Bundibugyo Virus Outbreak — Biostatistical Analysis
On 15 May 2026, DRC and Uganda declared an Ebola (Bundibugyo virus) outbreak. WHO declared a PHEIC on 16 May 2026 — the 17th DRC Ebola outbreak. As of 24 May, >1,010 cases and 130 deaths were reported across both countries. This document estimates R₀ and Rₜ using reported case data reconstructed from WHO, CDC, and ECDC situation reports.
# Install packages if needed
#pkgs <- c("EpiEstim", "incidence2", "tidyverse", "patchwork", "scales", "gt")
#new_pkgs <- pkgs[!pkgs %in% installed.packages()[,"Package"]]
#if(length(new_pkgs)) install.packages(new_pkgs, repos = "https://cloud.r-project.org")
library(EpiEstim)
library(tidyverse)
library(patchwork)
library(scales)
library(gt)Data reconstructed from WHO DON, CDC HAN, and ECDC situation reports (24 April – 24 May 2026). Daily new cases are interpolated between official cumulative anchor points.
df <- read_csv("ebola_drc_uganda_2026.csv", show_col_types = FALSE) |>
mutate(date = as.Date(date))
# DRC only for Rt (Uganda cases too few for robust estimation)
drc <- df |> filter(country == "DRC") |>
select(date, I = new_cases_estimated, intervention)
drc |>
select(Date = date, `New Cases` = I, Intervention = intervention) |>
gt() |>
tab_header(title = "DRC Daily Estimated New Cases") |>
tab_style(
style = cell_fill(color = "#fff3cd"),
locations = cells_body(rows = Intervention != "None")
) |>
cols_align("center")| DRC Daily Estimated New Cases | ||
| Date | New Cases | Intervention |
|---|---|---|
| 2026-04-24 | 1 | None |
| 2026-04-27 | 3 | None |
| 2026-04-30 | 5 | None |
| 2026-05-03 | 9 | None |
| 2026-05-06 | 17 | None |
| 2026-05-09 | 33 | None |
| 2026-05-12 | 62 | None |
| 2026-05-14 | 70 | None |
| 2026-05-15 | 46 | Outbreak declared |
| 2026-05-16 | 34 | PHEIC declared |
| 2026-05-17 | 40 | PHEIC declared |
| 2026-05-18 | 50 | Enhanced screening |
| 2026-05-19 | 130 | Enhanced screening |
| 2026-05-20 | 40 | Enhanced screening |
| 2026-05-21 | 35 | Response scaling |
| 2026-05-22 | 105 | Response scaling |
| 2026-05-23 | 120 | Response scaling |
| 2026-05-24 | 104 | Response scaling |
vlines <- drc |> filter(intervention != "None") |>
distinct(date, intervention)
p_epi <- ggplot(drc, aes(x = date, y = I)) +
geom_col(aes(fill = I), show.legend = FALSE) +
geom_vline(data = vlines, aes(xintercept = date, color = intervention),
linetype = "dashed", linewidth = 0.8) +
scale_fill_gradient(low = "#f7cac9", high = "#c0392b") +
scale_color_manual(values = c("Outbreak declared" = "#e67e22",
"PHEIC declared" = "#8e44ad",
"Enhanced screening"= "#2980b9",
"Response scaling" = "#27ae60")) +
scale_x_date(date_labels = "%b %d", date_breaks = "5 days") +
labs(title = "Ebola DRC 2026 — Daily New Cases",
subtitle = "Bundibugyo virus | Ituri, Nord-Kivu, Sud-Kivu provinces",
x = NULL, y = "New Cases", color = "Intervention") +
theme_minimal(base_size = 12) +
theme(legend.position = "bottom",
plot.title = element_text(face = "bold"))
p_epi
R₀ is estimated from the exponential growth phase (Apr 24 – May 15) using the Lotka-Euler equation:
\[R_0 = 1 + r \cdot T_g\]
where r is the growth rate and T_g is the mean generation time.
For Bundibugyo Ebola, we use a serial interval of mean = 12.0 days, SD = 5.3 days (based on prior Bundibugyo outbreaks; Althaus et al.; WHO Ebola Response Team literature).
# Exponential growth phase subset
growth_phase <- drc |> filter(date <= as.Date("2026-05-15"), I > 0)
# Fit log-linear model
fit <- lm(log(I + 1) ~ as.numeric(date), data = growth_phase)
r <- coef(fit)[2] # daily growth rate
# Generation time parameters (Bundibugyo; Althaus 2014 / WHO EVD team)
Tg_mean <- 12.0
Tg_sd <- 5.3
# R0 via Lotka-Euler (gamma-distributed generation time)
shape <- (Tg_mean / Tg_sd)^2
rate <- Tg_mean / Tg_sd^2
R0 <- (1 + r / rate)^shape
# Bootstrap CI
set.seed(42)
boot_r <- replicate(2000, {
samp <- sample_n(growth_phase, nrow(growth_phase), replace = TRUE)
coef(lm(log(I + 1) ~ as.numeric(date), data = samp))[2]
})
R0_boot <- (1 + boot_r / rate)^shape
R0_ci <- quantile(R0_boot, c(0.025, 0.975))
tibble(
Parameter = c("Daily growth rate (r)", "Mean serial interval", "R₀", "95% CI lower", "95% CI upper"),
Value = round(c(r, Tg_mean, R0, R0_ci[1], R0_ci[2]), 3)
) |>
gt() |>
tab_header(title = "R₀ Estimation — Exponential Growth Phase") |>
tab_style(style = cell_fill(color = "#fdecea"),
locations = cells_body(rows = Parameter == "R₀")) |>
fmt_number(columns = Value, decimals = 3)| R₀ Estimation — Exponential Growth Phase | |
| Parameter | Value |
|---|---|
| Daily growth rate (r) | 0.168 |
| Mean serial interval | 12.000 |
| R₀ | 5.454 |
| 95% CI lower | 4.315 |
| 95% CI upper | 6.579 |
Interpretation: An R₀ > 1 confirms sustained human-to-human transmission. R₀ values for past Ebola outbreaks typically range 1.5 – 2.5; Bundibugyo 2007 Uganda outbreak had R₀ ≈ 1.34 – 2.12.
Rₜ captures how transmissibility changes as interventions are applied. We use the parametric SI (serial interval) method from EpiEstim with a 7-day sliding window.
# Prepare incidence vector
inc_vec <- drc |>
arrange(date) |>
mutate(I = pmax(I, 0)) |>
pull(I)
# EpiEstim config — parametric serial interval
config <- make_config(
method = "parametric_si",
mean_si = 12.0,
std_si = 5.3,
t_start = 2:(length(inc_vec) - 6),
t_end = 8:length(inc_vec)
)
res <- estimate_R(incid = inc_vec, method = "parametric_si", config = config)
# Extract results with dates
rt_df <- res$R |>
as_tibble() |>
mutate(
date = drc$date[t_end],
Rt = `Mean(R)`,
lower = `Quantile.0.025(R)`,
upper = `Quantile.0.975(R)`
)
# Intervention dates for shading
interventions <- tibble(
xmin = as.Date(c("2026-05-15", "2026-05-16", "2026-05-18")),
xmax = as.Date(c("2026-05-16", "2026-05-18", "2026-05-24")),
label = c("Outbreak\ndeclared", "PHEIC\ndeclared", "Response\nscaling"),
ypos = c(3.8, 3.5, 3.2)
)
p_rt <- ggplot(rt_df, aes(x = date)) +
geom_rect(data = interventions,
aes(xmin = xmin, xmax = xmax, ymin = -Inf, ymax = Inf, fill = label),
alpha = 0.12, inherit.aes = FALSE) +
geom_ribbon(aes(ymin = lower, ymax = upper), fill = "#3498db", alpha = 0.25) +
geom_line(aes(y = Rt), color = "#2c3e50", linewidth = 1.1) +
geom_point(aes(y = Rt), color = "#e74c3c", size = 1.8) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red", linewidth = 0.9) +
annotate("text", x = min(rt_df$date) + 1, y = 1.08,
label = "Rₜ = 1 (control threshold)", color = "red", size = 3.2, hjust = 0) +
scale_fill_manual(values = c("Outbreak\ndeclared" = "#e67e22",
"PHEIC\ndeclared" = "#8e44ad",
"Response\nscaling" = "#27ae60")) +
scale_x_date(date_labels = "%b %d", date_breaks = "4 days") +
scale_y_continuous(limits = c(0, NA)) +
labs(title = "Effective Reproduction Number Rₜ — DRC Ebola 2026",
subtitle = "7-day sliding window | Parametric serial interval (mean=12d, SD=5.3d)",
x = NULL, y = "Rₜ", fill = "Intervention") +
theme_minimal(base_size = 12) +
theme(legend.position = "bottom",
plot.title = element_text(face = "bold"))
p_rt
p_epi / p_rt +
plot_annotation(
title = "Ebola DRC & Uganda 2026 — Transmission Analysis",
caption = "Sources: WHO DON-602/603, CDC HAN-530, ECDC Threat Assessment | Analysis: EpiEstim (Cori et al., 2013)",
theme = theme(plot.title = element_text(face = "bold", size = 14))
)
latest_rt <- rt_df |> slice_tail(n = 1)
tibble(
Metric = c("R₀ (exponential phase)", "Latest Rₜ (95% CI)",
"Total suspected cases (DRC)", "Total Uganda cases",
"CFR (confirmed)", "PHEIC declared"),
Value = c(
paste0(round(R0, 2), " (", round(R0_ci[1],2), "–", round(R0_ci[2],2), ")"),
paste0(round(latest_rt$Rt, 2),
" (", round(latest_rt$lower, 2), "–", round(latest_rt$upper, 2), ")"),
"904 (as of 23 May 2026)",
"7 confirmed (as of 23 May 2026)",
"~12% among confirmed",
"16 May 2026"
)
) |>
gt() |>
tab_header(
title = "Key Epidemiological Indicators",
subtitle = "Bundibugyo Ebola — DRC & Uganda 2026"
) |>
tab_style(style = list(cell_fill(color = "#fdecea"), cell_text(weight = "bold")),
locations = cells_body(rows = 1:2)) |>
cols_align("left", columns = Value)| Key Epidemiological Indicators | |
| Bundibugyo Ebola — DRC & Uganda 2026 | |
| Metric | Value |
|---|---|
| R₀ (exponential phase) | 5.45 (4.31–6.58) |
| Latest Rₜ (95% CI) | 3.92 (3.61–4.25) |
| Total suspected cases (DRC) | 904 (as of 23 May 2026) |
| Total Uganda cases | 7 confirmed (as of 23 May 2026) |
| CFR (confirmed) | ~12% among confirmed |
| PHEIC declared | 16 May 2026 |
Data reconstructed from WHO/CDC/ECDC official situation reports. Serial interval parameters from Althaus (2014) and WHO Ebola Response Team literature. Analysis uses EpiEstim (Cori et al., 2013, AJE).