As anthropogenic change continues to alter ecosystems worldwide, humans are experiencing more frequent outbreaks of novel and emerging infectious diseases. Effects of the recent outbreaks of Zika virus have the potential to drastically change the structure of human populations. For mosquito-borne diseases like Zika, a popular method for controlling disease is to reduce the number of breeding sites available to mosquito vectors. We present a mathematical model exploring how the synchronicity of these treatment efforts between four subdivisions of the landscape affect the size of an epidemic. These subdivisions represent local municipalities that are likely to enact control efforts independently and without coordination.
More people become infected with Zika when treatment rates are equal between all parts of the landscape (synchronicity is high) than when treatment rates differ between subdivisions. These results suggest that local municipalities will need to coordinate their treatment efforts to reduce synchronicity in order to more effectively reduce vector population sizes and control Zika outbreaks. These principles can also be applied to reduce the severity of other emerging vector-borne diseases.