• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

设计、实施和优化印度传染病建模能力建设模型。

Designing, Implementing and Optimising a Capacity‑Building Model for Infectious Disease Modelling in India.

作者信息

Tripathy Jaya Prasad, Lakshmi Pvm, Anand Tanu, Deshmukh Pradeep R

机构信息

Department of Community Medicine, All India Institute of Medical Sciences, Nagpur, India.

Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.

出版信息

Ann Glob Health. 2024 Dec 30;90(1):84. doi: 10.5334/aogh.4606. eCollection 2024.

DOI:10.5334/aogh.4606
PMID:39758807
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11697579/
Abstract

Mathematical models are not integrated into the policy‑making process in low‑ and middle‑income countries, including India, primarily due to limited capacity in building mathematical models, lack of trust in the model findings and the reluctance of policy‑makers to apply the model findings to formulate policies. There is a perceived need to create a critical mass of trained infectious disease experts and modelers within the public health and clinical domain. Thus, with the support of the Department of Health Research (DHR), we developed a 3‑month post‑graduate (PG) certificate course on infectious disease modelling, the first of such a course in India. The first cycle of the course was delivered during July to September 2024, which produced the first cohort of 20 infectious disease modellers in the country. This paper describes the structure, content and key components of the first course along with the experiences, strengths, challenges and way forward from the participants' perspective using a mixed methods approach. Most of the participants felt that the learning objectives were clear ( = 18, 90%), course content was well organised and delivered ( = 19, 95%) and the course structure allowed all participants to fully participate ( = 19, 95%) in the learning process. The strengths of the course were: hybrid mode of delivery, well‑designed course content, theory lectures followed by practical sessions, regular trainer-trainee communication, interactive discussion forums and the 3‑day contact workshop. The key challenges were non‑availability of recorded videos, evening timings of the sessions and difficulty of some topics. The challenges and recommendations will feed into the subsequent course cycles. Future courses are planned to be hosted on an online platform to facilitate participant completion of the course at their own pace. More collaboration with various stakeholders, nationally and internationally, will be sought to improve the content, delivery and robustness of the program.

摘要

数学模型未被纳入包括印度在内的低收入和中等收入国家的政策制定过程,主要原因是建立数学模型的能力有限、对模型结果缺乏信任以及政策制定者不愿将模型结果应用于政策制定。人们认为有必要在公共卫生和临床领域培养一批关键的训练有素的传染病专家和建模人员。因此,在卫生研究部(DHR)的支持下,我们开发了一个为期3个月的传染病建模研究生证书课程,这是印度首个此类课程。该课程的第一个周期于2024年7月至9月进行,培养出了该国首批20名传染病建模人员。本文采用混合方法,从参与者的角度描述了第一期课程的结构、内容和关键组成部分,以及经验、优势、挑战和未来方向。大多数参与者认为学习目标明确(n = 18,90%),课程内容组织良好且授课方式得当(n = 19,95%),课程结构使所有参与者都能充分参与(n = 19,95%)学习过程。该课程的优势包括:混合授课模式、精心设计的课程内容、理论讲座后接实践课程、培训师与学员定期沟通、互动式讨论论坛以及为期3天的面授研讨会。关键挑战包括没有录制视频、课程安排在晚上以及一些主题难度较大。这些挑战和建议将纳入后续课程周期。未来的课程计划在在线平台上举办,以便学员能够按照自己的节奏完成课程。将寻求与国内和国际的各利益相关方开展更多合作,以改进该项目的内容、授课方式和稳健性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8952/11697579/4fab939b729c/agh-90-1-4606-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8952/11697579/4fab939b729c/agh-90-1-4606-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8952/11697579/4fab939b729c/agh-90-1-4606-g1.jpg

相似文献

1
Designing, Implementing and Optimising a Capacity‑Building Model for Infectious Disease Modelling in India.设计、实施和优化印度传染病建模能力建设模型。
Ann Glob Health. 2024 Dec 30;90(1):84. doi: 10.5334/aogh.4606. eCollection 2024.
2
Evidence-based Decision Making: Infectious Disease Modeling Training for Policymakers in East Africa.循证决策:东非政策制定者传染病建模培训。
Ann Glob Health. 2024 Mar 22;90(1):22. doi: 10.5334/aogh.4383. eCollection 2024.
3
Blended learning across universities in a South-North-South collaboration: a case study.南北南合作背景下的高校混合式学习:一项案例研究
Health Res Policy Syst. 2016 Sep 2;14(1):67. doi: 10.1186/s12961-016-0136-x.
4
Framework to guide the use of mathematical modelling in evidence-based policy decision-making.循证政策决策中指导数学建模应用的框架。
BMJ Open. 2025 Apr 5;15(4):e093645. doi: 10.1136/bmjopen-2024-093645.
5
Implementing effective eLearning for scaling up global capacity building: findings from the malnutrition elearning course evaluation in Ghana.实施有效的电子学习以扩大全球能力建设:加纳营养不良电子学习课程评估的结果。
Glob Health Action. 2020 Dec 31;13(1):1831794. doi: 10.1080/16549716.2020.1831794.
6
Building Health System Capacity through Medical Education: A Targeted Needs Assessment to Guide Development of a Structured Internal Medicine Curriculum for Medical Interns in Botswana.通过医学教育建设卫生系统能力:以有针对性的需求评估为指导,为博茨瓦纳医学生制定结构化的内科课程。
Ann Glob Health. 2018 Apr 30;84(1):151-159. doi: 10.29024/aogh.22.
7
Management of Poisoned Patients: Implementing a Blended Toxicology Curriculum for Emergency Medicine Residents.中毒患者的管理:为急诊医学住院医师实施混合毒理学课程。
J Educ Teach Emerg Med. 2022 Apr 15;7(2):C1-C32. doi: 10.21980/J8C937. eCollection 2022 Apr.
8
Strengthening local capacity for mathematical modelling in low- and middle-income countries: the process and lessons learnt in implementing the first cohort of Nigeria malaria modelling fellowships.加强低收入和中等收入国家的数学建模本地能力:实施尼日利亚首批疟疾建模奖学金项目的过程与经验教训
Malar J. 2025 Apr 10;24(1):116. doi: 10.1186/s12936-025-05345-2.
9
Recommendations for the use of mathematical modelling to support decision-making on integration of non-communicable diseases into HIV care.关于使用数学建模来支持将非传染性疾病纳入艾滋病毒护理决策的建议。
J Int AIDS Soc. 2020 Jun;23 Suppl 1(Suppl 1):e25505. doi: 10.1002/jia2.25505.
10
Capacity building for implementation research: a methodology for advancing health research and practice.实施研究能力建设:推进健康研究与实践的方法学。
Health Res Policy Syst. 2020 Jun 1;18(1):53. doi: 10.1186/s12961-020-00568-y.

本文引用的文献

1
Global burden associated with 85 pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019.2019 年与 85 种病原体相关的全球负担:2019 年全球疾病负担研究的系统分析。
Lancet Infect Dis. 2024 Aug;24(8):868-895. doi: 10.1016/S1473-3099(24)00158-0. Epub 2024 Apr 16.
2
Evidence-based Decision Making: Infectious Disease Modeling Training for Policymakers in East Africa.循证决策:东非政策制定者传染病建模培训。
Ann Glob Health. 2024 Mar 22;90(1):22. doi: 10.5334/aogh.4383. eCollection 2024.
3
Emerging Infectious Diseases Are Virulent Viruses-Are We Prepared? An Overview.
新发传染病——烈性病毒来袭,我们准备好了吗?综述
Microorganisms. 2023 Oct 24;11(11):2618. doi: 10.3390/microorganisms11112618.
4
Role of mathematical modelling in future pandemic response policy.数学建模在未来大流行应对政策中的作用。
BMJ. 2022 Sep 15;378:e070615. doi: 10.1136/bmj-2022-070615.
5
Global research activity on mathematical modeling of transmission and control of 23 selected infectious disease outbreak.全球关于 23 种选定传染病暴发传播与控制的数学建模研究活动。
Global Health. 2022 Jan 21;18(1):4. doi: 10.1186/s12992-022-00803-x.
6
African based researchers' output on models for the transmission dynamics of infectious diseases and public health interventions: A scoping review.非洲本土研究人员关于传染病传播动力学模型和公共卫生干预措施的研究成果:范围综述。
PLoS One. 2021 May 6;16(5):e0250086. doi: 10.1371/journal.pone.0250086. eCollection 2021.
7
Modeling COVID-19 scenarios for the United States.美国的 COVID-19 情景建模。
Nat Med. 2021 Jan;27(1):94-105. doi: 10.1038/s41591-020-1132-9. Epub 2020 Oct 23.
8
Predictive models of COVID-19 in India: A rapid review.印度新冠疫情的预测模型:快速综述
Med J Armed Forces India. 2020 Oct;76(4):377-386. doi: 10.1016/j.mjafi.2020.06.001. Epub 2020 Jun 17.
9
Disease modeling for public health: added value, challenges, and institutional constraints.疾病建模在公共卫生中的应用:附加值、挑战和制度限制。
J Public Health Policy. 2020 Mar;41(1):39-51. doi: 10.1057/s41271-019-00206-0.
10
Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making.弥合传染病证据与政策之间的差距:模型如何助力公共卫生决策。
Int J Infect Dis. 2016 Jan;42:17-23. doi: 10.1016/j.ijid.2015.10.024. Epub 2015 Nov 3.