Mosquito Age Research Articles

Reagent-free detection of Plasmodium falciparum malaria infections in field-collected mosquitoes using mid-infrared spectroscopy and machine learning.

Field-derived metrics are critical for effective control of malaria, particularly in sub-Saharan Africa where the disease kills over half a million people yearly. One key metric is entomological inoculation rate, a direct measure of transmission intensities, computed as a product of human biting rates and prevalence of Plasmodium sporozoites in mosquitoes. Unfortunately, current methods for identifying infectious mosquitoes are laborious, time-consuming, and may require expensive reagents that are not always readily available. Here, we demonstrate the first field-application of mid-infrared spectroscopy and machine learning (MIRS-ML) to swiftly and accurately detect Plasmodium falciparum sporozoites in wild-caught Anopheles funestus, a major Afro-tropical malaria vector, without requiring any laboratory reagents. We collected 7178 female An. funestus from rural Tanzanian households using CDC-light traps, then desiccated and scanned their heads and thoraces using an FT-IR spectrometer. The sporozoite infections were confirmed using enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR), to establish references for training supervised algorithms. The XGBoost model was used to detect sporozoite-infectious specimen, accurately predicting ELISA and PCR outcomes with 92% and 93% accuracies respectively. These findings suggest that MIRS-ML can rapidly detect P. falciparum in field-collectedmosquitoes, with potential for enhancing surveillance in malaria-endemic regions. The technique is both fast, scanning 60-100 mosquitoes per hour, and cost-efficient, requiring no biochemical reactions and therefore no reagents. Given its previously proven capability in monitoring key entomological indicators like mosquito age, human blood index, and identities of vector species, we conclude that MIRS-ML could constitute a low-cost multi-functional toolkit for monitoring malaria risk and evaluating interventions.

Predicting the age of field Anopheles mosquitoes using mass spectrometry and deep learning.

Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control strategies targeting mosquito longevity, as the risk of pathogen transmission increases with mosquito age. However, the available tools to estimate field mosquito age are often approximate and time-consuming. Here, we show a rapid method that combines matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry with deep learning for mosquito age prediction. Using 2763 mass spectra from the head, legs, and thorax of 251 field-collected Anopheles arabiensis mosquitoes, we developed deep learning models that achieved a best mean absolute error of 1.74 days. We also demonstrate consistent performance at two ecological sites in Senegal, supported by age-related protein changes. Our approach is promising for malaria control and the field of vector biology, benefiting other disease vectors like Aedes mosquitoes.

Rapid classification of epidemiologically relevant age categories of the malaria vector, Anopheles funestus

BackgroundAccurately determining the age and survival probabilities of adult mosquitoes is crucial for understanding parasite transmission, evaluating the effectiveness of control interventions and assessing disease risk in communities. This study was aimed at demonstrating the rapid identification of epidemiologically relevant age categories of Anopheles funestus, a major Afro-tropical malaria vector, through the innovative combination of infrared spectroscopy and machine learning, instead of the cumbersome practice of dissecting mosquito ovaries to estimate age based on parity status.MethodsAnopheles funestus larvae were collected in rural south-eastern Tanzania and reared in an insectary. Emerging adult females were sorted by age (1–16 days old) and preserved using silica gel. Polymerase chain reaction (PCR) confirmation was conducted using DNA extracted from mosquito legs to verify the presence of An. funestus and to eliminate undesired mosquitoes. Mid-infrared spectra were obtained by scanning the heads and thoraces of the mosquitoes using an attenuated total reflection–Fourier transform infrared (ATR–FT-IR) spectrometer. The spectra (N = 2084) were divided into two epidemiologically relevant age groups: 1–9 days (young, non-infectious) and 10–16 days (old, potentially infectious). The dimensionality of the spectra was reduced using principal component analysis, and then a set of machine learning and multi-layer perceptron (MLP) models were trained using the spectra to predict the mosquito age categories.ResultsThe best-performing model, XGBoost, achieved overall accuracy of 87%, with classification accuracy of 89% for young and 84% for old An. funestus. When the most important spectral features influencing the model performance were selected to train a new model, the overall accuracy increased slightly to 89%. The MLP model, utilizing the significant spectral features, achieved higher classification accuracy of 95% and 94% for the young and old An. funestus, respectively. After dimensionality reduction, the MLP achieved 93% accuracy for both age categories.ConclusionsThis study shows how machine learning can quickly classify epidemiologically relevant age groups of An. funestus based on their mid-infrared spectra. Having been previously applied to An. gambiae, An. arabiensis and An. coluzzii, this demonstration on An. funestus underscores the potential of this low-cost, reagent-free technique for widespread use on all the major Afro-tropical malaria vectors. Future research should demonstrate how such machine-derived age classifications in field-collected mosquitoes correlate with malaria in human populations.Graphical

An analytically tractable, age-structured model of the impact of vector control on mosquito-transmitted infections.

Vector control is a vital tool utilised by malaria control and elimination programmes worldwide, and as such it is important that we can accurately quantify the expected public health impact of these methods. There are very few previous models that consider vector-control-induced changes in the age-structure of the vector population and the resulting impact on transmission. We analytically derive the steady-state solution of a novel age-structured deterministic compartmental model describing the mosquito feeding cycle, with mosquito age represented discretely by parity-the number of cycles (or successful bloodmeals) completed. Our key model output comprises an explicit, analytically tractable solution that can be used to directly quantify key transmission statistics, such as the effective reproductive ratio under control, Rc, and investigate the age-structured impact of vector control. Application of this model reinforces current knowledge that adult-acting interventions, such as indoor residual spraying of insecticides (IRS) or long-lasting insecticidal nets (LLINs), can be highly effective at reducing transmission, due to the dual effects of repelling and killing mosquitoes. We also demonstrate how larval measures can be implemented in addition to adult-acting measures to reduce Rc and mitigate the impact of waning insecticidal efficacy, as well as how mid-ranges of LLIN coverage are likely to experience the largest effect of reduced net integrity on transmission. We conclude that whilst well-maintained adult-acting vector control measures are substantially more effective than larval-based interventions, incorporating larval control in existing LLIN or IRS programmes could substantially reduce transmission and help mitigate any waning effects of adult-acting measures.

Effects of mosquito age and batch size on knockdown and mortality of laboratory-reared Anopheles dirus, Anopheles minimus, and wild-caught Anopheles harrisoni (Diptera: Culicidae) exposed to transfluthrin using WHO tube and CDC bottle bioassays.

WHO tube and CDC bottle bioassays are currently available for insecticide resistance monitoring and malaria transmission research. Multiple parameters including mosquito density, age, and nutritional status may affect the readout in these bioassays' tests. This study aims to assess the effects of experimental factors on knockdown and mortality measurements in dominant malaria vectors in Thailand following exposure to sublethal and lethal doses of transfluthrin. The effects of (i) 3 different mosquito batch sizes (5, 10, and 20 individuals) and (ii) 2 age groups (3-5 and 20-23 days old) on outcomes measured using the WHO tube (14.7 µg/cm2) and CDC bottle bioassay discriminating concentration (0.006 µg/cm2) against 2 laboratory strains: Anopheles dirus Peyton & Harrison and Anopheles minimus Theobald (species A) and wild-caught Anopheles harrisoni Harbach & Manguin (species C). Our results showed higher knockdown at 1-h exposure using WHO tube and CDC bottle bioassays containing 20 individuals compared to batches containing 10 and 5 individuals. Older mosquitoes showed greater susceptibility than younger test population, especially for An. mininus. Our study supports WHO recommendations for using 3- to 5-day-old mosquitoes. It also validates Praulin et al. (2022) proposal to divide the cohort into smaller batches with more test replicates when it is not practicable to test 25 mosquitoes per replicate.

Age, sex, and mating status discrimination in the sand fly Lutzomyia longipalpis using near infra-red spectroscopy (NIRS)

BackgroundUnderstanding aspects related to the physiology and capacity of vectors is essential for effectively controlling vector-borne diseases. The sand fly Lutzomyia longipalpis has great importance in medical entomology for disseminating Leishmania parasites, the causative agent of Leishmaniasis, one of the main neglected diseases listed by the World Health Organization (WHO). In this respect, it is necessary to evaluate the transmission potential of this species and the success of vector control interventions. Near-infrared spectroscopy (NIRS) has been used to estimate the age of mosquitoes in different conditions (laboratory, semi-field, and conservation), taxonomic analysis, and infection detection. However, no studies are using NIRS for sand flies.MethodsIn this study, we developed analytic models to estimate the age of L. longipalpis adults under laboratory conditions, identify their copulation state, and evaluate their gonotrophic cycle and diet.ResultsSand flies were classified with an accuracy of 58–82% in 3 age groups and 82–92% when separating them into young (<8 days) or old (>8 days) insects. The classification between mated and non-mated sandflies was 98–100% accurate, while the percentage of hits of females that had already passed the first gonotrophic cycle was only 59%.ConclusionsWe consider the age and copula estimation results very promising, as they provide essential aspects of vector capacity assessment, which can be obtained quickly and at a lower cost with NIRS.Graphical

Mosquito ageing modulates the development, virulence and transmission potential of pathogens.

Host age variation is a striking source of heterogeneity that can shape the evolution and transmission dynamic of pathogens. Compared with vertebrate systems, our understanding of the impact of host age on invertebrate-pathogen interactions remains limited. We examined the influence of mosquito age on key life-history traits driving human malaria transmission. Females of Anopheles coluzzii, a major malaria vector, belonging to three age classes (4-, 8- and 12-day-old), were experimentally infected with Plasmodium falciparum field isolates. Our findings revealed reduced competence in 12-day-old mosquitoes, characterized by lower oocyst/sporozoite rates and intensities compared with younger mosquitoes. Despite shorter median longevities in older age classes, infected 12-day-old mosquitoes exhibited improved survival, suggesting that the infection might act as a fountain of youth for older mosquitoes specifically. The timing of sporozoite appearance in the salivary glands remained consistent across mosquito age classes, with an extrinsic incubation period of approximately 13 days. Integrating these results into an epidemiological model revealed a lower vectorial capacity for older mosquitoes compared with younger ones, albeit still substantial owing to extended longevity in the presence of infection. Considering age heterogeneity provides valuable insights for ecological and epidemiological studies, informing targeted control strategies to mitigate pathogen transmission.

Evaluation of diffuse reflectance spectroscopy for predicting age, species, and cuticular resistance of Anopheles gambiae s.l under laboratory conditions

Mid-infrared spectroscopy (MIRS) combined with machine learning analysis has shown potential for quick and efficient identification of mosquito species and age groups. However, current technology to collect spectra is destructive to the sample and does not allow targeting specific tissues of the mosquito, limiting the identification of other important biological traits such as insecticide resistance. Here, we assessed the use of a non-destructive approach of MIRS for vector surveillance, micro diffuse reflectance spectroscopy (µDRIFT) using mosquito legs to identify species, age and cuticular insecticide resistance within the Anopheles gambiae s.l. complex. These mosquitoes are the major vectors of malaria in Africa and the focus on surveillance in malaria control programs. Legs required significantly less scanning time and showed more spectral consistence compared to other mosquito tissues. Machine learning models were able to identify An. gambiae and An. coluzzii with an accuracy of 0.73, two ages groups (3 and 10 days old) with 0.77 accuracy and we obtained accuracy of 0.75 when identifying cuticular insecticide resistance. Our results highlight the potential of different mosquito tissues and µDRIFT as tools for biological trait identification on mosquitoes that transmit malaria. These results can guide new ways of identifying mosquito traits which can help the creation of innovative surveillance programs by adapting new technology into mosquito surveillance and control tools.

Evaluation of ultra-low volume treatments on Culex quinquefasciatus (Diptera: Culicidae) abundance and relative age by parity dissection.

St. Tammany Parish Mosquito Abatement District relies on ultra-low volume (ULV) insecticides to manage adult Culex quinquefasciatus (Say 1823), the primary vector of West Nile virus in Louisiana, but abundance rarely declines post-treatment. Three field ULV applications each of adulticides containing deltamethrin, naled, or resmethrin were conducted from May through October 2022 to measure efficacy against free-flying Cx. quinquefasciatus. Female mosquitoes trapped before and after treatment were identified, counted, and age-graded by parity dissection. No insecticide applications reduced Cx. quinquefasciatus abundance, but trials with deltamethrin and naled significantly lowered average mosquito age in the area post-treatment. No trials with resmethrin reduced mosquito age, which corroborates laboratory susceptibility data indicating local resistance toward the pyrethroid. These trials establish parity dissections and relative age gradation as a means of measuring treatment success against Cx. quinquefasciatus.

Ultra-low volume (ULV) adulticide treatment impacts age structure of Culex species (Diptera: Culicidae) in a West Nile virus hotspot.

West Nile virus (WNV) invaded the continental United States over 20 years ago and continues to cause yearly seasonal outbreaks of human and veterinary disease. In the suburbs of Chicago, Illinois, ultra-low volume (ULV) truck-mounted adulticide spraying frequently is performed to reduce populations of Culex restuans Theobald and Cx. pipiens L. mosquitoes (Diptera: Culicidae) in an effort to lower the risk of WNV transmission. The effectiveness of this control method has not been rigorously evaluated, and evidence for Culex population reduction after ULV adulticide spraying has been inconclusive. Therefore, we evaluated the results of 5 sequential weekly truck-mounted adulticide applications of Zenivex® E20 (etofenprox) in 2 paired sites located in Cook County, IL, during the summer of 2018. Mosquito population abundance, age structure, and WNV infection prevalence were monitored and compared between paired treatment and nearby control sites. Adulticide treatment did not result in consistent short-term or long-term reductions in target WNV vector Culex abundance. However, there was a significant increase in the proportion of nulliparous females in the treated sites compared to control sites and a decrease in Cx. pipiens WNV infection rates at one of the treated sites. This evidence that ULV adulticide spraying altered the age structure and WNV infection prevalence in a vector population has important implications for WNV transmission risk management. Our findings also underscore the importance of measuring these important indicators in addition to abundance metrics when evaluating the efficacy of control methods.

Differences in Longevity and Temperature-Driven Extrinsic Incubation Period Correlate with Varying Dengue Risk in the Arizona-Sonora Desert Region.

Dengue transmission is determined by a complex set of interactions between the environment, Aedes aegypti mosquitoes, dengue viruses, and humans. Emergence in new geographic areas can be unpredictable, with some regions having established mosquito populations for decades without locally acquired transmission. Key factors such as mosquito longevity, temperature-driven extrinsic incubation period (EIP), and vector-human contact can strongly influence the potential for disease transmission. To assess how these factors interact at the edge of the geographical range of dengue virus transmission, we conducted mosquito sampling in multiple urban areas located throughout the Arizona-Sonora desert region during the summer rainy seasons from 2013 to 2015. Mosquito population age structure, reflecting mosquito survivorship, was measured using a combination of parity analysis and relative gene expression of an age-related gene, SCP-1. Bloodmeal analysis was conducted on field collected blood-fed mosquitoes. Site-specific temperature was used to estimate the EIP, and this predicted EIP combined with mosquito age were combined to estimate the abundance of "potential" vectors (i.e., mosquitoes old enough to survive the EIP). Comparisons were made across cities by month and year. The dengue endemic cities Hermosillo and Ciudad Obregon, both in the state of Sonora, Mexico, had higher abundance of potential vectors than non-endemic Nogales, Sonora, Mexico. Interestingly, Tucson, Arizona consistently had a higher estimated abundance of potential vectors than dengue endemic regions of Sonora, Mexico. There were no observed city-level differences in species composition of blood meals. Combined, these data offer insights into the critical factors required for dengue transmission at the ecological edge of the mosquito's range. However, further research is needed to integrate an understanding of how social and additional environmental factors constrain and enhance dengue transmission in emerging regions.

Rapid identification of mosquito species and age by mass spectrometric analysis

BackgroundA rapid, accurate method to identify and to age-grade mosquito populations would be a major advance in predicting the risk of pathogen transmission and evaluating the public health impact of vector control interventions. Whilst other spectrometric or transcriptomic methods show promise, current approaches rely on challenging morphological techniques or simple binary classifications that cannot identify the subset of the population old enough to be infectious. In this study, the ability of rapid evaporative ionisation mass spectrometry (REIMS) to identify the species and age of mosquitoes reared in the laboratory and derived from the wild was investigated.ResultsThe accuracy of REIMS in identifying morphologically identical species of the Anopheles gambiae complex exceeded 97% using principal component/linear discriminant analysis (PC-LDA) and 84% based on random forest analysis. Age separation into 3 different age categories (1 day, 5–6 days, 14–15 days) was achieved with 99% (PC-LDA) and 91% (random forest) accuracy. When tested on wild mosquitoes from the UK, REIMS data could determine the species and age of the specimens with accuracies of 91 and 90% respectively.ConclusionsThe accuracy of REIMS to resolve the species and age of Anopheles mosquitoes is comparable to that achieved by infrared spectroscopy approaches. The processing time and ease of use represent significant advantages over current, dissection-based methods. Importantly, the accuracy was maintained when using wild mosquitoes reared under differing environmental conditions, and when mosquitoes were stored frozen or desiccated. This high throughput approach thus has potential to conduct rapid, real-time monitoring of vector populations, providing entomological evidence of the impact of alternative interventions.

Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra

BackgroundOld mosquitoes are more likely to transmit malaria than young ones. Therefore, accurate prediction of mosquito population age can drastically improve the evaluation of mosquito-targeted interventions. However, standard methods for age-grading mosquitoes are laborious and costly. We have shown that Mid-infrared spectroscopy (MIRS) can be used to detect age-specific patterns in mosquito cuticles and thus can be used to train age-grading machine learning models. However, these models tend to transfer poorly across populations. Here, we investigate whether applying dimensionality reduction and transfer learning to MIRS data can improve the transferability of MIRS-based predictions for mosquito ages.MethodsWe reared adults of the malaria vector Anopheles arabiensis in two insectaries. The heads and thoraces of female mosquitoes were scanned using an attenuated total reflection-Fourier transform infrared spectrometer, which were grouped into two different age classes. The dimensionality of the spectra data was reduced using unsupervised principal component analysis or t-distributed stochastic neighbour embedding, and then used to train deep learning and standard machine learning classifiers. Transfer learning was also evaluated to improve transferability of the models when predicting mosquito age classes from new populations.ResultsModel accuracies for predicting the age of mosquitoes from the same population as the training samples reached 99% for deep learning and 92% for standard machine learning. However, these models did not generalise to a different population, achieving only 46% and 48% accuracy for deep learning and standard machine learning, respectively. Dimensionality reduction did not improve model generalizability but reduced computational time. Transfer learning by updating pre-trained models with 2% of mosquitoes from the alternate population improved performance to ~ 98% accuracy for predicting mosquito age classes in the alternative population.ConclusionCombining dimensionality reduction and transfer learning can reduce computational costs and improve the transferability of both deep learning and standard machine learning models for predicting the age of mosquitoes. Future studies should investigate the optimal quantities and diversity of training data necessary for transfer learning and the implications for broader generalisability to unseen datasets.

Relationships between biological age, distance from aquatic habitats and pyrethroid resistance status of Anopheles funestus mosquitoes in south-eastern Tanzania

BackgroundMalaria transmission can be highly heterogeneous between and within localities, and is influenced by factors such as survival and biting frequencies of Anopheles mosquitoes. This study investigated the relationships between the biological age, distance from aquatic habitats and pyrethroid resistance status of Anopheles funestus mosquitoes, which currently dominate malaria transmission in south-east Tanzania. The study also examined how such relationships may influence malaria transmission and control.MethodsFemale An. funestus were collected in houses located 50–100 m, 150–200 m or over 200 m from the nearest known aquatic habitats. The mosquitoes were exposed to 1×, 5× and 10× the diagnostic doses of deltamethrin or permethrin, or to the synergist, piperonyl butoxide (PBO) followed by the pyrethroids, then monitored for 24 h-mortality. Ovaries of exposed and non-exposed mosquitoes were dissected to assess parity as a proxy for biological age. Adults emerging from larval collections in the same villages were tested against the same insecticides at 3–5, 8–11 or 17–20 days old.FindingsMosquitoes collected nearest to the aquatic habitats (50-100 m) had the lowest mortalities compared to other distances, with a maximum of 51% mortality at 10× permethrin. For the age-synchronized mosquitoes collected as larvae, the insecticide-induced mortality assessed at both the diagnostic and multiplicative doses (1×, 5× and 10×) increased with mosquito age. The highest mortalities at 1× doses were observed among the oldest mosquitoes (17–20 days). At 10× doses, mortalities were 99% (permethrin) and 76% (deltamethrin) among 8–11 day-olds compared to 80% (permethrin) and 58% (deltamethrin) among 3–5 day-olds. Pre-exposure to PBO increased the potency of both pyrethroids. The proportion of parous females was highest among mosquitoes collected farthest from the habitats.ConclusionIn this specific setting, older An. funestus and those collected farthest from the aquatic habitats (near the centre of the village) were more susceptible to pyrethroids than the younger ones and those caught nearest to the habitats. These findings suggest that pyrethroid-based interventions may remain at least moderately effective despite widespread pyrethroid-resistance, by killing the older, less-resistant and potentially-infective mosquitoes. Further studies should investigate how and whether these observations could be exploited to optimize malaria control in different settings.

Back to the Future: Quantifying Wing Wear as a Method to Measure Mosquito Age.

Vector biologists have long sought the ability to accurately quantify the age of wild mosquito populations, a metric used to measure vector control efficiency. This has proven difficult due to the difficulties of working in the field and the biological complexities of wild mosquitoes. Ideal age grading techniques must overcome both challenges while also providing epidemiologically relevant age measurements. Given these requirements, the Detinova parity technique, which estimates age from the mosquito ovary and tracheole skein morphology, has been most often used for mosquito age grading despite significant limitations, including being based solely on the physiology of ovarian development. Here, we have developed a modernized version of the original mosquito aging method that evaluated wing wear, expanding it to estimate mosquito chronological age from wing scale loss. We conducted laboratory experiments using adult Anopheles gambiae held in insectary cages or mesocosms, the latter of which also featured ivermectin bloodmeal treatments to change the population age structure. Mosquitoes were age graded by parity assessments and both human- and computational-based wing evaluations. Although the Detinova technique was not able to detect differences in age population structure between treated and control mesocosms, significant differences were apparent using the wing scale technique. Analysis of wing images using averaged left- and right-wing pixel intensity scores predicted mosquito age at high accuracy (overall test accuracy: 83.4%, average training accuracy: 89.7%). This suggests that this technique could be an accurate and practical tool for mosquito age grading though further evaluation in wild mosquito populations is required.

Response of male adult Aedes mosquitoes to gamma radiation in different nitrogen environments.

The developmental stage of the mosquito is one of the main factors that affect its response to ionizing radiation. Irradiation of adults has been reported to have beneficial effects. However, the main challenge is to immobilize and compact a large number of adult male mosquitoes for homogenous irradiation with minimal deleterious effects on their quality. The present study investigates the use of nitrogen in the irradiation of adult Aedes albopictus and Ae. aegypti. Irradiation in nitrogen (N2) and in air after being treated with nitrogen (PreN2) were compared with irradiation in air at gamma radiation doses of 0, 55, 70, 90, 110, and 125 Gy. In both species, approximately 0% egg hatch rate was observed following doses above 55 Gy in air versus 70 Gy in PreN2 and 90 Gy in N2. Males irradiated at a high mosquito density showed similar egg hatch rates as those irradiated at a low density. Nitrogen treatments showed beneficial effects on the longevity of irradiated males for a given dose, revealing the radioprotective effect of anoxia. However, irradiation in N2 or PreN2 slightly reduced the male flight ability. Nitrogen treatment was found to be a reliable method for adult mosquito immobilization. Overall, our results demonstrated that nitrogen may be useful in adult Aedes mass irradiation. The best option seems to be PreN2 since it reduces the immobilization duration and requires a lower dose than that required in the N2 environment to achieve full sterility but with similar effects on male quality. However, further studies are necessary to develop standardized procedures including containers, time and pressure for flushing with nitrogen, immobilization duration considering mosquito species, age, and density.

Determinant Factors Related to the Event of Dengue Hemorrhagic Fever (DHF) in the Work Area of Payung Sekaki Health Center, Pekanbaru Regency

Dengue hemorrhagic fever (DHF) or dengue hemorrhagic fever (DHF) is currently one of the public health problems in Pekanbaru, Riau. The research design is an Unmatched Case Control Study. The case population is all DHF sufferers from 2019-2021, totaling 194 people and the control population is all non-DHF cases in the same period when DHF occurred in 2019-2-2021, totaling 7,624 people. The number of samples is 180 cases and 180 controls. Data were analyzed by univariate, bivariate and multivariate. The results of multivariate analysis, the most influential variables were the habit of hanging clothes (95% CI = 2,970-8,557), the use of repellents during the day (95% CI = 2,272-6,307), knowledge about dengue transmission (95% CI = 2,108-5,892), presence of larvae (CI 95% = 1.716-4.760), sleep during the day (95% CI = 1.699-4.699). The determinant factors related to the incidence of Dengue Hemorrhagic Fever (DHF ) in the Working Area of the Payung Sekaki Health Center are the presence of larvae, daytime sleep habits, hanging clothes habits, daytime use of repellants and knowledge of dengue transmission. While mosquito repellent plants, education, age and gender. It is recommended that the Health Center conduct health education so that people do not hang clothes that have been used, use repellents during the day, do 3M (closing water reservoirs, draining bathtubs, burying), not sleeping during the day and if sleeping during the day need to use tools or mosquito repellent.

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

BackgroundMonitoring 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.MethodsLaboratory-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.ResultsThe 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.ConclusionsWhen 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.Graphical

Standardization of the FAO/IAEA Flight Test for Quality Control of Sterile Mosquitoes.

Successful implementation of the sterile insect technique (SIT) against Aedes aegypti and Aedes albopictus relies on maintaining a consistent release of high-quality sterile males. Affordable, rapid, practical quality control tools based on the male’s flight ability (ability to escape from a flight device) may contribute to meeting this requirement. Therefore, this study aims to standardize the use of the original FAO/IAEA rapid quality control flight test device (FTD) (version 1.0), while improving handling conditions and reducing the device’s overall cost by assessing factors that could impact the subsequent flight ability of Aedes mosquitoes. The new FTD (version 1.1) is easier to use. The most important factors affecting escape rates were found to be tube color (or “shade”), the combined use of a lure and fan, mosquito species, and mosquito age and density (25; 50; 75; 100 males). Other factors measured but found to be less important were the duration of the test (30, 60, 90, 120 min), fan speed (normal 3000 rpm vs. high 6000 rpm), and mosquito strain origin. In addition, a cheaper version of the FTD (version 2.0) that holds eight individual tubes instead of 40 was designed and successfully validated against the new FTD (version 1.1). It was sensitive enough to distinguish between the effects of cold stress and high irradiation dose. Therefore, the eight-tube FTD may be used to assess Aedes’ flight ability. This study demonstrated that the new designs (versions 1.1 and 2.0) of the FTD could be used for standard routine quality assessments of Aedes mosquitoes required for an SIT and other male release-based programs.

Estimating female malaria mosquito age by quantifying Y-linked genes in stored male spermatozoa

Vector control strategies are among the most effective measures to combat mosquito-borne diseases, such as malaria. These strategies work by altering the mosquito age structure through increased mortality of the older female mosquitoes that transmit pathogens. However, methods to monitor changes to mosquito age structure are currently inadequate for programmatic implementation. Female mosquitoes generally mate a single time soon after emergence and draw down spermatozoa reserves with each oviposition cycle. Here, we demonstrate that measuring spermatozoa quantity in female Anopheles mosquitoes is an effective approach to assess mosquito age. Using multiplexed qPCR targeted at male spermatozoa, we show that Y-linked genes in female mosquitoes are exclusively found in the spermatheca, the organ that houses spermatozoa, and the quantity of these gene sequences significantly declines with age. The method can accurately identify mosquitoes more than 10 days old and thus old enough to potentially transmit pathogens harbored in the salivary glands during blood feeding. Furthermore, mosquito populations that differ by 10% in daily survivorship have a high likelihood of being distinguished using modest sample sizes, making this approach scalable for assessing the efficacy of vector intervention control programs.