关于r语言:Rt1啦上海疫情流行趋势分析

上海新冠疫情可视化面板

根本再生数R₀是指在一个齐全易感人群中，没有任何干涉措施的状况下，一个被传染病病原体感化的个体所能引起的第二代感化病例数，罕用于掂量病原体本身的流传力。(“流行病学专家解读
| 传染病的无效再生数与根本再生数,” n.d.)

时变再生数R_t能够了解为真实世界(往往有干涉措施，人群不是齐全易感)情景下，t时刻的再生数,
受干涉措施，感染者及易感者比例等因素影响，随工夫变动而变动。隔离等干涉措施的指标在于将R_t升高至1以下，R_t \< 1意味着新增病例数将逐步缩小，疫情失去管制。

应用R语言EpiEstim包预计R_t(Thompson et al.
2019)，须要假如系列距离(serial
interval)的散布,本文中假如系列距离均值为4天，标准差为2天(“新型冠状病毒Omicron变异株的流行病学特色及其迷信防控倡议,”
n.d.)。应用EpiEstim包默认的1周滑动窗进行剖析。后果如下：

library(tidyverse)library(EpiEstim)library(patchwork)## load datacase.asym.wider.sh<-read.csv('https://raw.githubusercontent.com/shalom-lab/covid.sh/main/local/share/case.asym.wider.sh.csv')# observationcases<-case.asym.wider.sh %>%  select(date,pos) %>%  mutate(date=as.Date(date)) %>%  rename(I=pos,dates=date)## make configconfig <- make_config(  mean_si = 4,  std_si = 2)## estimateres <- estimate_R(  incid = cases,  method = "parametric_si",  config = config)#plot(res)res.r<-res$R %>% as_tibble() %>%  rename(mean=`Mean(R)`,std=`Std(R)`,lbd=`Quantile.0.025(R)`,ubd=`Quantile.0.975(R)`) %>%  mutate(date=cases$dates[res$R$t_end])res.si <- as_tibble(list(time=as.integer(str_sub(names(res$si_distr),2)),                         frequency=as.vector(res$si_distr)))p1<-ggplot(data = cases,aes(x=dates,y=I))+  geom_col(fill= "#AD002AFF")+  scale_x_date(date_breaks = "2 days",date_labels = "%m/%d",expand = c(0,0.5))+  labs(x="",y="每日新增阳性数",title="Epidemic curve")+  theme_bw()+  theme(axis.text.x = element_text(angle=45,vjust=0.5,hjust = 0.5))p2<-ggplot(data = res.r,aes(x=date,y=mean))+  geom_ribbon(aes(ymin=lbd,ymax=ubd),fill= "#AD002AFF",alpha=0.2)+  geom_line(size=1,colour= "#AD002AFF")+  geom_hline(yintercept = 1,size=1,lty=2)+  scale_x_date(date_breaks = "2 days",date_labels = "%m/%d",expand = c(0,0.5),limits = c(as.Date('2022-03-09'),Sys.Date()-1))+  labs(x="",y="时变再生数Rt",title='')+  theme_bw()+  theme(axis.text.x = element_text(angle=45,vjust=0.5,hjust = 0.5))p3<-ggplot(data = res.si,aes(x=time,y=frequency))+  geom_line()+  labs(x="Time",y="Frequency",title='Assumptive Serial Interval Distribution')+  theme_bw()p1+p2+plot_layout(ncol = 1)p3

结果显示目前时变再生数Rt已降至1以下，Rt继续处于1以下将示意疫情失去无效管制,心愿持续放弃，期待早日解封~

参考资料

[1] Thompson, R. N., J. E. Stockwin, R. D. van Gaalen, J. A. Polonsky, Z. N.
Kamvar, P. A. Demarsh, E. Dahlqwist, et al. 2019. “Improved Inference of
Time-Varying Reproduction Numbers During Infectious Disease Outbreaks.”
Epidemics 29 (December): 100356.
https://doi.org/10.1016/j.epi....

[2] “新型冠状病毒Omicron变异株的流行病学特色及其迷信防控倡议.”
http://mp.weixin.qq.com/s?__b....

[3] “流行病学专家解读 | 传染病的无效再生数与根本再生数.”
http://mp.weixin.qq.com/s?__b....