Recently developed vaccines provide a new way of controlling rotavirus in sub-Saharan Africa. Models for the transmission dynamics of rotavirus are critical both for estimating current burden from imperfect surveillance and for assessing potential effects of vaccine intervention strategies. We examine rotavirus infection in the Maradi area in southern Niger using hospital surveillance data provided by Epicentre collected over two years. Additionally, a cluster survey of households in the region allows us to estimate the proportion of children with diarrhea who consulted at a health structure. Model fit and future projections are necessarily particular to a given model; thus, where there are competing models for the underlying epidemiology an ensemble approach can account for that uncertainty. We compare our results across several variants of Susceptible-Infectious-Recovered (SIR) compartmental models to quantify the impact of model-ing assumptions on our estimates. Model-specific parameters are estimated by Bayesian inference using Markov chain Monte Carlo. We then use Bayesian model averaging to generate ensemble estimates of the current dynamics, including estimates of R0, the burden of infection in the region, as well as the impact of vaccination on both the short-term dynamics and the long-term reduction of rotavirus incidence under varying levels of coverage. The ensemble of models predicts that the current burden of severe rotavirus disease is 2.9 to 4.1% of the population each year and that a 2-dose vaccine schedule achieving 70% coverage could reduce burden by 37-43%.

BackgroundIndividual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines.MethodsWe systematically identified publications in Web of Science and PubMed from 2006-2015 based on title/abstract/keywords screening (and full-text if necessary) to retrieve topics, modeling purposes and general specifications. We extracted detailed modeling features from papers on established vaccine-preventable childhood diseases based on full-text screening.ResultsWe identified 698 papers, which applied an IBM for infectious disease transmission, and listed these in a reference database, describing their general characteristics. The diversity of disease-topics and overall publication frequency have increased over time (38 to 115 annual publications from 2006 to 2015). The inclusion of intervention strategies (8 to 52) and economic consequences (1 to 20) are increasing, to the detriment of purely theoretical explorations. Unfortunately, terminology used to describe IBMs is inconsistent and ambiguous. We retrieved 24 studies on a vaccine-preventable childhood disease (covering 7 different diseases), with publication frequency increasing from the first such study published in 2008. IBMs have been useful to explore heterogeneous between- and within-host interactions, but combined applications are still sparse. The amount of missing information on model characteristics and study design is remarkable.ConclusionsIBMs are suited to combine heterogeneous within- and between-host interactions, which offers many opportunities, especially to analyze targeted interventions for endemic infections. We advocate the exchange of (open-source) platforms and stress the need for consistent “branding”. Using (existing) conventions and reporting protocols would stimulate cross-fertilization between research groups and fields, and ultimately policy making in decades to come.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-017-2699-8) contains supplementary material, which is available to authorized users.

Summary paragraph 34Plants acquire carbon through photosynthesis to sustain biomass production, autotrophic 35 respiration, and production of non-structural compounds for multiple purposes 1 . The fraction 36 of photosynthetic production used for biomass production, the biomass production 37 efficiency 2 , is a key determinant of the conversion of solar energy to biomass. In forest 38 ecosystems, biomass production efficiency was suggested to be related to site fertility 2 . Here 39 we present a global database of biomass production efficiency from 131 sites compiled from 40 individual studies using harvest, biometric, eddy covariance, or process-based model 41 estimates of production -dominated, however, by data from Europe and North America. We 42show that instead of site fertility, ecosystem management is the key factor that controls 43 biomass production efficiency in terrestrial ecosystems. In addition, in natural forests, 44 grasslands, tundra, boreal peatlands and marshes biomass production efficiency is 45 independent of vegetation, environmental and climatic drivers. This similarity of biomass 46 production efficiency across natural ecosystem types suggests that the ratio of biomass 47 production to gross primary productivity is constant across natural ecosystems. We suggest 48 that plant adaptation results in similar growth efficiency in high and low fertility natural 49 systems, but that nutrient influxes under managed conditions favour a shift to carbon 50 investment from the belowground flux of non-structural compounds to aboveground biomass. 51 52 53 Main text 54The fraction of gross primary production (GPP) used for biomass production (BP) of 55 terrestrial ecosystems has recently been coined biomass production efficiency (BPE) 2 . BPE is 56 typically used as a proxy for the carbon-use efficiency or NPP-to-GPP ratio, where NPP refers 57 to net primary production i.e. BP plus the production of non-structural organic compounds 1 . 58 4 Current knowledge about BPE is mainly derived from research on forests. Earlier work 59 reported BPE to be conservative across forests 3 , whereas more recent syntheses suggest high 60 inter-site variability 2,4 . The variation in BPE was first attributed to vegetation properties 61 (forest age) and climate variables 4 . More recently, it was shown that forest BPE in a range of 62 natural and managed sites was correlated with site fertility, with management as a secondary 63 BPE driver 2 . 64Fertility and management are strongly correlated as management enhances 65 productivity by increasing plant-available resources, including nutrients. For instance, 66 fertilization of grasslands directly increases the ecosystem nutrient stock, whereas forest 67 thinning indirectly increases nutrient availability at the tree level by reducing plant-plant 68 competition. In addition, fertile sites are more likely than infertile sites to be managed. 69Atmospheric deposition of nutrients, especially nitrogen (N), might further complicate the 70 relationship between BPE, fertility and ...

The detection of human papillomavirus (HPV) DNA in urine, a specimen easily obtained by a non-invasive self-sampling method, has been the subject of a considerable number of studies. This review provides an overview of 41 published studies; assesses how different methods and settings may contribute to the sometimes contradictory outcomes; and discusses the potential relevance of using urine samples in vaccine trials, disease surveillance, epidemiological studies, and specific settings of cervical cancer screening. Urine sampling, storage conditions, sample preparation, DNA extraction, and DNA amplification may all have an important impact on HPV DNA detection and the form of viral DNA that is detected. Possible trends in HPV DNA prevalence in urine could be inferred from the presence of risk factors or the diagnosis of cervical lesions. HPV DNA detection in urine is feasible and may become a useful tool but necessitates further improvement and standardization.

for identifying the sources of uncertainty that influence results most are also described. Besides guiding analysts, the guide and checklist may be useful to decision makers who need to assess how well uncertainty has been accounted for in a decision-analytic model before using the results to make a decision.