Spatial modelling of the infestation indices of Aedes aegypti: An innovative strategy for vector control actions in developing countries

Abstract

Background: Larval indices such as the house index (HI), Breteau index (BI) and container index (CI) are widely used to interpret arbovirus vector density in surveillance programmes. However, the use of such data as an alarm signal is rarely considered consciously when planning programmes. The present study aims to investigate the spatial distribution pattern of the infestation of Aedes aegypti, considering the data available in the Ae. aegypti Infestation Index Rapid Survey (LIRAa) for the city of Campina Grande, Paraíba State in Brazil. Methods: The global and local Moran's indices were used in spatial analysis to measure the effects of spatial dependencies between neighbourhoods, using secondary data related to HI and BI gathered from surveillance service. Results: Our analysis shows that there is a predominance of high rates of mosquito infestation, placing Campina Grande at a near-constant risk of arbovirus outbreaks and epidemics. A highly significant Moran's index value (P < 0.001) was observed, indicating a positive spatial dependency between the neighbourhoods in Campina Grande. Using the Moran mapping and LISA mapping, the autocorrelation patterns of Ae. aegypti infestation rates among neighbourhoods have revealed hotpots that should be considered a priority to preventive actions of the entomological surveillance services. Predominance of high infestation rates and clearer relationships of these between neighbourhoods were observed between the months of May and July, the period with the highest rainfall in the city. Conclusions: This analysis is an innovative strategy capable of providing detailed information on infestation locations to the relevant public health authorities, which will enable a more efficient allocation of resources, particularly for arbovirus prevention.[Figure not available: see fulltext.]