Abstract
Infectious diseases rarely exhibit simple dynamics. Outbreaks (defined as excess cases beyond response capabilities) have the potential to cause a disproportionately high burden due to overwhelming health care systems. The recommendations of international policy guidelines and research agendas are based on a perceived standardised definition of an outbreak characterised by a prolonged, high-caseload, extra-seasonal surge. In this analysis we apply multiple candidate outbreak definitions to reported dengue case data from Brazil to test this assumption. The methods identify highly heterogeneous outbreak characteristics in terms of frequency, duration and case burden. All definitions identify outbreaks with characteristics that vary over time and space. Further, definitions differ in their timeliness of outbreak onset, and thus may be more or less suitable for early intervention. This raises concerns about the application of current outbreak guidelines for early warning/identification systems. It is clear that quantitatively defining the characteristics of an outbreak is an essential prerequisite for effective reactive response. More work is needed so that definitions of disease outbreaks can take into account the baseline capacities of treatment, surveillance and control. This is essential if outbreak guidelines are to be effective and generalisable across a range of epidemiologically different settings.
Highlights
While much progress has been made in our ability to treat and reduce the long-term burden of many infectious diseases (Lim et al, 2013), unexpected surges in case numbers above the seasonally expected mean can frequently derail progress or push already stretched healthcare resources to breaking point (Cotter et al, 2013; Garg et al, 2008; Hay et al, 2003a, 2003b)
To compare the outbreak characteristics identified by each different outbreak definition we applied every definition to each state in Brazil
To compare outbreak characteristics we measured the total number of unique outbreaks identified by each definition and the percentage of total cases across the time series that were classified as outbreak cases
Summary
While much progress has been made in our ability to treat and reduce the long-term burden of many infectious diseases (Lim et al, 2013), unexpected surges in case numbers above the seasonally expected mean can frequently derail progress or push already stretched healthcare resources to breaking point (Cotter et al, 2013; Garg et al, 2008; Hay et al, 2003a, 2003b). Disease outbreaks often develop rapidly, are difficult or impossible to predict and cause a disproportionately high burden due to the lack of response capabilities (Garg et al, 2008; Grais et al, 2007; Najera, 1999; WHO Ebola Response Team, 2014). Brady et al / Epidemics 11 (2015) 92–102 variable (Simmons et al, 2012; Endy et al, 2011; Brady et al, 2014), making interpretation of the seasonal signals in reported case data difficult (Hay et al, 2013)
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