Spatial dynamics and the basic reproduction number of the 1991–1997 Cholera epidemic in Peru

After being cholera free for over 100 years, Peru experienced an unprecedented epidemic of Vibrio cholerae O1 that began in 1991 and generated multiple waves of disease over several years. We developed a mechanistic transmission model that accounts for seasonal variation in temperature to estimate spatial variability in the basic reproduction number ([Image: see text] ), the initial concentration of vibrios in the environment, and cholera reporting rates. From 1991-1997, cholera spread following a multi-wave pattern, with weekly incidence concentrated during warm seasons. The epidemic first hit the coastal departments of Peru and subsequently spread through the highlands and jungle regions. The correlation between model predictions and observations was high (range in R(2): 58% to 97%). Department-level population size and elevation explained significant variation in spatial-temporal transmission patterns. The overall R(0) across departments was estimated at 2.1 (95% CI: 0.8,7.3), high enough for sustained transmission. Geographic-region level [Image: see text] varied substantially from 2.4 (95% CI: 1.1, 7.3) for the coastal region, 1.9 (0.7, 6.4) for the jungle region, and 1.5 (0.9, 2.2) for the highlands region. At the department level, mean [Image: see text] ranged from 0.8 to 6.9. Department-level [Image: see text] were correlated with overall observed attack rates (Spearman ρ = 0.59, P = 0.002), elevation (ρ = −0.4, P = 0.04), and longitude (ρ = −0.6, P = 0.004). We find that both [Image: see text] and the initial concentration of vibrios were higher in coastal departments than other departments. Reporting rates were low, consistent with a substantial fraction of asymptomatic or mild cases associated with the El Tor cholera biotype. Our results suggest that cholera vibrios, autochthonous to plankton in the natural aquatic environment, may have triggered outbreaks in multiple coastal locations along the Pacific coast of Peru. Our methodology could be useful to investigate multi-wave epidemics of cholera and could be extended to conduct near real-time forecasts and investigate the impact of vaccination strategies.