A mathematical model on treatment-seeking behaviour on disease statistics

Abstract

Abrupt outbreak of a disease can force the government authorities of a nation to restrain routine activities and implement various non-pharmaceutical interventions (NPIs) prior to the accomplishment of adequate vaccines and formal medication. Such interventions can yield fruitful results if there is no inconsistency in the notified disease statistics. In pursuance of authentic statistics (incidence, mortality, etc.)  of the disease  outbreak, it is obligatory that the population seek treatment with those health services which are linked with the Government Health Surveillance System (GHSS) in order to get notified in the data being recorded. With the accessibility to informal healthcare services and distrust in formal healthcare services, individuals may choose alternative healthcare options not affiliated with GHSS and thus go unrecorded. So, in order to explore the impact of human treatment-seeking behaviour on the disease statistics, we propose a deterministic mathematical model that integrates human treatment-seeking behaviour with disease transmission using replicator dynamics equations and a compartmental SEIR model. We model the payoff for the replicator dynamics equation with a focus on the human choice between informal health care options and GHSS-linked health services based on the `cost and quality approach'.