Testing-isolation interventions will likely be insufficient to contain future novel disease outbreaks

When novel human diseases emerge into naive populations, identification and isolation of infected individuals forms the first line of defense against the invading pathogens 1,2 . Diagnostic testing plays a critical role 3,4 , but health agencies unprepared for a novel disease invasion may struggle to meet the massive testing capacities demanded by an epidemic outbreak 5 , potentially resulting in a failure of epidemic containment as with COVID-19 6 . What factors make a disease controllable versus uncontrollable with limited testing supplies remains unclear. Specifically, is the failure of testing-isolation unique to COVID-19, or is this a likely outcome across the spectrum of disease traits that may constitute future epidemics? Here, using a generalized mathematical disease model parameterized for each of seven different human diseases, we show that testing-isolation strategies will typically fail to contain epidemic outbreaks at practicably achievable testing capacities. From this analysis, we identify three key disease characteristics that govern controllability under resource constraints; the basic reproduction number, mean latent period, and non-symptomatic transmission index. Interactions among these characteristics play prominent roles in both explaining controllability differences among diseases and enhancing the efficacy of testing-isolation in combination with transmission-reduction measures. This study provides broad guidelines for managing controllability expectations during future novel disease invasions, describing which classes of diseases are most amenable to testing-isolation strategies alone and which will necessitate additional transmission-reduction measures like social distancing.