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Carter A, Msemburi W, Sim SY, Gaythorpe KAM, Lambach P, Lindstrand A, Hutubessy R. Modeling the impact of vaccination for the immunization Agenda 2030: Deaths averted due to vaccination against 14 pathogens in 194 countries from 2021 to 2030. Vaccine 2024; 42 Suppl 1:S28-S37. [PMID: 37537094 DOI: 10.1016/j.vaccine.2023.07.033] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 04/19/2023] [Accepted: 07/14/2023] [Indexed: 08/05/2023]
Abstract
BACKGROUND The Immunization Agenda 2030 (IA2030) Impact Goal 1.1. aims to reduce the number of future deaths averted through immunization in the next decade. To estimate the potential impact of the aspirational coverage targets for IA2030, we developed an analytical framework and estimated the number of deaths averted due to an ambitious vaccination coverage scenario from 2021 to 2030 in 194 countries. METHOD A demographic model was used to determine annual age-specific mortality estimates associated with vaccine coverage rates. For ten pathogens (Hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, yellow fever), we derived single measures of country-, age-, and pathogen-specific relative risk of deaths conditional upon coverage rates, leveraging the data from 18 modeling groups as part of the Vaccine Impact Model Consortium (VIMC) for 110 countries. We used a logistic regression model to extrapolate the relative risk estimates to countries that were not modeled by VIMC. For four pathogens (diphtheria, tetanus, pertussis and tuberculosis), we used estimates from the Global Burden of Disease 2019 study and existing literature on vaccine efficacy. A future scenario defining years of vaccine introduction and scale-up needed to reach aspirational targets was developed as an input to estimate the long-term impact of vaccination taking place from 2021 to 2030. FINDINGS Overall, an estimated 51.5 million (95 % CI: 44.0-63.2) deaths are expected to be averted due to vaccinations administered between the years 2021 and 2030. With immunization coverage projected to increase over 2021-2030 an average of 5.2 million per year (4.4-6.3) deaths will be averted annually, with 4.4 million (3.9-5.1) deaths be averted for the year 2021, gradually rising to 5.8 million (4.9-7.5) deaths averted in 2030. The largest proportion of deaths is attributed to Measles and Hepatitis B accounting for 18.8 million (17.8-20.0) and 14.0 million (11.5-16.9) of total deaths averted respectively. INTERPRETATION The results from this global analysis demonstrate the substantial potential mortality reductions achievable if the IA2030 targets are met by 2030. Deaths caused by vaccine preventable diseases disproportionately affect LMICs in the African region.
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Affiliation(s)
- Austin Carter
- University of Washington, Seattle, WA, USA; World Health Organization, Department of Immunization, Vaccines and Biologicals (IVB), Geneva, Switzerland.
| | - William Msemburi
- World Health Organization, Division of Data, Analytics and Delivery for Impact (DDI), Geneva, Switzerland.
| | - So Yoon Sim
- World Health Organization, Department of Immunization, Vaccines and Biologicals (IVB), Geneva, Switzerland.
| | | | - Philipp Lambach
- World Health Organization, Department of Immunization, Vaccines and Biologicals (IVB), Geneva, Switzerland.
| | - Ann Lindstrand
- World Health Organization, Department of Immunization, Vaccines and Biologicals (IVB), Geneva, Switzerland.
| | - Raymond Hutubessy
- World Health Organization, Department of Immunization, Vaccines and Biologicals (IVB), Geneva, Switzerland.
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Abegaz MY, Seid A, Awol SM, Hassen SL. Determinants of incomplete child vaccination among mothers of children aged 12-23 months in Worebabo district, Ethiopia: Unmatched case-control study. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0002088. [PMID: 37585408 PMCID: PMC10431650 DOI: 10.1371/journal.pgph.0002088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/30/2023] [Indexed: 08/18/2023]
Abstract
In nations like Ethiopia, vaccination rates are low despite being one of the most effective public health treatments to protect infants from common infectious diseases that can be prevented by immunization. In Worebabo District, the reasons of the underutilization of vaccination programs are poorly understood. Therefore, this study aimed to identify determinants of incomplete childhood vaccination in the study setting. Community based unmatched case-control study was carried out among 441 mothers of children aged 12-23 months old (147 cases and 294 controls) in Worebabo District, Ethiopia from March 1-April 30, 2020. Using a multistage sampling process, mothers were chosen. Health professionals were trained to collect data using a pre-tested standardized questionnaire. Data entered into Epi Info version 7.2 and put through statistical analysis in SPSS version 23. Binary logistic regression was performed to determine the odds ratio with a 95%CL. A p-value of under 0.05 was estimated statistically significant. The study found that older moms (>35 years old) were more likely than younger mothers to fail to properly immunize their children (AOR = 2.4, 95% CI: 1.09, 5.28). In addition, mothers with incomplete vaccinations had lower knowledge of the benefits of vaccination (AOR = 2.02, 95% CI: 1.20, 3.39), Negative attitudes towards immunization (AOR = 4.9, 95% CI: 2.82, 8.49), less access to prenatal care (AOR = 3.68, 95% CI: 1.58, 8.54), home delivery (AOR = 5.47, 95% CI: 2.58)., 11.58), absent home visits (AOR = 3.56, 95% CI: 1.69, 7.48), and longer time to reach vaccination site (>1 h) (AOR = 10.07)., 95% CI: 1.75, 57.79) were found associated with mother incomplete vaccination of the child. Mothers being older age, less access to antenatal care services, place of home delivery, longer time to reach vaccination site, negative attitude and poor knowledge towards the benefit of vaccination were associated with mothers' incomplete vaccination of the child. Therefore, health professionals should inform and counsel mothers about the advantages of childhood immunization as well as the consequences of incomplete or not vaccination of children at the time of the facility visit and by community health workers during the routine home visit.
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Affiliation(s)
- Mesfin Yimer Abegaz
- Department of Public Health St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Awol Seid
- Department of Public Health St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Shikur Mohammed Awol
- Department of Public Health St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Seid Legesse Hassen
- Amhara Public Health Institute, Research and Technology Transfer Directorate, Dessie, Ethiopia
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3
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Agent-based modelling of reactive vaccination of workplaces and schools against COVID-19. Nat Commun 2022; 13:1414. [PMID: 35301289 PMCID: PMC8931017 DOI: 10.1038/s41467-022-29015-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 02/17/2022] [Indexed: 12/30/2022] Open
Abstract
With vaccination against COVID-19 stalled in some countries, increasing vaccine accessibility and distribution could help keep transmission under control. Here, we study the impact of reactive vaccination targeting schools and workplaces where cases are detected, with an agent-based model accounting for COVID-19 natural history, vaccine characteristics, demographics, behavioural changes and social distancing. In most scenarios, reactive vaccination leads to a higher reduction in cases compared with non-reactive strategies using the same number of doses. The reactive strategy could however be less effective than a moderate/high pace mass vaccination program if initial vaccination coverage is high or disease incidence is low, because few people would be vaccinated around each case. In case of flare-ups, reactive vaccination could better mitigate spread if it is implemented quickly, is supported by enhanced test-trace-isolate and triggers an increased vaccine uptake. These results provide key information to plan an adaptive vaccination rollout. The authors use an agent-based model to investigate the potential of reactive vaccination strategies for COVID-19 outbreak mitigation. They find that distributing vaccines in schools and workplaces where cases are detected is more impactful than non-reactive strategies in a wide range of epidemic scenarios.
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Kretzschmar ME, Ashby B, Fearon E, Overton CE, Panovska-Griffiths J, Pellis L, Quaife M, Rozhnova G, Scarabel F, Stage HB, Swallow B, Thompson RN, Tildesley MJ, Villela D. Challenges for modelling interventions for future pandemics. Epidemics 2022; 38:100546. [PMID: 35183834 PMCID: PMC8830929 DOI: 10.1016/j.epidem.2022.100546] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 02/04/2022] [Accepted: 02/09/2022] [Indexed: 12/16/2022] Open
Abstract
Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross-disciplinary collaboration together with close communication between scientists and policy makers.
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Affiliation(s)
- Mirjam E Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Ben Ashby
- Department of Mathematical Sciences, University of Bath, Bath BA2 7AY, UK
| | - Elizabeth Fearon
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, UK
| | - Christopher E Overton
- Department of Mathematics, University of Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK; Clinical Data Science Unit, Manchester University NHS Foundation Trust, UK
| | - Jasmina Panovska-Griffiths
- The Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK; The Queen's College, University of Oxford, Oxford, UK
| | - Lorenzo Pellis
- Department of Mathematics, University of Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK; The Alan Turing Institute, London, UK
| | - Matthew Quaife
- TB Modelling Group, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK
| | - Ganna Rozhnova
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; BioISI-Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal
| | - Francesca Scarabel
- Department of Mathematics, University of Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK; CDLab - Computational Dynamics Laboratory, Department of Mathematics, Computer Science and Physics, University of Udine, Italy
| | - Helena B Stage
- Department of Mathematics, University of Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK; University of Potsdam, Germany; Humboldt University of Berlin, Germany
| | - Ben Swallow
- School of Mathematics and Statistics, University of Glasgow, Glasgow, UK; Scottish Covid-19 Response Consortium, UK
| | - Robin N Thompson
- Joint UNIversities Pandemic and Epidemiological Research, UK; Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry CV4 7AL, UK
| | - Michael J Tildesley
- Joint UNIversities Pandemic and Epidemiological Research, UK; Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry CV4 7AL, UK
| | - Daniel Villela
- Program of Scientific Computing, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
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5
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Vaccination and herd immunity thresholds in heterogeneous populations. J Math Biol 2021; 83:73. [PMID: 34878609 PMCID: PMC8651979 DOI: 10.1007/s00285-021-01686-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 08/23/2021] [Accepted: 10/21/2021] [Indexed: 10/29/2022]
Abstract
It has been suggested, without rigorous mathematical analysis, that the classical vaccine-induced herd immunity threshold (HIT) assuming a homogeneous population can be substantially higher than the minimum HIT obtained when considering population heterogeneities. We investigated this claim by developing, and rigorously analyzing, a vaccination model that incorporates various forms of heterogeneity and compared it with a model that considers a homogeneous population. By employing a two-group vaccination model in heterogeneous populations, we theoretically established conditions under which heterogeneity leads to different HIT values, depending on the relative values of the contact rates for each group, the type of mixing between the groups, the relative vaccine efficacy, and the relative population size of each group. For example, under biased random mixing assumption and when vaccinating a given group results in disproportionate prevention of higher transmission per capita, we show that it is optimal to vaccinate that group before vaccinating the other groups. We also found situations, under biased assortative mixing assumption, where it is optimal to vaccinate more than one group. We show that regardless of the form of mixing between the groups, the HIT values assuming a heterogeneous population are always lower than the HIT values obtained from a corresponding model with a homogeneous population. Using realistic numerical examples and parametrization (e.g., assuming assortative mixing together with vaccine efficacy of 95% and the value of the basic reproduction number, [Formula: see text], of the model set at [Formula: see text] 2.5), we demonstrate that the HIT value generated from a model that considers population heterogeneity (e.g., biased assortative mixing) is significantly lower (40%) compared with a HIT value of 63% obtained if the model uses homogeneous population.
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6
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Madewell ZJ, Dean NE, Berlin JA, Coplan PM, Davis KJ, Struchiner CJ, Halloran ME. Challenges of evaluating and modelling vaccination in emerging infectious diseases. Epidemics 2021; 37:100506. [PMID: 34628108 PMCID: PMC8491997 DOI: 10.1016/j.epidem.2021.100506] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 08/25/2021] [Accepted: 10/04/2021] [Indexed: 12/17/2022] Open
Abstract
Outbreaks of emerging pathogens pose unique methodological and practical challenges for the design, implementation, and evaluation of vaccine efficacy trials. Lessons learned from COVID-19 highlight the need for innovative and flexible study design and application to quickly identify promising candidate vaccines. Trial design strategies should be tailored to the dynamics of the specific pathogen, location of the outbreak, and vaccine prototypes, within the regional socioeconomic constraints. Mathematical and statistical models can assist investigators in designing infectious disease clinical trials. We introduce key challenges for planning, evaluating, and modelling vaccine efficacy trials for emerging pathogens.
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Affiliation(s)
- Zachary J Madewell
- Department of Biostatistics, University of Florida, Gainesville, FL, USA.
| | - Natalie E Dean
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Jesse A Berlin
- Global Epidemiology, Johnson & Johnson, Titusville, NJ, USA
| | - Paul M Coplan
- Medical Device Epidemiology and Real World Data Sciences, Johnson & Johnson, New Brunswick, NJ, USA; Department of Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | | | | | - M Elizabeth Halloran
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA
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7
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Oli AN, Ogwaluonye UC, Onubogu CU, Ozumba AF, Agbaenyi OH, Okeke KN, Onah SK, Okoro JC, Ifezulike CC, Emechebe GO. Public Knowledge and Opinion on Childhood Routine Immunizations in Two Major Cities of Anambra State, Nigeria. J Multidiscip Healthc 2021; 14:247-257. [PMID: 33564241 PMCID: PMC7866928 DOI: 10.2147/jmdh.s279397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 11/24/2020] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Immunization programs suffer recurrent setbacks in developing countries. PURPOSE We evaluated the knowledge and opinion of parents towards childhood immunization. MATERIALS AND METHODS A cross-sectional study was conducted among 2400 parents/guardians in two major Anambra cities. RESULTS The male:female ratio was 1:1 and about two-third (64.3%) of respondents were aged 21-40 years. The majority were married (85.0%), Christians (88.3%), and had heard about childhood immunization (92.3%) mainly from formal settings (56.5%). A little above half (56.2%) of them correctly cited "disease prevention" as reason for childhood immunization. A larger proportion of those that gave this correct response worked in tertiary institutions and had post-secondary school education (p<0.001). The majority of the respondents appropriately agreed or disagreed with opinions that can influence immunization uptake. However, some of them did not agree that immunization was important during the first year of life (16.7%) or afterwards (23.1%); to ensure full immunization (22.8%) or maintain proper immunization records (25.6%) of their children; and to actively support childhood immunization (33.9%). Likewise, some respondents would withhold immunization for perceived fear of adverse reactions (30.7%) or if naturally acquired infection was perceived to confer better protection (28.2%). Respondents who worked in tertiary institutions, and had higher education or family income were more likely to agree or disagree appropriately to opinions. Males had comparable opinions with females although females seemed to do better in opinions that reflect actual vaccination practice. CONCLUSION Awareness of the term "immunization" was high although knowledge of its indication did not measure up with this awareness, especially among the less educated. Most parents, especially those who worked in tertiary institutions,r had higher income, or education, were favorably disposed towards opinions that could positively influence immunization uptake. Efforts should be intensified at improving awareness on the indication, benefits and safety of immunization, and improving public opinions in order to optimize childhood immunization.
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Affiliation(s)
- Angus Nnamdi Oli
- Department of Pharmaceutical Microbiology and Biotechnology, Faculty of Pharmaceutical Sciences, Nnamdi Azikiwe University, Agulu, Anambra State, Nigeria
| | - Uchenna Chukwunonso Ogwaluonye
- Department of Pharmaceutical Microbiology and Biotechnology, Faculty of Pharmaceutical Sciences, Nnamdi Azikiwe University, Agulu, Anambra State, Nigeria
| | - Chinyere Ukamaka Onubogu
- Department of Paediatrics, Faculty of Medicine, Nnamdi Azikiwe University, Nnewi Campus, Nnewi, Anambra State, 435101, Nigeria
| | - Abraham Faith Ozumba
- Department of Pharmaceutical Microbiology and Biotechnology, Faculty of Pharmaceutical Sciences, Nnamdi Azikiwe University, Agulu, Anambra State, Nigeria
| | - Obinna Henry Agbaenyi
- Department of Pharmaceutical Microbiology and Biotechnology, Faculty of Pharmaceutical Sciences, Nnamdi Azikiwe University, Agulu, Anambra State, Nigeria
| | - Kenneth Nchekwube Okeke
- Department of Paediatrics, Faculty of Medicine, Nnamdi Azikiwe University, Nnewi Campus, Nnewi, Anambra State, 435101, Nigeria
| | - Stanley Kenechukwu Onah
- Department of Paediatrics, Faculty of Medicine, Nnamdi Azikiwe University, Nnewi Campus, Nnewi, Anambra State, 435101, Nigeria
| | - Jude C Okoro
- Department of Paediatrics, Imo State University Teaching Hospital, Orlu, Imo State, 473271, Nigeria
| | - Christian Chukwuemeka Ifezulike
- Department of Pediatrics, Faculty of Clinical Medicine, Chukwuemeka Odumegwu Ojukwu University, Awka Campus, Awka, Anambra State, 420108, Nigeria
| | - George O Emechebe
- Department of Pediatrics, Faculty of Clinical Medicine, Chukwuemeka Odumegwu Ojukwu University, Awka Campus, Awka, Anambra State, 420108, Nigeria
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8
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Cadena J, Marathe A, Vullikanti A. Critical spatial clusters for vaccine preventable diseases. SOCIAL, CULTURAL, AND BEHAVIORAL MODELING : 13TH INTERNATIONAL CONFERENCE, SBP-BRIMS 2020, WASHINGTON, DC, USA, OCTOBER 18-21, 2020, PROCEEDINGS. INTERNATIONAL CONFERENCE ON SOCIAL COMPUTING BEHAVIORAL-CULTURAL MODELING, AND PREDICTION ... 2020; 12268:213-223. [PMID: 35059694 PMCID: PMC8767959 DOI: 10.1007/978-3-030-61255-9_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The standard public health intervention for controlling the spread of highly contagious diseases, such as measles, is to vaccinate a large fraction of the population. However, it has been shown that in some parts of the United States, even though the average vaccination rate is high, geographical clusters of undervaccinated populations are emerging. Given that public health resources for response are limited, identifying and rank-ordering critical clusters can help prioritize and allocate scarce resources for surveillance and quick intervention. We quantify the criticality of a cluster as the additional number of infections caused if the immunization rate in a cluster reduces. This notion of criticality has not been studied before, and, based on clusters identified in prior research, we show that the current underimmunization rate in the cluster, and its criticality are not correlated. We apply our methods to a population model for the state of Minnesota, where we find undervaccinated clusters with significantly higher criticality than those obtained by other natural heuristics.
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Affiliation(s)
- Jose Cadena
- Lawrence Livermore National Laboratory, Livermore CA, USA
| | - Achla Marathe
- Department of Public Health Sciences, University of Virginia
- Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville VA, USA
| | - Anil Vullikanti
- Department of Computer Science, University of Virginia
- Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville VA, USA
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9
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Ezanno P, Andraud M, Beaunée G, Hoch T, Krebs S, Rault A, Touzeau S, Vergu E, Widgren S. How mechanistic modelling supports decision making for the control of enzootic infectious diseases. Epidemics 2020; 32:100398. [PMID: 32622313 DOI: 10.1016/j.epidem.2020.100398] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 05/07/2020] [Accepted: 05/29/2020] [Indexed: 12/28/2022] Open
Abstract
Controlling enzootic diseases, which generate a large cumulative burden and are often unregulated, is needed for sustainable farming, competitive agri-food chains, and veterinary public health. We discuss the benefits and challenges of mechanistic epidemiological modelling for livestock enzootics, with particular emphasis on the need for interdisciplinary approaches. We focus on issues arising when modelling pathogen spread at various scales (from farm to the region) to better assess disease control and propose targeted options. We discuss in particular the inclusion of farmers' strategic decision-making, the integration of within-host scale to refine intervention targeting, and the need to ground models on data.
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Affiliation(s)
- P Ezanno
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - M Andraud
- Unité épidémiologie et bien-être du porc, Anses Laboratoire de Ploufragan-Plouzané, Ploufragan, France.
| | - G Beaunée
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - T Hoch
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - S Krebs
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - A Rault
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - S Touzeau
- INRAE, CNRS, Université Côte d'Azur, ISA, France; Inria, INRAE, CNRS, Université Paris Sorbonne, Université Côte d'Azur, BIOCORE, France.
| | - E Vergu
- INRAE, Université Paris-Saclay, MaIAGE, 78350 Jouy-en-Josas, France.
| | - S Widgren
- Department of Disease Control and Epidemiology, National Veterinary Institute, 751 89 Uppsala, Sweden.
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10
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Abdur Rehman N, Salje H, Kraemer MUG, Subramanian L, Saif U, Chunara R. Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan. PLoS Negl Trop Dis 2020; 14:e0008273. [PMID: 32392225 PMCID: PMC7241855 DOI: 10.1371/journal.pntd.0008273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 05/21/2020] [Accepted: 04/07/2020] [Indexed: 11/19/2022] Open
Abstract
Increasing urbanization is having a profound effect on infectious disease risk, posing significant challenges for governments to allocate limited resources for their optimal control at a sub-city scale. With recent advances in data collection practices, empirical evidence about the efficacy of highly localized containment and intervention activities, which can lead to optimal deployment of resources, is possible. However, there are several challenges in analyzing data from such real-world observational settings. Using data on 3.9 million instances of seven dengue vector containment activities collected between 2012 and 2017, here we develop and assess two frameworks for understanding how the generation of new dengue cases changes in space and time with respect to application of different types of containment activities. Accounting for the non-random deployment of each containment activity in relation to dengue cases and other types of containment activities, as well as deployment of activities in different epidemiological contexts, results from both frameworks reinforce existing knowledge about the efficacy of containment activities aimed at the adult phase of the mosquito lifecycle. Results show a 10% (95% CI: 1-19%) and 20% reduction (95% CI: 4-34%) reduction in probability of a case occurring in 50 meters and 30 days of cases which had Indoor Residual Spraying (IRS) and fogging performed in the immediate vicinity, respectively, compared to cases of similar epidemiological context and which had no containment in their vicinity. Simultaneously, limitations due to the real-world nature of activity deployment are used to guide recommendations for future deployment of resources during outbreaks as well as data collection practices. Conclusions from this study will enable more robust and comprehensive analyses of localized containment activities in resource-scarce urban settings and lead to improved allocation of resources of government in an outbreak setting.
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Affiliation(s)
- Nabeel Abdur Rehman
- Computer Science and Engineering, Tandon School of Engineering, New York University, Brooklyn, New York, United States of America
| | | | | | | | - Umar Saif
- UNESCO Chair for ICTD, Lahore, Pakistan
| | - Rumi Chunara
- Computer Science and Engineering, Tandon School of Engineering, New York University, Brooklyn, New York, United States of America
- Department of Biostatistics, School of Global Public Health, New York University, New York, New York, United States of America
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11
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Cutts FT, Dansereau E, Ferrari MJ, Hanson M, McCarthy KA, Metcalf CJE, Takahashi S, Tatem AJ, Thakkar N, Truelove S, Utazi E, Wesolowski A, Winter AK. Using models to shape measles control and elimination strategies in low- and middle-income countries: A review of recent applications. Vaccine 2020; 38:979-992. [PMID: 31787412 PMCID: PMC6996156 DOI: 10.1016/j.vaccine.2019.11.020] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Revised: 11/07/2019] [Accepted: 11/08/2019] [Indexed: 01/30/2023]
Abstract
After many decades of vaccination, measles epidemiology varies greatly between and within countries. National immunization programs are therefore encouraged to conduct regular situation analyses and to leverage models to adapt interventions to local needs. Here, we review applications of models to develop locally tailored interventions to support control and elimination efforts. In general, statistical and semi-mechanistic transmission models can be used to synthesize information from vaccination coverage, measles incidence, demographic, and/or serological data, offering a means to estimate the spatial and age-specific distribution of measles susceptibility. These estimates complete the picture provided by vaccination coverage alone, by accounting for natural immunity. Dynamic transmission models can then be used to evaluate the relative impact of candidate interventions for measles control and elimination and the expected future epidemiology. In most countries, models predict substantial numbers of susceptible individuals outside the age range of routine vaccination, which affects outbreak risk and necessitates additional intervention to achieve elimination. More effective use of models to inform both vaccination program planning and evaluation requires the development of training to enhance broader understanding of models and where feasible, building capacity for modelling in-country, pipelines for rapid evaluation of model predictions using surveillance data, and clear protocols for incorporating model results into decision-making.
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Affiliation(s)
- F T Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | - E Dansereau
- Vaccine Delivery, Global Development, The Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - M J Ferrari
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA
| | - M Hanson
- Vaccine Delivery, Global Development, The Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - K A McCarthy
- Institute for Disease Modeling, 3150 139th Ave SE, Bellevue, WA 98005, USA
| | - C J E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - S Takahashi
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA; Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - A J Tatem
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Highfield, Southampton SO17 1BJ, UK
| | - N Thakkar
- Institute for Disease Modeling, 3150 139th Ave SE, Bellevue, WA 98005, USA
| | - S Truelove
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - E Utazi
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Highfield, Southampton SO17 1BJ, UK
| | - A Wesolowski
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - A K Winter
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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12
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Wang Z, Röst G, Moghadas SM. Delay in booster schedule as a control parameter in vaccination dynamics. J Math Biol 2019; 79:2157-2182. [PMID: 31494722 PMCID: PMC6858909 DOI: 10.1007/s00285-019-01424-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Revised: 08/16/2019] [Indexed: 02/03/2023]
Abstract
The use of multiple vaccine doses has proven to be essential in providing high levels of protection against a number of vaccine-preventable diseases at the individual level. However, the effectiveness of vaccination at the population level depends on several key factors, including the dose-dependent protection efficacy of vaccine, coverage of primary and booster doses, and in particular, the timing of a booster dose. For vaccines that provide transient protection, the optimal scheduling of a booster dose remains an important component of immunization programs and could significantly affect the long-term disease dynamics. In this study, we developed a vaccination model as a system of delay differential equations to investigate the effect of booster schedule using a control parameter represented by a fixed time-delay. By exploring the stability analysis of the model based on its reproduction number, we show the disease persistence in scenarios where the booster dose is sub-optimally scheduled. The findings indicate that, depending on the protection efficacy of primary vaccine series and the coverage of booster vaccination, the time-delay in a booster schedule can be a determining factor in disease persistence or elimination. We present model results with simulations for a vaccine-preventable bacterial disease, Heamophilus influenzae serotype b, using parameter estimates from the previous literature. Our study highlights the importance of timelines for multiple-dose vaccination in order to enhance the population-wide benefits of herd immunity.
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Affiliation(s)
- Zhen Wang
- Agent-Based Modelling Laboratory, York University, Toronto, M3J 1P3 Canada
| | - Gergely Röst
- Mathematical Institute, University of Oxford, Woodstock Road, Oxford, OX2 6GG UK
- Bolyai Institute, University of Szeged, Aradi vértanúk tere 1, Szeged, 6720 Hungary
| | - Seyed M. Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, M3J 1P3 Canada
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13
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Hortal M, Di Fabio JL. [Vaccine rejection and vaccination management: the grey areasRecusa vacinal e gestão da imunização: nuances e contrastes]. Rev Panam Salud Publica 2019; 43:e54. [PMID: 31258556 PMCID: PMC6555091 DOI: 10.26633/rpsp.2019.54] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Accepted: 04/26/2019] [Indexed: 01/08/2023] Open
Abstract
Vaccinating children has been an unquestioned tradition for many years. However, there is now great concern over the growing rejection of childhood vaccination, as well as other less evident obstacles that affect vaccination coverage.Multiple factors are involved in the rejection of a specific vaccine or vaccination in general, including actions by anti-vaccination groups, as well as disinformation or the dissemination of erroneous information. In some countries, delays in completing the immunization schedule may be due to poor program management. These factors compromise effective vaccination coverage, constituting a serious threat to public health.Susceptible populations constantly change, due to epidemiological shifts determined by phenomena such as globalization and various conflicts that interfere in the operation of health services. In recent years there have been outbreaks of previously controlled diseases such as diphtheria, whooping cough, and measles, resulting both from imported cases and from deficiencies in national immunization programs.This paper explores different aspects of the increasing frequency of vaccine rejection. There is a need for a review of its causes and for the design of innovative strategies and approaches to regain acceptance of vaccination and its place as the most cost-effective tool in public health.
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Affiliation(s)
- María Hortal
- Universidad de la RepúblicaPrograma de Desarrollo de las Ciencias BásicasUruguayPrograma de Desarrollo de las Ciencias Básicas, Universidad de la República, Uruguay.
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14
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Béraud G. Mathematical models and vaccination strategies. Vaccine 2018; 36:5366-5372. [DOI: 10.1016/j.vaccine.2017.10.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2017] [Revised: 08/23/2017] [Accepted: 10/05/2017] [Indexed: 01/11/2023]
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15
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Nguyen VK, Mikolajczyk R, Hernandez-Vargas EA. High-resolution epidemic simulation using within-host infection and contact data. BMC Public Health 2018; 18:886. [PMID: 30016958 PMCID: PMC6050668 DOI: 10.1186/s12889-018-5709-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 06/14/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Recent epidemics have entailed global discussions on revamping epidemic control and prevention approaches. A general consensus is that all sources of data should be embraced to improve epidemic preparedness. As a disease transmission is inherently governed by individual-level responses, pathogen dynamics within infected hosts posit high potentials to inform population-level phenomena. We propose a multiscale approach showing that individual dynamics were able to reproduce population-level observations. METHODS Using experimental data, we formulated mathematical models of pathogen infection dynamics from which we simulated mechanistically its transmission parameters. The models were then embedded in our implementation of an age-specific contact network that allows to express individual differences relevant to the transmission processes. This approach is illustrated with an example of Ebola virus (EBOV). RESULTS The results showed that a within-host infection model can reproduce EBOV's transmission parameters obtained from population data. At the same time, population age-structure, contact distribution and patterns can be expressed using network generating algorithm. This framework opens a vast opportunity to investigate individual roles of factors involved in the epidemic processes. Estimating EBOV's reproduction number revealed a heterogeneous pattern among age-groups, prompting cautions on estimates unadjusted for contact pattern. Assessments of mass vaccination strategies showed that vaccination conducted in a time window from five months before to one week after the start of an epidemic appeared to strongly reduce epidemic size. Noticeably, compared to a non-intervention scenario, a low critical vaccination coverage of 33% cannot ensure epidemic extinction but could reduce the number of cases by ten to hundred times as well as lessen the case-fatality rate. CONCLUSIONS Experimental data on the within-host infection have been able to capture upfront key transmission parameters of a pathogen; the applications of this approach will give us more time to prepare for potential epidemics. The population of interest in epidemic assessments could be modelled with an age-specific contact network without exhaustive amount of data. Further assessments and adaptations for different pathogens and scenarios to explore multilevel aspects in infectious diseases epidemics are underway.
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Affiliation(s)
- Van Kinh Nguyen
- Frankfurt Institute for Advanced Studies, Ruth-Moufang-Str. 1, Frankfurt am Main, 60438 Germany
- Helmholtz Centre for Infection Research, Inhoffen Str. 7, Braunschweig, 38124 Germany
| | - Rafael Mikolajczyk
- German Centre for Infection Research, Site Braunschweig-Hannover, Germany
- Hannover Medical School, Hannover, Germany
- Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Esteban Abelardo Hernandez-Vargas
- Frankfurt Institute for Advanced Studies, Ruth-Moufang-Str. 1, Frankfurt am Main, 60438 Germany
- Helmholtz Centre for Infection Research, Inhoffen Str. 7, Braunschweig, 38124 Germany
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16
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Abstract
Norovirus is one of the leading causes of viral gastroenteritis worldwide and responsible for substantial morbidity, mortality and healthcare costs. To further understanding of the epidemiology and control of norovirus, there has been much recent interest in describing the transmission dynamics of norovirus through mathematical models. In this study, we review the current modelling approaches for norovirus transmission. We examine the data and methods used to estimate these models that vary structurally and parametrically between different epidemiological contexts. Many of the existing studies at population level have focused on the same case notification dataset, whereas models from outbreak settings are highly specific and difficult to generalise. In this review, we explore the consistency in the description of norovirus transmission dynamics and the robustness of parameter estimates between studies. In particular, we find that there is considerable variability in estimates of key parameters such as the basic reproduction number, which may mean that the effort required to control norovirus at the population level may currently be underestimated.
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17
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Ultsch B, Damm O, Beutels P, Bilcke J, Brüggenjürgen B, Gerber-Grote A, Greiner W, Hanquet G, Hutubessy R, Jit M, Knol M, von Kries R, Kuhlmann A, Levy-Bruhl D, Perleth M, Postma M, Salo H, Siebert U, Wasem J, Wichmann O. Methods for Health Economic Evaluation of Vaccines and Immunization Decision Frameworks: A Consensus Framework from a European Vaccine Economics Community. PHARMACOECONOMICS 2016; 34:227-44. [PMID: 26477039 PMCID: PMC4766233 DOI: 10.1007/s40273-015-0335-2] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
BACKGROUND Incremental cost-effectiveness and cost-utility analyses [health economic evaluations (HEEs)] of vaccines are routinely considered in decision making on immunization in various industrialized countries. While guidelines advocating more standardization of such HEEs (mainly for curative drugs) exist, several immunization-specific aspects (e.g. indirect effects or discounting approach) are still a subject of debate within the scientific community. OBJECTIVE The objective of this study was to develop a consensus framework for HEEs of vaccines to support the development of national guidelines in Europe. METHODS A systematic literature review was conducted to identify prevailing issues related to HEEs of vaccines. Furthermore, European experts in the field of health economics and immunization decision making were nominated and asked to select relevant aspects for discussion. Based on this, a workshop was held with these experts. Aspects on 'mathematical modelling', 'health economics' and 'decision making' were debated in group-work sessions (GWS) to formulate recommendations and/or--if applicable--to state 'pros' and 'contras'. RESULTS A total of 13 different aspects were identified for modelling and HEE: model selection, time horizon of models, natural disease history, measures of vaccine-induced protection, duration of vaccine-induced protection, indirect effects apart from herd protection, target population, model calibration and validation, handling uncertainty, discounting, health-related quality of life, cost components, and perspectives. For decision making, there were four aspects regarding the purpose and the integration of HEEs of vaccines in decision making as well as the variation of parameters within uncertainty analyses and the reporting of results from HEEs. For each aspect, background information and an expert consensus were formulated. CONCLUSIONS There was consensus that when HEEs are used to prioritize healthcare funding, this should be done in a consistent way across all interventions, including vaccines. However, proper evaluation of vaccines implies using tools that are not commonly used for therapeutic drugs. Due to the complexity of and uncertainties around vaccination, transparency in the documentation of HEEs and during subsequent decision making is essential.
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Affiliation(s)
- Bernhard Ultsch
- Department for Infectious Disease Epidemiology, Immunisation Unit, Robert Koch Institute (RKI), Seestr. 10, 13353, Berlin, Germany.
| | | | | | | | | | | | | | | | | | - Mark Jit
- London School of Hygiene and Tropical Medicine (LSHTM), London, UK
- Public Health England (PHE), London, UK
| | - Mirjam Knol
- Centre for Infectious Disease Control (RIVM), Bilthoven, The Netherlands
| | | | | | | | | | | | - Heini Salo
- National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Uwe Siebert
- University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria
- ONCOTYROL, Center for Personalized Cancer Medicine, Innsbruck, Austria
| | | | - Ole Wichmann
- Department for Infectious Disease Epidemiology, Immunisation Unit, Robert Koch Institute (RKI), Seestr. 10, 13353, Berlin, Germany
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18
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Kraemer MUG, Hay SI, Pigott DM, Smith DL, Wint GRW, Golding N. Progress and Challenges in Infectious Disease Cartography. Trends Parasitol 2015; 32:19-29. [PMID: 26604163 DOI: 10.1016/j.pt.2015.09.006] [Citation(s) in RCA: 66] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2015] [Revised: 07/30/2015] [Accepted: 09/17/2015] [Indexed: 02/02/2023]
Abstract
Quantitatively mapping the spatial distributions of infectious diseases is key to both investigating their epidemiology and identifying populations at risk of infection. Important advances in data quality and methodologies have allowed for better investigation of disease risk and its association with environmental factors. However, incorporating dynamic human behavioural processes in disease mapping remains challenging. For example, connectivity among human populations, a key driver of pathogen dispersal, has increased sharply over the past century, along with the availability of data derived from mobile phones and other dynamic data sources. Future work must be targeted towards the rapid updating and dissemination of appropriately designed disease maps to guide the public health community in reducing the global burden of infectious disease.
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Affiliation(s)
- Moritz U G Kraemer
- Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK.
| | - Simon I Hay
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892-2220, USA
| | - David M Pigott
- Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - David L Smith
- Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892-2220, USA; Sanaria Institute for Global Health and Tropical Medicine, Rockville, MD 20850, USA
| | - G R William Wint
- Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK; Environmental Research Group Oxford (ERGO), Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK
| | - Nick Golding
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
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19
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Fefferman NH, Naumova EN. Dangers of vaccine refusal near the herd immunity threshold: a modelling study. THE LANCET. INFECTIOUS DISEASES 2015; 15:922-6. [PMID: 25981883 DOI: 10.1016/s1473-3099(15)00053-5] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
BACKGROUND Childhood vaccination remains the focus of heated public debate. Parents struggle to understand the potential risks associated with vaccination but both parents and physicians assume that they understand the risks associated with infection. This study was done to characterise how modern vaccination practices have altered patient risks from infection. METHODS In this modelling study, we use mathematical analysis to explore how modern-era vaccination practices have changed the risks of severe outcomes for some infections by changing the landscape for disease transmission. We show these effects using published data from outbreaks in the USA for measles, chickenpox, and rubella. Calculation of risk estimation was the main outcome of this study. FINDINGS Our calculations show that negative outcomes are 4·5 times worse for measles, 2·2 times worse for chickenpox, and 5·8 times worse for rubella than would be expected in a pre-vaccine era in which the average age at infection would have been lower. INTERPRETATION As vaccination makes preventable illness rarer, for some diseases, it also increases the expected severity of each case. Because estimates of case risks rely on data for severity generated during a pre-vaccine era they underestimate negative outcomes in the modern post-vaccine epidemiological landscape. Physicians and parents should understand when making decisions about their children's health and safety that remaining unvaccinated in a predominantly vaccine-protected community exposes their children to the most severe possible outcomes for many preventable diseases. FUNDING None.
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Affiliation(s)
- Nina H Fefferman
- Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, NJ, USA; Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), Rutgers University, Piscataway, NJ, USA; Tufts University Initiative for the Forecasting and Modeling of Infectious Diseases, Tufts University, Medford, MA, USA.
| | - Elena N Naumova
- Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), Rutgers University, Piscataway, NJ, USA; Tufts University Initiative for the Forecasting and Modeling of Infectious Diseases, Tufts University, Medford, MA, USA; Department of Civil and Environmental Engineering, Tufts University, Medford, MA, USA
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20
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Five challenges in evolution and infectious diseases. Epidemics 2015; 10:40-4. [DOI: 10.1016/j.epidem.2014.12.003] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Revised: 12/09/2014] [Accepted: 12/10/2014] [Indexed: 01/09/2023] Open
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21
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Funk S, Bansal S, Bauch CT, Eames KTD, Edmunds WJ, Galvani AP, Klepac P. Nine challenges in incorporating the dynamics of behaviour in infectious diseases models. Epidemics 2014; 10:21-5. [PMID: 25843377 DOI: 10.1016/j.epidem.2014.09.005] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2014] [Revised: 09/09/2014] [Accepted: 09/16/2014] [Indexed: 01/03/2023] Open
Abstract
Traditionally, the spread of infectious diseases in human populations has been modelled with static parameters. These parameters, however, can change when individuals change their behaviour. If these changes are themselves influenced by the disease dynamics, there is scope for mechanistic models of behaviour to improve our understanding of this interaction. Here, we present challenges in modelling changes in behaviour relating to disease dynamics, specifically: how to incorporate behavioural changes in models of infectious disease dynamics, how to inform measurement of relevant behaviour to parameterise such models, and how to determine the impact of behavioural changes on observed disease dynamics.
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Affiliation(s)
- Sebastian Funk
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK.
| | - Shweta Bansal
- Department of Biology, Georgetown University, Washington, DC 20057, USA; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA
| | - Chris T Bauch
- Department of Applied Mathematics, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Ken T D Eames
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - W John Edmunds
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - Alison P Galvani
- School of Public Health, Yale University, New Haven, CT 06520, USA
| | - Petra Klepac
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB3 0WA, UK
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