The effect of screening on the health burden of chlamydia: An evaluation of compartmental models based on person-days of infection

Sexually transmitted diseases are detrimental to the health and economic well-being of society. Consequently, predicting impending outbreaks and identifying effective disease interventions through the use of epidemiological tools, such as compartmental models, is of the utmost importance. Unfortunately, traditional compartmental models, specifically the differential equation models attributed to the work of Kermack and McKendrick, require either a duration of infection that follows the exponential or Erlang distribution, despite the biological invalidity of such assumptions. As these assumptions negatively impact the quality of model predictions, alternative approaches are required that capture the variability in the duration of infection, along with its associated effects on the trajectory of disease, and in the evaluation of disease interventions. So, we apply an entirely new family of differential equation compartmental models based on the quantity, “person-days of infection,” to predict the trajectory of a disease. Importantly, this new family of models can alternative duration of infection distributions. As proof of concept, we calibrate our model to recent trends of chlamydia incidence in the United States and utilize a general statistical distribution that features periodic hazard rates. We then evaluate how increasing sexually transmitted disease screening rates alter predictions of incidence and saves disability adjusted life-years over a 5-year horizon. Our findings illustrate that increasing the annual screening rate of chlamydia from 35% to 40%-70% would annually avert 6.1-40.3 incidence and 1.68-11.14 disability adjusted life-years per 1000 people. This suggests increasing the screening rate of sexually transmitted diseases in the United States would greatly aid in ongoing public health efforts to curtail the rising trends in preventable sexually transmitted diseases.