for Journals by Title or ISSN
for Articles by Keywords
help
  Subjects -> HEALTH AND SAFETY (Total: 1296 journals)
    - CIVIL DEFENSE (18 journals)
    - DRUG ABUSE AND ALCOHOLISM (87 journals)
    - HEALTH AND SAFETY (526 journals)
    - HEALTH FACILITIES AND ADMINISTRATION (377 journals)
    - OCCUPATIONAL HEALTH AND SAFETY (105 journals)
    - PHYSICAL FITNESS AND HYGIENE (101 journals)
    - WOMEN'S HEALTH (82 journals)

HEALTH AND SAFETY (526 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: 9)
Acta Informatica Medica     Open Access   (Followers: 1)
Acta Scientiarum. Health Sciences     Open Access  
Adultspan Journal     Hybrid Journal  
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10)
Advances in Public Health     Open Access   (Followers: 23)
African Health Sciences     Open Access   (Followers: 2)
African Journal for Physical, Health Education, Recreation and Dance     Full-text available via subscription   (Followers: 6)
African Journal of Health Professions Education     Open Access   (Followers: 6)
Afrimedic Journal     Open Access   (Followers: 2)
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: 13)
American Journal of Health Education     Hybrid Journal   (Followers: 30)
American Journal of Health Promotion     Hybrid Journal   (Followers: 24)
American Journal of Health Sciences     Open Access   (Followers: 6)
American Journal of Health Studies     Full-text available via subscription   (Followers: 10)
American Journal of Preventive Medicine     Hybrid Journal   (Followers: 25)
American Journal of Public Health     Full-text available via subscription   (Followers: 201)
American Journal of Public Health Research     Open Access   (Followers: 29)
American Medical Writers Association Journal     Full-text available via subscription   (Followers: 2)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4)
Annals of Global Health     Open Access   (Followers: 9)
Annals of Health Law     Open Access   (Followers: 3)
Annals of Tropical Medicine and Public Health     Open Access   (Followers: 15)
Applied Biosafety     Hybrid Journal  
Applied Research In Health And Social Sciences : Interface And Interaction     Open Access   (Followers: 2)
Archive of Community Health     Open Access  
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: 8)
Asia Pacific Journal of Health Management     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Public Health     Hybrid Journal   (Followers: 8)
Asian Journal of Gambling Issues and Public Health     Open Access   (Followers: 3)
Association of Schools of Allied Health Professions     Full-text available via subscription   (Followers: 6)
Atención Primaria     Open Access   (Followers: 1)
Australasian Journal of Paramedicine     Open Access   (Followers: 2)
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: 5)
Behavioral Healthcare     Full-text available via subscription   (Followers: 6)
Best Practices in Mental Health     Full-text available via subscription   (Followers: 8)
Bijzijn     Hybrid Journal   (Followers: 2)
Bijzijn XL     Hybrid Journal   (Followers: 1)
Biomedical Safety & Standards     Full-text available via subscription   (Followers: 8)
BLDE University Journal of Health Sciences     Open Access  
BMC Oral Health     Open Access   (Followers: 5)
BMC Pregnancy and Childbirth     Open Access   (Followers: 20)
BMJ Simulation & Technology Enhanced Learning     Full-text available via subscription   (Followers: 7)
Brazilian Journal of Medicine and Human Health     Open Access  
Buletin Penelitian Kesehatan     Open Access   (Followers: 2)
Buletin Penelitian Sistem Kesehatan     Open Access  
Bulletin of the World Health Organization     Open Access   (Followers: 17)
Cadernos de Educação, Saúde e Fisioterapia     Open Access   (Followers: 1)
Cadernos Saúde Coletiva     Open Access   (Followers: 1)
Canadian Family Physician     Partially Free   (Followers: 12)
Canadian Journal of Community Mental Health     Full-text available via subscription   (Followers: 12)
Canadian Journal of Human Sexuality     Hybrid Journal   (Followers: 1)
Canadian Journal of Public Health     Full-text available via subscription   (Followers: 20)
Case Reports in Women's Health     Open Access   (Followers: 3)
Case Studies in Fire Safety     Open Access   (Followers: 12)
Central Asian Journal of Global Health     Open Access   (Followers: 2)
Central European Journal of Public Health     Full-text available via subscription   (Followers: 4)
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  
Christian Journal for Global Health     Open Access  
Ciência & Saúde Coletiva     Open Access   (Followers: 2)
Ciencia y Cuidado     Open Access  
Ciencia, Tecnología y Salud     Open Access  
ClinicoEconomics and Outcomes Research     Open Access   (Followers: 2)
CME     Hybrid Journal   (Followers: 1)
CoDAS     Open Access  
Community Health     Open Access   (Followers: 2)
Conflict and Health     Open Access   (Followers: 8)
Contraception and Reproductive Medicine     Open Access  
Curare     Open Access  
Current Opinion in Behavioral Sciences     Hybrid Journal   (Followers: 3)
Day Surgery Australia     Full-text available via subscription   (Followers: 2)
Digital Health     Open Access   (Followers: 1)
Dramatherapy     Hybrid Journal   (Followers: 2)
Drogues, santé et société     Full-text available via subscription  
Duazary     Open Access   (Followers: 1)
Early Childhood Research Quarterly     Hybrid Journal   (Followers: 15)
East African Journal of Public Health     Full-text available via subscription   (Followers: 3)
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity     Hybrid Journal   (Followers: 16)
EcoHealth     Hybrid Journal   (Followers: 4)
Education for Health     Open Access   (Followers: 5)
electronic Journal of Health Informatics     Open Access   (Followers: 6)
ElectronicHealthcare     Full-text available via subscription   (Followers: 4)
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: 2)
Environmental Sciences Europe     Open Access   (Followers: 2)
Epidemics     Open Access   (Followers: 4)
Epidemiologic Perspectives & Innovations     Open Access   (Followers: 5)
Epidemiology, Biostatistics and Public Health     Open Access   (Followers: 20)
Ethics, Medicine and Public Health     Full-text available via subscription   (Followers: 2)
Ethiopian Journal of Health Development     Open Access   (Followers: 8)
Ethiopian Journal of Health Sciences     Open Access   (Followers: 7)
Ethnicity & Health     Hybrid Journal   (Followers: 13)
European Journal of Investigation in Health, Psychology and Education     Open Access   (Followers: 2)
European Medical, Health and Pharmaceutical Journal     Open Access  
Evaluation & the Health Professions     Hybrid Journal   (Followers: 10)
Evidence-based Medicine & Public Health     Open Access   (Followers: 6)
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: 8)
Family & Community Health     Partially Free   (Followers: 12)
Family Medicine and Community Health     Open Access   (Followers: 6)
Family Relations     Partially Free   (Followers: 11)
Fatigue : Biomedicine, Health & Behavior     Hybrid Journal   (Followers: 1)
Food and Public Health     Open Access   (Followers: 11)
Frontiers in Public Health     Open Access   (Followers: 7)
Gaceta Sanitaria     Open Access   (Followers: 3)
Galen Medical Journal     Open Access  
Geospatial Health     Open Access  
Gesundheitsökonomie & Qualitätsmanagement     Hybrid Journal   (Followers: 9)
Giornale Italiano di Health Technology Assessment     Full-text available via subscription  
Global Health : Science and Practice     Open Access   (Followers: 5)
Global Health Promotion     Hybrid Journal   (Followers: 16)
Global Journal of Health Science     Open Access   (Followers: 9)
Global Journal of Public Health     Open Access   (Followers: 12)
Global Medical & Health Communication     Open Access   (Followers: 1)
Globalization and Health     Open Access   (Followers: 5)
Hacia la Promoción de la Salud     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: 8)
Health and Social Care Chaplaincy     Hybrid Journal   (Followers: 7)
Health and Social Work     Hybrid Journal   (Followers: 51)
Health Behavior and Policy Review     Full-text available via subscription   (Followers: 1)
Health Care Analysis     Hybrid Journal   (Followers: 14)
Health Inform     Full-text available via subscription  
Health Information Management Journal     Hybrid Journal   (Followers: 15)
Health Issues     Full-text available via subscription   (Followers: 2)
Health Notions     Open Access  
Health Policy     Hybrid Journal   (Followers: 36)
Health Policy and Technology     Hybrid Journal   (Followers: 1)
Health Professional Student Journal     Open Access   (Followers: 1)
Health Promotion International     Hybrid Journal   (Followers: 21)
Health Promotion Journal of Australia : Official Journal of Australian Association of Health Promotion Professionals     Full-text available via subscription   (Followers: 10)
Health Promotion Practice     Hybrid Journal   (Followers: 15)
Health Prospect     Open Access   (Followers: 1)
Health Psychology     Full-text available via subscription   (Followers: 48)
Health Psychology Research     Open Access   (Followers: 18)
Health Psychology Review     Hybrid Journal   (Followers: 40)
Health Renaissance     Open Access  
Health Research Policy and Systems     Open Access   (Followers: 12)
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: 2)
Health Systems     Hybrid Journal   (Followers: 3)
Health Voices     Full-text available via subscription  
Health, Culture and Society     Open Access   (Followers: 13)
Health, Risk & Society     Hybrid Journal   (Followers: 12)
Healthcare     Open Access   (Followers: 1)
Healthcare in Low-resource Settings     Open Access   (Followers: 1)
Healthcare Quarterly     Full-text available via subscription   (Followers: 8)
Healthy-Mu Journal     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  
HIV & AIDS Review     Full-text available via subscription   (Followers: 11)
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)
IMTU Medical Journal     Full-text available via subscription  
Indian Journal of Health Sciences     Open Access   (Followers: 2)
Indonesian Journal for Health Sciences     Open Access   (Followers: 1)
Inmanencia. Revista del Hospital Interzonal General de Agudos (HIGA) Eva Perón     Open Access  
Innovative Journal of Medical and Health Sciences     Open Access  
Institute for Security Studies Papers     Full-text available via subscription   (Followers: 5)
interactive Journal of Medical Research     Open Access  
International Health     Hybrid Journal   (Followers: 5)
International Journal for Equity in Health     Open Access   (Followers: 7)
International Journal for Quality in Health Care     Hybrid Journal   (Followers: 34)
International Journal of Applied Behavioral Sciences     Open Access   (Followers: 2)
International Journal of Behavioural and Healthcare Research     Hybrid Journal   (Followers: 8)
International Journal of Circumpolar Health     Open Access   (Followers: 1)
International Journal of Community Medicine and Public Health     Open Access   (Followers: 5)
International Journal of E-Health and Medical Communications     Full-text available via subscription   (Followers: 2)
International Journal of Environmental Research and Public Health     Open Access   (Followers: 20)
International Journal of Evidence-Based Healthcare     Hybrid Journal   (Followers: 8)
International Journal of Food Safety, Nutrition and Public Health     Hybrid Journal   (Followers: 16)
International Journal of Health & Allied Sciences     Open Access   (Followers: 3)
International Journal of Health Care Quality Assurance     Hybrid Journal   (Followers: 10)

        1 2 3 | Last

Journal Cover Epidemics
  [SJR: 1.268]   [H-I: 20]   [4 followers]  Follow
    
  This is an Open Access Journal Open Access journal
   ISSN (Print) 1755-4365 - ISSN (Online) 1878-0067
   Published by Elsevier Homepage  [3089 journals]
  • Learning from multi-model comparisons: Collaboration leads to insights,
           but limitations remain

    • Authors: T.D. Hollingsworth; G.F. Medley
      Pages: 1 - 3
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): T.D. Hollingsworth, G.F. Medley


      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.02.014
      Issue No: Vol. 18 (2017)
       
  • Modelling the elimination of river blindness using long-term
           epidemiological and programmatic data from Mali and Senegal

    • Authors: Martin Walker; Wilma A. Stolk; Matthew A. Dixon; Christian Bottomley; Lamine Diawara; Mamadou O. Traoré; Sake J. de Vlas; María-Gloria Basáñez
      Pages: 4 - 15
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): Martin Walker, Wilma A. Stolk, Matthew A. Dixon, Christian Bottomley, Lamine Diawara, Mamadou O. Traoré, Sake J. de Vlas, María-Gloria Basáñez
      The onchocerciasis transmission models EPIONCHO and ONCHOSIM have been independently developed and used to explore the feasibility of eliminating onchocerciasis from Africa with mass (annual or biannual) distribution of ivermectin within the timeframes proposed by the World Health Organization (WHO) and endorsed by the 2012 London Declaration on Neglected Tropical Diseases (i.e. by 2020/2025). Based on the findings of our previous model comparison, we implemented technical refinements and tested the projections of EPIONCHO and ONCHOSIM against long-term epidemiological data from two West African transmission foci in Mali and Senegal where the observed prevalence of infection was brought to zero circa 2007–2009 after 15–17 years of mass ivermectin treatment. We simulated these interventions using programmatic information on the frequency and coverage of mass treatments and trained the model projections using longitudinal parasitological data from 27 communities, evaluating the projected outcome of elimination (local parasite extinction) or resurgence. We found that EPIONCHO and ONCHOSIM captured adequately the epidemiological trends during mass treatment but that resurgence, while never predicted by ONCHOSIM, was predicted by EPIONCHO in some communities with the highest (inferred) vector biting rates and associated pre-intervention endemicities. Resurgence can be extremely protracted such that low (microfilarial) prevalence between 1% and 5% can be maintained for 3–5 years before manifesting more prominently. We highlight that post-treatment and post-elimination surveillance protocols must be implemented for long enough and with high enough sensitivity to detect possible residual latent infections potentially indicative of resurgence. We also discuss uncertainty and differences between EPIONCHO and ONCHOSIM projections, the potential importance of vector control in high-transmission settings as a complementary intervention strategy, and the short remaining timeline for African countries to be ready to stop treatment safely and begin surveillance in order to meet the impending 2020/2025 elimination targets.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.02.005
      Issue No: Vol. 18 (2017)
       
  • Predicting lymphatic filariasis transmission and elimination dynamics
           using a multi-model ensemble framework

    • Authors: Morgan E. Smith; Brajendra K. Singh; Michael A. Irvine; Wilma A. Stolk; Swaminathan Subramanian; T. Déirdre Hollingsworth; Edwin Michael
      Pages: 16 - 28
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): Morgan E. Smith, Brajendra K. Singh, Michael A. Irvine, Wilma A. Stolk, Swaminathan Subramanian, T. Déirdre Hollingsworth, Edwin Michael
      Mathematical models of parasite transmission provide powerful tools for assessing the impacts of interventions. Owing to complexity and uncertainty, no single model may capture all features of transmission and elimination dynamics. Multi-model ensemble modelling offers a framework to help overcome biases of single models. We report on the development of a first multi-model ensemble of three lymphatic filariasis (LF) models (EPIFIL, LYMFASIM, and TRANSFIL), and evaluate its predictive performance in comparison with that of the constituents using calibration and validation data from three case study sites, one each from the three major LF endemic regions: Africa, Southeast Asia and Papua New Guinea (PNG). We assessed the performance of the respective models for predicting the outcomes of annual MDA strategies for various baseline scenarios thought to exemplify the current endemic conditions in the three regions. The results show that the constructed multi-model ensemble outperformed the single models when evaluated across all sites. Single models that best fitted calibration data tended to do less well in simulating the out-of-sample, or validation, intervention data. Scenario modelling results demonstrate that the multi-model ensemble is able to compensate for variance between single models in order to produce more plausible predictions of intervention impacts. Our results highlight the value of an ensemble approach to modelling parasite control dynamics. However, its optimal use will require further methodological improvements as well as consideration of the organizational mechanisms required to ensure that modelling results and data are shared effectively between all stakeholders.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.02.006
      Issue No: Vol. 18 (2017)
       
  • Comparison and validation of two mathematical models for the impact of
           mass drug administration on Ascaris lumbricoides and hookworm infection

    • Authors: Luc E. Coffeng; James E. Truscott; Sam H. Farrell; Hugo C. Turner; Rajiv Sarkar; Gagandeep Kang; Sake J. de Vlas; Roy M. Anderson
      Pages: 38 - 47
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): Luc E. Coffeng, James E. Truscott, Sam H. Farrell, Hugo C. Turner, Rajiv Sarkar, Gagandeep Kang, Sake J. de Vlas, Roy M. Anderson
      The predictions of two mathematical models of the transmission dynamics of Ascaris lumbricoides and hookworm infection and the impact of mass drug administration (MDA) are compared, using data from India. One model has an age structured partial differential equation (PDE) deterministic framework for the distribution of parasite numbers per host and sexual mating. The second model is an individual-based stochastic model. Baseline data acquired prior to treatment are used to estimate key transmission parameters, and forward projections are made, given the known MDA population coverage. Predictions are compared with observed post-treatment epidemiological patterns. The two models could equally well predict the short-term impact of deworming on A. lumbricoides and hookworm infection levels, despite being fitted to different subsets and/or summary statistics of the data. As such, the outcomes give confidence in their use as aids to policy formulation for the use of PCT to control A. lumbricoides and hookworm infection. The models further largely agree in a qualitative sense on the added benefit of semi-annual vs. annual deworming and targeting of the entire population vs. only children, as well as the potential for interruption of transmission. Further, this study also illustrates that long-term predictions are sensitive to modelling assumptions about which age groups contribute most to transmission, which depends on human demography and age-patterns in exposure and contribution to the environmental reservoir of infection, the latter being notoriously difficult to empirically quantify.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.02.001
      Issue No: Vol. 18 (2017)
       
  • Probabilistic forecasts of trachoma transmission at the district level: A
           statistical model comparison

    • Authors: Amy Pinsent; Fengchen Liu; Michael Deiner; Paul Emerson; Ana Bhaktiari; Travis C. Porco; Thomas Lietman; Manoj Gambhir
      Pages: 48 - 55
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): Amy Pinsent, Fengchen Liu, Michael Deiner, Paul Emerson, Ana Bhaktiari, Travis C. Porco, Thomas Lietman, Manoj Gambhir
      The World Health Organization and its partners are aiming to eliminate trachoma as a public health problem by 2020. In this study, we compare forecasts of TF prevalence in 2011 for 7 different statistical and mechanistic models across 9 de-identified trachoma endemic districts, representing 4 unique trachoma endemic countries. We forecast TF prevalence between 1–6 years ahead in time and compare the 7 different models to the observed 2011 data using a log-likelihood score. An SIS model, including a district-specific random effect for the district-specific transmission coefficient, had the highest log-likelihood score across all 9 districts and was therefore the best performing model. While overall the deterministic transmission model was the least well performing model, although it did comparably well to the other models for 8 of 9 districts. We perform a statistically rigorous comparison of the forecasting ability of a range of mathematical and statistical models across multiple endemic districts between 1 and 6 years ahead of the last collected TF prevalence data point in 2011, assessing results against surveillance data. This study is a step towards making statements about likelihood and time to elimination with regard to the WHO GET2020 goals.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.01.007
      Issue No: Vol. 18 (2017)
       
  • Measuring and modelling the effects of systematic non-adherence to mass
           drug administration

    • Authors: Louise Dyson; Wilma A. Stolk; Sam H. Farrell; T. Déirdre Hollingsworth
      Pages: 56 - 66
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): Louise Dyson, Wilma A. Stolk, Sam H. Farrell, T. Déirdre Hollingsworth
      It is well understood that the success or failure of a mass drug administration campaign critically depends on the level of coverage achieved. To that end coverage levels are often closely scrutinised during campaigns and the response to underperforming campaigns is to attempt to improve coverage. Modelling work has indicated, however, that the quality of the coverage achieved may also have a significant impact on the outcome. If the coverage achieved is likely to miss similar people every round then this can have a serious detrimental effect on the campaign outcome. We begin by reviewing the current modelling descriptions of this effect and introduce a new modelling framework that can be used to simulate a given level of systematic non-adherence. We formalise the likelihood that people may miss several rounds of treatment using the correlation in the attendance of different rounds. Using two very simplified models of the infection of helminths and non-helminths, respectively, we demonstrate that the modelling description used and the correlation included between treatment rounds can have a profound effect on the time to elimination of disease in a population. It is therefore clear that more detailed coverage data is required to accurately predict the time to disease elimination. We review published coverage data in which individuals are asked how many previous rounds they have attended, and show how this information may be used to assess the level of systematic non-adherence. We note that while the coverages in the data found range from 40.5% to 95.5%, still the correlations found lie in a fairly narrow range (between 0.2806 and 0.5351). This indicates that the level of systematic non-adherence may be similar even in data from different years, countries, diseases and administered drugs.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.02.002
      Issue No: Vol. 18 (2017)
       
  • Elimination of visceral leishmaniasis in the Indian subcontinent: a
           comparison of predictions from three transmission models

    • Authors: Epke A. Le Rutte; Lloyd A.C. Chapman; Luc E. Coffeng; Sarah Jervis; Epco C. Hasker; Shweta Dwivedi; Morchan Karthick; Aritra Das; Tanmay Mahapatra; Indrajit Chaudhuri; Marleen C. Boelaert; Graham F. Medley; Sridhar Srikantiah; T. Deirdre Hollingsworth; Sake J. de Vlas
      Pages: 67 - 80
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): Epke A. Le Rutte, Lloyd A.C. Chapman, Luc E. Coffeng, Sarah Jervis, Epco C. Hasker, Shweta Dwivedi, Morchan Karthick, Aritra Das, Tanmay Mahapatra, Indrajit Chaudhuri, Marleen C. Boelaert, Graham F. Medley, Sridhar Srikantiah, T. Deirdre Hollingsworth, Sake J. de Vlas
      We present three transmission models of visceral leishmaniasis (VL) in the Indian subcontinent (ISC) with structural differences regarding the disease stage that provides the main contribution to transmission, including models with a prominent role of asymptomatic infection, and fit them to recent case data from 8 endemic districts in Bihar, India. Following a geographical cross-validation of the models, we compare their predictions for achieving the WHO VL elimination targets with ongoing treatment and vector control strategies. All the transmission models suggest that the WHO elimination target (<1 new VL case per 10,000 capita per year at sub-district level) is likely to be met in Bihar, India, before or close to 2020 in sub-districts with a pre-control incidence of 10 VL cases per 10,000 people per year or less, when current intervention levels (60% coverage of indoor residual spraying (IRS) of insecticide and a delay of 40days from onset of symptoms to treatment (OT)) are maintained, given the accuracy and generalizability of the existing data regarding incidence and IRS coverage. In settings with a pre-control endemicity level of 5/10,000, increasing the effective IRS coverage from 60 to 80% is predicted to lead to elimination of VL 1–3 years earlier (depending on the particular model), and decreasing OT from 40 to 20days to bring elimination forward by approximately 1year. However, in all instances the models suggest that L. donovani transmission will continue after 2020 and thus that surveillance and control measures need to remain in place until the longer-term aim of breaking transmission is achieved.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.01.002
      Issue No: Vol. 18 (2017)
       
  • Comparison and validation of two computational models of Chagas disease: A
           thirty year perspective from Venezuela

    • Authors: Sarah M. Bartsch; Jennifer K. Peterson; Daniel L. Hertenstein; Laura Skrip; Martial Ndeffo-Mbah; Alison P. Galvani; Andrew P. Dobson; Bruce Y. Lee
      Pages: 81 - 91
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): Sarah M. Bartsch, Jennifer K. Peterson, Daniel L. Hertenstein, Laura Skrip, Martial Ndeffo-Mbah, Alison P. Galvani, Andrew P. Dobson, Bruce Y. Lee
      Background Mathematical models can help aid public health responses to Chagas disease. Models are typically developed to fulfill a particular need, and comparing outputs from different models addressing the same question can help identify the strengths and weaknesses of the models in answering particular questions, such as those for achieving the 2020 goals for Chagas disease. Methods Using two separately developed models (PHICOR/CIDMA model and Princeton model), we simulated dynamics for domestic transmission of Trypanosoma cruzi (T. cruzi). We compared how well the models targeted the last 9 years and last 19 years of the 1968–1998 historical seroprevalence data from Venezuela. Results Both models were able to generate the T. cruzi seroprevalence for the next time period within reason to the historical data. The PHICOR/CIDMA model estimates of the total population seroprevalence more closely followed the trends seen in the historic data, while the Princeton model estimates of the age-specific seroprevalence more closely followed historic trends when simulating over 9 years. Additionally, results from both models overestimated T. cruzi seroprevalence among younger age groups, while underestimating the seroprevalence of T. cruzi in older age groups. Conclusion The PHICOR/CIDMA and Princeton models differ in level of detail and included features, yet both were able to generate the historical changes in T. cruzi seroprevalence in Venezuela over 9 and 19-year time periods. Our model comparison has demonstrated that different model structures can be useful in evaluating disease transmission dynamics and intervention strategies.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.02.004
      Issue No: Vol. 18 (2017)
       
  • Data-driven models to predict the elimination of sleeping sickness in
           former Equateur province of DRC

    • Authors: K.S. Rock; A. Pandey; M.L. Ndeffo-Mbah; K.E. Atkins; C. Lumbala; A. Galvani; M.J. Keeling
      Pages: 101 - 112
      Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18
      Author(s): K.S. Rock, A. Pandey, M.L. Ndeffo-Mbah, K.E. Atkins, C. Lumbala, A. Galvani, M.J. Keeling
      Approaching disease elimination, it is crucial to be able to assess progress towards key objectives using quantitative tools. For Gambian human African trypanosomiasis (HAT), the ultimate goal is to stop transmission by 2030, while intermediary targets include elimination as a public health problem − defined as <1 new case per 10,000 inhabitants in 90% of foci, and <2000 reported cases by 2020. Using two independent mathematical models, this study assessed the achievability of these goals in the former Equateur province of the Democratic Republic of Congo, which historically had endemic levels of disease. The two deterministic models used different assumptions on disease progression, risk of infection and non-participation in screening, reflecting biological uncertainty. To validate the models a censor-fit-uncensor procedure was used to fit to health-zone level data from 2000 to 2012; initially the last six years were censored, then three and the final step utilised all data. The different model projections were used to evaluate the expected transmission and reporting for each health zone within each province under six intervention strategies using currently available tools. In 2012 there were 197 reported HAT cases in former Equateur reduced from 6828 in 2000, however this reflects lower active testing for HAT (1.3% of the population compared to 7.2%). Modelling results indicate that there are likely to be <300 reported cases in former Equateur in 2020 if screening continues at the mean level for 2000–2012 (6.2%), and <120 cases if vector control is introduced. Some health zones may fail to achieve <1 new case per 10,000 by 2020 without vector control, although most appear on track for this target using medical interventions alone. The full elimination goal will be harder to reach; between 39 and 54% of health zones analysed may have to improve their current medical-only strategy to stop transmission completely by 2030.

      PubDate: 2017-03-10T03:58:40Z
      DOI: 10.1016/j.epidem.2017.01.006
      Issue No: Vol. 18 (2017)
       
  • Epidemix – an Interactive Multi-Model Application for Teaching and
           Visualizing Infectious Disease Transmission

    • Authors: Ulrich Muellner; Guillaume Fournié; Petra Muellner; Christina Ahlstrom; Dirk U. Pfeiffer
      Abstract: Publication date: Available online 11 December 2017
      Source:Epidemics
      Author(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 (http://shinyapps.rvc.ac.uk) 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.

      PubDate: 2017-12-12T08:37:19Z
      DOI: 10.1016/j.epidem.2017.12.003
       
  • An infectious way to teach students about outbreaks

    • Authors: 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
      Abstract: Publication date: Available online 9 December 2017
      Source:Epidemics
      Author(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.

      PubDate: 2017-12-12T08:37:19Z
      DOI: 10.1016/j.epidem.2017.12.002
       
  • Modeling HIV disease progression and transmission at population-level: The
           potential impact of modifying disease progression in HIV treatment
           programs

    • Authors: 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
      Abstract: Publication date: Available online 5 December 2017
      Source:Epidemics
      Author(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
      Introduction Mathematical 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. Methods We 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. Results The average duration of HIV infection was 9.5 years. The duration of disease before reaching CD4 200cells/μL was 2.53 years longer for females than males. Relative to a baseline of ART initiation at CD4≤500cells/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. Conclusion Even 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.

      PubDate: 2017-12-12T08:37:19Z
      DOI: 10.1016/j.epidem.2017.12.001
       
  • Quantitative risk assessment of salmon louse-induced mortality of
           seaward-migrating post-smolt Atlantic salmon

    • Authors: Anja Bråthen Kristoffersen; Lars Qviller; Kari Olli Helgesen; Knut Wiik Vollset; Hildegunn Viljugrein; Peder Andreas Jansen
      Abstract: Publication date: Available online 2 December 2017
      Source:Epidemics
      Author(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.

      PubDate: 2017-12-12T08:37:19Z
      DOI: 10.1016/j.epidem.2017.11.001
       
  • Dynamics and Control of Infections on Social Networks of Population Types

    • Authors: Brian G. Williams; Christopher Dye
      Abstract: Publication date: Available online 26 October 2017
      Source:Epidemics
      Author(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.

      PubDate: 2017-11-03T02:03:08Z
      DOI: 10.1016/j.epidem.2017.10.002
       
  • The RAPIDD Ebola Forecasting Challenge Special Issue: Preface

    • Authors: Cécile Viboud; Lone Simonsen; Gerardo Chowell; Alessandro Vespignani
      Abstract: Publication date: Available online 24 October 2017
      Source:Epidemics
      Author(s): Cécile Viboud, Lone Simonsen, Gerardo Chowell, Alessandro Vespignani


      PubDate: 2017-10-26T01:41:16Z
      DOI: 10.1016/j.epidem.2017.10.003
       
  • Comparison of cluster-based and source-attribution methods for estimating
           transmission risk using large HIV sequence databases

    • Authors: Stéphane Le Vu; Oliver Ratmann; Valerie Delpech; Alison E. Brown; O. Noel Gill; Anna Tostevin; Christophe Fraser; Erik M. Volz
      Abstract: Publication date: Available online 20 October 2017
      Source:Epidemics
      Author(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.

      PubDate: 2017-10-26T01:41:16Z
      DOI: 10.1016/j.epidem.2017.10.001
       
  • IFC, Ed Board

    • Abstract: Publication date: September 2017
      Source:Epidemics, Volume 20


      PubDate: 2017-09-27T17:01:57Z
       
  • MODELLING MULTI-SITE TRANSMISSION OF THE HUMAN PAPILLOMAVIRUS AND ITS
           IMPACT ON VACCINATION EFFECTIVENESS

    • Authors: P. Lemieux-Mellouki; M. Drolet; M. Jit; G. Gingras; M. Brisson
      Abstract: Publication date: Available online 25 August 2017
      Source:Epidemics
      Author(s): P. Lemieux-Mellouki, M. Drolet, M. Jit, G. Gingras, M. Brisson
      OBJECTIVE Previous HPV models have only included genital transmission, when evidence suggests that transmission between several anatomical sites occurs. We compared model predictions of population-level HPV vaccination effectiveness against genital HPV16 infection in women, using a 1) uni-site (genital site), and a 2) multi-site model (genital and one extragenital site). METHODS We developed a uni-site and a multi-site deterministic HPV transmission model, assuming natural immunity was either site-specific or systemic. Both models were calibrated to genital HPV16 prevalence (5%-7.5%), whilst the multi-site model was calibrated to HPV16 prevalence representative of oral (0%-1%) and anal (1%-7.5%) sites. For each model, we identified 2,500 parameter sets that fit endemic genital and extragenital prevalences within pre-specified target ranges. In the Base-case analysis, vaccination was girls-only with 40% coverage. Vaccine efficacy was 100% for all sites with lifetime protection. The outcome was the relative reduction in genital HPV16 prevalence among women at post-vaccination equilibrium (RRprev). RRprev was stratified by extragenital prevalence pre-vaccination. RESULTS Under assumptions of site-specific immunity, RRprev with the multi-site model was generally greater than with the uni-site model. Differences between the uni-site and multi-site models were greater when transmission from the extragenital site to the genital site was high. Under assumptions of systemic immunity, the multi-site and uni-site models yielded similar RRprev in the scenario without immunity after extragenital infection. In the scenario with systemic immunity after extragenital infection, the multi-site model yielded lower predictions of RRprev than the uni-site model. CONCLUSIONS Modelling genital-site only transmission may overestimate vaccination impact if extragenital infections contribute to systemic natural immunity or underestimate vaccination impact if a high proportion of genital infections originate from extragenital infections. Under current understanding of heterosexual HPV transmission and immunity, a substantial bias from using uni-site models in predicting vaccination effectiveness against genital HPV infection is unlikely to occur.

      PubDate: 2017-09-03T02:59:30Z
      DOI: 10.1016/j.epidem.2017.08.001
       
  • The impact of current infection levels on the cost-benefit of vaccination

    • Authors: Matt J. Keeling; Katherine A. Broadfoot; Samik Datta
      Abstract: Publication date: Available online 8 July 2017
      Source:Epidemics
      Author(s): Matt J. Keeling, Katherine A. Broadfoot, Samik Datta
      When considering a new vaccine program or modifying an existing one, economic cost-benefit analysis, underpinned by predictive epidemiological modelling, is a key component. This analysis is intimately linked to the willingness to pay for additional QALYs (quality-adjusted life-years) gained; currently in England and Wales a health program is economically viable if the cost per QALY gained is less than £ 20,000, and models are often used to assess if a vaccine program is likely to fall below this threshold cost. Before a program begins, infection levels are generally high and therefore vaccination may be expected to have substantial effects and therefore will often be economically viable. However, once a program is established, and infection rates are lower, it might be expected that a re-evaluation of the program (using current incidence information) will show it to be less cost-effective. This is the scenario we examine here with analytical tools and simple ODE models. Surprisingly we show that in most cases the benefits from maintaining an existing vaccination program are at least equal to those of starting the program initially, and in the majority of scenarios the differences between the two are minimal. In practical terms, this is an extremely helpful finding, allowing us to assert that the action of immunising individuals does not de-value the vaccination program.

      PubDate: 2017-07-12T01:50:50Z
      DOI: 10.1016/j.epidem.2017.06.004
       
  • Zika virus dynamics: When does sexual transmission matter'

    • Authors: Ondrej Maxian; Anna Neufeld; Emma J. Talis; Lauren M. Childs; Julie C. Blackwood
      Abstract: Publication date: Available online 29 June 2017
      Source:Epidemics
      Author(s): Ondrej Maxian, Anna Neufeld, Emma J. Talis, Lauren M. Childs, Julie C. Blackwood
      The Zika virus (ZIKV) has captured worldwide attention with the ongoing epidemic in South America and its link to severe birth defects, most notably microcephaly. ZIKV is spread to humans through a combination of vector and sexual transmission, but the relative contribution of these transmission routes to the overall epidemic remains largely unknown. Furthermore, a disparity in the reported number of infections between males and females has been observed. We develop a mathematical model that describes the transmission dynamics of ZIKV to determine the processes driving the observed epidemic patterns. Our model reveals a 4.8% contribution of sexual transmission to the basic reproductive number, R 0. This contribution is too minor to independently sustain an outbreak but suggests that vector transmission is the main driver of the ongoing epidemic. We also find a minor, yet statistically significant, difference in the mean number of cases in males and females, both at the peak of the epidemic and at equilibrium. While this suggests an intrinsic disparity between males and females, the differences do not account for the vastly greater number of reported cases for females, indicative of a large reporting bias. In addition, we identify conditions under which sexual transmission may play a key role in sparking an epidemic, including temperate areas where ZIKV mosquito vectors are less prevalent.

      PubDate: 2017-07-02T21:33:22Z
      DOI: 10.1016/j.epidem.2017.06.003
       
  • Optimally capturing latency dynamics in models of tuberculosis
           transmission

    • Authors: Romain Ragonnet; James M. Trauer; Nick Scott; Michael T. Meehan; Justin T. Denholm; Emma S. McBryde
      Abstract: Publication date: Available online 16 June 2017
      Source:Epidemics
      Author(s): Romain Ragonnet, James M. Trauer, Nick Scott, Michael T. Meehan, Justin T. Denholm, Emma S. McBryde
      Although different structures are used in modern tuberculosis (TB) models to simulate TB latency, it remains unclear whether they are all capable of reproducing the particular activation dynamics empirically observed. We aimed to determine which of these structures replicate the dynamics of progression accurately. We reviewed 88 TB-modelling articles and classified them according to the latency structure employed. We then fitted these different models to the activation dynamics observed from 1352 infected contacts diagnosed in Victoria (Australia) and Amsterdam (Netherlands) to obtain parameter estimates. Six different model structures were identified, of which only those incorporating two latency compartments were capable of reproducing the activation dynamics empirically observed. We found important differences in parameter estimates by age. We also observed marked differences between our estimates and the parameter values used in many previous models. In particular, when two successive latency phases are considered, the first period should have a duration that is much shorter than that used in previous studies. In conclusion, structures incorporating two latency compartments and age-stratification should be employed to accurately replicate the dynamics of TB latency. We provide a catalogue of parameter values and an approach to parameter estimation from empiric data for calibration of future TB-models.

      PubDate: 2017-06-21T21:09:58Z
      DOI: 10.1016/j.epidem.2017.06.002
       
  • A Human Time Dose Response Model for Q fever

    • Authors: Charles W. Heppell; Joseph R. Egan; Ian Hall
      Abstract: Publication date: Available online 15 June 2017
      Source:Epidemics
      Author(s): Charles W. Heppell, Joseph R. Egan, Ian Hall
      The causative agent of Q fever, Coxiella burnetii, has the potential to be developed for use in biological warfare and it is classified as a bioterrorism threat agent by the Centers for Disease Control and Prevention (CDC) and as a category B select agent by the National Institute of Allergy and Infectious Diseases (NIAID). In this paper we focus on the in-host properties that arise when an individual inhales a dose of C.burnetii and establish a human time-dose response model. We also propagate uncertainty throughout the model allowing us to robustly estimate key properties including the infectious dose and incubation period. Using human study data conducted in the 1950's we conclude that the dose required for a 50% probability of infection is about 15 organisms, and that one inhaled organism of C.burnetti can cause infection in 5% of the exposed population. In addition, we derive a low dose incubation period of 17.6 days and an extracellular doubling time of half a day. In conclusion this paper provides a framework for detailing the parameters and approaches that would be required for risk assessments associated with exposures to C.burnetii that might cause human infection.

      PubDate: 2017-06-16T21:00:27Z
      DOI: 10.1016/j.epidem.2017.06.001
       
  • IFC, Ed Board

    • Abstract: Publication date: June 2017
      Source:Epidemics, Volume 19


      PubDate: 2017-06-16T21:00:27Z
       
  • Corrigendum to “Impact of waning acquired immunity and asymptomatic
           infections on case-control studies for enteric pathogens” [Epidemics 17
           (2016) 56–63]

    • Authors: A.H. Havelaar; A. Swart
      Abstract: Publication date: Available online 4 May 2017
      Source:Epidemics
      Author(s): A.H. Havelaar, A. Swart


      PubDate: 2017-05-08T18:55:48Z
      DOI: 10.1016/j.epidem.2017.03.006
       
  • Inferring epidemiological dynamics of infectious diseases using Tajima's D
           statistic on nucleotide sequences of pathogens

    • Authors: Kiyeon Kim; Ryosuke Omori; Kimihito Ito
      Abstract: Publication date: Available online 1 May 2017
      Source:Epidemics
      Author(s): Kiyeon Kim, Ryosuke Omori, Kimihito Ito
      The estimation of the basic reproduction number is essential to understand epidemic dynamics, and time series data of infected individuals are usually used for the estimation. However, such data are not always available. Methods to estimate the basic reproduction number using genealogy constructed from nucleotide sequences of pathogens have been proposed so far. Here, we propose a new method to estimate epidemiological parameters of outbreaks using the time series change of Tajima's D statistic on the nucleotide sequences of pathogens. To relate the time evolution of Tajima's D to the number of infected individuals, we constructed a parsimonious mathematical model describing both the transmission process of pathogens among hosts and the evolutionary process of the pathogens. As a case study we applied this method to the field data of nucleotide sequences of pandemic influenza A (H1N1) 2009 viruses collected in Argentina. The Tajima's D-based method estimated basic reproduction number to be 1.55 with 95% highest posterior density (HPD) between 1.31 and 2.05, and the date of epidemic peak to be 10th July with 95% HPD between 22nd June and 9th August. The estimated basic reproduction number was consistent with estimation by birth–death skyline plot and estimation using the time series of the number of infected individuals. These results suggested that Tajima's D statistic on nucleotide sequences of pathogens could be useful to estimate epidemiological parameters of outbreaks.

      PubDate: 2017-05-02T18:48:06Z
      DOI: 10.1016/j.epidem.2017.04.004
       
  • Publicly available software tools for decision-makers during an emergent
           epidemic—systematic evaluation of utility and usability

    • Authors: David James Heslop; Abrar Ahmad Chughtai; Chau Minh Bui; C. Raina MacIntyre
      Abstract: Publication date: Available online 26 April 2017
      Source:Epidemics
      Author(s): David James Heslop, Abrar Ahmad Chughtai, Chau Minh Bui, C. Raina MacIntyre
      Epidemics and emerging infectious diseases are becoming an increasing threat to global populations − challenging public health practitioners, decision makers and researchers to plan, prepare, identify and respond to outbreaks in near real-timeframes. The aim of this research is to evaluate the range of public domain and freely available software epidemic modelling tools. Twenty freely utilisable software tools underwent assessment of software usability, utility and key functionalities. Stochastic and agent based tools were found to be highly flexible, adaptable, had high utility and many features, but low usability. Deterministic tools were highly usable with average to good levels of utility.

      PubDate: 2017-05-02T18:48:06Z
      DOI: 10.1016/j.epidem.2017.04.002
       
  • Mathematical modeling of ovine footrot in the UK: the effect of
           Dichelobacter nodosus and Fusobacterium necrophorum on the disease
           dynamics

    • Authors: Jolene Atia; Emma Monaghan; Jasmeet Kaler; Kevin Purdy; Laura Green; Matt Keeling
      Abstract: Publication date: Available online 12 April 2017
      Source:Epidemics
      Author(s): Jolene Atia, Emma Monaghan, Jasmeet Kaler, Kevin Purdy, Laura Green, Matt Keeling
      Dichelobacter nodosus is a virulent, invasive, anaerobic bacterium that is believed to be the causative agent of ovine footrot, an infectious bacterial disease of sheep that causes lameness. Another anaerobe, Fusobacterium necrophorum, has been intimately linked with the disease occurrence and severity. Here we examine data from a longitudinal study of footrot on one UK farm, including quantitative PCR (qPCR) estimates of bacterial load of D. nodosus and F.necrophorum. The data is at foot level; all feet were monitored for five weeks assessing disease severity (healthy, interdigital dermatitis (ID), or severe footrot (SFR)) and bacterial load (number of bacteria/swab). We investigate the role of D.nodosus and F.necrophorum in the progress of the disease using a continuous-time Markov model with 12 different states characterising the foot. The transition rates between the adjacent states are the (34) model parameters, these are determined using Metropolis Hasting MCMC. Our aim is to determine the predictive relationship between past and future D. nodosus and F. necrophorum load and disease states. We demonstrate a high level of predictive accuracy at the population level for the D.nodosus model, although the dynamics of individual feet is highly stochastic. However, we note that this predictive accuracy at population level is only high in more diseased states for F.necrophorum model. This supports our hypothesis that D.nodosus load and status of the foot work in combination to give rise to severe footrot and lameness, and that D.nodosus load plays the primary role in the initiation and progression of footrot, while F.necrophorum load rather increases disease severity of SFR.

      PubDate: 2017-04-19T10:58:23Z
      DOI: 10.1016/j.epidem.2017.04.001
       
  • Displacement of Sexual Partnerships in Trials of Sexual Behavior
           Interventions: A Model-Based Assessment of Consequences

    • Authors: Alethea W. McCormick; Nadia N. Abuelezam; Thomas Fussell; George R. Seage; Marc Lipsitch
      Abstract: Publication date: Available online 2 April 2017
      Source:Epidemics
      Author(s): Alethea W. McCormick, Nadia N. Abuelezam, Thomas Fussell, George R. Seage, Marc Lipsitch
      We investigated the impact of the displacement of sexual activity from adherent recipients of an intervention to others within or outside a trial population on the results from hypothetical trials of different sexual behavior interventions. A short-term model of HIV-prevention interventions that lead to female rejection of male partnership requests showed the impact of displacement expected at the start of a trial. An agent-based model, with sexual mixing and other South African specific demographics, evaluated consequences of displacement for sexual behavior interventions targeting young females in South Africa. This model measured the cumulative incidence among adherent, non-adherent, control and non-enrolled females in a hypothetical trial of HIV prevention. When males made more than one attempt to seek a partnership, interventions reduced short-term HIV infection risk among adherent females, but increased it among non-adherent females as well as controls, non-enrolled (females eligible for the trial but not chosen to participate) and ineligible females (females that did not qualify for the trial due to age). The impact of displacement depends on the intervention and the adherence. In both models, the risk to individuals who are not members of the adherent intervention group will increase with displacement leading to a biased calculation for the effect estimates for the trial. Likewise, intent-to-treat effect estimates become nonlinear functions of the proportion adherent.
      Graphical abstract image

      PubDate: 2017-04-05T10:29:35Z
      DOI: 10.1016/j.epidem.2017.03.007
       
  • Elucidating transmission dynamics and host-parasite-vector relationships
           for rodent-borne Bartonella spp. in Madagascar

    • Authors: Cara E. Brook; Ying Bai; Emily O. Yu; Hafaliana C. Ranaivoson; Haewon Shin; Andrew P. Dobson; C. Jessica E. Metcalf; Michael Y. Kosoy; Katharina Dittmar
      Abstract: Publication date: Available online 16 March 2017
      Source:Epidemics
      Author(s): Cara E. Brook, Ying Bai, Emily O. Yu, Hafaliana C. Ranaivoson, Haewon Shin, Andrew P. Dobson, C. Jessica E. Metcalf, Michael Y. Kosoy, Katharina Dittmar
      Bartonella spp. are erythrocytic bacteria transmitted via arthropod vectors, which infect a broad range of vertebrate hosts, including humans. We investigated transmission dynamics and host-parasite-vector relationships for potentially zoonotic Bartonella spp. in invasive Rattus rattus hosts and associated arthropod ectoparasites in Madagascar. We identified five distinct species of Bartonella (B. elizabethae 1, B. elizabethae 2, B. phoceensis 1, B. rattimassiliensis 1, and B. tribocorum 1) infecting R. rattus rodents and their ectoparasites. We fit standard epidemiological models to species-specific age-prevalence data for the four Bartonella spp. with sufficient data, thus quantifying age-structured force of infection. Known zoonotic agents, B. elizabethae 1 and 2, were best described by models exhibiting high forces of infection in early age class individuals and allowing for recovery from infection, while B. phoceensis 1 and B. rattimassiliensis 1 were best fit by models of lifelong infection without recovery and substantially lower forces of infection. Nested sequences of B. elizabethae 1 and 2 were recovered from rodent hosts and their Synopsyllus fonquerniei and Xenopsylla cheopsis fleas, with a particularly high prevalence in the outdoor-dwelling, highland-endemic S. fonquerniei. These findings expand on force of infection analyses to elucidate the ecological niche of the zoonotic Bartonella elizabethae complex in Madagascar, hinting at a potential vector role for S. fonquerniei. Our analyses underscore the uniqueness of such ecologies for Bartonella species, which pose a variable range of potential zoonotic threats.

      PubDate: 2017-03-17T09:38:13Z
      DOI: 10.1016/j.epidem.2017.03.004
       
  • The impact of stratified immunity on the transmission dynamics of
           influenza

    • Authors: Hsiang-Yu Yuan; Marc Baguelin; Kin O. Kwok; Nimalan Arinaminpathy; Edwin van Leeuwen; Steven Riley
      Abstract: Publication date: Available online 12 March 2017
      Source:Epidemics
      Author(s): Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin van Leeuwen, Steven Riley
      Although empirical studies show that protection against influenza infection in humans is closely related to antibody titres, influenza epidemics are often described under the assumption that individuals are either susceptible or not. Here we develop a model in which antibody titre classes are enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Fitting only with pre- and post-wave serological data during 2009 pandemic in Hong Kong, we demonstrate that with stratified immunity, the timing and the magnitude of the epidemic dynamics can be reconstructed more accurately than is possible with binary seropositivity data. We also show that increased infectiousness of children relative to adults and age-specific mixing are required to reproduce age-specific seroprevalence observed in Hong Kong, while pre-existing immunity in the elderly is not. Overall, our results suggest that stratified immunity in an aged-structured heterogeneous population plays a significant role in determining the shape of influenza epidemics.

      PubDate: 2017-03-17T09:38:13Z
      DOI: 10.1016/j.epidem.2017.03.003
       
  • On the duration of the period between exposure to HIV and detectable
           infection

    • Authors: Bernhard P. Konrad; Darlene Taylor; Jessica M. Conway; Gina S. Ogilvie; Daniel Coombs
      Abstract: Publication date: Available online 11 March 2017
      Source:Epidemics
      Author(s): Bernhard P. Konrad, Darlene Taylor, Jessica M. Conway, Gina S. Ogilvie, Daniel Coombs
      HIV infection cannot be detected immediately after exposure because plasma viral loads are too small initially. The duration of this phase of infection (the “eclipse period”) is difficult to estimate because precise dates of exposure are rarely known. Therefore, the reliability of clinical HIV testing during the first few weeks of infections is unknown, creating anxiety among HIV-exposed individuals and their physicians. We address this by fitting stochastic models of early HIV infection to detailed viral load records for 78 plasma donors, taken during the period of exposure and infection. We first show that the classic stochastic birth-death model does not satisfactorily describe early infection. We therefore apply a different stochastic model that includes infected cells and virions separately. Since every plasma donor in our data eventually becomes infected, we must condition the model to reflect this bias, before fitting to the data. Applying our best estimates of unknown parameter values, we estimate the mean eclipse period to be 8-10 days. We further estimate the reliability of a negative test t days after potential exposure.

      PubDate: 2017-03-17T09:38:13Z
      DOI: 10.1016/j.epidem.2017.03.002
       
  • IFC, Ed Board

    • Abstract: Publication date: March 2017
      Source:Epidemics, Volume 18


      PubDate: 2017-03-10T03:58:40Z
       
  • Dynamics Affecting the Risk of Silent Circulation When Oral Polio
           Vaccination Is Stopped

    • Authors: J.S. Koopman; C.J. Henry; J.H. Park; M.C. Eisenberg; E.L. Ionides; J.N. Eisenberg
      Abstract: Publication date: Available online 1 March 2017
      Source:Epidemics
      Author(s): J.S. Koopman, C.J. Henry, J.H. Park, M.C. Eisenberg, E.L. Ionides, J.N. Eisenberg
      Waning immunity could allow transmission of polioviruses without causing poliomyelitis by promoting silent circulation (SC). Undetected SC when oral polio vaccine (OPV) use is stopped could cause difficult to control epidemics. Little is known about waning. To develop theory about what generates SC, we modeled a range of waning patterns. We varied both OPV and wild polio virus (WPV) transmissibility, the time from beginning vaccination to reaching low polio levels, and the infection to paralysis ratio (IPR). There was longer SC when waning continued over time rather than stopping after a few years, when WPV transmissibility was higher or OPV transmissibility was lower, and when the IPR was higher. These interacted in a way that makes recent emergence of prolonged SC a possibility. As the time to reach low infection levels increased, vaccine rates needed to eliminate polio increased and a threshold was passed where prolonged low-level SC emerged. These phenomena were caused by increased contributions to the force of infection from reinfections. The resulting SC occurs at low levels that would be difficult to detect using environmental surveillance. For all waning patterns, modest levels of vaccination of adults shortened SC. Previous modeling studies may have missed these phenomena because 1) they used models with no or very short duration waning and 2) they fit models to paralytic polio case counts. Our analyses show that polio case counts can’t predict SC because nearly identical polio case count patterns can be generated by a range of waning patterns that generate different patterns of SC. We conclude that the possibility of prolonged SC is real but unquantified, that vaccinating modest fractions of adults could reduce SC risk, and that joint analysis of acute flaccid paralysis and environmental surveillance data can help assess SC risks and ensure low risks before stopping OPV.

      PubDate: 2017-03-04T00:45:22Z
      DOI: 10.1016/j.epidem.2017.02.013
       
  • Modelling H5N1 in Bangladesh across spatial scales: model complexity and
           zoonotic transmission risk

    • Authors: Edward M. Hill; Thomas House; Madhur S. Dhingra; Wantanee Kalpravidh; Subhash Morzaria; Muzaffar G. Osmani; Mat Yamage; Xiangming Xiao; Marius Gilbert; Michael J. Tildesley
      Abstract: Publication date: Available online 21 February 2017
      Source:Epidemics
      Author(s): Edward M. Hill, Thomas House, Madhur S. Dhingra, Wantanee Kalpravidh, Subhash Morzaria, Muzaffar G. Osmani, Mat Yamage, Xiangming Xiao, Marius Gilbert, Michael J. Tildesley
      Highly pathogenic avian influenza H5N1 remains a persistent public health threat, capable of causing infection in humans with a high mortality rate while simultaneously negatively impacting the livestock industry. A central question is to determine regions that are likely sources of newly emerging influenza strains with pandemic causing potential. A suitable candidate is Bangladesh, being one of the most densely populated countries in the world and having an intensifying farming system. It is therefore vital to establish the key factors, specific to Bangladesh, that enable both continued transmission within poultry and spillover across the human-animal interface. We apply a modelling framework to H5N1 epidemics in the Dhaka region of Bangladesh, occurring from 2007 onwards, that resulted in large outbreaks in the poultry sector and a limited number of confirmed human cases. This model consisted of separate poultry transmission and zoonotic transmission components. Utilising poultry farm spatial and population information a set of competing nested models of varying complexity were fitted to the observed case data, with parameter inference carried out using Bayesian methodology and goodness-of-fit verified by stochastic simulations. For the poultry transmission component, successfully identifying a model of minimal complexity, which enabled the accurate prediction of the size and spatial distribution of cases in H5N1 outbreaks, was found to be dependent on the administration level being analysed. A consistent outcome of non-optimal reporting of infected premises materialised in each poultry epidemic of interest, though across the outbreaks analysed there were substantial differences in the estimated transmission parameters. The zoonotic transmission component found the main contributor to spillover transmission of H5N1 in Bangladesh was found to differ from one poultry epidemic to another. We conclude by discussing possible explanations for these discrepancies in transmission behaviour between epidemics, such as changes in surveillance sensitivity and biosecurity practices.

      PubDate: 2017-02-25T00:38:17Z
      DOI: 10.1016/j.epidem.2017.02.007
       
  • Population effect of influenza vaccination under co-circulation of
           

    • Authors: Colin J. Worby; Jacco Wallinga; Marc Lipsitch; Edward Goldstein
      Abstract: Publication date: Available online 21 February 2017
      Source:Epidemics
      Author(s): Colin J. Worby, Jacco Wallinga, Marc Lipsitch, Edward Goldstein
      Some past epidemics of different influenza subtypes (particularly A/H3N2) in the US saw co-circulation of vaccine-type and variant strains. There is evidence that natural infection with one influenza subtype offers short-term protection against infection with another influenza subtype (henceforth, cross-immunity). This suggests that such cross-immunity for strains within a subtype is expected to be strong. Therefore, while vaccination effective against one strain may reduce transmission of that strain, this may also lead to a reduction of the vaccine-type strain's ability to suppress spread of a variant strain. It remains unclear what the joint effect of vaccination and cross-immunity is for co-circulating influenza strains within a subtype, and what is the potential benefit of a bivalent vaccine that protects against both strains. We simulated co-circulation of vaccine-type and variant strains under a variety of scenarios. In each scenario, we considered the case when the vaccine efficacy against the variant strain is lower than the efficacy against the vaccine-type strain (monovalent vaccine), as well the case when vaccine is equally efficacious against both strains (bivalent vaccine). Administration of a bivalent vaccine results in a significant reduction in the overall incidence of infection compared to administration of a monovalent vaccine, even with lower coverage by the bivalent vaccine. Additionally, we found that with greater cross-immunity, increasing coverage levels for the monovalent vaccine becomes less beneficial, while introducing the bivalent vaccine becomes more beneficial. Our work exhibits the limitations of influenza vaccines that have low efficacy against non-vaccine strains, and demonstrates the benefits of vaccines that offer good protection against multiple influenza strains. The results elucidate the need for guarding against the potential co-circulation of non-vaccine strains for an influenza subtype, at least during select seasons, possibly through inclusion of multiple strains within a subtype (particularly A/H3N2) in a vaccine.

      PubDate: 2017-02-25T00:38:17Z
      DOI: 10.1016/j.epidem.2017.02.008
       
  • Gender asymmetry in concurrent partnerships and HIV prevalence

    • Authors: Ka Yin Leung; Kimberly A. Powers; Mirjam Kretzschmar
      Abstract: Publication date: Available online 20 January 2017
      Source:Epidemics
      Author(s): Ka Yin Leung, Kimberly A. Powers, Mirjam Kretzschmar
      The structure of the sexual network of a population plays an essential role in the transmission of HIV. Concurrent partnerships, i.e. partnerships that overlap in time, are important in determining this network structure. Men and women may differ in their concurrent behavior, e.g. in the case of polygyny where women are monogamous while men may have concurrent partnerships. Polygyny has been shown empirically to be negatively associated with HIV prevalence, but the epidemiological impacts of other forms of gender-asymmetric concurrency have not been formally explored. Here we investigate how gender asymmetry in concurrency, including polygyny, can affect the disease dynamics. We use a model for a dynamic network where individuals may have concurrent partners. The maximum possible number of simultaneous partnerships can differ for men and women, e.g. in the case of polygyny. We control for mean partnership duration, mean lifetime number of partners, mean degree, and sexually active lifespan. We assess the effects of gender asymmetry in concurrency on two epidemic phase quantities (R 0 and the contribution of the acute HIV stage to R 0) and on the endemic HIV prevalence. We find that gender asymmetry in concurrent partnerships is associated with lower levels of all three epidemiological quantities, especially in the polygynous case. This effect on disease transmission can be attributed to changes in network structure, where increasing asymmetry leads to decreasing network connectivity.

      PubDate: 2017-01-22T23:02:58Z
      DOI: 10.1016/j.epidem.2017.01.003
       
  • Characterising pandemic severity and transmissibility from data collected
           during first few hundred studies

    • Authors: Andrew J. Black; Nicholas Geard; James M. McCaw; Jodie McVernon; Joshua V. Ross
      Abstract: Publication date: Available online 19 January 2017
      Source:Epidemics
      Author(s): Andrew J. Black, Nicholas Geard, James M. McCaw, Jodie McVernon, Joshua V. Ross
      Early estimation of the probable impact of a pandemic influenza outbreak can assist public health authorities to ensure that response measures are proportionate to the scale of the threat. Recently, frameworks based on transmissibility and severity have been proposed for initial characterization of pandemic impact. Data requirements to inform this assessment may be provided by “First Few Hundred” (FF100) studies, which involve surveillance—possibly in person, or via telephone—of household members of confirmed cases. This process of enhanced case finding enables detection of cases across the full spectrum of clinical severity, including the date of symptom onset. Such surveillance is continued until data for a few hundred cases, or satisfactory characterization of the pandemic strain, has been achieved. We present a method for analysing these data, at the household level, to provide a posterior distribution for the parameters of a model that can be interpreted in terms of severity and transmissibility of a pandemic strain. We account for imperfect case detection, where individuals are only observed with some probability that can increase after a first case is detected. Furthermore, we test this methodology using simulated data generated by an independent model, developed for a different purpose and incorporating more complex disease and social dynamics. Our method recovers transmissibility and severity parameters to a high degree of accuracy and provides a computationally efficient approach to estimating the impact of an outbreak in its early stages.
      Graphical abstract image Highlights

      PubDate: 2017-01-22T23:02:58Z
      DOI: 10.1016/j.epidem.2017.01.004
       
  • A comparative analysis of Chikungunya and Zika transmission

    • Authors: Julien Riou; Chiara Poletto; Pierre-Yves Boëlle
      Abstract: Publication date: Available online 18 January 2017
      Source:Epidemics
      Author(s): Julien Riou, Chiara Poletto, Pierre-Yves Boëlle
      The recent global dissemination of Chikungunya and Zika has fostered public health concern worldwide. To better understand the drivers of transmission of these two arboviral diseases, we propose a joint analysis of Chikungunya and Zika epidemics in the same territories, taking into account the common epidemiological features of the epidemics: transmitted by the same vector, in the same environments, and observed by the same surveillance systems. We analyse eighteen outbreaks in French Polynesia and the French West Indies using a hierarchical time-dependent SIR model accounting for the effect of virus, location and weather on transmission, and based on a disease specific serial interval. We show that Chikungunya and Zika have similar transmission potential in the same territories (transmissibility ratio between Zika and Chikungunya of 1.04 [95% credible interval: 0.97; 1.13]), but that detection and reporting rates were different (around 19% for Zika and 40% for Chikungunya). Temperature variations between 22°C and 29°C did not alter transmission, but increased precipitation showed a dual effect, first reducing transmission after a two-week delay, then increasing it around five weeks later. The present study provides valuable information for risk assessment and introduces a modelling framework for the comparative analysis of arboviral infections that can be extended to other viruses and territories.

      PubDate: 2017-01-22T23:02:58Z
      DOI: 10.1016/j.epidem.2017.01.001
       
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
 
Home (Search)
Subjects A-Z
Publishers A-Z
Customise
APIs
Your IP address: 54.196.182.102
 
About JournalTOCs
API
Help
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2016