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COVID-19: Exponential Growth in London

area_name

area_type

area_data

  Area.name == area_name &

    Area.type == area_type,,

  ][,Specimen.date := as.Date(Specimen.date)

    ][,c(“Specimen.date”,”Daily.lab.confirmed.cases”)][

      order(Specimen.date)

      ]

area_data

                   data.table(Specimen.date = seq(

                     min(area_data[,Specimen.date]),

                     max(area_data[,Specimen.date]),

                     by = “1 day”

                   )), all = TRUE, by = “Specimen.date”)

setkey(area_data, Specimen.date)

setnafill(area_data, type = “const”, fill = 0,

          cols = c(“Daily.lab.confirmed.cases”))

area_data[,roll_mean := frollmean(Daily.lab.confirmed.cases, n = 7, align = “right”)]

######################################

###########Exponential model##########

######################################

area_data[,increasing := c(rep(NA,7), roll_mean[-(1:7)]- roll_mean[-((.N-6):.N)]>0)]

end_date

  Specimen.date[1], by=”increasing”]$V1

start_date

  increasing==FALSE & Specimen.date

     Specimen.date[1], by=”increasing”]$V1

exp_lm_data start_date & Specimen.date

exp_lm_data[, days := 1:.N]

exp_lm

exp_lm_data[,fitted_numbers := exp(fitted.values(exp_lm))]

predicted_data

predicted_data[,Specimen.date := min(exp_lm_data$Specimen.date)+ lubridate::days(days)]

predicted_data[,predicted_numbers := exp(predict.lm(exp_lm, predicted_data))]

#####################################

m_area_data

                    measure.vars = c(“Daily.lab.confirmed.cases”,”roll_mean”))

exp_lm_data

                    id.vars=”Specimen.date”,

                    measure.vars = c(“fitted_numbers”,”predicted_numbers”))

m_area_data

area_plot

  geom_bar(data = subset(m_area_data, variable == “Daily.lab.confirmed.cases”),

           stat = “identity”) +

  geom_line(data = subset(m_area_data, variable != “Daily.lab.confirmed.cases”)) +

  labs(x=”Specimen Date”, y=”Number of Confirmed Cases”,

       fill = “”, color = “”) +

  scale_fill_manual(values = c(“#ff0000″,”#05d153″,”#cad105″,”#000000”),

                    labels = c(sprintf(“%s # Daily Confirmed cases”,area_name),

                               “fitted”,”predicted”,”7 day average”)) +

  scale_color_manual(values = c(“#ff0000″,”#05d153″,”#cad105″,”#000000”),

                     labels = c(sprintf(“%s # Daily Confirmed cases”,area_name),

                                “fitted”,”predicted”,”7 day average”)) +

  scale_x_date(date_breaks = “4 weeks”, date_labels = “%Y-%m-%d”) +

  theme_bw() %+replace% theme(legend.position = “top”,

                              legend.justification = “left”)

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