Abstract
Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and when little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associated Aedes occurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our exploratory space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. The Ae. aegypti model contained the highest number of districts with more dengue cases than would be expected given baseline population levels, followed by the model accounting for both Ae. aegypti and Ae. albopictus. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, potentially improving efforts to understand outbreak dynamics at national scales.
Highlights
Dengue disease, a viral infection transmitted to humans by Aedes mosquitoes, is endemic to 128 countries, with 3.9 billion people considered at-risk globally [1]
Dengue cases have increased in tropical regions worldwide owing to urbanization, globalization, and climate change facilitating the spread of Aedes mosquito vectors
This is concerning when more than one vector species is present, and little is known about their likely role in local transmission, which may result in inaccurate or incomplete risk projection or case clustering models
Summary
A viral infection transmitted to humans by Aedes mosquitoes, is endemic to 128 countries, with 3.9 billion people considered at-risk globally [1]. Despite the commonality of these programs and unforeseen cost of cutting them [8], surveillance budgets are often limited [9,10], restricting the scope and quality of the work This is concerning in developing regions such as Central America, where the burden of disease is high [1] and per capita public health expenditure is among the lowest of any region of the world [11]. Surveillance of both diseases and vectors is an essential component of integrated disease management programs that can be used to determine risk changes in space and time, providing the evidence for more targeted prevention and control interventions [12]. This is concerning when more than one vector species is present, and little is known about their likely role in local transmission, which may result in inaccurate or incomplete risk projection or case clustering models
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