중남미
연구정보
[보건] Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru Special Issue Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru
페루 국외연구자료 연구보고서 - Entropy 발간일 : 2024-05-01 등록일 : 2024-06-07 원문링크
Amid the COVID-19 pandemic, understanding the spatial and temporal dynamics of the disease is crucial for effective public health interventions. This study aims to analyze COVID-19 data in Peru using a Bayesian spatio-temporal generalized linear model to elucidate mortality patterns and assess the impact of vaccination efforts. Leveraging data from 194 provinces over 651 days, our analysis reveals heterogeneous spatial and temporal patterns in COVID-19 mortality rates. Higher vaccination coverage is associated with reduced mortality rates, emphasizing the importance of vaccination in mitigating the pandemic's impact. The findings underscore the value of spatio-temporal data analysis in understanding disease dynamics and guiding targeted public health interventions.
본 페이지에 등재된 자료는 운영기관(KIEP) 및 EMERiCs의 공식적인 입장을 대변하고 있지 않습니다.
