Effects of a new outdoor mosquito control device, the mosquito landing box, on densities and survival of the malaria vector, Anopheles arabiensis, inside controlled semi-field settings

Background The significance of malaria transmission occurring outdoors has risen even in areas where indoor interventions such as long-lasting insecticidal nets and indoor residual spraying are common. The actual contamination rates and effectiveness of recently developed outdoor mosquito control device, the mosquito landing box (MLB), on densities and daily survival of host-seeking laboratory Anopheles arabiensis, which readily bites humans outdoors was demonstrated. Methods Experiments were conducted in large semi-field systems (SFS) with human volunteers inside, to mimic natural ecosystems, and using MLBs baited with natural or synthetic human odours and carbon dioxide. The MLBs were dusted with 10 % pyriproxyfen (PPF) or entomopathogenic fungi (Metarhizium anisopliae) spores to mark mosquitoes physically contacting the devices. Each night, 400 laboratory-reared An. arabiensis females were released in one SFS chamber with two MLBs, and another chamber without MLBs (control). Mosquitoes were individually recaptured while attempting to bite volunteers inside SFS or by aspiration from SFS walls. Mosquitoes from chambers with PPF-treated MLBs and respective controls were individually dipped in water-filled cups containing ten conspecific third-instar larvae, whose subsequent development was monitored. Mosquitoes recaptured from chambers with fungi-treated MLBs were observed for fungal hyphal growth on their cadavers. Separately, effects on daily survival were determined by exposing An. arabiensis in chambers having MLBs treated with 5 % pirimiphos methyl compared to chambers without MLBs (control), after which the mosquitoes were recaptured and monitored individually until they died. Results Up to 63 % (152/240) and 43 % (92/210) of mosquitoes recaptured inside treatment chambers were contaminated with pyriproxyfen and M. anisopliae, respectively, compared to 8 % (19/240) and 0 % (0/164) in controls. The mean number of larvae emerging from cups in which adults from chambers with PPF-treated MLBs were dipped was significantly lower [0.75 (0.50–1.01)], than in controls [28.79 (28.32–29.26)], P < 0.001). Daily survival of mosquitoes exposed to 5 % pirimiphos methyl was nearly two-fold lower than controls [hazard ratio (HR) = 1.748 (1.551–1.920), P < 0.001]. Conclusion High contamination rates in exposed mosquitoes even in presence of humans, demonstrates potential of MLBs for controlling outdoor-biting malaria vectors, either by reducing their survival or directly killing host-seeking mosquitoes. The MLBs also have potential for dispensing filial infanticides, such as PPF, which mosquitoes can transmit to their aquatic habitats for mosquito population control. Keywords: Mosquito landing box; Malaria; Elimination; Anopheles arabiensis ; Pirimiphos methyl; Outdoor biting; Pyriproxyfen; Metarhizium anisopliae ; Semi-field syste

Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis

Background: The propensity of diferent Anopheles mosquitoes to bite humans instead of other vertebrates infuences their capacity to transmit pathogens to humans. Unfortunately, determining proportions of mosquitoes that have fed on humans, i.e. Human Blood Index (HBI), currently requires expensive and time-consuming laboratory procedures involving enzyme-linked immunosorbent assays (ELISA) or polymerase chain reactions (PCR). Here, midinfrared (MIR) spectroscopy and supervised machine learning are used to accurately distinguish between vertebrate blood meals in guts of malaria mosquitoes, without any molecular techniques. Methods: Laboratory-reared Anopheles arabiensis females were fed on humans, chickens, goats or bovines, then held for 6 to 8 h, after which they were killed and preserved in silica. The sample size was 2000 mosquitoes (500 per host species). Five individuals of each host species were enrolled to ensure genotype variability, and 100 mosquitoes fed on each. Dried mosquito abdomens were individually scanned using attenuated total refection-Fourier transform infrared (ATR-FTIR) spectrometer to obtain high-resolution MIR spectra (4000 cm−1 to 400 cm−1 ). The spectral data were cleaned to compensate atmospheric water and CO2 interference bands using Bruker-OPUS software, then transferred to Python™ for supervised machine-learning to predict host species. Seven classifcation algorithms were trained using 90% of the spectra through several combinations of 75–25% data splits. The best performing model was used to predict identities of the remaining 10% validation spectra, which had not been used for model training or testing. Results: The logistic regression (LR) model achieved the highest accuracy, correctly predicting true vertebrate blood meal sources with overall accuracy of 98.4%. The model correctly identifed 96% goat blood meals, 97% of bovine blood meals, 100% of chicken blood meals and 100% of human blood meals. Three percent of bovine blood meals were misclassifed as goat, and 2% of goat blood meals misclassifed as human. Conclusion: Mid-infrared spectroscopy coupled with supervised machine learning can accurately identify multiple vertebrate blood meals in malaria vectors, thus potentially enabling rapid assessment of mosquito blood-feeding histories and vectorial capacities. The technique is cost-efective, fast, simple, and requires no reagents other than desiccants. However, scaling it up will require field validation of the findings and boosting relevant technical capacity in affected countries

Comparison of the CDC Backpack aspirator and the Prokopack aspirator for sampling indoor- and outdoor-resting mosquitoes in southern Tanzania.

BACKGROUND\ud \ud Resting mosquitoes can easily be collected using an aspirating device. The most commonly used mechanical aspirator is the CDC Backpack aspirator. Recently, a simple, and low-cost aspirator called the Prokopack has been devised and proved to have comparable performance. The following study evaluates the Prokopack aspirator compared to the CDC backpack aspirator when sampling resting mosquitoes in rural Tanzania.\ud \ud METHODS\ud \ud Mosquitoes were sampled in- and outdoors of 48 typical rural African households using both aspirators. The aspirators were rotated between collectors and households in a randomized, Latin Square design. Outdoor collections were performed using artificial resting places (large barrel and car tyre), underneath the outdoor kitchen (kibanda) roof and from a drop-net. Data were analysed with generalized linear models.\ud \ud RESULTS\ud \ud The number of mosquitoes collected using the CDC Backpack and the Prokopack aspirator were not significantly different both in- and outdoors (indoors p = 0.735; large barrel p = 0.867; car tyre p = 0.418; kibanda p = 0.519). The Prokopack was superior for sampling of drop-nets due to its smaller size. The number mosquitoes collected per technician was more consistent when using the Prokopack aspirator. The Prokopack was more user-friendly: technicians preferred using the it over the CDC backpack aspirator as it weighs considerably less, retains its charge for longer and is easier to manoeuvre.\ud \ud CONCLUSIONS\ud \ud The Prokopack proved in the field to be more advantageous than the CDC Backpack aspirator. It can be self assembled using simple, low-cost and easily attainable materials. This device is a useful tool for researchers or vector-control surveillance programs operating in rural Africa, as it is far simpler and quicker than traditional means of sampling resting mosquitoes. Further longitudinal evaluations of the Prokopack aspirator versus the gold standard pyrethrum spray catch for indoor resting catches are recommended

Fine-scale distribution of malaria mosquitoes biting or resting outside human dwellings in three low-altitude Tanzanian villages.

BACKGROUND: While malaria transmission in Africa still happens primarily inside houses, there is a substantial proportion of Anopheles mosquitoes that bite or rest outdoors. This situation may compromise the performance of indoor insecticidal interventions such as insecticide-treated nets (ITNs). This study investigated the distribution of malaria mosquitoes biting or resting outside dwellings in three low-altitude villages in south-eastern Tanzania. The likelihood of malaria infections outdoors was also assessed. METHODS: Nightly trapping was done outdoors for 12 months to collect resting mosquitoes (using resting bucket traps) and host-seeking mosquitoes (using odour-baited Suna® traps). The mosquitoes were sorted by species and physiological states. Pooled samples of Anopheles were tested to estimate proportions infected with Plasmodium falciparum parasites, estimate proportions carrying human blood as opposed to other vertebrate blood and identify sibling species in the Anopheles gambiae complex and An. funestus group. Environmental and anthropogenic factors were observed and recorded within 100 meters from each trapping positions. Generalised additive models were used to investigate relationships between these variables and vector densities, produce predictive maps of expected abundance and compare outcomes within and between villages. RESULTS: A high degree of fine-scale heterogeneity in Anopheles densities was observed between and within villages. Water bodies covered with vegetation were associated with 22% higher densities of An. arabiensis and 51% lower densities of An. funestus. Increasing densities of houses and people outdoors were both associated with reduced densities of An. arabiensis and An. funestus. Vector densities were highest around the end of the rainy season and beginning of the dry seasons. More than half (14) 58.3% of blood-fed An. arabiensis had bovine blood, (6) 25% had human blood. None of the Anopheles mosquitoes caught outdoors was found infected with malaria parasites. CONCLUSION: Outdoor densities of both host-seeking and resting Anopheles mosquitoes had significant heterogeneities between and within villages, and were influenced by multiple environmental and anthropogenic factors. Despite the high Anopheles densities outside dwellings, the substantial proportion of non-human blood-meals and absence of malaria-infected mosquitoes after 12 months of nightly trapping suggests very low-levels of outdoor malaria transmission in these villages

Effects of sample preservation methods and duration of storage on the performance of mid-infrared spectroscopy for predicting the age of malaria vectors

Background: Monitoring the biological attributes of mosquitoes is critical for understanding pathogen transmission and estimating the impacts of vector control interventions on the survival of vector species. Infrared spectroscopy and machine learning techniques are increasingly being tested for this purpose and have been proven to accurately predict the age, species, blood-meal sources, and pathogen infections in Anopheles and Aedes mosquitoes. However, as these techniques are still in early-stage implementation, there are no standardized procedures for handling samples prior to the infrared scanning. This study investigated the effects of different preservation methods and storage duration on the performance of mid-infrared spectroscopy for age-grading females of the malaria vector, Anopheles arabiensis. Methods: Laboratory-reared An. arabiensis (N = 3681) were collected at 5 and 17 days post-emergence, killed with ethanol, and then preserved using silica desiccant at 5 °C, freezing at − 20 °C, or absolute ethanol at room temperature. For each preservation method, the mosquitoes were divided into three groups, stored for 1, 4, or 8 weeks, and then scanned using a mid-infrared spectrometer. Supervised machine learning classifiers were trained with the infrared spectra, and the support vector machine (SVM) emerged as the best model for predicting the mosquito ages. Results: The model trained using silica-preserved mosquitoes achieved 95% accuracy when predicting the ages of other silica-preserved mosquitoes, but declined to 72% and 66% when age-classifying mosquitoes preserved using ethanol and freezing, respectively. Prediction accuracies of models trained on samples preserved in ethanol and freezing also reduced when these models were applied to samples preserved by other methods. Similarly, models trained on 1-week stored samples had declining accuracies of 97%, 83%, and 72% when predicting the ages of mosquitoes stored for 1, 4, or 8 weeks respectively. Conclusions: When using mid-infrared spectroscopy and supervised machine learning to age-grade mosquitoes, the highest accuracies are achieved when the training and test samples are preserved in the same way and stored for similar durations. However, when the test and training samples were handled differently, the classification accuracies declined significantly. Protocols for infrared-based entomological studies should therefore emphasize standardized sample-handling procedures and possibly additional statistical procedures such as transfer learning for greater accuracy