How heterogeneity in density dependence affects disease spread: when lifestyle matters

People's lifestyles play a major role in disease risk. Some employment sectors and transport modes involve fixed exposures regardless of community size, while in other settings exposure tracks with population density. MERS-CoV, a coronavirus discovered in Saudi Arabia in 2012 closely related to those causing SARS and COVID-19, appears to need extended contact time for transmission, making some segments of a community at greater risk than others. We model mathematically how heterogeneity in contact rate structure impacts disease spread, using as a case study a MERS outbreak in two Saudi Arabian communities. We divide the at-risk population into segments with exposure rates either independent of population density or density-dependent. Analysis shows disease spread is minimized for intermediate size populations with a limited proportion of individuals in the density-independent group. In the case study, the high proportion of density-independent exposure may explain the historical outbreak's extinction in the larger city.

Automated summary

People's lifestyles have a significant impact on disease risk, with different employment sectors and transport modes having varying degrees of exposure. The transmission of MERS-CoV, a coronavirus related to SARS and COVID-19, appears to require extended contact time, making certain segments of a community more vulnerable than others. By mathematically modeling the impact of heterogeneity in contact rates on disease spread, using a MERS outbreak in two Saudi Arabian communities, it was found that minimizing disease spread requires a moderate population size with a limited proportion of individuals in the density-independent exposure group. The predominance of density-independent exposure may explain the extinction of the historical outbreak in the larger city.