Relationship between clinical signs and transmission of an infectious disease and the implications for control.
Ontology highlight
ABSTRACT:
SUBMITTER: Charleston B
PROVIDER: S-EPMC5844461 | biostudies-literature | 2011 May
REPOSITORIES: biostudies-literature
Publications
Relationship between clinical signs and transmission of an infectious disease and the implications for control.
Charleston Bryan B Bankowski Bartlomies M BM Gubbins Simon S Chase-Topping Margo E ME Schley David D Howey Richard R Barnett Paul V PV Gibson Debi D Juleff Nicholas D ND Woolhouse Mark E J ME
Science (New York, N.Y.) 20110501 6030
Control of many infectious diseases relies on the detection of clinical cases and the isolation, removal, or treatment of cases and their contacts. The success of such "reactive" strategies is influenced by the fraction of transmission occurring before signs appear. We performed experimental studies of foot-and-mouth disease transmission in cattle and estimated this fraction at less than half the value expected from detecting virus in body fluids, the standard proxy measure of infectiousness. Th ...[more]
Similar Datasets
Project description:For infectious pathogens such as Staphylococcus aureus and Streptococcus pneumoniae, some hosts may carry the pathogen and transmit it to others, yet display no symptoms themselves. These asymptomatic carriers contribute to the spread of disease but go largely undetected and can therefore undermine efforts to control transmission. Understanding the natural history of carriage and its relationship to disease is important for the design of effective interventions to control transmission. Mathematical models of infectious diseases are frequently used to inform decisions about control and should therefore accurately capture the role played by asymptomatic carriers. In practice, incorporating asymptomatic carriers into models is challenging due to the sparsity of direct evidence. This absence of data leads to uncertainty in estimates of model parameters and, more fundamentally, in the selection of an appropriate model structure. To assess the implications of this uncertainty, we systematically reviewed published models of carriage and propose a new model of disease transmission with asymptomatic carriage. Analysis of our model shows how different assumptions about the role of asymptomatic carriers can lead to different conclusions about the transmission and control of disease. Critically, selecting an inappropriate model structure, even when parameters are correctly estimated, may lead to over- or under-estimates of intervention effectiveness. Our results provide a more complete understanding of the role of asymptomatic carriers in transmission and highlight the importance of accurately incorporating carriers into models used to make decisions about disease control.
| S-EPMC5830799 | biostudies-literature
Project description:PurposeThe percentage of children who are symptomatic has been shown to increase with the number of signs of convergence insufficiency (CI). Our goal was to investigate whether there is a relationship between the severity of the clinical signs of CI and symptom level reported in children with a three-sign symptomatic CI.MethodsThe Convergence Insufficiency Treatment Trial enrolled 221 children with symptomatic CI from ages 9 to 17 years. Inclusion criteria included the following three signs of CI: (1) exophoria at near at least 4Δ greater than at distance, (2) insufficient positive fusional vergence (PFV) at near, and (3) a receded near point of convergence (NPC) of 6 cm break or greater. The relationships between the severity of each sign of CI (mild, moderate, and severe) and the level of symptoms as measured by the Convergence Insufficiency Symptom Survey (CISS) at baseline were evaluated.ResultsMean CISS scores were not significantly different between mild, moderate, and severe exophoria (p = 0.60), PFV blur (p = 0.99), Sheard's criterion (p = 0.89), or NPC break (p = 0.84). There was also no difference between the frequency of subjects scoring at mild, moderate, or severe levels on the CISS and the severity of each sign of CI. Correlations between individual clinical signs and the CISS score were very low and not statistically significant.ConclusionsAmong symptomatic children with a CISS score of 16 or higher and three clinical signs of CI, there is no further association between the severity of the clinical signs and their level of symptoms.
| S-EPMC3929100 | biostudies-literature
Project description:The control of emergence and spread of infectious diseases depends critically on the details of the genetic makeup of pathogens and hosts, their immunological, behavioral and ecological traits, and the pattern of temporal and spatial contacts among the age/stage-classes of susceptible and infectious host individuals.We show that failing to acknowledge the existence of heterogeneities in the transmission rate among age/stage-classes can make traditional eradication and control strategies ineffective, and in some cases, policies aimed at controlling pathogen emergence can even increase disease incidence in the host. When control strategies target for reduction in numbers those subsets of the population that effectively limit the production of new susceptible individuals, then control can produce a flush of new susceptibles entering the population. The availability of a new cohort of susceptibles may actually increase disease incidence. We illustrate these general points using Classical Swine Fever as a reference disease.Negative effects of culling are robust to alternative formulations of epidemiological processes and underline the importance of better assessing transmission structure in the design of wildlife disease control strategies.
| S-EPMC1945090 | biostudies-literature
Project description:IntroductionThis systematic review examines the relationship between blood loss and clinical signs and explores its use to trigger clinical interventions in the management of obstetric haemorrhage.MethodsA systematic review of the literature was carried out using a comprehensive search strategy to identify studies presenting data on the relationship of clinical signs & symptoms and blood loss. Methodological quality was assessed using the STROBE checklist and the general guidelines of MOOSE.Results30 studies were included and five were performed in women with pregnancy-related haemorrhage (other studies were carried in non-obstetric populations). Heart rate (HR), systolic blood pressure (SBP) and shock index were the parameters most frequently studied. An association between blood loss and HR changes was observed in 22 out of 24 studies, and between blood loss and SBP was observed in 17 out of 23 studies. An association was found in all papers reporting on the relationship of shock index and blood loss. Seven studies have used Receiver Operating Characteristic Curves to determine the accuracy of clinical signs in predicting blood loss. In those studies the AUC ranged from 0.56 to 0.74 for HR, from 0.56 to 0.79 for SBP and from 0.77 to 0.84 for shock index. In some studies, HR, SBP and shock index were associated with increased mortality.ConclusionWe found a substantial variability in the relationship between blood loss and clinical signs, making it difficult to establish specific cut-off points for clinical signs that could be used as triggers for clinical interventions. However, the shock index can be an accurate indicator of compensatory changes in the cardiovascular system due to blood loss. Considering that most of the evidence included in this systematic review is derived from studies in non-obstetric populations, further research on the use of the shock index in obstetric populations is needed.
| S-EPMC3590203 | biostudies-literature
Project description:BackgroundThe speed of vaccine development has been a singular achievement during the COVID-19 pandemic, although uptake has not been universal. Vaccine opponents often frame their opposition in terms of the rights of the unvaccinated. We sought to explore the impact of mixing of vaccinated and unvaccinated populations on risk of SARS-CoV-2 infection among vaccinated people.MethodsWe constructed a simple susceptible-infectious-recovered compartmental model of a respiratory infectious disease with 2 connected subpopulations: people who were vaccinated and those who were unvaccinated. We simulated a spectrum of patterns of mixing between vaccinated and unvaccinated groups that ranged from random mixing to complete like-with-like mixing (complete assortativity), in which people have contact exclusively with others with the same vaccination status. We evaluated the dynamics of an epidemic within each subgroup and in the population as a whole.ResultsWe found that the risk of infection was markedly higher among unvaccinated people than among vaccinated people under all mixing assumptions. The contact-adjusted contribution of unvaccinated people to infection risk was disproportionate, with unvaccinated people contributing to infections among those who were vaccinated at a rate higher than would have been expected based on contact numbers alone. We found that as like-with-like mixing increased, attack rates among vaccinated people decreased from 15% to 10% (and increased from 62% to 79% among unvaccinated people), but the contact-adjusted contribution to risk among vaccinated people derived from contact with unvaccinated people increased.InterpretationAlthough risk associated with avoiding vaccination during a virulent pandemic accrues chiefly to people who are unvaccinated, their choices affect risk of viral infection among those who are vaccinated in a manner that is disproportionate to the portion of unvaccinated people in the population.
| S-EPMC9054088 | biostudies-literature
Project description:BackgroundEstimating infectious disease parameters such as the serial interval (time between symptom onset in primary and secondary cases) and reproductive number (average number of secondary cases produced by a primary case) are important in understanding infectious disease dynamics. Many estimation methods require linking cases by direct transmission, a difficult task for most diseases.MethodsUsing a subset of cases with detailed genetic and/or contact investigation data to develop a training set of probable transmission events, we build a model to estimate the relative transmission probability for all case-pairs from demographic, spatial and clinical data. Our method is based on naive Bayes, a machine learning classification algorithm which uses the observed frequencies in the training dataset to estimate the probability that a pair is linked given a set of covariates.ResultsIn simulations, we find that the probabilities estimated using genetic distance between cases to define training transmission events are able to distinguish between truly linked and unlinked pairs with high accuracy (area under the receiver operating curve value of 95%). Additionally, only a subset of the cases, 10-50% depending on sample size, need to have detailed genetic data for our method to perform well. We show how these probabilities can be used to estimate the average effective reproductive number and apply our method to a tuberculosis outbreak in Hamburg, Germany.ConclusionsOur method is a novel way to infer transmission dynamics in any dataset when only a subset of cases has rich contact investigation and/or genetic data.
| S-EPMC7394954 | biostudies-literature
Project description:The size and concentration of exhaled particles may influence respiratory infection transmission risk. We assessed variation in exhaled particle production between individuals, factors associated with high production and stability over time. We measured exhaled particle production during tidal breathing in a sample of 79 healthy volunteers, using optical particle counter technology. Repeat measurements (several months after baseline) were obtained for 37 of the 79 participants. Multilevel linear regression models of log transformed particle production measures were used to assess risk factors for high production. Stability between measurements over time was assessed using Lin's correlation coefficients. Ninety-nine percent of expired particles were <1?m in diameter. Considerable variation in exhaled particle production was observed between individuals and within individuals over time. Distribution of particle production was right skewed. Approximately 90% of individuals produce <150 particles per litre in normal breathing. A few individuals had measurements of over 1000 particles per litre (maximum 1456). Particle production increased with age (p<0.001) and was associated with high tree pollen counts. Particle production levels did not remain stable over time [rho 0.14 (95%CI -0.10, 0.38, p=0.238)]. Sub-micron particles conducive to airborne rather than droplet transmission form the great majority of exhaled particles in tidal breathing. There is a high level of variability between subjects but measurements are not stable over time. Production increases with age and may be influenced by airway inflammation caused by environmental irritants. Further research is needed to determine whether the observed variations in exhaled particle production affect transmission of respiratory infection.
| S-EPMC3901511 | biostudies-literature
Project description:IntroductionThe increase in international travel brought about by globalisation has enabled the rapid spread of emerging pathogens with epidemic and pandemic potential. While travel connectivity-based assessments may help understand patterns of travel network-mediated epidemics, such approaches are rarely carried out in sufficient detail for Oceania where air travel is the dominant method of transportation between countries.DesignTravel data from the Australian Bureau of Statistics, Stats NZ and the United Nations World Tourism Organization websites were used to calculate travel volumes in 2018 within Oceania and between Oceania and the rest of the world. The Infectious Disease Vulnerability Index (IDVI) was incorporated into the analysis as an indicator of each country's capacity to contain an outbreak. Travel networks were developed to assess the spread of infectious diseases (1) into and from Oceania, (2) within Oceania and (3) between each of the Pacific Island Countries and Territories (PICTs) and their most connected countries.ResultsOceania was highly connected to countries in Asia, Europe and North America. Australia, New Zealand and several PICTs were highly connected to the USA and the UK (least vulnerable countries for outbreaks based on the IDVI), and to China (intermediate low vulnerable country). High variability was also observed between the PICTs in the geographical distribution of their international connections. The PICTs with the highest number of international connections were Fiji, French Polynesia, Guam and Papua New Guinea.ConclusionTravel connectivity assessments may help to accurately stratify the risk of infectious disease importation and outbreaks in countries depending on disease transmission in other parts of the world. This information is essential to track future requirements for scaling up and targeting outbreak surveillance and control strategies in Oceania.
| S-EPMC8361703 | biostudies-literature
Project description:The mathematical modeling of ecological interactions is an essential tool in predicting the behavior of complex systems across landscapes. The scientific literature is growing with examples of models used to explore predator-prey interactions, resource selection, population growth, and dynamics of disease transmission. These models provide managers with an efficient alternative means of testing new management and control strategies without resorting to empirical testing that is often costly, time-consuming, and impractical. This chapter presents a review of four types of mathematical models used to understand and predict the spread of infectious diseases in wild animals: compartmental, metapopulation, spatial, and contact network models. Descriptions of each model’s uses and limitations are used to provide a look at the complexities involved in modeling the spread of diseases and the trade-offs that accompany selecting one modeling approach over another. Potential avenues for the improvement and use of these models in future studies are also discussed, as are specific examples of how each type of model has improved our understanding of infectious diseases in populations of wild animals.
| S-EPMC7123867 | biostudies-literature
Project description:BackgroundIn Thailand, rabies remains a neglected disease with authorities continuing to rely on human death statistics while ignoring the financial burden resulting from an enormous increase in post-exposure prophylaxis. Past attempts to conduct a mass dog vaccination and sterilization program have been limited to Bangkok city and have not been successful. We have used molecular epidemiology to define geographic localization of rabies virus phylogroups and their pattern of spread in Thailand.MethodsWe analyzed 239 nucleoprotein gene sequences from animal and human brain samples collected from all over Thailand between 1998 and 2002. We then reconstructed a phylogenetic tree correlating these data with geographical information.ResultsAll sequences formed a monophyletic tree of 2 distinct phylogroups, TH1 and TH2. Three subgroups were identified in the TH1 subgroup and were distributed in the middle region of the country. Eight subgroups of TH2 viruses were identified widely distributed throughout the country overlapping the TH1 territory. There was a correlation between human-dependent transportation routes and the distribution of virus.ConclusionInter-regional migration paths of the viruses might be correlated with translocation of dogs associated with humans. Interconnecting factors between human socioeconomic and population density might determine the transmission dynamics of virus in a rural-to-urban polarity. The presence of 2 or more rabies virus groups in a location might be indicative of a gene flow, reflecting a translocation of dogs within such region and adjacent areas. Different approaches may be required for rabies control based on the homo- or heterogeneity of the virus. Areas containing homogeneous virus populations should be targeted first. Control of dog movement associated with humans is essential.
| S-EPMC1184074 | biostudies-literature