用于控制蚊媒疾病的数学和统计模型：哥斯达黎加的经验。
Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica.
作者信息
Vásquez Paola, Sanchez Fabio, Barboza Luis A, García Yury E, Calvo Juan G, Chou-Chen Shu-Wei, Mery Gustavo
机构信息
Universidad de Costa Rica San José Costa Rica Universidad de Costa Rica, San José, Costa Rica.
University of California Davis DavisCalifornia United States of America University of California Davis, Davis, California, United States of America.
出版信息
Rev Panam Salud Publica. 2022 Aug 30;46:e113. doi: 10.26633/RPSP.2022.113. eCollection 2022.
OBJECTIVE
To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases.
METHODS
Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making.
RESULTS
The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations.
CONCLUSIONS
Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning.
目的
总结在哥斯达黎加开展的研究结果，该研究运用数学和统计方法来研究蚊媒疾病的传播动态。
方法
选取并综述了三篇对哥斯达黎加病媒传播疾病进行数学和统计分析的文章。这些论文展示了运用不同定量方法来理解疾病动态并支持决策制定的价值和相关性。
结果
这些调查结果：1）显示了第二种病原体（如基孔肯雅热）出现时对登革热病例报告的影响；2）使用贝叶斯推理恢复寨卡病毒动态中的关键参数；3）展示了使用机器学习算法和气候变量来预测五个不同地点的登革热相对风险。
结论
数学和统计建模能够描述蚊媒疾病的传播动态，提供定量信息以支持预防/控制方法和资源分配规划。
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