Viggo Andreasen

Roskilde University, Roskilde, Zealand, Denmark

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Publications (51)171.28 Total impact

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    Full-text · Conference Paper · Dec 2015
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    ABSTRACT: Phenotypic variation is common in most pathogens, yet the mechanisms that maintain this diversity are still poorly understood. We asked whether continuous host variation in susceptibility helps maintain phenotypic variation, using experiments conducted with a baculovirus that infects gypsy moth (Lymantria dispar) larvae. We found that an empirically observed tradeoff between mean transmission rate and variation in transmission, which results from host heterogeneity, promotes long-term coexistence of two pathogen types in simulations of a population model. This tradeoff introduces an alternative strategy for the pathogen: a low-transmission, low-variability type can coexist with the high-transmission type favoured by classical non-heterogeneity models. In addition, this tradeoff can help explain the extensive phenotypic variation we observed in field-collected pathogen isolates, in traits affecting virus fitness including transmission and environmental persistence. Similar heterogeneity tradeoffs might be a general mechanism promoting phenotypic variation in any pathogen for which hosts vary continuously in susceptibility.
    No preview · Article · Sep 2015 · Ecology Letters
  • J Boel · M Søgaard · V Andreasen · J O Jarløv · M Arpi
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    ABSTRACT: When introducing new antibiotic guidelines for empirical treatment of bacteremia, it is imperative to evaluate the performance of the new guideline. We examined the utility of administrative data to evaluate the effect of new antibiotic guidelines and the prognostic impact of appropriate empirical treatment. We categorized 2,008 adult patients diagnosed with bacteremia between 2010 and 2012 according to whether they received cephalosporins or fluoroquinolones (old regimen) or not (new regimen). We used administrative data to extract individual level data on mortality, readmission, and appropriateness of treatment, and computed adjusted hazard ratios (HRs) and 95 % confidence intervals (CIs) for 30-day mortality and post-discharge readmission by regimen and appropriateness of treatment. In total, 945 (47.1 %) were treated by the old regimen and 1,063 (52.9 %) by the new. The median length of stay (8 days) did not differ by regimen and neither did the proportion of those receiving appropriate empirical treatment (84.1 % vs. 85.5 %). However, fewer patients with the new regimen were admitted to the intensive care unit (ICU; 3.8 % vs. 12.0 %) and they had lower 30-day mortality (16.4 % vs. 23.4 %). The adjusted 30-day mortality HR for appropriate versus inappropriate treatment was 0.79 (95 % CI 0.62-1.01) and 0.83 (95 % CI 0.66-1.05) for the new versus the old regimen. The HR for 30-day readmission for appropriate versus inappropriate treatment was 0.91 (95 % CI 0.73-1.13) and 1.05 (95 % CI 0.87-1.25) for the new versus the old regimen. This study demonstrates that administrative data can be useful for evaluating the effect and quality of new bacteremia treatment guidelines.
    No preview · Article · Apr 2015 · European Journal of Clinical Microbiology
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    Adam J Kucharski · Viggo Andreasen · Julia R Gog
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    ABSTRACT: Pathogens that consist of multiple antigenic variants are a serious public health concern. These infections, which include dengue virus, influenza and malaria, generate substantial morbidity and mortality. However, there are considerable theoretical challenges involved in modelling such infections. As well as describing the interaction between strains that occurs as a result cross-immunity and evolution, models must balance biological realism with mathematical and computational tractability. Here we review different modelling approaches, and suggest a number of biological problems that are potential candidates for study with these methods. We provide a comprehensive outline of the benefits and disadvantages of available frameworks, and describe what biological information is preserved and lost under different modelling assumptions. We also consider the emergence of new disease strains, and discuss how models of pathogens with multiple strains could be developed further in future. This includes extending the flexibility and biological realism of current approaches, as well as interface with data.
    Preview · Article · Mar 2015 · Journal of Mathematical Biology
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    ABSTRACT: Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health. Copyright © 2015, American Association for the Advancement of Science.
    Full-text · Article · Mar 2015 · Science
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    ABSTRACT: Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.
    No preview · Article · Jan 2015
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    ABSTRACT: Population epidemiological models where hosts can be infected sequentially by different strains have the potential to help us understand many important diseases. Researchers have in recent years started to develop and use such models, but the extra layer of complexity from multiple strains brings with it many technical challenges. It is therefore hard to build models which have realistic assumptions yet are tractable. Here we outline some of the main challenges in this area. First we begin with the fundamental question of how to translate from complex small-scale dynamics within a host to useful population models. Next we consider the nature of so-called "strain space". We describe two key types of host heterogeneities, and explain how models could help generate a better understanding of their effects. Finally, for diseases with many strains, we consider the challenge of modelling how immunity accumulates over multiple exposures. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
    Full-text · Article · Oct 2014 · Epidemics
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    ABSTRACT: Vaccination has been one of the most successful public health measures since the introduction of basic sanitation. Substantial mortality and morbidity reductions have been achieved via vaccination against many infections, and the list of diseases that are potentially controllable by vaccines is growing steadily. We introduce key challenges for modeling in shaping our understanding and guiding policy decisions related to vaccine preventable diseases. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
    Full-text · Article · Aug 2014 · Epidemics
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    Mick Roberts · Viggo Andreasen · Alun Lloyd · Lorenzo Pellis
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    ABSTRACT: Deterministic models have a long history of being applied to the study of infectious disease epidemiology. We highlight and discuss nine challenges in this area. The first two concern the endemic equilibrium and its stability. We indicate the need for models that describe multi-strain infections, infections with time-varying infectivity, and those where superinfection is possible. We then consider the need for advances in spatial epidemic models, and draw attention to the lack of models that explore the relationship between communicable and non-communicable diseases. The final two challenges concern the uses and limitations of deterministic models as approximations to stochastic systems. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
    Full-text · Article · Jan 2014 · Epidemics
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    ABSTRACT: This study examined the association between prenatal exposure to pandemic influenza and cardiovascular events in adulthood. Using Danish surveillance data to identify months when influenza activity was highest during three previous pandemics (1918, 1957, and 1968), persons were defined as exposed/unexposed based on whether they were in utero during peak months of one of the pandemics. Episodes of acute myocardial infarction (MI) and stroke were identified in the Danish National Registry of Patients covering all Danish hospitals since 1977. Information from Danish national registries on all persons with a Civil Personal Registry number and birthdates in 1915 through 1922, 1954 through 1960, and 1966 through 1972 was collected. Crude incidence rate ratios (IRRs) were calculated per pandemic. Generalized linear models were fit to estimate IRRs adjusted for sex. For acute MI, sex-adjusted IRRs for persons in utero during peaks of the 1918, 1957, and 1968 pandemics, compared with those born afterward, were 1·02 (95% confidence interval (CI): 0·99, 1·05), 0·96 (95% CI: 0·87, 1·05), and 1·18 (95% CI: 0·96, 1·45), respectively. For stroke, the corresponding IRRs were 0·99 (95% CI: 0·97, 1·02), 0·99 (95% CI: 0·92, 1·05), and 0·85 (95% CI: 0·77, 0·94), respectively. There was generally no evidence of an association between prenatal influenza exposure and acute MI or stroke in adulthood. However, survivor bias and left truncation of outcomes for the 1918 pandemic are possible, and the current young ages of persons included in the analyses for the 1957 and 1968 pandemics may warrant later re-evaluation.
    Full-text · Article · Jan 2014 · Influenza and Other Respiratory Viruses
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    ABSTRACT: Clostridium difficile infection (CDI) is gradually being recognised as a cause of morbidity in the community. We investigated the incidence and clinical characteristics of CDI in a community setting and characterised the C. difficile strains by toxin gene profiling and polymerase chain reaction (PCR) ribotyping. Patients included in the study had attended general practice, primarily because of diarrhoea; CDI patients (259 patients; 121 <2 years of age) had positive cultures for toxigenic C. difficile and non-CDI patients (455 patients) were culture-negative. Outcome variables included the frequency and duration of diarrhoea, vomiting, stomach ache, fever >38 °C, weight loss and sick leave. Data were analysed by logistic regression. CDI patients <2 and ≥2 years of age with C. difficile as the only enteropathogen in the faecal sample reported slimy stools (65 % vs. 62 %), stomach ache (60 % vs. 75 %), weight loss (50 % vs. 76 %) and duration of diarrhoea >15 days (59 % vs. 73 %) as the predominant symptoms. CDI patients ≥2 years old reported duration of diarrhoea >15 days more often compared to non-CDI patients (73 % vs. 27 %, p < 0.0001). The annual incidence of CDI was 518 and 23/100,000 for patients <2 and ≥2 years of age, respectively, and 46/100,000 in the subgroup of patients ≥60 years of age. CDI was characterised by stomach ache and persistent diarrhoea, often leading to weight loss. This emphasises the importance of diagnosing CDI not only in hospitalised patients, but also in individuals ≥2 years of age attending general practice because of gastrointestinal symptoms, especially in the elderly, where the incidence of CDI is high.
    No preview · Article · Dec 2013 · European Journal of Clinical Microbiology
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    ABSTRACT: SUMMARY To identify risk factors for Clostridium difficile infection (CDI) in Danish patients consulting general practice with gastrointestinal symptoms, a prospective matched case-control study was performed; cases (N = 259) had positive cultures for toxigenic C. difficile and controls (N = 455) negative cultures. Data were analysed by conditional logistic regression. In patients aged ⩾2 years (138 cases), hospitalization [odds ratio (OR) 8·4, 95% confidence interval (CI) 3·1-23], consumption of beef (OR 5·5, 95% CI 2·0-15), phenoxymethylpenicillin (OR 15, 95% CI 2·7-82), dicloxacillin (OR 27, 95% CI 3·6-211), and extended spectrum penicillins (OR 9·2, 95% CI 1·9-45) were associated with CDI. In patients aged <2 years none of these were associated with CDI, but in a subgroup analysis contact with animals was associated with CDI (OR 8·1, 95% CI 1·0-64). This study emphasizes narrow-spectrum penicillins, and suggests beef consumption, as risk factors for CDI in adults, and indicates a different epidemiology of CDI in infants.
    No preview · Article · Sep 2013 · Epidemiology and Infection
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    ABSTRACT: Understanding the biological mechanisms underlying episodic outbreaks of infectious diseases is one of mathematical epidemiology's major goals. Historic records are an invaluable source of information in this enterprise. Pertussis (whooping cough) is a re-emerging infection whose intermittent bouts of large multiannual epidemics interspersed between periods of smaller-amplitude cycles remain an enigma. It has been suggested that recent increases in pertussis incidence and shifts in the age-distribution of cases may be due to diminished natural immune boosting. Here we show that a model that incorporates this mechanism can account for a unique set of pre-vaccine-era data from Copenhagen. Under this model, immune boosting induces transient bursts of large amplitude outbreaks. In the face of mass vaccination, the boosting model predicts larger and more frequent outbreaks than do models with permanent or passively-waning immunity. Our results emphasize the importance of understanding the mechanisms responsible for maintaining immune memory for pertussis epidemiology.
    Preview · Article · Aug 2013 · PLoS ONE
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    Full-text · Article · May 2012 · The Journal of Infectious Diseases
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    Full-text · Article · Apr 2012 · The Journal of Infectious Diseases
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    ABSTRACT: The average age of infection is expected to vary during seasonal epidemics in a way that is predictable from the epidemiological features, such as the duration of infectiousness and the nature of population mixing. However, it is not known whether such changes can be detected and verified using routinely collected data. We examined the correlation between the weekly number and average age of cases using data on pre-vaccination measles and rotavirus. We show that age-incidence patterns can be observed and predicted for these childhood infections. Incorporating additional information about important features of the transmission dynamics improves the correspondence between model predictions and empirical data. We then explored whether knowledge of the age-incidence pattern can shed light on the epidemiological features of diseases of unknown aetiology, such as Kawasaki disease (KD). Our results indicate KD is unlikely to be triggered by a single acute immunizing infection, but is consistent with an infection of longer duration, a non-immunizing infection or co-infection with an acute agent and one with longer duration. Age-incidence patterns can lend insight into important epidemiological features of infections, providing information on transmission-relevant population mixing for known infections and clues about the aetiology of complex paediatric diseases.
    Full-text · Article · Mar 2012 · Proceedings of the Royal Society B: Biological Sciences
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    ABSTRACT: Although pregnancy is a recognized risk factor for severe influenza infection, the effect of influenza on miscarriages and births remains unclear. We examined the relationship between influenza and birth rates during the 1918 pandemic in the United States, Denmark, Sweden, and Norway. We compiled monthly birth rates from 1911 through 1930 in 3 Scandinavian countries and the United States, identified periods of unusually low or high birth rates, and quantified births as "missing" or "in excess" of the normal expectation. Using monthly influenza data, we correlated the timing of peak pandemic exposure and depressions in birth rates, and identified pregnancy stages at risk of influenza-related miscarriage. Birth rates declined in all study populations in spring 1919 by a mean of 2.2 births per 1000 persons, representing a 5%-15% drop below baseline levels (P < .05). The 1919 natality depression reached its trough 6.1-6.8 months after the autumn pandemic peak, suggesting that missing births were attributable to excess first trimester miscarriages in ∼1 in 10 women who were pregnant during the peak of the pandemic. Pandemic-related mortality was insufficient to explain observed patterns. The observed birth depressions were consistent with pandemic influenza causing first trimester miscarriages in ∼1 in 10 pregnant women. Causality is suggested by temporal synchrony across geographical areas.
    Full-text · Article · Oct 2011 · The Journal of Infectious Diseases
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    Viggo Andreasen
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    ABSTRACT: We study the final size equation for an epidemic in a subdivided population with general mixing patterns among subgroups. The equation is determined by a matrix with the same spectrum as the next generation matrix and it exhibits a threshold controlled by the common dominant eigenvalue, the basic reproduction number R0. There is a unique positive solution giving the size of the epidemic if and only if R0 exceeds unity. When mixing heterogeneities arise only from variation in contact rates and proportionate mixing, the final size of the epidemic in a heterogeneously mixing population is always smaller than that in a homogeneously mixing population with the same basic reproduction number R0. For other mixing patterns, the relation may be reversed.
    Preview · Article · Oct 2011 · Bulletin of Mathematical Biology
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    ABSTRACT: The 1918 influenza pandemic was associated with an unusual age pattern of mortality, with most deaths occurring among young adults. Few studies have addressed changes in the age distribution for influenza-related mortality in the pre-pandemic and post-pandemic period, which has implications for pandemic preparedness. In the present paper, we analyse the age patterns of influenza-related excess mortality in the decades before and after the 1918 pandemic, using detailed historic surveillance data from Copenhagen.
    Full-text · Article · Jul 2011 · Vaccine
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    Viggo Andreasen · Lone Simonsen
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    ABSTRACT: Measuring the burden of historic pandemics is not straightforward and often must be based on suboptimal mortality data. For example, the critical 1918 pandemic global burden estimate was based on excess in annual all-cause mortality--calculated as the difference between deaths during 1918-1920 and the surrounding 3-year periods. One intriguing result was a ∼ 40-fold between-country variation in pandemic mortality burden: ∼ 0.2% of Danes died, compared to ∼ 8% of populations in some Indian provinces (Murray et al., 2006 [16]). Using the same methodology and data source we explore the robustness of this methodology for different age-groups. For infants the country estimates varied 100-fold, from 15 to 1500 excess deaths/10,000 population, while for adults ≥ 45 years estimates ranged from -70 to 170/10,000 population. In contrast, estimates for children, 1-14 years, and adults aged 15-44 years, were far more stable. We next used detailed mortality data from Copenhagen to compare such estimates to the more precise estimates obtained from monthly mortality time series data and respiratory deaths. We found that the all-cause annual method substantially underestimated due to an unexplained depression in all-cause mortality in Denmark in 1918 and deaths caused by other epidemic diseases during the baseline periods. We conclude that country estimates for infants and older adults were highly variable by the Murray method due to substantial variability in annual all-cause mortality. A more precise 1918 pandemic burden estimate would be gotten from either focusing analysis on persons age 1-44 who suffered 95% of all pandemic deaths and had a substantial rise over their baseline mortality level, or if possible focus analysis on annual respiratory deaths. For less severe pandemics, including the ongoing 2009 H1N1 pandemic, the use of all-cause mortality data requires careful consideration of excess deaths in defined pandemic periods and a focus on age groups known to be at risk.
    Full-text · Article · Jul 2011 · Vaccine

Publication Stats

2k Citations
171.28 Total Impact Points

Institutions

  • 1993-2015
    • Roskilde University
      • Department of Science, Systems and Models (NSM)
      Roskilde, Zealand, Denmark
  • 2012
    • National Institutes of Health
      • Division of International Epidemiology and Population Studies (DIEPS)
      Bethesda, MD, United States
  • 1984-1989
    • Cornell University
      • Center for Applied Mathematics
      Ithaca, New York, United States