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
자료이용안내
국내외 주요 기관에서 발표하는 자료들을 수집하여 제공하고 있습니다. 수록 자료의 자세한 내용은 해당 기관으로 문의하시기 바랍니다.
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.
