Incubation periods impact the spatial predictability of cholera and Ebola outbreaks in Sierra Leone

Rebecca Kahn,  View ORCID ProfileCorey M. Peak,  View ORCID ProfileJuan Fernández-Gracia, Alexandra Hill, Amara Jambai, Louisa Ganda,  View ORCID ProfileMarcia C. Castro, and Caroline O. Buckee

PNAS March 3, 2020 117 (9) 5067-5073;

Significance

Understanding how infectious diseases spread is critical for preventing and containing outbreaks. While advances have been made in forecasting epidemics, much is still unknown. Here we show that the incubation period, the time between exposure to a pathogen and onset of symptoms, is an important factor in predicting spatiotemporal spread of disease and provides one explanation for the different trajectories of recent Ebola and cholera outbreaks in Sierra Leone. We find that outbreaks of pathogens with longer incubation periods, such as Ebola, tend to have less predictable spread, whereas pathogens with shorter incubation periods, such as cholera, spread in a more predictable, wavelike pattern. These findings have implications for the scale and timing of reactive interventions, such as vaccination campaigns.

Abstract

Forecasting the spatiotemporal spread of infectious diseases during an outbreak is an important component of epidemic response. However, it remains challenging both methodologically and with respect to data requirements, as disease spread is influenced by numerous factors, including the pathogen’s underlying transmission parameters and epidemiological dynamics, social networks and population connectivity, and environmental conditions. Here, using data from Sierra Leone, we analyze the spatiotemporal dynamics of recent cholera and Ebola outbreaks and compare and contrast the spread of these two pathogens in the same population. We develop a simulation model of the spatial spread of an epidemic in order to examine the impact of a pathogen’s incubation period on the dynamics of spread and the predictability of outbreaks. We find that differences in the incubation period alone can determine the limits of predictability for diseases with different natural history, both empirically and in our simulations. Our results show that diseases with longer incubation periods, such as Ebola, where infected individuals can travel farther before becoming infectious, result in more long-distance sparking events and less predictable disease trajectories, as compared to the more predictable wave-like spread of diseases with shorter incubation periods, such as cholera.

See https://www.pnas.org/content/117/9/5067

Fig. 1:

The proportion of cholera and Ebola cases reported over time differed between district and chiefdom levels. The times between the onset of an outbreak and when half or all of its cases were reported were longer when outbreaks were aggregated by district instead of chiefdom, which has implications for the optimal scale for surveillance and response measures. The median time for a chiefdom cholera outbreak to report half of its case total was 3.9 wk, and a median of 7.9 wk for district cholera outbreaks. For Ebola, chiefdoms reported half of their cases at a median of 13.9 wk, and districts reported at a median of 23.5 wk.