Unforeseen costs of cutting mosquito surveillance budgets

Abstract

A budget proposal to stop the U.S. Centers for Disease Control and Prevention (CDC) funding in surveillance and research for mosquito-borne diseases such as dengue and West Nile virus has the potential to leave the country ill-prepared to handle new emerging diseases and manage existing ones. In order to demonstrate the consequences of such a measure, if implemented, we evaluated the impact of delayed control responses to dengue epidemics (a likely scenario emerging from the proposed CDC budget cut) in an economically developed urban environment. We used a mathematical model to generate hypothetical scenarios of delayed response to a dengue introduction (a consequence of halted mosquito surveillance) in the City of Cairns, Queensland, Australia. We then coupled the results of such a model with mosquito surveillance and case management costs to estimate the cumulative costs of each response scenario. Our study shows that halting mosquito surveillance can increase the management costs of epidemics by up to an order of magnitude in comparison to a strategy with sustained surveillance and early case detection. Our analysis shows that the total costs of preparedness through surveillance are far lower than the ones needed to respond to the introduction of vector-borne pathogens, even without consideration of the cost in human lives and well-being. More specifically, our findings provide a science-based justification for the re-assessment of the current proposal to slash the budget of the CDC vector-borne diseases program, and emphasize the need for improved and sustainable systems for vector-borne disease surveillance.

Figure 1. Impacts of hypothetical scenarios of delayed response of vector control to Dengue virus outbreaks.

The basic reproduction number, R₀ (the average number of secondary cases after the introduction of an infection) for the 2003 and 2009 dengue fever outbreaks that affected the city of Cairns, Australia, was estimated by fitting an exponential function to the observed weekly epidemic curves before vector control interventions began (6 weeks in 2003 and 4 weeks in 2009). The effective reproduction number, R_t (the average number of secondary cases per primary case at time t) of each outbreak was estimated by accumulating the number of cases in biweekly periods (the average generation time of dengue is ∼14 days) and computing the ratio between consecutive two-week periods. The hypothetical epidemic curves for the 2003 (A) and 2009 (B) outbreaks under different scenarios for response times (res) of vector control activities to a dengue introduction (res = 2, 4, 6 and 8 weeks) were computed by estimating the number of cases in the absence of control (between t₀ and res) using R₀, and then generating the rest of each epidemic time series by multiplying the number of cases by the estimated post intervention R_t in the original series. Blue lines indicate a faster response time than in the actual outbreak, red lines indicate scenarios where the response is delayed in comparison to the actual outbreak, and green lines indicate the actual outbreak. Values on top of the green lines are estimates for R_t. Cumulative cost (in 2009 US$) of each res scenario were estimated for the 2003 (C) and 2009 (D) outbreaks. Figure legends refer to each res scenario (A,B) and to the final epidemic size of each scenario (C,D).