Epidemiology: Dimensions of Superspreading

University of Oxford, Oxford, England, United Kingdom
Nature (Impact Factor: 41.46). 12/2005; 438(7066):293-5. DOI: 10.1038/438293a
Source: PubMed


Analyses of contact-tracing data on the spread of infectious disease, combined with mathematical models, show that control measures require better knowledge of variability in individual infectiousness.

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    • "Comparison of a new real-time quantitative PCR (qPCR) which is specific for the envelope gene's transmembrane region has been done with a competitive ELISA (cELISA). Such comparative test has led to the conclusion that qPCR may be used as a supplemental tool for diagnosis and for measuring the load of the virus [71, 145]. "
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    ABSTRACT: Irrespective of aetiology, infectious respiratory diseases of sheep and goats contribute to 5.6 percent of the total diseases of small ruminants. These infectious respiratory disorders are divided into two groups: the diseases of upper respiratory tract, namely, nasal myiasis and enzootic nasal tumors, and diseases of lower respiratory tract, namely, peste des petits ruminants (PPR), parainfluenza, Pasteurellosis, Ovine progressive pneumonia, mycoplasmosis, caprine arthritis encephalitis virus, caseous lymphadenitis, verminous pneumonia, and many others. Depending upon aetiology, many of them are acute and fatal in nature. Early, rapid, and specific diagnosis of such diseases holds great importance to reduce the losses. The advanced enzyme-linked immunosorbent assays (ELISAs) for the detection of antigen as well as antibodies directly from the samples and molecular diagnostic assays along with microsatellites comprehensively assist in diagnosis as well as treatment and epidemiological studies. The present review discusses the advancements made in the diagnosis of common infectious respiratory diseases of sheep and goats. It would update the knowledge and help in adapting and implementing appropriate, timely, and confirmatory diagnostic procedures. Moreover, it would assist in designing appropriate prevention protocols and devising suitable control strategies to overcome respiratory diseases and alleviate the economic losses.
    Veterinary Medicine International 06/2014; Volume 2014 Special Issue(Article ID 508304):16 pages. DOI:10.1155/2014/508304
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    • "A patient who travels away from home to low-lying areas where malaria is endemic might have the most probable effect on malaria spatiotemporal patterns in high-altitude villages. Travel often increases exposure to infectious disease and can affect disease prevention and control efforts [36]. Travel has also contributed to the global spread of malaria during the history of humankind [37]. "
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    ABSTRACT: Background Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Methods Spatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit. Results Malaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages. Conclusion The study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.
    Malaria Journal 06/2014; 13(1):223. DOI:10.1186/1475-2875-13-223 · 3.11 Impact Factor
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    • "To our knowledge the relationship between host-to-host transmission heterogeneity and host genetic diversity has not been experimentally examined in IHNV or other viral systems. Ultimately, heterogeneity in transmission between individuals can drastically affect the accuracy of estimates of important epidemiological parameters such as the mean number of infections caused by an infected individual at a population level, or R o (Capparelli et al., 2009; Fraser et al., 2007; Galvani and May, 2005; Lloyd-Smith et al., 2005; Matthews et al., 2006; Woolhouse et al., 1997). As such, the results from this study support the work of other groups suggesting that the processes regulating natural between-host variation in pathogen burdens are more complex than previously assumed, and epidemiological models of pathogen transmission may benefit from incorporating pathogen-load variation, even in host populations with low genetic diversity (Capparelli et al., 2009; Fraser et al., 2007; Lloyd-Smith et al., 2005; Matthews et al., 2006; Woolhouse et al., 1997). "
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    ABSTRACT: Little is known about the factors that drive the high levels of between-host variation in pathogen burden that are frequently observed in viral infections. Here, two factors thought to impact viral load variability, host genetic diversity and stochastic processes linked with viral entry into the host, were examined. This work was conducted with the aquatic vertebrate virus, Infectious hematopoietic necrosis virus (IHNV), in its natural host, rainbow trout. It was found that in controlled in vivo infections of IHNV, a suggestive trend of reduced between-fish viral load variation was observed in a clonal population of isogenic trout compared to a genetically diverse population of out-bred trout. However, this trend was not statistically significant for any of the four viral genotypes examined, and high levels of fish-to-fish variation persisted even in the isogenic trout population. A decrease in fish-to-fish viral load variation was also observed in virus injection challenges that bypassed the host entry step, compared to fish exposed to the virus through the natural water-borne immersion route of infection. This trend was significant for three of the four virus genotypes examined and suggests host entry may play a role in viral load variability. However, high levels of viral load variation also remained in the injection challenges. Together, these results indicate that although host genetic diversity and viral entry may play some role in between-fish viral load variation, they are not major factors. Other biological and non-biological parameters that may influence viral load variation are discussed.
    Virus Research 01/2012; 165(1):71-80. DOI:10.1016/j.virusres.2012.01.010 · 2.32 Impact Factor
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