Using an individual-based model of dengue transmission, we explored how different assumptions about the movement and spatial distribution of the vector can affect dengue incidence in humans. We found that the tendency for the most important vector of dengue, A. aegypti, to stay within a building and fly only short distances greatly affects its vectorial capacity. However, once a model is calibrated to obtain a realistic human infection attack rate, the population-wide effectiveness of mass dengue vaccination is robust to these assumptions. Although the model variants were calibrated to produce the same average infection attack rates, the spatial heterogeneity of infection risk could be different. When mosquito mobility is low, dengue risk would be elevated near dengue cases and lower elsewhere. In areas of high risk, a vaccine that confers “leaky” protection would be less effective in areas of high risk than one that confers “all-or-none” protection. However, the difference in the effectiveness of mass vaccination using the leaky or all-or-none assumption was minor.
Households may be the primary venue for dengue infection in humans. A. aegypti
are known to breed in small containers associated with households, which may lead to spatial clustering at the household level 
. Clusters of cases appear in households, consistent with a single source of infection 
. Households members of symptomatic dengue cases have been found to have a relatively high probability of being infected, though often asymptomatically 
. These phenomena are best captured by mathematical models that explicitly include households, such as the model used here. In one model variant, we assumed an exponential instead of uniform distribution for the number of mosquitoes per location. Because there is little empirical data on adult mosquito counts per household, we chose a simple distribution that requires only one parameter. Using a more realistic or data-driven distribution might affect the results.
Dengue outbreaks often occur in small spatial clusters, probably because of the short flight range of A. aegypti
. Perifocal spraying measures typically target a 100 meter radius around detected cases of dengue fever. Studies have found that the risk of dengue infection was significantly higher for children living within 100 meters of another infected child than in control clusters 
. The elevated risk of infection in these clusters was for only a few days, evidence that risk was associated with individual dengue outbreaks 
. The focal nature of dengue outbreaks can also be detected in spatial patterns of immunity to the four serotypes 
. Therefore, spatial effects might play an important role in the multi-year dynamics of dengue.
A recent modeling study found that the fine-scale spatial distribution of mosquitoes could affect dengue transmission, since some houses had a superabundance of mosquitoes 
. Our results indicate that such fine-scale heterogeneity might “wash out” when studying larger geographic areas. Including the ability for mosquitoes to disperse to other households dilutes the differences in mosquito populations in households with different production rates 
. We did not study coarser scales of spatial heterogeneity, such as regions that include both urban and rural populations.
Human movement probably plays a role in the spatial spread of dengue. A recent study demonstrated that visiting households with dengue-infected individuals was associated with an increased risk of infection 
. Additional evidence for the role of human movement on the spread of dengue is the apparent spread of dengue along major roads 
. In our model, we assumed that symptomatic people tend to stay home from school and work, which increases transmission in households. Thus, it may be important to capture these detailed human movements to estimate the risk of dengue, which was not our focus here.
We found that the incidence of dengue in the model was highly sensitive to the parameters associated with transmissibility but less so to the size of the mosquito population, which is consistent with simple deterministic compartmental models of vector-borne pathogens 
. Therefore, it may be unwise for modelers to borrow point estimates of transmission parameters directly from the experimental literature. It may also be unwise to extract parameter values from other models, since models with different assumptions may produce different results even with the same parameterization. For example, we found that when vectors in the model are not constrained by space, they were able to spread dengue much more effectively. Here, we decided to adjust transmissibility and vector population size in the different model variants in order to obtain consistent and realistic human infection attack rates.
Keeping the limitations of our mathematical model in mind, we can draw a few general conclusions. Although fine-grained spatial heterogeneity in the mosquito population likely has significant effects on dengue transmission within individual households, the ability of mosquitoes, and people, to move reduces the effects of these heterogeneities. Focal interventions, such as perifocal spraying, may require careful and fine-grained spatial modeling 
, but interventions that cover large regions, such as mass vaccination, might be insensitive to these features. However, there are features relevant to dengue transmission that occur at a coarser spatial scale, such as urbanization or mosquito habitat differences, and modeling dengue outbreaks in these regions probably requires a better understanding of dengue epidemiology.