49 research outputs found
Reframing Optimal Control Problems for Infectious Disease Management in Low-Income Countries
Optimal control theory can be a useful tool to identify the best strategies for the management of infectious diseases. In most of the applications to disease control with ordinary differential equations, the objective functional to be optimized is formulated in monetary terms as the sum of intervention costs and the cost associated with the burden of disease. We present alternate formulations that express epidemiological outcomes via health metrics and reframe the problem to include features such as budget constraints and epidemiological targets. These alternate formulations are illustrated with a compartmental cholera model. The alternate formulations permit us to better explore the sensitivity of the optimal control solutions to changes in available budget or the desired epidemiological target. We also discuss some limitations of comprehensive cost assessment in epidemiology
Seasonality of Influenza A(H3N2) Virus: A Hong Kong Perspective (1997â2006)
BACKGROUND: The underlying basis for the seasonality of influenza A viruses is still uncertain. Phylogenetic studies investigated this phenomenon but have lacked sequences from more subtropical and tropical regions, particularly from Southeast Asia. METHODOLOGY/PRINCIPAL FINDINGS: 281 complete hemagglutinin (HA) and neuraminidase (NA) sequences were obtained from influenza A(H3N2) viruses, collected over 10 years (1997-2006) from Hong Kong. These dated sequences were analyzed with influenza A(H3N2) vaccine strain sequences (Syd/5/97, Mos/10/99, Fuj/411/02, Cal/7/04) and 315 other publicly available dated sequences from elsewhere, worldwide. In addition, the NA sequence alignment was inspected for the presence of any naturally occurring, known, neuraminidase inhibitor (NAI) resistance-associated amino acid mutations (R292K and E119V). Before 2001, the Hong Kong HA and NA sequences clustered more closely with the older vaccine sequences (Syd/5/97, Mos/10/99) than did sequences from elsewhere. After 2001, this trend reversed with significant clusters containing HA and NA sequences from different locations, isolated at different times, suggesting that viral migration may account for much of the influenza A(H3N2) seasonality during this 10-year period. However, at least one example from Hong Kong was found suggesting that in some years, influenza A(H3N2) viruses may persist in the same location, perhaps continuing to circulate, sub-clinically, at low levels between seasons, to re-emerge in the influenza season the following year, relatively unchanged. None of these Hong Kong influenza A(H3N2) NA sequences contained any of the known NAI-resistance associated mutations. CONCLUSIONS/SIGNIFICANCE: The seasonality of influenza A(H3N2) may be largely due to global migration, with similar viruses appearing in different countries at different times. However, occasionally, some viruses may remain within a single location and continue to circulate within that population, to re-emerge during the next influenza season, with relatively little genetic change. Naturally occurring NAI resistance mutations were absent or, at least, very rare in this population
Integration of satellite remote sensing data in ecosystem modelling at local scales: Practices and trends
1. Spatiotemporal ecological modelling of terrestrial ecosystems relies on climatological and biophysical Earth observations. Due to their increasing availability, global coverage, frequent acquisition and high spatial resolution, satellite remote sensing (SRS) products are frequently integrated to in situ data in the development of ecosystem models (EMs) quantifying the interaction among the vegetation component and the hydrological, energy and nutrient cycles. This review highlights the main advances achieved in the last decade in combining SRS data with EMs, with particular attention to the challenges modellers face for applications at local scales (e.g. small watersheds).
2. We critically review the literature on progress made towards integration of SRS data into terrestrial EMs: (1) as input to define model drivers; (2) as reference to validate model results; and (3) as a tool to sequentially update the state variables, and to quantify and reduce model uncertainty.
3. The number of applications provided in the literature shows that EMs may profit greatly from the inclusion of spatial parameters and forcings provided by vegetation and climaticârelated SRS products. Limiting factors for the application of such models to local scales are: (1) mismatch between the resolution of SRS products and model grid; (2) unavailability of specific products in free and public online repositories; (3) temporal gaps in SRS data; and (4) quantification of model and measurement uncertainties. This review provides examples of possible solutions adopted in recent literature, with particular reference to the spatiotemporal scales of analysis and data accuracy. We propose that analysis methods such as stochastic downscaling techniques and multiâsensor/multiâplatform fusion approaches are necessary to improve the quality of SRS data for local applications. Moreover, we suggest coupling models with data assimilation techniques to improve their forecast abilities.
4. This review encourages the use of SRS data in EMs for local applications, and underlines the necessity for a closer collaboration among EM developers and remote sensing scientists. With more upcoming satellite missions, especially the Sentinel platforms, concerted efforts to further integrate SRS into modelling are in great demand and these types of applications will certainly proliferate
Biomassa radicular da cultura de cana-de-açĂșcar em sistema convencional e plantio direto com e sem calcĂĄrio
Getting a free ride on poultry farms: how highly pathogenic avian influenza may persist in spite of its virulence
Within-host mechanisms of immune regulation explain the contrasting dynamics of two helminth species in both single and dual infections
Variation in the intensity and duration of infections is often driven by variation in the network and strength of host immune responses. While many of the immune mechanisms and components are known for parasitic helminths, how these relationships change from single to multiple infections and impact helminth dynamics remains largely unclear. Here, we used laboratory data from a rabbit-helminth system and developed a within-host model of infection to investigate different scenarios of immune regulation in rabbits infected with one or two helminth species. Model selection suggests that the immunological pathways activated against Trichostrongylus retortaeformis and Graphidium strigosum are similar. However, differences in the strength of these immune signals lead to the contrasting dynamics of infections, where the first parasite is rapidly cleared and the latter persists with high intensities. In addition to the reactions identified in single infections, rabbits with both helminths also activate new pathways that asymmetrically affect the dynamics of the two species. These new signals alter the intensities but not the general trend of the infections. The type of interactions described can be expected in many other host-helminth systems. Our immune framework is flexible enough to capture different mechanisms and their complexity, and provides essential insights to the understanding of multi-helminth infections
Shifts in the thermal niche of fruit trees under climate change: The case of peach cultivation in France
Climate influences plant phenological traits, thus playing a key role in defining the geographical range of crops. Foreseeing the impact of climate change on fruit trees is essential to inform policy decisions to guide the adaptation to new climatic conditions. To this end, we propose and use a phenological process-based model to assess the impacts of climate change upon the phenology, the suitability and the distribution of economically important cultivars of peach (Prunus persica), across the entire continental France. The model combines temperature dependent sub-models of dormancy, blooming, fruit survival and ripening, using chilling units, forcing units, frost occurrence and growing degree days, respectively. We find that climate change could have divergent impacts on peach production. On the one hand, blooming would occur earlier, warmer temperatures would decrease spring frost occurrence and fruit ripening would be easily achieved before the start of fall. On the other hand, milder winters would impede the plant buds from breaking endodormancy, with consequent abnormal patterns of fruit development or even blooming failure. This latter impact would dramatically shift the geographic range of sites where peach production will be profitable. This shift would mainly be from the south of France (Languedoc-Roussillon, RhĂŽne-Alpes and Provence-Alpes-CĂŽte d'Azur), to northwestern areas where the winter chilling requirement would still be fulfilled. Our study provides novel insights for understanding and forecasting climate change impacts on peach phenology and it is the first framework that maps the ecological thermal niche of peach at a national level