Substantiating freedom from parasitic infection by combining transmission model predictions with disease surveys.
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ABSTRACT:
SUBMITTER: Michael E
PROVIDER: S-EPMC6193962 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe fox tapeworm Echinococcus multilocularis has foxes and other canids as definitive host and rodents as intermediate hosts. However, most mammals can be accidental intermediate hosts and the larval stage may cause serious disease in humans. The parasite has never been detected in Sweden, Finland and mainland Norway. All three countries require currently an anthelminthic treatment for dogs and cats prior to entry in order to prevent introduction of the parasite. Documentation of freedom from E. multilocularis is necessary for justification of the present import requirements.MethodsThe probability that Sweden, Finland and mainland Norway were free from E. multilocularis and the sensitivity of the surveillance systems were estimated using scenario trees. Surveillance data from five animal species were included in the study: red fox (Vulpes vulpes), raccoon dog (Nyctereutes procyonoides), domestic pig, wild boar (Sus scrofa) and voles and lemmings (Arvicolinae).ResultsThe cumulative probability of freedom from EM in December 2009 was high in all three countries, 0.98 (95% CI 0.96-0.99) in Finland and 0.99 (0.97-0.995) in Sweden and 0.98 (0.95-0.99) in Norway.ConclusionsResults from the model confirm that there is a high probability that in 2009 the countries were free from E. multilocularis. The sensitivity analyses showed that the choice of the design prevalences in different infected populations was influential. Therefore more knowledge on expected prevalences for E. multilocularis in infected populations of different species is desirable to reduce residual uncertainty of the results.
| S-EPMC3049754 | biostudies-literature
Project description:Temperature constrains the transmission of many pathogens. Interventions that target temperature-sensitive life stages, such as vector control measures that kill intermediate hosts, could shift the thermal optimum of transmission, thereby altering seasonal disease dynamics and rendering interventions less effective at certain times of the year and with global climate change. To test these hypotheses, we integrated an epidemiological model of schistosomiasis with empirically determined temperature-dependent traits of the human parasite Schistosoma mansoni and its intermediate snail host (Biomphalaria spp.). We show that transmission risk peaks at 21.7 °C (Topt ), and simulated interventions targeting snails and free-living parasite larvae increased Topt by up to 1.3 °C because intervention-related mortality overrode thermal constraints on transmission. This Topt shift suggests that snail control is more effective at lower temperatures, and global climate change will increase schistosomiasis risk in regions that move closer to Topt Considering regional transmission phenologies and timing of interventions when local conditions approach Topt will maximize human health outcomes.
| S-EPMC7980429 | biostudies-literature
Project description:Background and aimsSince the advent of molecular phylogenetics, numerous attempts have been made to infer the evolutionary trajectories of chromosome numbers on DNA phylogenies. Ideally, such inferences should be evaluated against cytogenetic data. Towards this goal, we carried out phylogenetic modelling of chromosome number change and fluorescence in situ hybridization (FISH) in a medium sized genus of Araceae to elucidate if data from chromosomal markers would support maximum likelihood-inferred changes in chromosome numbers among close relatives. Typhonium, the focal genus, includes species with 2n = 65 and 2n = 8, the lowest known count in the family.MethodsA phylogeny from nuclear and plastid sequences (96 taxa, 4252 nucleotides) and counts for all included species (15 of them first reported here) were used to model chromosome number evolution, assuming discrete events, such as polyploidization and descending or ascending dysploidy, occurring at different rates. FISH with three probes (5S rDNA, 45S rDNA and Arabidopsis-like telomeres) was performed on ten species with 2n = 8 to 2n = 24.Key resultsThe best-fitting models assume numerous past chromosome number reductions. Of the species analysed with FISH, the two with the lowest chromosome numbers contained interstitial telomeric signals (Its), which together with the phylogeny and modelling indicates decreasing dysploidy as an explanation for the low numbers. A model-inferred polyploidization in another species is matched by an increase in rDNA sites.ConclusionsThe combination of a densely sampled phylogeny, ancestral state modelling and FISH revealed that the species with n = 4 is highly derived, with the FISH data pointing to a Robertsonian fusion-like chromosome rearrangement in the ancestor of this species.
| S-EPMC3936593 | biostudies-literature
Project description:Environmental effects on the transmission of many parasitic diseases are well recognized, but the role of specific factors like climate and agricultural practices in modulating transmission is seldom characterized quantitatively. Based on studies of Schistosoma japonicum transmission in irrigated agricultural environments in western China, a mathematical model was used to quantify environmental impacts on transmission intensity. The model was calibrated by using field data from intervention studies in three villages and simulated to predict the effects of alternative control options. Both the results of these interventions and earlier epidemiological findings confirm the central role of environmental factors, particularly those relating to snail habitat and agricultural and sanitation practices. Moreover, the findings indicate the inadequacy of current niclosamide-praziquantel strategies alone to achieve sustainable interruption of transmission in some endemic areas. More generally, the analysis suggests a village-specific index of transmission potential and how this potential is modulated by time-varying factors, including climatological variables, seasonal water-contact patterns, and irrigation practices. These time-variable factors, a village's internal potential, and its connectedness to its neighbors provide a framework for evaluating the likelihood of sustained schistosomiasis transmission and suggest an approach to quantifying the role of environmental factors for other parasitic diseases.
| S-EPMC1852328 | biostudies-literature
Project description:HIV-1 pol sequences obtained through baseline drug resistance testing of patients newly diagnosed between 2013 and 2017 were analyzed for genetic similarity. For 927 patients the information on genetic similarity was combined with demographic data and with information on the recency of infection. Overall, 48.3% of the patients were genetically linked with 11.4% belonging to a pair and 36.9% involved in a cluster of ?3 members. The percentage of early diagnosed (?4 months after infection) was 28.6%. Patients of Belgian origin were more frequently involved in transmission clusters (49.7% compared to 15.3%) and diagnosed earlier (37.4% compared to 12.2%) than patients of Sub-Saharan African origin. Of the infections reported to be locally acquired, 69.5% were linked (14.1% paired and 55.4% in a cluster). Equal parts of early and late diagnosed individuals (59.9% and 52.4%, respectively) were involved in clusters. The identification of a genetically linked individual for the majority of locally infected patients suggests a high rate of diagnosis in this population. Diagnosis however is often delayed for >4 months after infection increasing the opportunities for onward transmission. Prevention of local infection should focus on earlier diagnosis and protection of the still uninfected members of sexual networks with human immunodeficiency virus (HIV)-infected members.
| S-EPMC6950120 | biostudies-literature
Project description:We illustrate the extraordinary potential of the (far-IR) Origins Survey Spectrometer (OSS) on board the Origins Space Telescope (OST) to address a variety of open issues on the co-evolution of galaxies and AGNs. We present predictions for blind surveys, each of 1000 h, with different mapped areas (a shallow survey covering an area of 10 deg2 and a deep survey of 1 deg2) and two different concepts of the OST/OSS: with a 5.9m telescope (Concept 2, our reference configuration) and with a 9.1 m telescope (Concept 1, previous configuration). In 1000 h, surveys with the reference concept will detect from ~ 1.9 × 106 to ~ 8.7 × 106 lines from ~ 4.8 × 105-2.7 × 106 star-forming galaxies and from ~ 1.4 × 104 to ~ 3.8 × 104 lines from ~ 1.3 × 104-3.5 × 104 AGNs. The shallow survey will detect substantially more sources than the deep one; the advantage of the latter in pushing detections to lower luminosities/higher redshifts turns out to be quite limited. The OST/OSS will reach, in the same observing time, line fluxes more than one order of magnitude fainter than the SPICA/SMI and will cover a much broader redshift range. In particular it will detect tens of thousands of galaxies at z ? 5, beyond the reach of that instrument. The polycyclic aromatic hydrocarbons lines are potentially bright enough to allow the detection of hundreds of thousands of star-forming galaxies up to z ~ 8.5, i.e. all the way through the re-ionization epoch. The proposed surveys will allow us to explore the galaxy-AGN co-evolution up to z ~ 5.5 - 6 with very good statistics. OST Concept 1 does not offer significant advantages for the scientific goals presented here.
| S-EPMC7440398 | biostudies-literature
Project description:RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM) approach was used to quantitatively model RNA interference activities.Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams) and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative.The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid sequences can be found at the following site: ftp://scitoolsftp.idtdna.com/SEQ2SVM/.
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Project description:Since the turn of the century, the global community has made great progress towards the elimination of gambiense human African trypanosomiasis (HAT). Elimination programs, primarily relying on screening and treatment campaigns, have also created a rich database of HAT epidemiology. Mathematical models calibrated with these data can help to fill remaining gaps in our understanding of HAT transmission dynamics, including key operational research questions such as whether integrating vector control with current intervention strategies is needed to achieve HAT elimination. Here we explore, via an ensemble of models and simulation studies, how including or not disease stage data, or using more updated data sets affect model predictions of future control strategies.
| S-EPMC6994134 | biostudies-literature
Project description:Guinea worm disease (GWD) is both a neglected tropical disease and an environmentally driven infectious disease. Environmentally driven infectious diseases remain one of the biggest health threats for human welfare in developing countries and the threat is increased by the looming danger of climate change. In this paper we present a multiscale model of GWD that integrates the within-host scale and the between-host scale. The model is used to concurrently examine the interactions between the three organisms that are implicated in natural cases of GWD transmission, the copepod vector, the human host, and the protozoan worm parasite (Dracunculus medinensis), and identify their epidemiological roles. The results of the study (through sensitivity analysis of R0) show that the most efficient elimination strategy for GWD at between-host scale is to give highest priority to copepod vector control by killing the copepods in drinking water (the intermediate host) by applying chemical treatments (e.g., temephos, an organophosphate). This strategy should be complemented by health education to ensure that greater numbers of individuals and communities adopt behavioural practices such as voluntary reporting of GWD cases, prevention of GWD patients from entering drinking water bodies, regular use of water from safe water sources, and, in the absence of such water sources, filtering or boiling water before drinking. Taking into account the fact that there is no drug or vaccine for GWD (interventions which operate at within-host scale), the results of our study show that the development of a drug that kills female worms at within-host scale would have the highest impact at this scale domain with possible population level benefits that include prevention of morbidity and prevention of transmission.
| S-EPMC5541828 | biostudies-other
Project description:In the last three decades, the appreciation of the role of infections in cancer aetiology has greatly expanded. Among the 13 million new cancer cases that occurred worldwide in 2008, around 2 million (16%) were attributable to infections. Concurrently, the approach to prevention of infection-related cancers is shifting from cancer control to infection control, for example, vaccination and the detection of infected individuals. In support of this change, the use of infection transmission models has entered the field of infection-related cancer epidemiology. These models are useful to understand the infection transmission processes, to estimate the key parameters that govern the spread of infection, and to project the potential impact of different preventive measures. However, the concepts, terminology, and methods used to study infection transmission are not yet well known in the domain of cancer epidemiology. This review aims to concisely illustrate the main principles of transmission dynamics, the basic structure of infection transmission models, and their use in combination with empirical data. We also briefly summarise models of carcinogenesis and discuss their specificities and possible integration with models of infection natural history.
| S-EPMC3887312 | biostudies-other