COVID-19和结核病:感染传播的数学建模,考虑到减少查
Anna Starshinova1, Nikolay Osipov2,3, Irina Dovgalyk4
1Almazov National Medical Research Centre, 197341 St. Petersburg, Russia.
在COVID-19大流行期间减少结核病 (TB) 查显著增加了未来的感染. 大规模查对于及时检测和控制Mycobacterium结核病 (M. tb) 传播至关重要.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 数学建模的数学建模
背景情况:
- 随着COVID-19大流行,全球结核病 (TB) 控制计划中断,导致查和干预减少.
- 未被检测到的Mycobacterium结核病病例 (M. tb) 构成了未来结核病传播的重大风险.
- 俄罗斯联邦2008年至2021年的结核病统计数据提供了数据来建模这些影响.
研究的目的:
- 开发一个模型,说明未被发现的结核病例如何影响未来的M. tb感染.
- 分析结核病发病率,查覆盖率和细菌分泌率之间的关系.
- 在COVID-19大流行期间量化减少结核病干预措施的影响.
主要方法:
- 统计分析官方结核病发病率,预防检查覆盖率和细菌分泌数据 (2008-2021年).
- 使用R v.4.2.1来描述TB动态的数学模型的开发.
- 利用2020年流行病引起的结核病干预措施的波动作为关键数据点.
主要成果:
- 开发了一个高度准确的模型 (调整R平方=0.9969),显示最小的随机变化.
- 该模型表明,由于查减少而遗漏的结核病例导致未来感染的大幅增加.
- 当前一年的结核病患病率取决于前一年的患病率和当前/之前的查覆盖率.
结论:
- 大规模人口查对于有效控制结核病和及时识别传染病例至关重要.
- 持续的查工作至关重要,以减轻流行病相关干扰的长期后果.
- 该模型为维持和加强结核病查计划的必要性提供了有力的证据.
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