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资源简介：
LSHTM COVID-19 Projections
应用场景：
创建时间：
2020-05-13
相关数据集
Final regression model for predictors of the pathogen prevalence index and number of pathogens.
Variable definitions: Temperature: Log mean annual temperature (c). Frost months: 1 = presence 0 = absence. Island: 1 = mainland 0 = island. Driest month: Log lowest precipitation in driest month (mm)
NIAID Data Ecosystem70
MODELOS LINEALES GENERALIZADOS PARA PREDECIR LOS CASOS DE COVID-19: CASO PERUANO
DATOS DE COVID-19 EN PERÚ: ARCHIVO STATA Las variables de estudio son contagios de COVID-19 por departamento del Perú, mes en el cual ocurrió el contagio y grupo etario contagiado (adolescente, joven,
NIAID Data Ecosystem50
Forecasted peaks and dates of peak daily confirmed cases, total infectious cases, hospitalizations, and ICU cases, given current vaccination and social distancing measures.
90% confidence intervals are given in parentheses.
Figshare2022-12-13 更新10
Predicted annual number of Lassa virus infections and infection rate.
Predicted annual number of Lassa virus infections and infection rate.
NIAID Data Ecosystem70
Deviance and Dawid-Sebastiani score (mean ± standard deviation) for all three diseases and both BSTIM and the hhh4 model.
Deviance and Dawid-Sebastiani score (mean ± standard deviation) for all three diseases and both BSTIM and the hhh4 model.
NIAID Data Ecosystem40
