Ebola Bungdiyo
Victoria Etuk
2026-05-31
Epidemic Curve and Rt estimation of the 2026 Ebola Bundibugyo Outbreak in the Democratic Republic of Congo
Background
The World Health Organisation declared the Bundibugyo Ebola outbreak a Public Health Emergency of International Concern on the 17th of May, 2026. This is a preliminary analysis to describe the epidemic curve and determine the effective Reproduction number of the outbreak.
The ebola bundibugyo outbreak data used in this analysis was pulled from the github page of INRB Unité de Modélisation et Intelligence Epidémique “https://github.com/INRB-UMIE/Ebola_DRC_2026/blob/main/data/insp_sitrep/processed/insp_sitrep__new_confirmed_cases__daily.csv, using confirmed case data.
The data in the analysis covers from May 14, 2026 till May 27, 2026.
## Date Number.of.cases
## 1 2026-05-14 0
## 2 2026-05-15 13
## 3 2026-05-16 0
## 4 2026-05-17 0
## 5 2026-05-18 20
## 6 2026-05-19 16
## 7 2026-05-20 11
## 8 2026-05-21 21
## 9 2026-05-22 13
## 10 2026-05-23 11
## 11 2026-05-24 4
## 12 2026-05-25 1
## 13 2026-05-26 16
## 14 2026-05-27 5Sort the data by date
ebola_data<- ebola_data%>%arrange(Date)
ebola_data## Date Number.of.cases
## 1 2026-05-14 0
## 2 2026-05-15 13
## 3 2026-05-16 0
## 4 2026-05-17 0
## 5 2026-05-18 20
## 6 2026-05-19 16
## 7 2026-05-20 11
## 8 2026-05-21 21
## 9 2026-05-22 13
## 10 2026-05-23 11
## 11 2026-05-24 4
## 12 2026-05-25 1
## 13 2026-05-26 16
## 14 2026-05-27 5#The epicurve. A total of 131 confirmed cases was reported in DRC from 14th May to 27th May, 2026. The epidemic curve below shows that the highest number of cases were reported on the 18th and 20th of May, 2026 (20 and 21 cases respectively)
ebola_data_plot<- ebola_data
ebola_data_plot$Date <- as_date(ebola_data_plot$Date)
epicurve<- ggplot2::ggplot(data=ebola_data_plot, mapping = aes(x= Date, y=Number.of.cases))+geom_col(colour="red", fill="red", width=0.5)+scale_x_date(date_labels = "%d %b %Y", date_breaks = "2 days")+labs(title = "Epidemic curve-Ebola 2026 DRC Bundibugyo Ebola outbreak", x="Date", y="Number of cases reported")
epicurve
#Estimating Rt Using the incidence package
i <- ebola_data$Date %>% incidence()
i## <incidence object>
## [14 cases from days 2026-05-14 to 2026-05-27]
##
## $counts: matrix with 14 rows and 1 columns
## $n: 14 cases in total
## $dates: 14 dates marking the left-side of bins
## $interval: 1 day
## $timespan: 14 days
## $cumulative: FALSEi$counts <- ebola_data %>% select(Number.of.cases) %>% as.matrix()
i$n <- ebola_data %>% select(Number.of.cases) %>% sum()
i## <incidence object>
## [131 cases from days 2026-05-14 to 2026-05-27]
## [1 groups: Number.of.cases]
##
## $counts: matrix with 14 rows and 1 columns
## $n: 131 cases in total
## $dates: 14 dates marking the left-side of bins
## $interval: 1 day
## $timespan: 14 days
## $cumulative: FALSEplot(i)## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## ℹ The deprecated feature was likely used in the incidence package.
## Please report the issue at <https://github.com/reconhub/incidence/issues>.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
To estimate R0, we use the Epi estim package, and the first few dates (one week). There are no published serial intervals of Ebola Bundibugyo, so we use an approximate serial interval from the Zaire and Sudan Strains as published by Chowell, Gerardo, and Hiroshi Nishiura. “Transmission dynamics and control of Ebola virus disease (EVD): a review.” BMC medicine vol. 12 196. 10 Oct. 2014, doi:10.1186/s12916-014-0196-0. The estimated R between May 15 and May 21 is ~50.
res_r0 <- estimate_R(
incid = i,
method = "parametric_si",
config = make_config(list(
mean_si = 12.0,
std_si = 5.2,
t_start = c(2),
t_end = c(7)
))
)## Warning in check_si_distr(si_distr, "warning"): si_distr does not sum to 1.plot(res_r0)
Using EpiEstim to estimate the effective R number
Using published serial intervals obtained from: Chowell, Gerardo, and Hiroshi Nishiura. “Transmission dynamics and control of Ebola virus disease (EVD): a review.” BMC medicine vol. 12 196. 10 Oct. 2014, doi:10.1186/s12916-014-0196-0, we estimate the effective Reproduction number over from 14th May to 27th May.
There was a pronounced reduction in the effective R number between 14th May to 27th May. Although the Rt is still greater than 1, the sharp reduction in Rt shows a possible effect of response activities by stakeholders and adoption of public health measures by the public.
s_interval <- make_config(
mean_si = 12.0,
std_si = 5.2
)my_R <- estimate_R(i,method="parametric_si",config=s_interval)## Default config will estimate R on weekly sliding windows.
## To change this change the t_start and t_end arguments.## Warning in check_si_distr(si_distr, "warning"): si_distr does not sum to 1.plot(my_R)
as_tibble(my_R$R)## # A tibble: 7 × 11
## t_start t_end `Mean(R)` `Std(R)` `Quantile.0.025(R)` `Quantile.0.05(R)`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 8 39.7 4.39 31.6 32.8
## 2 3 9 23.1 2.55 18.3 19.0
## 3 4 10 15.9 1.65 12.9 13.3
## 4 5 11 10.7 1.09 8.67 8.97
## 5 6 12 5.85 0.662 4.62 4.80
## 6 7 13 4.19 0.474 3.31 3.44
## 7 8 14 2.91 0.343 2.28 2.37
## # ℹ 5 more variables: `Quantile.0.25(R)` <dbl>, `Median(R)` <dbl>,
## # `Quantile.0.75(R)` <dbl>, `Quantile.0.95(R)` <dbl>,
## # `Quantile.0.975(R)` <dbl>Response activities by WHO, Africa CDC and the ministries of health of the affected countries are still ongoing. The analysis will be updated weekly as more data becomes available.