Abstract

BackgroundVector control measures are critical for the prevention and reduction of dengue virus (DENV) transmission. Effective vector control is reliant not only on knowledge of mosquito abundance, but also on the timely and accurate detection of mosquito-borne infection. Mosquito-based virus surveillance programs typically rely on pool-based mosquito testing, although whether individual-based mosquito testing is a feasible alternative to this has not been widely studied. Applying an individual-based mosquito testing approach, we conducted a 1-month surveillance study of DENV in adult Aedes aegypti mosquitoes in homes of suspected dengue patients during the 2015 peak dengue season in Tarlac City, Philippines to more accurately assess the mosquito infection rate and identify the DENV serotypes and genotypes concurrently co-circulating in mosquitoes and patients there.MethodsWe performed a one-step multiplex real-time reverse transcription-polymerase chain reaction (RT-PCR) assay for the simultaneous detection and serotyping of DENV in patients and individual female Ae. aegypti mosquitoes. Additionally, we performed sequencing and phylogenetic analyses to further characterize the detected DENV serotypes in mosquitoes and patients at the genotype level.ResultsWe collected a total of 583 adult Ae. aegypti mosquitoes, of which we individually tested 359 female mosquitoes for the presence of DENV. Ten (2.8%) of the 359 female mosquitoes were positive for the presence of DENV. We detected DENV-1, DENV-2, and DENV-4 in the field-collected mosquitoes, which was consistent with the serotypes concurrently found in infected patients. Sequencing and phylogenetic analyses of the detected DENV serotypes based on the partial sequence of the evelope (E) gene revealed three genotypes concurrently present in the sampled mosquitoes and patients during the study period, namely DENV-1 genotype IV, DENV-2 Cosmopolitan genotype, and DENV-4 genotype II.ConclusionsWe demonstrated the utility of a one-step multiplex real-time RT-PCR assay for the individual-based DENV surveillance of mosquitoes. Our findings reinforce the importance of detecting and monitoring virus activity in local mosquito populations, which are critical for dengue prevention and control.

Highlights

  • Vector control measures are critical for the prevention and reduction of dengue virus (DENV) trans‐ mission

  • Given that there is no consensus on the best pool size for mosquito screening, there is uncertainty concerning the accuracy of estimated minimum infection rates (MIRs) and maximal likelihood estimates (MLE) [22, 23]

  • In conclusion, we demonstrated that individual-based mosquito testing using a one-step multiplex real-time RT-Polymerase chain reaction (PCR) assay is a potential tool for mosquito-based DENV surveillance

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Summary

Introduction

Vector control measures are critical for the prevention and reduction of dengue virus (DENV) trans‐ mission. Effective vector control is reliant on knowledge of mosquito abundance, and on the timely and accurate detection of mosquito-borne infection. Mosquito-based virus surveillance programs typically rely on pool-based mosquito testing, whether individual-based mosquito testing is a feasible alternative to this has not been widely studied. Applying an individual-based mosquito testing approach, we conducted a 1-month surveil‐ lance study of DENV in adult Aedes aegypti mosquitoes in homes of suspected dengue patients during the 2015 peak dengue season in Tarlac City, Philippines to more accurately assess the mosquito infection rate and identify the DENV serotypes and genotypes concurrently co-circulating in mosquitoes and patients there. Screening of mosquito pools has been widely utilized in mosquito-based virus surveillance programs owing to its cost-effectiveness, and in part, due to the small amount of viral RNA recovered from a single mosquito. Given that there is no consensus on the best pool size for mosquito screening, there is uncertainty concerning the accuracy of estimated minimum infection rates (MIRs) and maximal likelihood estimates (MLE) [22, 23]

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