RAPID: A comparative online simulation tool for COVID-19 vaccine allocation

RAPID：用于 COVID-19 疫苗分配的比较在线模拟工具

• 批准号: 2210382
• 负责人: Laura Matrajt
• 金额: $ 19.93万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2210382&HistoricalAwards=false
• 关键词: RAPID; comparative; online; simulation; tool

This project will develop a mathematical model of SARS-CoV-2 transmission that takes into account the use of several types of vaccines, genetic variation in the virus, and multiple age groups. The COVID-19 pandemic has produced immense suffering throughout the world, with over 5 million deaths as of January 2022, but low- and middle-income countries have carried an increased burden both from the health crisis and from the economic crisis arising from the pandemic. While high-income countries have vaccinated the majority of their eligible populations, less than 2.3% of the population of low-income countries have been immunized. This is expected to change in the following months, as more vaccines will be available to these countries. As more vaccines become available to them, public health officials in these countries will likely develop vaccine allocation strategies based on a mix of vaccines (there are currently over 20 vaccines available worldwide) that differ in effectiveness against circulating variants, arriving at different times, and in different quantities. However, these countries usually lack resources to develop models to guide vaccine allocation. This project will develop a free, user-friendly online tool that will simulate country-specific multi-strain COVID-19 epidemics in conjunction with vaccination campaigns with multiple vaccines. By simulating the epidemic and producing key outcomes including expected numbers of deaths, hospitalizations, and cases, this tool will allow decision-makers in up to 177 countries around the world to compare scenarios of vaccine allocation. This project will develop a multi-strain, multi-vaccines mathematical model of SARS-CoV-2 transmission and vaccination that will then be used to develop an open-source, online, free, user-friendly comparative tool for vaccine allocation. This tool has the potential to to evaluate in-silico different vaccine allocations with country- or region-specific characteristics. The tool will allow users to input a variety of country-specific parameters including: the type, effectiveness and quantities (coverage, number of doses, distribution) of vaccines; co-circulating variants with different transmissibility, virulence, and cross-protection; social distancing interventions, demographics; and variable time horizons. It will simulate different vaccine allocation scenarios and project for each of them key outcomes (expected numbers of deaths, hospitalizations, and cases). This project was funded in collaboration with the CDC to support rapid-response research projects to further advance federal infectious disease modeling capabilities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将建立一个SARS-CoV-2传播的数学模型，该模型将考虑到几种疫苗的使用、病毒的遗传变异和多个年龄组。2019冠状病毒病大流行在全世界造成了巨大痛苦，截至2022年1月，已有500多万人死亡，但低收入和中等收入国家因大流行引起的卫生危机和经济危机而承受着更大的负担。虽然高收入国家已为大多数符合条件的人口接种了疫苗，但低收入国家只有不到2.3%的人口接种了疫苗。随着向这些国家提供更多疫苗，这种情况预计将在今后几个月内发生变化。随着向这些国家提供更多的疫苗，这些国家的公共卫生官员可能会根据疫苗组合（目前全世界有20多种疫苗）制定疫苗分配战略，这些疫苗对流行变体的有效性不同，到达的时间不同，数量也不同。然而，这些国家通常缺乏资源来开发指导疫苗分配的模式。该项目将开发一个免费、用户友好的在线工具，结合多种疫苗接种运动，模拟针对具体国家的COVID-19多毒株流行情况。通过模拟疫情并得出关键结果，包括预期死亡人数、住院人数和病例数，该工具将使全球多达177个国家的决策者能够比较疫苗分配情况。该项目将建立一个SARS-CoV-2传播和疫苗接种的多菌株、多疫苗数学模型，然后用于开发一个开源、在线、免费、用户友好的疫苗分配比较工具。这一工具有可能对具有国家或区域具体特点的不同疫苗分配情况进行计算机评价。该工具将允许用户输入各种针对具体国家的参数，包括：疫苗的类型、有效性和数量（覆盖面、剂量数、分配）；具有不同传播力、毒力和交叉保护的共循环变异；社会距离干预措施，人口统计；以及可变的时间范围。它将模拟不同的疫苗分配方案，并对每种方案的关键结果（预计死亡人数、住院人数和病例数）进行预测。该项目是与美国疾病控制与预防中心合作资助的，旨在支持快速反应研究项目，进一步提高联邦传染病建模能力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。