Summary by: Culzean Kennedy
Transmissibility serves as one of the primary indicators of the threat posed by an emergent pathogen. The incorporation of this important function into compartmental models enables researchers interested in forecasting epidemic dynamics to estimate the size of infectious and susceptible populations. Early in an epidemic, in the absence of drug and vaccine treatments, behavioral interventions, including isolation measures, provide a crucial means of limiting human-to-human transmission between infectious and susceptible individuals. These behavior-dependent removal efforts complicate modeling attempts by altering interactions between infected individuals and the at-risk population, resulting in a deviation from predicted transmission modes and rates. Additionally, the intensity of these interventions varies throughout an epidemic; Increasing epidemic awareness results in higher removal rates due to what is referred to as societal learning. Health care access, funding and the magnitude of informational campaigns largely determine the effectiveness of behavioral modifications and the speed at which they are implemented, making these measures difficult to predict. In a recent study, researchers, including CEID Director John Drake, sought to determine how the mean removal rate of infectious individuals from susceptible populations changed over the course of various outbreaks in different settings.
Using data obtained from seven recent outbreaks of Ebola virus disease (EVD), Severe Acute Respiratory Syndrome (SARS), and Middle East Respiratory Syndrome (MERS), researchers quantified the mean removal rates (MMR) and days from symptom onset to hospitalization (DSOH). Regression analyses provided insight to researchers regarding whether the serial interval and epidemic week accurately predict DSOH and MMR. The results of analyses within SARS and MERS outbreaks indicated that the lower mean estimates of serial interval-based models might provide a better prediction of MMR and DSOH values due to its narrowed confidence. Across all epidemics, isolation rates increased with both epidemic week and serial interval, but outbreak type and location influenced the speed at which populations develop and maintain these vital health responses; the observed differences in rates of adaptation further emphasized the disadvantage of areas with limited health care access and public health investment. The study itself provides a range of feasible values for the MMR of previous outbreaks which could potentially be incorporated into models for the emergence of infectious disease with insufficient data available from previous outbreaks. Additionally, this study supported the importance of incorporating a similar range of values to account for the removal of infectious individuals when seeking to accurately forecast the epidemiology of a similar emerging pathogen in a similar setting.
Lodge, E. K., Schatz, A. M., & Drake, J. M. (2020). Protective Population Behavior Change in Outbreaks of Emerging Infectious Disease. bioRxiv, 2020.2001.2027.921536. doi:10.1101/2020.01.27.921536