Effects of clustered transmission on epidemic growth Comment on "Mathematical models to characterize early epidemic growth: A review" by Gerardo Chowell et al.
Characterizing the early growth profile of an epidemic outbreak is key for predicting the likely trajectory of the number of cases and for designing adequate control measures. Epidemic profiles characterized by exponential growth have been widely observed in the past and a grounding theoretical framework for the analysis of infectious disease dynamics was provided by the pioneering work of Kermack and McKendrick [1] In particular, exponential growth stems from the assumption that pathogens spread in homogeneous mixing populations; that is, individuals of the population mix uniformly and randomly with each other. However, this assumption was readily recognized as highly questionable [2] and sub exponential profiles of epidemic growth have been observed in a number of epidemic outbreaks, including HIV/AIDS, foot and mouth disease, measles and, more recently, Ebola [3,4] In this systematic review [5] Chowell and colleagues assess which classes of mathematical models are adequate to deal with epidemic outbreaks characterized by sub exponential growth. They claim that "incorporating dynamic contact networks into models of disease spread may be required for modeling more realistic early epidemic growth profiles, while models based on static networks are expected to quickly approach an exponential growth regime in the absence of susceptible depletion or mitigation mechanisms" They argue that profiles of sub exponential growth might be induced by disease severity through a modification of the structure of the contact network, with sick individuals confined in households and hospitals, and hence limited transmission in other settings (e.g. school, workplace, leisure places) and reduced long distance interactions. I agree with the interpretation of Chowell and colleagues. Indeed, in my view there are, although very preliminary, empirical data supporting their conclusions. Their analysis consistently shows sub exponential growth of Ebola cases at different geographical scales in West Africa [3 5] From the comparative analysis of three chains of Ebola transmission in West Africa [6 8] a strikingly consistent pattern emerges: more than 70% of transmission events occurred among family members, and most of the remaining transmission events occurred among friends and health care workers. More in detail, 72% of cases were exposed in family or extended family in Conakry, Guinea [6] similar to the 74.3% estimated for Pujehun district, Sierra Leone [7] and to the 71.4% estimated for Montserrado, Liberia [8] Moreover, a modeling study conducted in Liberia [9] shows that in the first months of the epidemic, from June to mid August 2014, a fraction as a high as
Physics of life reviews