, especially in developing countries. In order to obtain a better understanding of their health impact, summary measures of population health may be calculated, such as the Disability-Adjusted Life Year (DALY). However, the data required to calculate such measures are often not readily available for these diseases, which may lead to a vicious circle of under-recognition and under-funding.MethodologyWe examined the burden of PZs in Nepal through a systematic review of online and offline data sources. PZs were classified qualitatively according to endemicity, and where possible a quantitative burden assessment was conducted in terms of the annual number of incident cases, deaths and DALYs.Principal FindingsBetween 2000 and 2012, the highest annual burden was imposed by neurocysticercosis and congenital toxoplasmosis (14,268 DALYs [95% Credibility Interval (CrI): 5450–27,694] and 9255 DALYs [95% CrI: 6135–13,292], respectively), followed by cystic echinococcosis (251 DALYs [95% CrI: 105–458]). Nepal is probably endemic for trichinellosis, toxocarosis, diphyllobothriosis, foodborne trematodosis, taeniosis, and zoonotic intestinal helminthic and protozoal infections, but insufficient data were available to quantify their health impact. Sporadic cases of alveolar echinococcosis, angiostrongylosis, capillariosis, dirofilariosis, gnathostomosis, sparganosis and cutaneous leishmaniosis may occur.Conclusions/SignificanceIn settings with limited surveillance capacity, it is possible to quantify the health impact of PZs and other neglected diseases, thereby interrupting the vicious circle of neglect. In Nepal, we found that several PZs are endemic and are imposing a significant burden to public health, higher than that of malaria, and comparable to that of HIV/AIDS. However, several critical data gaps remain. Enhanced surveillance for the endemic PZs identified in this study would enable additional burden estimates, and a more complete picture of the impact of these diseases.