The Influence of Spatial Configuration of Residential Area and Vector Populations on Dengue Incidence Patterns in an Individual-Level Transmission Model

Abstract

Dengue is a mosquito-borne infectious disease that is endemic in tropical and subtropical countries. Many individual-level simulation models have been developed to test hypotheses about dengue virus transmission. Often these efforts assume that human host and mosquito vector populations are randomly or uniformly distributed in the environment. Although, the movement of mosquitoes is affected by spatial configuration of buildings and mosquito populations are highly clustered in key buildings, little research has focused on the influence of the local built environment in dengue transmission models. We developed an agent-based model of dengue transmission in a village setting to test the importance of using realistic environments in individual-level models of dengue transmission. The results from one-way ANOVA analysis of simulations indicated that the differences between scenarios in terms of infection rates as well as serotype-specific dominance are statistically significant. Specifically, the infection rates in scenarios of a realistic environment are more variable than those of a synthetic spatial configuration. With respect to dengue serotype-specific cases, we found that a single dengue serotype is more often dominant in realistic environments than in synthetic environments. An agent-based approach allows a fine-scaled analysis of simulated dengue incidence patterns. The results provide a better understanding of the influence of spatial heterogeneity on dengue transmission at a local scale.

Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models

“…Albopictus mosquitoes which apart from being dengue vectors, are responsible for spreading other pathogens such as Zika, yellow fever, chikungunya, and others [ 24 , 32 , 62 , 69 , 70 , 71 , 72 ]. Ten studies modeled dengue disease using either ABM or other modeling techniques as represented in Table A1 in Appendix C [ 14 , 25 , 26 , 73 , 74 , 75 , 76 , 77 , 78 ]. Eighteen studies have considered climatic factors in modeling the diseases, thirteen studies have involved environmental factors in modeling the diseases, out of which, eleven studies have included both climatic and environmental factors.…”

“…The disease is a major public health concern with economic implications. Mahmood et al [ 14 ] reported that 3.98 billion people in 128 countries are at risk of contracting dengue [ 13 , 26 , 27 ]. An annual estimate of over 105 million dengue cases is reported [ 11 , 28 ].…”

A joint spatial marked point process model for dengue and severe dengue in Medellin, Colombia

“…Typically, point process models are fitted using a regular spatial grid which approximates the latent field and the spatial pattern (20,32). Also, should the data at hand allow it, space-time kernel density estimation (STKDE) could be used for spatiotemporal disease transmission models, which could be computationally intensive and are not necessarily comparable with the methods proposed here (33)(34)(35)(36)41). For ease of applicability among the public health community, data availability, and to avoid issues associated with the interpolation of population offsets, we followed the approach proposed by Pinto Jr. et al, (36) and used the actual neighborhood map and population information as the spatial grid.…”

“…Here, the individual spatial location (exact longitude and latitude) of an outcome is denominated by a point pattern (22, 23, 32). There are several other proposed models used to assess the point pattern distribution of dengue, including the analysis of disease transmission using agent-based models (33), and analysis using space-time kernel density estimation (34, 35). Here, we propose a model-based approach wherein the logarithm of the intensity of notified dengue cases across Medellin is modelled through a latent Gaussian random field (22, 31, 32).…”

Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission

“…This process results in single serotypes predominating in local areas during a single transmission season (Endy et al, 2002). Therefore, examining the local serotype-dominance during DENV outbreaks would be a pattern of interest [40]. Importantly, when local transmission of DENV is responsible for a majority of infections, temporally successive infections should largely be of the same serotype.…”