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HEALTH AND SAFETY (599 journals)                  1 2 3 | Last

Showing 1 - 200 of 203 Journals sorted alphabetically
16 de Abril     Open Access  
A Life in the Day     Hybrid Journal   (Followers: 12)
Acta Informatica Medica     Open Access   (Followers: 1)
Acta Scientiarum. Health Sciences     Open Access   (Followers: 1)
Adultspan Journal     Hybrid Journal   (Followers: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10)
Advances in Public Health     Open Access   (Followers: 24)
African Health Sciences     Open Access   (Followers: 3)
African Journal for Physical, Health Education, Recreation and Dance     Full-text available via subscription   (Followers: 7)
African Journal of Health Professions Education     Open Access   (Followers: 6)
Afrimedic Journal     Open Access   (Followers: 2)
Ageing & Society     Hybrid Journal   (Followers: 40)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 4)
AJOB Primary Research     Partially Free   (Followers: 3)
American Journal of Family Therapy     Hybrid Journal   (Followers: 11)
American Journal of Health Economics     Full-text available via subscription   (Followers: 12)
American Journal of Health Education     Hybrid Journal   (Followers: 32)
American Journal of Health Promotion     Hybrid Journal   (Followers: 28)
American Journal of Health Sciences     Open Access   (Followers: 7)
American Journal of Health Studies     Full-text available via subscription   (Followers: 11)
American Journal of Preventive Medicine     Hybrid Journal   (Followers: 28)
American Journal of Public Health     Full-text available via subscription   (Followers: 217)
American Journal of Public Health Research     Open Access   (Followers: 28)
American Medical Writers Association Journal     Full-text available via subscription   (Followers: 5)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 5)
Annals of Global Health     Open Access   (Followers: 10)
Annals of Health Law     Open Access   (Followers: 3)
Annals of Tropical Medicine and Public Health     Open Access   (Followers: 13)
Applied Biosafety     Hybrid Journal  
Applied Research In Health And Social Sciences: Interface And Interaction     Open Access   (Followers: 3)
Archive of Community Health     Open Access   (Followers: 1)
Archives of Medicine and Health Sciences     Open Access   (Followers: 3)
Arquivos de Ciências da Saúde     Open Access  
Asia Pacific Journal of Counselling and Psychotherapy     Hybrid Journal   (Followers: 10)
Asia Pacific Journal of Health Management     Full-text available via subscription   (Followers: 4)
Asia-Pacific Journal of Public Health     Hybrid Journal   (Followers: 9)
Asian Journal of Gambling Issues and Public Health     Open Access   (Followers: 4)
Atención Primaria     Open Access   (Followers: 1)
Australasian Journal of Paramedicine     Open Access   (Followers: 3)
Australian Advanced Aesthetics     Full-text available via subscription   (Followers: 4)
Australian Family Physician     Full-text available via subscription   (Followers: 3)
Australian Indigenous HealthBulletin     Free   (Followers: 6)
Autism & Developmental Language Impairments     Open Access   (Followers: 8)
Behavioral Healthcare     Full-text available via subscription   (Followers: 7)
Bijzijn     Hybrid Journal   (Followers: 1)
Bijzijn XL     Hybrid Journal  
Biomedical Safety & Standards     Full-text available via subscription   (Followers: 8)
Birat Journal of Health Sciences     Open Access  
BLDE University Journal of Health Sciences     Open Access  
BMC Oral Health     Open Access   (Followers: 6)
BMC Pregnancy and Childbirth     Open Access   (Followers: 22)
BMJ Simulation & Technology Enhanced Learning     Hybrid Journal   (Followers: 10)
Boletin Médico de Postgrado     Open Access  
Brazilian Journal of Medicine and Human Health     Open Access  
Buletin Penelitian Kesehatan     Open Access   (Followers: 2)
Buletin Penelitian Sistem Kesehatan     Open Access  
Cadernos de Educação, Saúde e Fisioterapia     Open Access   (Followers: 1)
Cadernos Saúde Coletiva     Open Access   (Followers: 1)
Cambridge Quarterly of Healthcare Ethics     Hybrid Journal   (Followers: 11)
Canadian Family Physician     Partially Free   (Followers: 12)
Canadian Journal of Community Mental Health     Full-text available via subscription   (Followers: 9)
Canadian Journal of Human Sexuality     Hybrid Journal   (Followers: 2)
Canadian Journal of Public Health     Hybrid Journal   (Followers: 20)
Case Reports in Women's Health     Open Access   (Followers: 3)
Case Studies in Fire Safety     Open Access   (Followers: 15)
Central Asian Journal of Global Health     Open Access   (Followers: 2)
CES Medicina     Open Access  
Child Abuse Research in South Africa     Full-text available via subscription   (Followers: 1)
Child's Nervous System     Hybrid Journal  
Childhood Obesity and Nutrition     Open Access   (Followers: 10)
Children     Open Access   (Followers: 2)
CHRISMED Journal of Health and Research     Open Access   (Followers: 2)
Christian Journal for Global Health     Open Access  
Ciência & Saúde Coletiva     Open Access   (Followers: 2)
Ciencia e Innovación en Salud     Open Access  
Ciencia y Cuidado     Open Access   (Followers: 1)
Ciencia y Salud Virtual     Open Access  
Ciencia, Tecnología y Salud     Open Access   (Followers: 2)
Clinical and Experimental Health Sciences     Open Access  
ClinicoEconomics and Outcomes Research     Open Access   (Followers: 2)
CME     Hybrid Journal   (Followers: 2)
CoDAS     Open Access  
Community Health     Open Access   (Followers: 3)
Conflict and Health     Open Access   (Followers: 7)
Contraception and Reproductive Medicine     Open Access   (Followers: 1)
Curare     Open Access  
Current Opinion in Behavioral Sciences     Hybrid Journal   (Followers: 4)
Day Surgery Australia     Full-text available via subscription   (Followers: 2)
Digital Health     Open Access   (Followers: 4)
Disaster Medicine and Public Health Preparedness     Hybrid Journal   (Followers: 13)
Dramatherapy     Hybrid Journal   (Followers: 2)
Drogues, santé et société     Full-text available via subscription   (Followers: 1)
Duazary     Open Access   (Followers: 1)
Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi / Journal of Duzce University Health Sciences Institute     Open Access  
Early Childhood Research Quarterly     Hybrid Journal   (Followers: 20)
East African Journal of Public Health     Full-text available via subscription   (Followers: 4)
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity     Hybrid Journal   (Followers: 20)
EcoHealth     Hybrid Journal   (Followers: 4)
Education for Health     Open Access   (Followers: 6)
electronic Journal of Health Informatics     Open Access   (Followers: 6)
ElectronicHealthcare     Full-text available via subscription   (Followers: 3)
Elsevier Ergonomics Book Series     Full-text available via subscription   (Followers: 5)
Emergency Services SA     Full-text available via subscription   (Followers: 2)
Ensaios e Ciência: Ciências Biológicas, Agrárias e da Saúde     Open Access  
Environmental Disease     Open Access   (Followers: 3)
Environmental Sciences Europe     Open Access   (Followers: 1)
Epidemics     Open Access   (Followers: 5)
Epidemiologic Perspectives & Innovations     Open Access   (Followers: 5)
Epidemiology, Biostatistics and Public Health     Open Access   (Followers: 19)
Ethics, Medicine and Public Health     Full-text available via subscription   (Followers: 6)
Ethiopian Journal of Health Development     Open Access   (Followers: 7)
Ethiopian Journal of Health Sciences     Open Access   (Followers: 7)
Ethnicity & Health     Hybrid Journal   (Followers: 13)
Eurasian Journal of Health Technology Assessment     Open Access  
European Journal of Investigation in Health, Psychology and Education     Open Access   (Followers: 2)
European Medical, Health and Pharmaceutical Journal     Open Access   (Followers: 1)
Evaluation & the Health Professions     Hybrid Journal   (Followers: 10)
Evidence-based Medicine & Public Health     Open Access   (Followers: 7)
Evidência - Ciência e Biotecnologia - Interdisciplinar     Open Access  
Expressa Extensão     Open Access  
Face à face     Open Access   (Followers: 1)
Families, Systems, & Health     Full-text available via subscription   (Followers: 9)
Family & Community Health     Hybrid Journal   (Followers: 12)
Family Medicine and Community Health     Open Access   (Followers: 7)
Family Relations     Partially Free   (Followers: 11)
Fatigue : Biomedicine, Health & Behavior     Hybrid Journal   (Followers: 2)
Finnish Journal of eHealth and eWelfare : Finjehew     Open Access  
Food and Public Health     Open Access   (Followers: 15)
Food Quality and Safety     Open Access   (Followers: 1)
Frontiers in Public Health     Open Access   (Followers: 7)
Gaceta Sanitaria     Open Access   (Followers: 3)
Galen Medical Journal     Open Access  
Gazi Sağlık Bilimleri Dergisi     Open Access  
Geospatial Health     Open Access  
Gesundheitsökonomie & Qualitätsmanagement     Hybrid Journal   (Followers: 9)
Giornale Italiano di Health Technology Assessment     Full-text available via subscription  
Global Challenges     Open Access  
Global Health : Science and Practice     Open Access   (Followers: 7)
Global Health Promotion     Hybrid Journal   (Followers: 15)
Global Journal of Health Science     Open Access   (Followers: 10)
Global Journal of Public Health     Open Access   (Followers: 13)
Global Medical & Health Communication     Open Access   (Followers: 2)
Global Mental Health     Open Access   (Followers: 8)
Global Reproductive Health     Open Access  
Global Security : Health, Science and Policy     Open Access   (Followers: 1)
Globalization and Health     Open Access   (Followers: 5)
Hacia la Promoción de la Salud     Open Access  
Hastane Öncesi Dergisi     Open Access  
Hastings Center Report     Hybrid Journal   (Followers: 3)
HEADline     Hybrid Journal  
Health & Place     Hybrid Journal   (Followers: 15)
Health & Justice     Open Access   (Followers: 5)
Health : An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine     Hybrid Journal   (Followers: 7)
Health and Human Rights     Free   (Followers: 10)
Health and Social Care Chaplaincy     Hybrid Journal   (Followers: 8)
Health and Social Work     Hybrid Journal   (Followers: 56)
Health Behavior and Policy Review     Full-text available via subscription   (Followers: 3)
Health Care Analysis     Hybrid Journal   (Followers: 15)
Health Inform     Full-text available via subscription  
Health Information Management Journal     Hybrid Journal   (Followers: 21)
Health Issues     Full-text available via subscription   (Followers: 2)
Health Notions     Open Access  
Health Policy     Hybrid Journal   (Followers: 43)
Health Policy and Technology     Hybrid Journal   (Followers: 4)
Health Professional Student Journal     Open Access   (Followers: 3)
Health Promotion International     Hybrid Journal   (Followers: 22)
Health Promotion Journal of Australia : Official Journal of Australian Association of Health Promotion Professionals     Full-text available via subscription   (Followers: 8)
Health Promotion Practice     Hybrid Journal   (Followers: 16)
Health Prospect     Open Access   (Followers: 1)
Health Psychology     Full-text available via subscription   (Followers: 52)
Health Psychology Bulletin     Open Access  
Health Psychology Research     Open Access   (Followers: 19)
Health Psychology Review     Hybrid Journal   (Followers: 40)
Health Renaissance     Open Access  
Health Research Policy and Systems     Open Access   (Followers: 14)
Health SA Gesondheid     Open Access   (Followers: 2)
Health Science Reports     Open Access  
Health Sciences and Disease     Open Access   (Followers: 2)
Health Services Insights     Open Access   (Followers: 1)
Health Systems     Hybrid Journal   (Followers: 4)
Health Voices     Full-text available via subscription  
Health, Culture and Society     Open Access   (Followers: 12)
Health, Risk & Society     Hybrid Journal   (Followers: 13)
Healthcare     Open Access   (Followers: 3)
Healthcare in Low-resource Settings     Open Access   (Followers: 1)
Healthcare Quarterly     Full-text available via subscription   (Followers: 8)
Healthcare Technology Letters     Open Access  
Healthy Aging Research     Open Access  
HERD : Health Environments Research & Design Journal     Full-text available via subscription  
Highland Medical Research Journal     Full-text available via subscription  
Hispanic Health Care International     Full-text available via subscription  
Histoire, médecine et santé     Open Access  
HIV & AIDS Review     Full-text available via subscription   (Followers: 12)
Home Health Care Services Quarterly     Hybrid Journal   (Followers: 6)
Hong Kong Journal of Social Work, The     Hybrid Journal   (Followers: 2)
Hospitals & Health Networks     Free   (Followers: 4)
IEEE Journal of Translational Engineering in Health and Medicine     Open Access   (Followers: 3)
IJS Global Health     Open Access  
IMTU Medical Journal     Full-text available via subscription  
Indian Journal of Health Sciences     Open Access   (Followers: 2)

        1 2 3 | Last

Journal Cover
Journal Prestige (SJR): 1.812
Citation Impact (citeScore): 3
Number of Followers: 5  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1755-4365 - ISSN (Online) 1878-0067
Published by Elsevier Homepage  [3157 journals]
  • Quantitative risk assessment of salmon louse-induced mortality of
           seaward-migrating post-smolt Atlantic salmon

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Anja Bråthen Kristoffersen, Lars Qviller, Kari Olli Helgesen, Knut Wiik Vollset, Hildegunn Viljugrein, Peder Andreas Jansen The Norwegian government recently implemented a new management system to regulate salmon farming in Norway, aiming to promote environmentally sustainable growth in the aquaculture industry. The Norwegian coast has been divided into 13 production zones and the volume of salmonid production in the zones will be regulated based on salmon lice effects on wild salmonids. Here we present a model for assessing salmon louse-induced mortality of seaward-migrating post-smolts of Atlantic salmon. The model quantifies expected salmon lice infestations and louse-induced mortality of migrating post-smolt salmon from 401 salmon rivers draining into Norwegian coastal waters. It is assumed that migrating post-smolts follow the shortest path from river outlets to the high seas, at constant progression rates. During this migration, fish are infested by salmon lice of farm origin according to an empirical infestation model. Furthermore, louse-induced mortality is estimated from the estimated louse infestations. Rivers draining into production zones on the West Coast of Norway were at the highest risk of adverse lice effects. In comparison, rivers draining into northerly production zones, along with the southernmost production zone, were at lower risk. After adjusting for standing stock biomass, estimates of louse-egg output varied by factors of up to 8 between production zones. Correlation between biomass adjusted output of louse infestation and densities of farmed salmon in the production zones suggests that a large-scale density-dependent host-parasite effect is a major driver of louse infestation rates and parasite-induced mortality. The estimates are sensitive to many of the processes in the chain of events in the model. Nevertheless, we argue that the model is suited to assess spatial and temporal risks associated with farm-origin salmon lice.
  • Contact tracing for the control of infectious disease epidemics: Chronic
           Wasting Disease in deer farms

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Chris Rorres, Maria Romano, Jennifer A. Miller, Jana M. Mossey, Tony H. Grubesic, David E. Zellner, Gary Smith Contact tracing is a crucial component of the control of many infectious diseases, but is an arduous and time consuming process. Procedures that increase the efficiency of contact tracing increase the chance that effective controls can be implemented sooner and thus reduce the magnitude of the epidemic. We illustrate a procedure using Graph Theory in the context of infectious disease epidemics of farmed animals in which the epidemics are driven mainly by the shipment of animals between farms. Specifically, we created a directed graph of the recorded shipments of deer between deer farms in Pennsylvania over a timeframe and asked how the properties of the graph could be exploited to make contact tracing more efficient should Chronic Wasting Disease (a prion disease of deer) be discovered in one of the farms. We show that the presence of a large strongly connected component in the graph has a significant impact on the number of contacts that can arise.
  • Species interactions may help explain the erratic periodicity of whooping
           cough dynamics

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Samit Bhattacharyya, Matthew J. Ferrari, Ottar N. Bjørnstad Incidence of whooping cough exhibits variable dynamics across time and space. The periodicity of this disease varies from annual to five years in different geographic regions in both developing and developed countries. Many hypotheses have been put forward to explain this variability such as nonlinearity and seasonality, stochasticity, variable recruitment of susceptible individuals via birth, immunization, and immune boosting. We propose an alternative hypothesis to describe the variability in periodicity – the intricate dynamical variability of whooping cough may arise from interactions between its dominant etiological agents of Bordetella pertussis and Bordetella parapertussis. We develop a two-species age-structured model, where two pathogens are allowed to interact by age-dependent convalescence of individuals with severe illness from infections. With moderate strength of interactions, the model exhibits multi-annual coexisting attractors that depend on the R0 of the two pathogens. We also examine how perturbation from case importation and noise in transmission may push the system from one dynamical regime to another. The coexistence of multi-annual cycles and the behavior of switching between attractors suggest that variable dynamics of whopping cough could be an emergent property of its multi-agent etiology.
  • The importance of being urgent: The impact of surveillance target and
           scale on mosquito-borne disease control

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Samantha R. Schwab, Chris M. Stone, Dina M. Fonseca, Nina H. Fefferman With the emergence or re-emergence of numerous mosquito-borne diseases in recent years, effective methods for emergency vector control responses are necessary to reduce human infections. Current vector control practices often vary significantly between different jurisdictions, and are executed independently and at different spatial scales. Various types of surveillance information (e.g. number of human infections or adult mosquitoes) trigger the implementation of control measures, though the target and scale of surveillance vary locally. This patchy implementation of control measures likely alters the efficacy of control.We modeled six different scenarios, with larval mosquito control occurring in response to surveillance data of different types and at different scales (e.g. across the landscape or in each patch). Our results indicate that: earlier application of larvicide after an escalation of disease risk achieves much greater reductions in human infections than later control implementation; uniform control across the landscape provides better outbreak mitigation than patchy control application; and different types of surveillance data require different levels of sensitivity in their collection to effectively inform control measures. Our simulations also demonstrate a potential logical fallacy of reactive, surveillance-driven vector control: measures stop being implemented as soon as they are deemed effective. This false sense of security leads to patchier control efforts that will do little to curb the size of future vector-borne disease outbreaks. More investment should be placed in collecting high quality information that can trigger early and uniform implementation, while researchers work to discover more informative metrics of human risk to trigger more effective control.
  • epidemix—An interactive multi-model application for teaching and
           visualizing infectious disease transmission

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Ulrich Muellner, Guillaume Fournié, Petra Muellner, Christina Ahlstrom, Dirk U. Pfeiffer Mathematical models of disease transmission are used to improve our understanding of patterns of infection and to identify factors influencing them. During recent public and animal health crises, such as pandemic influenza, Ebola, Zika, foot-and-mouth disease, models have made important contributions in addressing policy questions, especially through the assessment of the trajectory and scale of outbreaks, and the evaluation of control interventions. However, their mathematical formulation means that they may appear as a “black box” to those without the appropriate mathematical background. This may lead to a negative perception of their utility for guiding policy, and generate expectations, which are not in line with what these models can deliver. It is therefore important for policymakers, as well as public health and animal health professionals and researchers who collaborate with modelers and use results generated by these models for policy development or research purpose, to understand the key concepts and assumptions underlying these models.The software application epidemix ( presented here aims to make mathematical models of disease transmission accessible to a wider audience of users. By developing a visual interface for a suite of eight models, users can develop an understanding of the impact of various modelling assumptions – especially mixing patterns – on the trajectory of an epidemic and the impact of control interventions, without having to directly deal with the complexity of mathematical equations and programming languages. Models are compartmental or individual-based, deterministic or stochastic, and assume homogeneous or heterogeneous-mixing patterns (with the probability of transmission depending on the underlying structure of contact networks, or the spatial distribution of hosts). This application is intended to be used by scientists teaching mathematical modelling short courses to non-specialists – including policy makers, public and animal health professionals and students – and wishing to develop hands-on practicals illustrating key concepts of disease dynamics and control.
  • An infectious way to teach students about outbreaks

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Íde Cremin, Oliver Watson, Alastair Heffernan, Natsuko Imai, Norin Ahmed, Sandra Bivegete, Teresia Kimani, Demetris Kyriacou, Preveina Mahadevan, Rima Mustafa, Panagiota Pagoni, Marisa Sophiea, Charlie Whittaker, Leo Beacroft, Steven Riley, Matthew C. Fisher The study of infectious disease outbreaks is required to train today’s epidemiologists. A typical way to introduce and explain key epidemiological concepts is through the analysis of a historical outbreak. There are, however, few training options that explicitly utilise real-time simulated stochastic outbreaks where the participants themselves comprise the dataset they subsequently analyse. In this paper, we present a teaching exercise in which an infectious disease outbreak is simulated over a five-day period and subsequently analysed. We iteratively developed the teaching exercise to offer additional insight into analysing an outbreak. An R package for visualisation, analysis and simulation of the outbreak data was developed to accompany the practical to reinforce learning outcomes. Computer simulations of the outbreak revealed deviations from observed dynamics, highlighting how simplifying assumptions conventionally made in mathematical models often differ from reality. Here we provide a pedagogical tool for others to use and adapt in their own settings.
  • Modeling HIV disease progression and transmission at population-level: The
           potential impact of modifying disease progression in HIV treatment

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Jennifer M. Ross, Roger Ying, Connie L. Celum, Jared M. Baeten, Katherine K. Thomas, Pamela M. Murnane, Heidi van Rooyen, James P. Hughes, Ruanne V. Barnabas IntroductionMathematical models that incorporate HIV disease progression dynamics can estimate the potential impact of strategies that delay HIV disease progression and reduce infectiousness for persons not on antiretroviral therapy (ART). Suppressive treatment of HIV-positive persons co-infected with herpes simplex virus-2 (HSV-2) with valacyclovir, an HSV-2 antiviral, can lower HIV viral load, but the impact of partially-suppressive valacyclovir relative to fully-suppressive ART on population HIV transmission has not been estimated.MethodsWe modeled HIV disease progression as a function of changes in viral load and CD4 count over time among ART naïve persons. The disease progression Markov model was nested within a dynamic model of HIV transmission at population level. We assumed that valacyclovir reduced HIV viral load by 1.23 log copies/μL, and that persons treated with valacyclovir initiated ART more rapidly when their CD4 fell below 500 due to retention in HIV care. We estimated the potential impact of valacyclovir on onward transmission of HIV in three scenarios of different ART and valacyclovir population coverage.ResultsThe average duration of HIV infection was 9.5 years. The duration of disease before reaching CD4 200 cells/μL was 2.53 years longer for females than males. Relative to a baseline of ART initiation at CD4 ≤ 500 cells/μL, the valacyclovir scenario resulted in 167,000 fewer HIV infections over ten years, with an incremental cost-effectiveness ratio (ICER) of $5276 per HIV infection averted. A Test and Treat scenario with 70% ART coverage and no valacyclovir resulted in 350,000 fewer HIV infections at an ICER of $2822 and $812 per HIV infection averted and QALY gained, respectively.ConclusionEven when compared with valacyclovir suppression, a drug that reduces HIV viral load, universal treatment for HIV is the optimal strategy for averting new infections and increasing public health benefit. Universal HIV treatment would most effectively and efficiently reduce the HIV burden.
  • Digital Dermatitis in dairy cattle: The contribution of different disease
           classes to transmission

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Floor Biemans, Piter Bijma, Natasja M. Boots, Mart C.M. de Jong Digital Dermatitis (DD) is a claw disease mainly affecting the hind feet of dairy cattle. Digital Dermatitis is an infectious disease, transmitted via the environment, where the infectious “agent” is a combination of bacteria. The standardized classification for DD lesions developed by Döpfer et al. (1997) and extended by Berry et al. (2012) has six distinct classes: healthy (M0), an active granulomatous area of 0–2 cm (M1), an ulcerative lesion of>2 cm (M2), an ulcerative lesion covered by a scab (M3), alteration of the skin (M4), and a combination of M4 and M1 (M4.1).We hypothesize that classes M1, M2, M3, M4, and M4.1 are the potentially infectious classes that can contribute to the basic reproduction ratio (R0), the average number of new infections caused by a typical infected individual. Here, we determine differences in infectivity between the classes, the sojourn time in each of the classes, and the contribution of each class to R0.The analysis is based on data from twelve farms in the Netherlands that were visited every two weeks, eleven times.We found that 93.89% of the transitions from M0 was observed as a transition to class M4, and feet with another class-at-infection rapidly transitioned to class M4. As a consequence, about 70% of the infectious time was spent in class M4. Transmission rate parameters of class-at-infection M1, M2, M3, and M4 were not significantly different from each other, but differed from class-at-infection M4.1. However, due to the relative large amount of time spend in class M4, regardless of the class-at-infection, R0 was almost completely determined by this class. The R0 was 2.36, to which class-at-infection M4 alone contributed 88.5%.Thus, M4 lesions should be prevented to lower R0 to a value below one, while painful M2 lesions should be prevented for animal welfare reasons.
  • Dynamics and control of infections on social networks of population types

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Brian G. Williams, Christopher Dye Random mixing in host populations has been a convenient simplifying assumption in the study of epidemics, but neglects important differences in contact rates within and between population groups. For HIV/AIDS, the assumption of random mixing is inappropriate for epidemics that are concentrated in groups of people at high risk, including female sex workers (FSW) and their male clients (MCF), injecting drug users (IDU) and men who have sex with men (MSM). To find out who transmits infection to whom and how that affects the spread and containment of infection remains a major empirical challenge in the epidemiology of HIV/AIDS. Here we develop a technique, based on the routine sampling of infection in linked population groups (a social network of population types), which shows how an HIV/AIDS epidemic in Can Tho Province of Vietnam began in FSW, was propagated mainly by IDU, and ultimately generated most cases among the female partners of MCF (FPM). Calculation of the case reproduction numbers within and between groups, and for the whole network, provides insights into control that cannot be deduced simply from observations on the prevalence of infection. Specifically, the per capita rate of HIV transmission was highest from FSW to MCF, and most HIV infections occurred in FPM, but the number of infections in the whole network is best reduced by interrupting transmission to and from IDU. This analysis can be used to guide HIV/AIDS interventions using needle and syringe exchange, condom distribution and antiretroviral therapy. The method requires only routine data and could be applied to infections in other populations.
  • Comparison of cluster-based and source-attribution methods for estimating
           transmission risk using large HIV sequence databases

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Stéphane Le Vu, Oliver Ratmann, Valerie Delpech, Alison E. Brown, O. Noel Gill, Anna Tostevin, Christophe Fraser, Erik M. Volz Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission.A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors.We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors.
  • IFC, Ed Board

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s):
  • A Bayesian evidence synthesis approach to estimate disease prevalence in
           hard-to-reach populations: hepatitis C in New York City

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): Sarah Tan, Susanna Makela, Daliah Heller, Kevin Konty, Sharon Balter, Tian Zheng, James H. Stark Existing methods to estimate the prevalence of chronic hepatitis C (HCV) in New York City (NYC) are limited in scope and fail to assess hard-to-reach subpopulations with highest risk such as injecting drug users (IDUs). To address these limitations, we employ a Bayesian multi-parameter evidence synthesis model to systematically combine multiple sources of data, account for bias in certain data sources, and provide unbiased HCV prevalence estimates with associated uncertainty. Our approach improves on previous estimates by explicitly accounting for injecting drug use and including data from high-risk subpopulations such as the incarcerated, and is more inclusive, utilizing ten NYC data sources. In addition, we derive two new equations to allow age at first injecting drug use data for former and current IDUs to be incorporated into the Bayesian evidence synthesis, a first for this type of model. Our estimated overall HCV prevalence as of 2012 among NYC adults aged 20–59 years is 2.78% (95% CI 2.61–2.94%), which represents between 124,900 and 140,000 chronic HCV cases. These estimates suggest that HCV prevalence in NYC is higher than previously indicated from household surveys (2.2%) and the surveillance system (2.37%), and that HCV transmission is increasing among young injecting adults in NYC. An ancillary benefit from our results is an estimate of current IDUs aged 20–59 in NYC: 0.58% or 27,600 individuals.
  • Assessing the variability in transmission of bovine tuberculosis within
           Spanish cattle herds

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): G. Ciaravino, A. García-Saenz, S. Cabras, A. Allepuz, J. Casal, I. García-Bocanegra, A. De Koeijer, S. Gubbins, J.L. Sáez, D. Cano-Terriza, S. Napp In Spain, despite years of efforts to eradicate bovine tuberculosis (bTB), the disease is still endemic, with some areas of high prevalence. In this context, the surveillance and control plans may need to be re-evaluated, and understanding the dynamics of bTB spread within Spanish herds may help to develop new strategies for reducing the time for detection of infected herds and for the elimination of bTB from the herds already infected. Here, we developed a compartmental stochastic model to simulate bTB within-herd transmission, fed it with epidemiological data from 22 herds (obtained from a previous work) and carried out parameter inference using Approximate Bayesian Computing methods We also estimated the “Within-herd transmission potential Number” (Rh), i.e. the average number of secondary cases generated by a single animal infected introduced into a totally susceptible herd, considering different scenarios depending on the frequency of controls. The median global values obtained for the transmission parameters were: for the transmission coefficient (β), 0.014 newly infected animals per infectious individual per day (i.e. 5.2 per year), for the rate at which infected individuals become infectious (α), 0.01 per day (equivalent to a latent period of 97 days), and for the rate at which infected individuals become reactive to the skin test (α1), 0.08 per day (equivalent to a period of 12 days for an infected animal to become reactive). However, the results also evidenced a great variability in the estimates of those parameters (in particular β and α) among the 22 herds. Considering a 6-month interval between tests, the mean Rh was 0.23, increasing to 0.82 with an interval of 1 year, and to 2.01 and 3.47 with testing intervals of 2 and 4 years, respectively.
  • Modeling Marek's disease virus transmission: A framework for evaluating
           the impact of farming practices and evolution

    • Abstract: Publication date: June 2018Source: Epidemics, Volume 23Author(s): David A. Kennedy, Patricia A. Dunn, Andrew F. Read Marek's disease virus (MDV) is a pathogen of chickens whose control has twice been undermined by pathogen evolution. Disease ecology is believed to be the main driver of this evolution, yet mathematical models of MDV disease ecology have never been confronted with data to test their reliability. Here, we develop a suite of MDV models that differ in the ecological mechanisms they include. We fit these models with maximum likelihood using iterated filtering in ‘pomp’ to data on MDV concentration in dust collected from two commercial broiler farms. We find that virus dynamics are influenced by between-flock variation in host susceptibility to virus, shedding rate from infectious birds, and cleanout efficiency. We also find evidence that virus is reintroduced to farms approximately once per month, but we do not find evidence that virus sanitization rates vary between flocks. Of the models that survive model selection, we find agreement between parameter estimates and previous experimental data, as well as agreement between field data and the predictions of these models. Using the set of surviving models, we explore how changes to farming practices are predicted to influence MDV-associated condemnation risk (production losses at slaughter). By quantitatively capturing the mechanisms of disease ecology, we have laid the groundwork to explore the future trajectory of virus evolution.
  • Estimating the effective reproduction number of dengue considering
           temperature-dependent generation intervals

    • Abstract: Publication date: Available online 31 May 2018Source: EpidemicsAuthor(s): Claudia T. Codeço, Daniel A.M. Villela, Flavio C. Coelho The effective reproduction number, Rt, is a measure of transmission that can be calculated from standard incidence data to timely detect the beginning of epidemics. It has being increasingly used for surveillance of directly transmitted diseases. However, current methods for Rt estimation do not apply for vector borne diseases, whose transmission cycle depends on temperature. Here we propose a method that provides dengue's Rt estimates in the presence of temperature-mediated seasonality and apply this method to simulated and real data from two cities in Brazil where dengue is endemic. The method shows good precision in the simulated data. When applied to the real data, it shows differences in the transmission profile of the two cities and identifies periods of higher transmission.
  • Practical unidentifiability of a simple vector-borne disease model:
           Implications for parameter estimation and intervention assessment

    • Abstract: Publication date: Available online 26 May 2018Source: EpidemicsAuthor(s): Yu-Han Kao, Marisa C. Eisenberg Mathematical modeling has an extensive history in vector-borne disease epidemiology, and is increasingly used for prediction, intervention design, and understanding mechanisms. Many studies rely on parameter estimation to link models and data, and to tailor predictions and counterfactuals to specific settings. However, few studies have formally evaluated whether vector-borne disease models can properly estimate the parameters of interest given the constraints of a particular dataset. Identifiability analysis allows us to examine whether model parameters can be estimated uniquely—a lack of consideration of such issues can result in misleading or incorrect parameter estimates and model predictions. Here, we evaluate both structural (theoretical) and practical identifiability of a commonly used compartmental model of mosquito-borne disease, using the 2010 dengue epidemic in Taiwan as a case study. We show that while the model is structurally identifiable, it is practically unidentifiable under a range of human and mosquito time series measurement scenarios. In particular, the transmission parameters form a practically identifiable combination and thus cannot be estimated separately, potentially leading to incorrect predictions of the effects of interventions. However, in spite of the unidentifiability of the individual parameters, the basic reproduction number was successfully estimated across the unidentifiable parameter ranges. These identifiability issues can be resolved by directly measuring several additional human and mosquito life-cycle parameters both experimentally and in the field. While we only consider the simplest case for the model, we show that a commonly used model of vector-borne disease is unidentifiable from human and mosquito incidence data, making it difficult or impossible to estimate parameters or assess intervention strategies. This work illustrates the importance of examining identifiability when linking models with data to make predictions and inferences, and particularly highlights the importance of combining laboratory, field, and case data if we are to successfully estimate epidemiological and ecological parameters using models.
  • Kernel-density estimation and approximate Bayesian computation for
           flexible epidemiological model fitting in Python

    • Abstract: Publication date: Available online 26 May 2018Source: EpidemicsAuthor(s): Michael A. Irvine, T. Déirdre Hollingsworth Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community.
  • Tuberculosis outbreak investigation using phylodynamic analysis

    • Abstract: Publication date: Available online 22 May 2018Source: EpidemicsAuthor(s): Denise Kühnert, Mireia Coscolla, Daniela Brites, David Stucki, John Metcalfe, Lukas Fenner, Sebastien Gagneux, Tanja Stadler The fast evolution of pathogenic viruses has allowed for the development of phylodynamic approaches that extract information about the epidemiological characteristics of viral genomes. Thanks to advances in whole genome sequencing, they can be applied to slowly evolving bacterial pathogens like Mycobacterium tuberculosis. In this study, we investigate and compare the epidemiological dynamics underlying two M. tuberculosis outbreaks using phylodynamic methods. Specifically, we (i) test if the outbreak data sets contain enough genetic variation to estimate short-term evolutionary rates and (ii) reconstruct epidemiological parameters such as the effective reproduction number.The first outbreak occurred in the Swiss city of Bern (1987–2012) and was caused by a drug-susceptible strain belonging to the phylogenetic M. tuberculosis Lineage 4. The second outbreak was caused by a multidrug-resistant (MDR) strain of Lineage 2, imported from the Wat Tham Krabok (WTK) refugee camp in Thailand into California.There is little temporal signal in the Bern data set and moderate temporal signal in the WTK data set. Thanks to its high sampling proportion (90%) the Bern outbreak allows robust estimation of epidemiological parameters despite the poor temporal signal. Conversely, there is much uncertainty in the epidemiological estimates concerning the sparsely sampled (9%) WTK outbreak. Our results suggest that both outbreaks peaked around 1990, although they were only recognized as outbreaks in 1993 (Bern) and 2004 (WTK). Furthermore, individuals were infected for a significantly longer period (around 9 years) in the WTK outbreak than in the Bern outbreak (4–5 years).Our work highlights both the limitations and opportunities of phylodynamic analysis of outbreaks involving slowly evolving pathogens: (i) estimation of the evolutionary rate is difficult on outbreak time scales and (ii) a high sampling proportion allows quantification of the age of the outbreak based on the sampling times, and thus allows for robust estimation of epidemiological parameters.
  • Identifying human encounters that shape the transmission of Streptococcus
           pneumoniae and other acute respiratory infections

    • Abstract: Publication date: Available online 19 May 2018Source: EpidemicsAuthor(s): Olivier le Polain de Waroux, Stefan Flasche, Adam J Kucharski, Celine Langendorf, Donny Ndazima, Juliet Mwanga-Amumpaire, Rebecca F Grais, Sandra Cohuet, W John Edmunds Although patterns of social contacts are believed to be an important determinant of infectious disease transmission, it remains unclear how the frequency and nature of human interactions shape an individual’s risk of infection. We analysed data on daily social encounters individually matched to data on S. pneumoniae carriage and acute respiratory symptoms (ARS), from 566 individuals who took part in a survey in South-West Uganda. We found that the frequency of physical (i.e. skin-to-skin), long (≥1 h) and household contacts – which capture some measure of close (i.e. relatively intimate) contact – was higher among pneumococcal carriers than non-carriers, and among people with ARS compared to those without, irrespective of their age. With each additional physical encounter the age-adjusted risk of carriage and ARS increased by 6% (95%CI 2-9%) and 7% (2-13%) respectively. In contrast, the number of casual contacts (
  • The role of age-mixing patterns in HIV transmission dynamics: Novel
           hypotheses from a field study in Cape Town, South Africa

    • Abstract: Publication date: Available online 18 May 2018Source: EpidemicsAuthor(s): Roxanne Beauclair, Niel Hens, Wim Delva BackgroundAge-disparate relationships are thought to put young women at increased risk of HIV, though current evidence is inconclusive. Studying population-level age-mixing patterns as well as individual-level measures of age difference variation may provide insight into the persistence and magnitude of the epidemic in South Africa.MethodsWe used data from a survey in Cape Town (n = 506) to describe age-mixing dynamics in the four population strata of HIV negative and HIV positive male and female participants. Mixed-effects models were used to calculate the average increase in partner age for each year increase in age of participant, the average partner age for 15 year olds, and the between-subject and the within-subject standard deviation of partner ages. We conducted 2000 bootstrap replications of the models. Using negative binomial models, we also explored whether HIV status was associated with participants having a larger range in partner ages.ResultsHIV positive women had large variability in partner ages at the population level, and at the individual level had nearly three times the expected range of partner ages compared to HIV negative women. This pattern may increase the potential for HIV transmission across birth cohorts and may partially explain the persistence of the epidemic in South Africa. Young men, who have been previously absent from the age-disparity discourse, also choose older partners who may be putting them at increased risk of HIV infection due to the high HIV prevalence among older age categories of women.
  • Modelling the global spread of diseases: A review of current practice and

    • Abstract: Publication date: Available online 18 May 2018Source: EpidemicsAuthor(s): Caroline E. Walters, Margaux M.I. Meslé, Ian M. Hall Mathematical models can aid in the understanding of the risks associated with the global spread of infectious diseases. To assess the current state of mathematical models for the global spread of infectious diseases, we reviewed the literature highlighting common approaches and good practice, and identifying research gaps. We followed a scoping study method and extracted information from 78 records on: modelling approaches; input data (epidemiological, population, and travel) for model parameterization; model validation data.We found that most epidemiological data come from published journal articles, population data come from a wide range of sources, and travel data mainly come from statistics or surveys, or commercial datasets. The use of commercial datasets may benefit the modeller, however makes critical appraisal of their model by other researchers more difficult. We found a minority of records (26) validated their model. We posit that this may be a result of pandemics, or far-reaching epidemics, being relatively rare events compared with other modelled physical phenomena (e.g. climate change). The sparsity of such events, and changes in outbreak recording, may make identifying suitable validation data difficult.We appreciate the challenge of modelling emerging infections given the lack of data for both model parameterisation and validation, and inherent complexity of the approaches used. However, we believe that open access datasets should be used wherever possible to aid model reproducibility and transparency. Further, modellers should validate their models where possible, or explicitly state why validation was not possible.
  • Concurrency of partnerships, consistency with data, and control of
           sexually transmitted infections

    • Abstract: Publication date: Available online 14 May 2018Source: EpidemicsAuthor(s): Trystan Leng, Matt J. Keeling Sexually transmitted infections (STIs) are a globally increasing public health problem. Mathematical models, carefully matched to available epidemiological and behavioural data, have an important role to play in predicting the action of control measures. Here, we explore the effect of concurrent sexual partnerships on the control of a generic STI with susceptible-infected-susceptible dynamics. Concurrency refers to being in more than one sexual partnership at the same time, and is difficult to measure accurately. We assess the impact of concurrency through the development of three nested pair-formation models: one where infection can only be transmitted via stable sexual partnerships, one where infection can also be transmitted via casual partnerships between single individuals, and one where those individuals in stable partnerships can also acquire infection from casual partnerships. For each model, we include the action of vaccination before sexual debut to inform about the ability to control. As expected, for a fixed transmission rate, concurrency increases both the endemic prevalence of infection and critical level of vaccination required to eliminate the disease significantly. However, when the transmission rate is scaled to maintain a fixed endemic prevalence across models, concurrency has a far smaller impact upon the critical level of vaccination required. Further, when we also constrain the models to have a fixed number of new partnerships over time (both long-term and casual), then increasing concurrency can slightly decrease the critical level of vaccination. These results highlight that accurate measures and models of concurrency may not always be needed for reliable forecasts when models are closely matched to prevalence data. We find that, while increases in concurrency within a population are likely to generate public-health problems, the inclusion of concurrency may be unnecessary when constructing models to determine the efficacy of the control of STIs by vaccination.
  • A model for leptospire dynamics and control in the Norway rat (Rattus
           norvegicus) the reservoir host in urban slum environments

    • Abstract: Publication date: Available online 5 May 2018Source: EpidemicsAuthor(s): Amanda Minter, Peter J. Diggle, Federico Costa, James Childs, Albert I. Ko, Mike Begon Leptospirosis is a zoonosis that humans can contract via contact with animal reservoirs directly or with water contaminated with their urine. The primary reservoir of pathogenic leptospires within urban slum environments is the Norway rat (Rattus norvegicus). Motivated by the annual outbreaks of human leptospirosis in slum urban settings, the within population infection dynamics of the Norway rat were investigated in Pau da Lima, an community in Salvador, Brazil. A mechanistic model of the dynamics of leptospire infection was informed by extensive field and laboratory data was developed and explored analytically. To identify the intraspecific transmission route of most importance, a global sensitivity analysis of the basic reproduction number to its components was performed. In addition, different methods of rodent control were investigated by calculating target reproduction numbers. Our results suggest environmental transmission plays an important role in the maintenance of infection in the rodent population. To control numbers of wild Norway rats, combinations of controls are recommended but environmental control should also be investigated to reduce prevalence of infection in rats.
  • Epidemics on dynamic networks

    • Abstract: Publication date: Available online 28 April 2018Source: EpidemicsAuthor(s): Jessica Enright, Rowland Raymond Kao In many populations, the patterns of potentially infectious contacts are transients that can be described as a network with dynamic links. The relative timescales of link and contagion dynamics and the characteristics that drive their tempos can lead to important differences to the static case. Here, we propose some essential nomenclature for their analysis, and then review the relevant literature. We describe recent advances in they apply to infection processes, considering all of the methods used to record, measure and analyse them, and their implications for disease transmission. Finally, we outline some key challenges and opportunities in the field.
  • Role of animal movement and indirect contact among farms in transmission
           of porcine epidemic diarrhea virus

    • Abstract: Publication date: Available online 12 April 2018Source: EpidemicsAuthor(s): Kimberly VanderWaal, Andres Perez, Montse Torremorrell, Robert M. Morrison, Meggan Craft Epidemiological models of the spread of pathogens in livestock populations primarily focus on direct contact between farms based on animal movement data, and in some cases, local spatial spread based on proximity between premises. The roles of other types of indirect contact among farms is rarely accounted for. In addition, data on animal movements is seldom available in the United States. However, the spread of porcine epidemic diarrhea virus (PEDv) in U.S. swine represents one of the best documented emergences of a highly infectious pathogen in the U.S. livestock industry, providing an opportunity to parameterize models of pathogen spread via direct and indirect transmission mechanisms in swine. Using observed data on pig movements during the initial phase of the PEDv epidemic, we developed a network-based and spatially explicit epidemiological model that simulates the spread of PEDv via both indirect and direct movement-related contact in order to answer unresolved questions concerning factors facilitating between-farm transmission. By modifying the likelihood of each transmission mechanism and fitting this model to observed epidemiological dynamics, our results suggest that between-farm transmission was primarily driven by direct mechanisms related to animal movement and indirect mechanisms related to local spatial spread based on geographic proximity. However, other forms of indirect transmission among farms, including contact via contaminated vehicles and feed, were responsible for high consequence transmission events resulting in the introduction of the virus into new geographic areas. This research is among the first reports of farm-level animal movements in the U.S. swine industry and, to our knowledge, represents the first epidemiological model of commercial U.S. swine using actual data on farm-level animal movement.
  • Using state-space models to predict the abundance of juvenile and adult
           sea lice on Atlantic salmon

    • Abstract: Publication date: Available online 11 April 2018Source: EpidemicsAuthor(s): Adel Elghafghuf, Raphael Vanderstichel, Sophie St-Hilaire, Henrik Stryhn Sea lice are marine parasites affecting salmon farms, and are considered one of the most costly pests of the salmon aquaculture industry. Infestations of sea lice on farms significantly increase opportunities for the parasite to spread in the surrounding ecosystem, making control of this pest a challenging issue for salmon producers. The complexity of controlling sea lice on salmon farms requires frequent monitoring of the abundance of different sea lice stages over time. Industry-based data sets of counts of lice are amenable to multivariate time-series data analyses.In this study, two sets of multivariate autoregressive state-space models were applied to Chilean sea lice data from six Atlantic salmon production cycles on five isolated farms (at least 20 km seaway distance away from other known active farms), to evaluate the utility of these models for predicting sea lice abundance over time on farms. The models were constructed with different parameter configurations, and the analysis demonstrated large heterogeneity between production cycles for the autoregressive parameter, the effects of chemotherapeutant bath treatments, and the process-error variance. A model allowing for different parameters across production cycles had the best fit and the smallest overall prediction errors. However, pooling information across cycles for the drift and observation error parameters did not substantially affect model performance, thus reducing the number of necessary parameters in the model. Bath treatments had strong but variable effects for reducing sea lice burdens, and these effects were stronger for adult lice than juvenile lice. Our multivariate state-space models were able to handle different sea lice stages and provide predictions for sea lice abundance with reasonable accuracy up to five weeks out.
  • Age difference between heterosexual partners in Britain: Implications for
           the spread of Chlamydia trachomatis

    • Abstract: Publication date: Available online 31 March 2018Source: EpidemicsAuthor(s): Joost H. Smid, Victor Garcia, Nicola Low, Catherine H. Mercer, Christian L. Althaus Heterosexual partners often differ in age. Integrating realistic patterns of sexual mixing by age into dynamic transmission models has been challenging. The effects of these patterns on the transmission of sexually transmitted infections (STI) including Chlamydia trachomatis (chlamydia), the most common bacterial STI are not well understood. We describe age mixing between new heterosexual partners using age- and sex-specific data about sexual behavior reported by people aged 16–63 years in the 2000 and 2010 British National Surveys of Sexual Attitudes and Lifestyles. We incorporate mixing patterns into a compartmental transmission model fitted to age- and sex-specific, chlamydia positivity from the same surveys, to investigate C. trachomatis transmission. We show that distributions of ages of new sex partners reported by women and by men in Britain are not consistent with each other. After balancing these distributions, new heterosexual partnerships tend to involve men who are older than women (median age difference 2, IQR −1, 5 years). We identified the most likely age combinations of heterosexual partners where incident C. trachomatis infections are generated. The model results show that in>50% of chlamydia transmitting partnerships, at least one partner is ≥25 years old. This study illustrates how sexual behavior data can be used to reconstruct detailed sexual mixing patterns by age, and how these patterns can be integrated into dynamic transmission models. The proposed framework can be extended to study the effects of age-dependent transmission on incidence in any STI.
  • Contagion! The BBC Four Pandemic – The model behind the documentary

    • Abstract: Publication date: Available online 22 March 2018Source: EpidemicsAuthor(s): Petra Klepac, Stephen Kissler, Julia Gog To mark the centenary of the 1918 influenza pandemic, the broadcasting network BBC have put together a 75-min documentary called ‘Contagion! The BBC Four Pandemic’. Central to the documentary is a nationwide citizen science experiment, during which volunteers in the United Kingdom could download and use a custom mobile phone app called BBC Pandemic, and contribute their movement and contact data for a day.As the ‘maths team’, we were asked to use the data from the app to build and run a model of how a pandemic would spread in the UK. The headline results are presented in the TV programme. Here, we document in detail how the model works, and how we shaped it according the incredibly rich data coming from the BBC Pandemic app.We have barely scratched the depth of the volunteer data available from the app. The work presented in this article had the sole purpose of generating a single detailed simulation of a pandemic influenza-like outbreak in the UK. When the BBC Pandemic app has completed its collection period, the vast dataset will be made available to the scientific community (expected early 2019). It will take much more time and input from a broad range of researchers to fully exploit all that this dataset has to offer. But here at least we were able to harness some of the power of the BBC Pandemic data to contribute something which we hope will capture the interest and engagement of a broad audience.
  • Robust qualitative estimation of time-varying contact rates in uncertain

    • Abstract: Publication date: Available online 15 March 2018Source: EpidemicsAuthor(s): Marco Tulio Angulo, Jorge X. Velasco-Hernandez We will inevitably face new epidemics where the lack of long time-series data and the uncertainty about the outbreak dynamics make difficult to obtain quantitative predictions. Here we present an algorithm to qualitatively infer time-varying contact rates from short time-series data, letting us predict the start, relative magnitude and decline of epidemic outbreaks. Using real time-series data of measles, dengue, and the current zika outbreak, we demonstrate our algorithm can outperform existing algorithms based on estimating reproductive numbers.
  • A simple approach to measure transmissibility and forecast incidence

    • Abstract: Publication date: March 2018Source: Epidemics, Volume 22Author(s): Pierre Nouvellet, Anne Cori, Tini Garske, Isobel M. Blake, Ilaria Dorigatti, Wes Hinsley, Thibaut Jombart, Harriet L. Mills, Gemma Nedjati-Gilani, Maria D. Van Kerkhove, Christophe Fraser, Christl A. Donnelly, Neil M. Ferguson, Steven Riley Outbreaks of novel pathogens such as SARS, pandemic influenza and Ebola require substantial investments in reactive interventions, with consequent implementation plans sometimes revised on a weekly basis. Therefore, short-term forecasts of incidence are often of high priority. In light of the recent Ebola epidemic in West Africa, a forecasting exercise was convened by a network of infectious disease modellers. The challenge was to forecast unseen “future” simulated data for four different scenarios at five different time points. In a similar method to that used during the recent Ebola epidemic, we estimated current levels of transmissibility, over variable time-windows chosen in an ad hoc way. Current estimated transmissibility was then used to forecast near-future incidence. We performed well within the challenge and often produced accurate forecasts. A retrospective analysis showed that our subjective method for deciding on the window of time with which to estimate transmissibility often resulted in the optimal choice. However, when near-future trends deviated substantially from exponential patterns, the accuracy of our forecasts was reduced. This exercise highlights the urgent need for infectious disease modellers to develop more robust descriptions of processes – other than the widespread depletion of susceptible individuals – that produce non-exponential patterns of incidence.
  • The RAPIDD Ebola forecasting challenge special issue: Preface

    • Abstract: Publication date: March 2018Source: Epidemics, Volume 22Author(s): Cécile Viboud, Lone Simonsen, Gerardo Chowell, Alessandro Vespignani
  • IFC, Ed Board

    • Abstract: Publication date: March 2018Source: Epidemics, Volume 22Author(s):
  • Forecasting Ebola with a regression transmission model

    • Abstract: Publication date: March 2018Source: Epidemics, Volume 22Author(s): Jason Asher We describe a relatively simple stochastic model of Ebola transmission that was used to produce forecasts with the lowest mean absolute error among Ebola Forecasting Challenge participants. The model enabled prediction of peak incidence, the timing of this peak, and final size of the outbreak. The underlying discrete-time compartmental model used a time-varying reproductive rate modeled as a multiplicative random walk driven by the number of infectious individuals. This structure generalizes traditional Susceptible-Infected-Recovered (SIR) disease modeling approaches and allows for the flexible consideration of outbreaks with complex trajectories of disease dynamics.
  • Two approaches to forecast Ebola synthetic epidemics

    • Abstract: Publication date: March 2018Source: Epidemics, Volume 22Author(s): David Champredon, Michael Li, Benjamin M. Bolker, Jonathan Dushoff We use two modelling approaches to forecast synthetic Ebola epidemics in the context of the RAPIDD Ebola Forecasting Challenge. The first approach is a standard stochastic compartmental model that aims to forecast incidence, hospitalization and deaths among both the general population and health care workers. The second is a model based on the renewal equation with latent variables that forecasts incidence in the whole population only. We describe fitting and forecasting procedures for each model and discuss their advantages and drawbacks. We did not find that one model was consistently better in forecasting than the other.
  • Identifying genotype specific elevated-risk areas and associated herd risk
           factors for bovine tuberculosis spread in British cattle

    • Abstract: Publication date: Available online 1 March 2018Source: EpidemicsAuthor(s): R.J. Orton, M. Deason, P.R. Bessell, D.M. Green, R.R. Kao, L.C.M. Salvador Bovine tuberculosis (bTB) is a chronic zoonosis with major health and economic impact on the cattle industry. Despite extensive control measures in cattle and culling trials in wildlife, the reasons behind the expansion of areas with high incidence of bTB breakdowns in Great Britain remain unexplained. By balancing the importance of cattle movements and local transmission on the observed pattern of cattle outbreaks, we identify areas at elevated risk of infection from specific Mycobacterium bovis genotypes. We show that elevated-risk areas (ERAs) were historically more extensive than previously understood, and that cattle movements alone are insufficient for ERA spread, suggesting the involvement of other factors. For all genotypes, we find that, while the absolute risk of infection is higher in ERAs compared to areas with intermittent risk, the statistically significant risk factors are remarkably similar in both, suggesting that these risk factors can be used to identify incipient ERAs before this is indicated by elevated incidence alone. Our findings identify research priorities for understanding bTB dynamics, improving surveillance and guiding management to prevent further ERA expansion.Graphical abstractGraphical abstract for this article
  • The distribution of district-level leprosy incidence in India is
           geometric-stable, consistent with subcriticality

    • Abstract: Publication date: Available online 14 February 2018Source: EpidemicsAuthor(s): Thomas M. Lietman, Lee Worden, Fengchen Liu, Travis C. Porco Mathematical models predict that the community-level incidence of a controlled infectious disease across a region approaches a geometric distribution. This could hold over larger regions, if new cases remain proportional to existing cases. Leprosy has been disappearing for centuries, making an excellent candidate for testing this hypothesis. Here, we show the annual new case detection rate of leprosy in Indian districts to be consistent with a geometric distribution. For 2008–2013, goodness-of-fit testing was unable to exclude the geometric, and the shape parameter of the best fit negative binomial distribution was close to unity (0.95, 95% CI 0.87–1.03). Ramifications include that a district-level cross-sectional survey may reveal whether an infectious disease is headed towards elimination, that apparent outliers are expected and not necessarily representative of program failure, and that proportion 1/e of a small geographical unit may not meet a control threshold even when a larger area has.
  • Acute illness from Campylobacter jejuni may require high doses while
           infection occurs at low doses

    • Abstract: Publication date: Available online 8 February 2018Source: EpidemicsAuthor(s): Peter F.M. Teunis, Axel Bonačić Marinović, David R. Tribble, Chad K. Porter, Arno Swart Data from a set of different studies on the infectivity and pathogenicity of Campylobacter jejuni were analyzed with a multilevel model, allowing for effects of host species (nonhuman primates and humans) and different strains of the pathogen.All challenge studies involved high doses of the pathogen, resulting in all exposed subjects to become infected. In only one study a dose response effect (increasing trend with dose) for infection was observed. High susceptibility to infection with C. jejuni was found in a joint analysis of outbreaks and challenge studies. For that reason four outbreaks, associated with raw milk consumption, were also included in the present study.The high doses used for inoculation did not cause all infected subjects to develop acute enteric symptoms. The observed outcomes are consistent with a dose response effect for acute symptoms among infected subjects: a conditional illness dose response relation. Nonhuman primates and human volunteers did not appear to have different susceptibilities for developing enteric symptoms, but exposure in outbreaks (raw milk) did lead to a higher probability of symptomatic campylobacteriosis.
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