New insight into avian malaria vectors in New Zealand

BACKGROUND

Mosquitoes (Culicidae) are vectors for most malaria parasites of the Plasmodium species and are required for Plasmodium spp. to complete their life cycle. Despite having 16 species of mosquitoes and the detection of many Plasmodium species in birds, little is known about the role of different mosquito species in the avian malaria life cycle in New Zealand.

METHODS

In this study, we used nested polymerase chain reaction (PCR) and real-time PCR to determine Plasmodium spp. prevalence and diversity of mitochondrial cytochrome b gene sequences in wild-caught mosquitoes sampled across ten sites on the North Island of New Zealand during 2012-2014. The mosquitoes were pooled by species and location collected, and the thorax and abdomens were examined separately for Plasmodium spp. DNA. Akaike information criterion (AIC) modeling was used to test whether location, year of sampling, and mosquito species were significant predictors of minimum infection rates (MIR).

RESULTS

We collected 788 unengorged mosquitoes of six species, both native and introduced. The most frequently caught mosquito species were the introduced Aedes notoscriptus and the native Culex pervigilans. Plasmodium sp DNA was detected in 37% of matched thorax and abdomen pools. When considered separately, 33% of abdomen and 23% of thorax pools tested positive by nested PCR. The MIR of the positive thorax pools from introduced mosquito species was 1.79% for Ae. notoscriptus and 0% for Cx. quinquefasciatus, while the MIR for the positive thorax pools of native mosquito species was 4.9% for Cx. pervigilans and 0% for Opifex fuscus. For the overall MIR, site and mosquito species were significant predictors of Plasmodium overall MIR. Aedes notoscriptus and Cx. pervigilans were positive for malaria DNA in the thorax samples, indicating that they may play a role as avian malaria vectors. Four different Plasmodium lineages (SYAT05, LINN1, GRW6, and a new lineage of P (Haemamoeba) sp. AENOT11) were identified in the pooled samples.

CONCLUSIONS

This is the first detection of avian Plasmodium DNA extracted from thoraxes of native Culex and introduced Aedes mosquito species in New Zealand and therefore the first study providing an indication of potential vectors in this country.

Field evaluation of an automated mosquito surveillance system which classifies Aedes and Culex mosquitoes by genus and sex

BACKGROUND

Mosquito-borne diseases are a major concern for public and veterinary health authorities, highlighting the importance of effective vector surveillance and control programs. Traditional surveillance methods are labor-intensive and do not provide high temporal resolution, which may hinder a full assessment of the risk of mosquito-borne pathogen transmission. Emerging technologies for automated remote mosquito monitoring have the potential to address these limitations; however, few studies have tested the performance of such systems in the field.

METHODS

In the present work, an optical sensor coupled to the entrance of a standard mosquito suction trap was used to record 14,067 mosquito flights of Aedes and Culex genera at four temperature regimes in the laboratory, and the resulting dataset was used to train a machine learning (ML) model. The trap, sensor, and ML model, which form the core of an automated mosquito surveillance system, were tested in the field for two classification purposes: to discriminate Aedes and Culex mosquitoes from other insects that enter the trap and to classify the target mosquitoes by genus and sex. The field performance of the system was assessed using balanced accuracy and regression metrics by comparing the classifications made by the system with those made by the manual inspection of the trap.

RESULTS

The field system discriminated the target mosquitoes (Aedes and Culex genera) with a balanced accuracy of 95.5% and classified the genus and sex of those mosquitoes with a balanced accuracy of 88.8%. An analysis of the daily and seasonal temporal dynamics of Aedes and Culex mosquito populations was also performed using the time-stamped classifications from the system.

CONCLUSIONS

This study reports results for automated mosquito genus and sex classification using an optical sensor coupled to a mosquito trap in the field with highly balanced accuracy. The compatibility of the sensor with commercial mosquito traps enables the sensor to be integrated into conventional mosquito surveillance methods to provide accurate automatic monitoring with high temporal resolution of Aedes and Culex mosquitoes, two of the most concerning genera in terms of arbovirus transmission.