Genetic markers associated with the widespread insecticide resistance in malaria vector Anopheles funestus populations across Tanzania.

BACKGROUND: Anopheles funestus is a leading vector of malaria in most parts of East and Southern Africa, yet its ecology and responses to vector control remain poorly understood compared with other vectors such as Anopheles gambiae and Anopheles arabiensis. This study presents the first large-scale survey of the genetic and phenotypic expression of insecticide resistance in An. funestus populations in Tanzania. METHODS: We performed insecticide susceptibility bioassays on An. funestus mosquitoes in nine regions with moderate-to-high malaria prevalence in Tanzania, followed by genotyping for resistance-associated mutations (CYP6P9a, CYP6P9b, L119F-GSTe2) and structural variants (SV4.3 kb, SV6.5 kb). Generalized linear models were used to assess relationships between genetic markers and phenotypic resistance. An interactive R Shiny tool was created to visualize the data and support evidence-based interventions. RESULTS: Pyrethroid resistance was universal but reversible by piperonyl-butoxide (PBO). However, carbamate resistance was observed in only five of the nine districts, and dichloro-diphenyl-trichloroethane (DDT) resistance was found only in the Kilombero valley, south-eastern Tanzania. Conversely, there was universal susceptibility to the organophosphate pirimiphos-methyl in all sites. Genetic markers of resistance had distinct geographical patterns, with CYP6P9a-R and CYP6P9b-R alleles, and the SV6.5 kb structural variant absent or undetectable in the north-west but prevalent in all other sites, while SV4.3 kb was prevalent in the north-western and western regions but absent elsewhere. Emergent L119F-GSTe2, associated with deltamethrin resistance, was detected in heterozygous form in districts bordering Mozambique, Malawi and the Democratic Republic of Congo. The resistance landscape was most complex in western Tanzania, in Tanganyika district, where all five genetic markers were detected. There was a notable south-to-north spread of resistance genes, especially CYP6P9a-R, though this appears to be interrupted, possibly by the Rift Valley. CONCLUSIONS: This study underscores the need to expand resistance monitoring to include An. funestus alongside other vector species, and to screen for both the genetic and phenotypic signatures of resistance. The findings can be visualized online via an interactive user interface and could inform data-driven decision-making for resistance management and vector control. Since this was the first large-scale survey of resistance in Tanzania's An. funestus, we recommend regular updates with greater geographical and temporal coverage.

Behaviour and distribution of Aedes aegypti mosquitoes and their relation to dengue incidence in two transmission hotspots in coastal Ecuador.

BACKGROUND: Dengue (DENV) transmission is endemic throughout coastal Ecuador, showing heterogeneous incidence patterns in association with fine-scale variation in Aedes aegypti vector populations and other factors. Here, we investigated the impact of micro-climate and neighbourhood-level variation in urbanization on Aedes abundance, resting behaviour and associations with dengue incidence in two endemic areas. METHODOLOGY/PRINCIPAL FINDINGS: Aedes aegypti were collected in Quinindé and Portoviejo, two urban cantons with hyperendemic dengue transmission in coastal Ecuador. Aedes vectors were sampled in and around houses within urban and peri-urban neighbourhoods at four time periods. We tested for variation in vector abundance and resting behaviour in relation to neighbourhood urbanization level and microclimatic factors. Aedes abundance increased towards the end of the rainy season, was significantly higher in Portoviejo than in Quinindé, and in urban than in peri-urban neighbourhoods. Aedes vectors were more likely to rest inside houses in Portoviejo but had similar abundance in indoor and outdoor resting collections in Quinindé. Over the study period, DENV incidence was lower in Quinindé than in Portoviejo. Relationships between weekly Ae. aegypti abundance and DENV incidence were highly variable between trapping methods; with positive associations being detected only between BG-sentinel and outdoor Prokopack collections. CONCLUSIONS/SIGNIFICANCE: Aedes aegypti abundance was significantly higher in urban than peri-urban neighbourhoods, and their resting behaviour varied between study sites. This fine-scale spatial heterogeneity in Ae. aegypti abundance and behaviour could generate site-specific variation in human exposure and the effectiveness of indoor-based interventions. The trap-dependent nature of associations between Aedes abundance and local DENV incidence indicates further work is needed to identify robust entomological indicators of infection risk.

Geospatial modelling of dry season habitats of the malaria vector, Anopheles funestus, in south-eastern Tanzania.

BACKGROUND: Anopheles funestus is a major malaria vector in Eastern and Southern Africa and is currently the dominant malaria-transmitting vector in many parts of Tanzania. Previous research has identified its preference for specific aquatic habitats, especially those that persist in dry months. This observation suggests the potential for targeted control through precise habitat mapping and characterization. In this study, we investigated the influence of habitat characteristics, land cover and human population densities on An. funestus distribution during dry seasons. Based on the results, we developed a habitat suitability model for this vector species in south-eastern Tanzania. METHODS: Eighteen villages in south-eastern Tanzania were surveyed during the dry season from September-December 2021. Water bodies were systematically inspected for mosquito larvae and characterized by their physico-chemical characteristics and surrounding environmental features. A generalized linear model was used to assess the presence of An. funestus larvae as a function of the physico-chemical characteristics, land use and human population densities. The results obtained from this model were used to generate spatially explicit predictions of habitat suitability in the study districts. RESULTS: Of the 1466 aquatic habitats surveyed, 440 were positive for An. funestus, with river streams having the highest positivity (74%; n = 322) followed by ground pools (15%; n = 67). The final model had an 83% accuracy in predicting positive An. funestus habitats, with the most important characteristics being permanent waters, clear waters with or without vegetation or movement and shading over the habitats. There was also a positive association of An. funestus presence with forested areas and a negative association with built-up areas. Human population densities had no influence on An. funestus distribution. CONCLUSIONS: The results of this study underscore the crucial role of both the specific habitat characteristics and key environmental factors, notably land cover, in the distribution of An. funestus. In this study area, An. funestus predominantly inhabits river streams and ground pools, with a preference for clear, perennial waters with shading. The strong positive association with more pristine environments with tree covers and the negative association with built-up areas underscore the importance of ecological transitions in vector distribution and malaria transmission risk. Such spatially explicit predictions could enable more precise interventions, particularly larval source management, to accelerate malaria control.

Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis.

Studies on the applications of infrared (IR) spectroscopy and machine learning (ML) in public health have increased greatly in recent years. These technologies show enormous potential for measuring key parameters of malaria, a disease that still causes about 250 million cases and 620,000 deaths, annually. Multiple studies have demonstrated that the combination of IR spectroscopy and machine learning (ML) can yield accurate predictions of epidemiologically relevant parameters of malaria in both laboratory and field surveys. Proven applications now include determining the age, species, and blood-feeding histories of mosquito vectors as well as detecting malaria parasite infections in both humans and mosquitoes. As the World Health Organization encourages malaria-endemic countries to improve their surveillance-response strategies, it is crucial to consider whether IR and ML techniques are likely to meet the relevant feasibility and cost-effectiveness requirements-and how best they can be deployed. This paper reviews current applications of IR spectroscopy and ML approaches for investigating malaria indicators in both field surveys and laboratory settings, and identifies key research gaps relevant to these applications. Additionally, the article suggests initial target product profiles (TPPs) that should be considered when developing or testing these technologies for use in low-income settings.

A novel tetra-primer ARMS-PCR approach for the molecular karyotyping of chromosomal inversion 2Ru in the main malaria vectors Anopheles gambiae and Anopheles coluzzii.

BACKGROUND: Chromosomal inversion polymorphisms have been associated with adaptive behavioral, physiological, morphological and life history traits in the two main Afrotropical malaria vectors, Anopheles coluzzii and Anopheles gambiae. The understanding of the adaptive value of chromosomal inversion systems is constrained by the feasibility of cytological karyotyping. In recent years in silico and molecular approaches have been developed for the genotyping of most widespread inversions (2La, 2Rb and 2Rc). The 2Ru inversion, spanning roughly 8% of chromosome 2R, is commonly polymorphic in West African populations of An. coluzzii and An. gambiae and shows clear increases in frequency with increasing rainfall seasonally and geographically. The aim of this work was to overcome the constraints of currently available cytological and high-throughput molecular assays by developing a simple PCR assay for genotyping the 2Ru inversion in individual specimens of both mosquito species. METHODS: We designed tetra-primer amplification refractory mutation system (ARMS)-PCR assays based on five tag single-nucleotide polymorphisms (SNPs) previously shown to be strongly correlated with 2Ru inversion orientation. The most promising assay was validated against laboratory and field samples of An. coluzzii and An. gambiae karyotyped either cytogenetically or molecularly using a genotyping-in-thousands by sequencing (GT-seq) high-throughput approach that employs targeted sequencing of multiplexed PCR amplicons. RESULTS: A successful assay was designed based on the tag SNP at position 2R, 31710303, which is highly predictive of the 2Ru genotype. The assay, which requires only one PCR, and no additional post-PCR processing other than electrophoresis, produced a clear banding pattern for 98.5% of the 454 specimens tested, which is a 96.7% agreement with established karyotyping methods. Sequences were obtained for nine of the An. coluzzii specimens manifesting 2Ru genotype discrepancies with GT-seq. Possible sources of these discordances are discussed. CONCLUSIONS: The tetra-primer ARMS-PCR assay represents an accurate, streamlined and cost-effective method for the molecular karyotyping of the 2Ru inversion in An. coluzzii and An. gambiae. Together with approaches already available for the other common polymorphic inversions, 2La, 2Rb and 2Rc, this assay will allow investigations of the adaptive value of the complex set of inversion systems observed in the two major malaria vectors in the Afrotropical region.

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.

Heritability of biting time behaviours in the major African malaria vector Anopheles arabiensis.

BACKGROUND: The use of insecticide-treated nets for malaria control has been associated with shifts in mosquito vector feeding behaviour including earlier and outdoor biting on humans. The relative contribution of phenotypic plasticity and heritability to these behavioural shifts is unknown. Elucidation of the mechanisms behind these shifts is crucial for anticipating impacts on vector control. METHODS: A novel portable semi-field system (PSFS) was used to experimentally measure heritability of biting time in the malaria vector Anopheles arabiensis in Tanzania. Wild An. arabiensis from hourly collections using the human landing catch (HLC) method were grouped into one of 3 categories based on their time of capture: early (18:00-21:00), mid (22:00-04:00), and late (05:00-07:00) biting, and placed in separate holding cages. Mosquitoes were then provided with a blood meal for egg production and formation of first filial generation (F1). The F1 generation of each biting time phenotype category was reared separately, and blood fed at the same time as their mothers were captured host-seeking. The resultant eggs were used to generate the F2 generation for use in heritability assays. Heritability was assessed by releasing F2 An. arabiensis into the PSFS, recording their biting time during a human landing catch and comparing it to that of their F0 grandmothers. RESULTS: In PSFS assays, the biting time of F2 offspring (early: 18:00-21:00, mid: 22:00-04:00 or late: 05:00-07:00) was significantly positively associated with that of their wild-caught F0 grandmothers, corresponding to an estimated heritability of 0.110 (95% CI 0.003, 0.208). F2 from early-biting F0 were more likely to bite early than F2 from mid or late-biting F0. Similarly, the probability of biting late was higher in F2 derived from mid and late-biting F0 than from early-biting F0. CONCLUSIONS: Despite modest heritability, our results suggest that some of the variation in biting time is attributable to additive genetic variation. Selection can, therefore, act efficiently on mosquito biting times, highlighting the need for control methods that target early and outdoor biting mosquitoes.

Advances in the genetic characterization of the malaria vector, Anopheles funestus, and implications for improved surveillance and control.

Anopheles mosquitoes present a major public health challenge in sub-Saharan Africa; notably, as vectors of malaria that kill over half a million people annually. In parts of the east and southern Africa region, one species in the Funestus group, Anopheles funestus, has established itself as an exceptionally dominant vector in some areas, it is responsible for more than 90% of all malaria transmission events. However, compared to other malaria vectors, the species is far less studied, partly due to difficulties in laboratory colonization and the unresolved aspects of its taxonomy and systematics. Control of An. funestus is also increasingly difficult because it has developed widespread resistance to public health insecticides. Fortunately, recent advances in molecular techniques are enabling greater insights into species identity, gene flow patterns, population structure, and the spread of resistance in mosquitoes. These advances and their potential applications are reviewed with a focus on four research themes relevant to the biology and control of An. funestus in Africa, namely: (i) the taxonomic characterization of different vector species within the Funestus group and their role in malaria transmission; (ii) insecticide resistance profile; (iii) population genetic diversity and gene flow, and (iv) applications of genetic technologies for surveillance and control. The research gaps and opportunities identified in this review will provide a basis for improving the surveillance and control of An. funestus and malaria transmission in Africa.

Spatial dynamics of malaria transmission.

The Ross-Macdonald model has exerted enormous influence over the study of malaria transmission dynamics and control, but it lacked features to describe parasite dispersal, travel, and other important aspects of heterogeneous transmission. Here, we present a patch-based differential equation modeling framework that extends the Ross-Macdonald model with sufficient skill and complexity to support planning, monitoring and evaluation for Plasmodium falciparum malaria control. We designed a generic interface for building structured, spatial models of malaria transmission based on a new algorithm for mosquito blood feeding. We developed new algorithms to simulate adult mosquito demography, dispersal, and egg laying in response to resource availability. The core dynamical components describing mosquito ecology and malaria transmission were decomposed, redesigned and reassembled into a modular framework. Structural elements in the framework-human population strata, patches, and aquatic habitats-interact through a flexible design that facilitates construction of ensembles of models with scalable complexity to support robust analytics for malaria policy and adaptive malaria control. We propose updated definitions for the human biting rate and entomological inoculation rates. We present new formulas to describe parasite dispersal and spatial dynamics under steady state conditions, including the human biting rates, parasite dispersal, the "vectorial capacity matrix," a human transmitting capacity distribution matrix, and threshold conditions. An [Formula: see text] package that implements the framework, solves the differential equations, and computes spatial metrics for models developed in this framework has been developed. Development of the model and metrics have focused on malaria, but since the framework is modular, the same ideas and software can be applied to other mosquito-borne pathogen systems.

Comparative evaluation of different versions of exposure-free mosquito electrocuting traps and barrier screen trap for monitoring outdoor densities and biting time phenotypes by malaria and filariasis vectors in Tanzania.

BACKGROUND: Estimating human exposure to mosquito vectors is crucial for the prediction of malaria transmission and intervention impact. The human landing catch method is frequently used to directly measure estimate exposure rates; however, there has been an increasing shift from this method to exposure-free alternatives, such as the mosquito electrocuting traps (MET) and other approaches. While these latter methods can provide robust and representative values of human exposure and mosquito density, they often still require a human volunteer, which poses logistical challenges. Additionally, in the case of the MET, the early MET prototype (METe) required human volunteers to wear protective clothing that could be uncomfortable. We investigated two alternative trapping approaches to address these challenges by comparing the performance of the METe prototype to: (i) a modified caged MET prototype that offers full protection to users (METc) and (ii) a barrier screen trap (BST) designed to passively sample (host-seeking and blood-fed) mosquitoes outdoors without requiring a human participant. METHODS: The relative performance of the METe, METc and BST were evaluated in a 3 × 3 Latin square field experiment design conducted in south-eastern Tanzania over 12 nights of sampling. The outcomes of interest were the nightly catch of mosquitoes and biting time estimates. RESULTS: The METc and BST caught similar numbers of An. arabiensis as the METe (relative ratio [RR] = 0.76, 95% confidence interval [CI]: 0.42-1.39, P = 0.38 and RR = 1.13, 95% CI: 0.63-2.04, P = 0.69, respectively). Similarly, the METc and BST caught similar numbers of Culex spp. as the METe (RR = 0.87, 95% CI: 0.62-1.22, P = 0.42 and RR = 0.80, 95% CI: 0.57-1.12, P = 0.199, respectively). All three trapping methods indicated a similar pattern of biting activity by An. arabiensis and Culex spp., characterized by biting starting in the early evening (18:00-22:00), peaking when people are typically sleeping (22:00-05:00) and dropping off drastically toward the morning (05:00-07:00). CONCLUSIONS: The modifications made to the METe design to improve user comfort and remove the need for protective clothing did not result in an underestimation of mosquito vector abundance nor misrepresentation of their biting time pattern. We recommend the METc for use over the METe design. Similarly, the BST demonstrated potential for monitoring malaria and filariasis vector densities in Tanzania.

A statistical calibration tool for methods used to sample outdoor-biting mosquitoes.

BACKGROUND: Improved methods for sampling outdoor-biting mosquitoes are urgently needed to improve surveillance of vector-borne diseases. Such tools could potentially replace the human landing catch (HLC), which, despite being the most direct option for measuring human exposures, raises significant ethical and logistical concerns. Several alternatives are under development, but detailed evaluation still requires common frameworks for calibration relative to HLC. The aim of this study was to develop and validate a statistical framework for predicting human-biting rates from different exposure-free alternatives. METHODS: We obtained mosquito abundance data (Anopheles arabiensis, Anopheles funestus and Culex spp.) from a year-long Tanzanian study comparing six outdoor traps [Suna Trap (SUN), BG Sentinel (BGS), M-Trap (MTR), M-Trap + CDC (MTRC), Ifakara Tent Trap-C (ITT-C) and Mosquito Magnet-X Trap (MMX)] and HLC. Generalised linear models were developed within a Bayesian framework to investigate associations between the traps and HLC, taking intra- and inter-specific density dependence into account. The best model was used to create a calibration tool for predicting HLC-equivalents. RESULTS: For An. arabiensis, SUN catches had the strongest correlation with HLC (R2 = 19.4), followed by BGS (R2 = 17.2) and MTRC (R2 = 13.1) catches. The least correlated catch was MMX (R2 = 2.5). For An. funestus, BGS had the strongest correlation with the HLC (R2 = 53.4), followed by MTRC (R2 = 37.4) and MTR (R2 = 37.4). For Culex mosquitoes, the traps most highly correlated with the HLC were MTR (R2 = 45.4) and MTRC (R2 = 44.2). Density dependence, both between and within species, influenced the performance of only BGS traps. An interactive Shiny App calibration tool was developed for this and similar applications. CONCLUSION: We successfully developed a calibration tool to assess the performance of different traps for assessing outdoor-biting risk, and established a valuable framework for estimating human exposures based on the trap catches. The performance of candidate traps varied between mosquito taxa; thus, there was no single optimum. Although all the traps tested underestimated the HLC-derived exposures, it was possible to mathematically define their representativeness of the true biting risk, with or without density dependence. The results of this study emphasise the need to aim for a consistent and representative sampling approach, as opposed to simply seeking traps that catch the most mosquitoes.

Using Bayesian state-space models to understand the population dynamics of the dominant malaria vector, Anopheles funestus in rural Tanzania.

BACKGROUND: It is often assumed that the population dynamics of the malaria vector Anopheles funestus, its role in malaria transmission and the way it responds to interventions are similar to the more elaborately characterized Anopheles gambiae. However, An. funestus has several unique ecological features that could generate distinct transmission dynamics and responsiveness to interventions. The objectives of this work were to develop a model which will: (1) reconstruct the population dynamics, survival, and fecundity of wild An. funestus populations in southern Tanzania, (2) quantify impacts of density dependence on the dynamics, and (3) assess seasonal fluctuations in An. funestus demography. Through quantifying the population dynamics of An. funestus, this model will enable analysis of how their stability and response to interventions may differ from that of An. gambiae sensu lato. METHODS: A Bayesian State Space Model (SSM) based on mosquito life history was fit to time series data on the abundance of female An. funestus sensu stricto collected over 2 years in southern Tanzania. Prior values of fitness and demography were incorporated from empirical data on larval development, adult survival and fecundity from laboratory-reared first generation progeny of wild caught An. funestus. The model was structured to allow larval and adult fitness traits to vary seasonally in response to environmental covariates (i.e. temperature and rainfall), and for density dependency in larvae. The effects of density dependence and seasonality were measured through counterfactual examination of model fit with or without these covariates. RESULTS: The model accurately reconstructed the seasonal population dynamics of An. funestus and generated biologically-plausible values of their survival larval, development and fecundity in the wild. This model suggests that An. funestus survival and fecundity annual pattern was highly variable across the year, but did not show consistent seasonal trends either rainfall or temperature. While the model fit was somewhat improved by inclusion of density dependence, this was a relatively minor effect and suggests that this process is not as important for An. funestus as it is for An. gambiae populations. CONCLUSION: The model's ability to accurately reconstruct the dynamics and demography of An. funestus could potentially be useful in simulating the response of these populations to vector control techniques deployed separately or in combination. The observed and simulated dynamics also suggests that An. funestus could be playing a role in year-round malaria transmission, with any apparent seasonality attributed to other vector species.

Using ecological observations to improve malaria control in areas where Anopheles funestus is the dominant vector.

The most important malaria vectors in sub-Saharan Africa are Anopheles gambiae, Anopheles arabiensis, Anopheles funestus, and Anopheles coluzzii. Of these, An. funestus presently dominates in many settings in east and southern Africa. While research on this vector species has been impeded by difficulties in creating laboratory colonies, available evidence suggests it has certain ecological vulnerabilities that could be strategically exploited to greatly reduce malaria transmission in areas where it dominates. This paper examines the major life-history traits of An. funestus, its aquatic and adult ecologies, and its responsiveness to key interventions. It then outlines a plausible strategy for reducing malaria transmission by the vector and sustaining the gains over the medium to long term. To illustrate the propositions, the article uses data from south-eastern Tanzania where An. funestus mediates over 85% of malaria transmission events and is highly resistant to key public health insecticides, notably pyrethroids. Both male and female An. funestus rest indoors and the females frequently feed on humans indoors, although moderate to high degrees of zoophagy can occur in areas with large livestock populations. There are also a few reports of outdoor-biting by the species, highlighting a broader range of behavioural phenotypes that can be considered when designing new interventions to improve vector control. In comparison to other African malaria vectors, An. funestus distinctively prefers permanent and semi-permanent aquatic habitats, including river streams, ponds, swamps, and spring-fed pools. The species is therefore well-adapted to sustain its populations even during dry months and can support year-round malaria transmission. These ecological features suggest that highly effective control of An. funestus could be achieved primarily through strategic combinations of species-targeted larval source management and high quality insecticide-based methods targeting adult mosquitoes in shelters. If done consistently, such an integrated strategy has the potential to drastically reduce local populations of An. funestus and significantly reduce malaria transmission in areas where this vector species dominates. To sustain the gains, the programmes should be complemented with gradual environmental improvements such as house modification to maintain biting exposure at a bare minimum, as well as continuous engagements of the resident communities and other stakeholders.

Exposure of Primate Reservoir Hosts to Mosquito Vectors in Malaysian Borneo.

Several vector-borne pathogens of primates have potential for human spillover. An example is the simian malaria Plasmodium knowlesi which is now a major public health problem in Malaysia. Characterization of exposure to mosquito vectors is essential for assessment of the force of infection within wild simian populations, however few methods exist to do so. Here we demonstrate the use of thermal imaging and mosquito magnet independence traps (MMIT) to assess the abundance, diversity and infection rates in mosquitoes host seeking near long-tailed macaque (Macaca fasicularis) sleeping sites in the Lower Kinabatangan Wildlife Sanctuary, Malaysian Borneo. The primary Plasmodium knowlesi vector, Anopheles balabacensis, was trapped at higher abundance near sleeping sites than control trees. Although none of the An. balabacensis collected (n = 15) were positive for P. knowlesi by PCR screening, two were infected with another simian malaria Plasmodium inui. Analysis of macaque stools from sleeping sites confirmed a high prevalence of Plasmodium infection, suspected to be P. inui. Recently, natural transmission of P. inui has been detected in humans and An. cracens in Peninsular Malaysia. The presence of P. inui in An. balabacensis here and previously in human-biting collections highlight its potential for spillover from macaques to humans in Sabah. We advocate the use of MMITs for non-invasive sampling of mosquito vectors that host seek on wild simian populations.

Rapid age-grading and species identification of natural mosquitoes for malaria surveillance.

The malaria parasite, which is transmitted by several Anopheles mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of mosquito vectors. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We present a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquito cuticle that simultaneously identifies the species and age class of three main malaria vectors in natural populations. Using spectra from over 40, 000 ecologically and genetically diverse An. gambiae, An. arabiensis, and An. coluzzii females, we develop a deep transfer learning model that learns and predicts the age of new wild populations in Tanzania and Burkina Faso with minimal sampling effort. Additionally, the model is able to detect the impact of simulated control interventions on mosquito populations, measured as a shift in their age structures. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.

A protocol for a longitudinal, observational cohort study of infection and exposure to zoonotic and vector-borne diseases across a land-use gradient in Sabah, Malaysian Borneo: a socio-ecological systems approach.

Introduction. Landscape changes disrupt environmental, social and biological systems, altering pathogen spillover and transmission risks. This study aims to quantify the impact of specific land management practices on spillover and transmission rates of zoonotic and vector-borne diseases within Malaysian Borneo. This protocol describes a cohort study with integrated ecological sampling to assess how deforestation and agricultural practices impact pathogen flow from wildlife and vector populations to human infection and detection by health facilities. This will focus on malaria, dengue and emerging arboviruses (Chikungunya and Zika), vector-borne diseases with varying contributions of simian reservoirs within this setting. Methods. A prospective longitudinal observational cohort study will be established in communities residing or working within the vicinity of the Stability of Altered Forest Ecosystems (SAFE) Project, a landscape gradient within Malaysian Borneo encompassing different plantation and forest types. The primary outcome of this study will be transmission intensity of selected zoonotic and vector-borne diseases, as quantified by changes in pathogen-specific antibody levels. Exposure will be measured using paired population-based serological surveys conducted at the beginning and end of the two-year cohort study. Secondary outcomes will include the distribution and infection rates of Aedes and Anopheles mosquito vectors, human risk behaviours and clinical cases reported to health facilities. Longitudinal data on human behaviour, contact with wildlife and GPS tracking of mobility patterns will be collected throughout the study period. This will be integrated with entomological surveillance to monitor densities and pathogen infection rates of Aedes and Anopheles mosquitoes relative to land cover. Within surrounding health clinics, continuous health facility surveillance will be used to monitor reported infections and febrile illnesses. Models will be developed to assess spillover and transmission rates relative to specific land management practices and evaluate abilities of surveillance systems to capture these risks.

Wild populations of malaria vectors can mate both inside and outside human dwellings.

BACKGROUND: Wild populations of Anopheles mosquitoes are generally thought to mate outdoors in swarms, although once colonized, they also mate readily inside laboratory cages. This study investigated whether the malaria vectors Anopheles funestus and Anopheles arabiensis can also naturally mate inside human dwellings. METHOD: Mosquitoes were sampled from three volunteer-occupied experimental huts in a rural Tanzanian village at 6:00 p.m. each evening, after which the huts were completely sealed and sampling was repeated at 11:00 p.m and 6 a.m. the next morning to compare the proportions of inseminated females. Similarly timed collections were done inside local unsealed village houses. Lastly, wild-caught larvae and pupae were introduced inside or outside experimental huts constructed inside two semi-field screened chambers. The huts were then sealed and fitted with exit traps, allowing mosquito egress but not entry. Mating was assessed in subsequent days by sampling and dissecting emergent adults caught indoors, outdoors and in exit traps. RESULTS: Proportions of inseminated females inside the experimental huts in the village increased from approximately 60% at 6 p.m. to approximately 90% the following morning despite no new mosquitoes entering the huts after 6 p.m. Insemination in the local homes increased from approximately 78% to approximately 93% over the same time points. In the semi-field observations of wild-caught captive mosquitoes, the proportions of inseminated An. funestus were 20.9% (95% confidence interval [CI]: ± 2.8) outdoors, 25.2% (95% CI: ± 3.4) indoors and 16.8% (± 8.3) in exit traps, while the proportions of inseminated An. arabiensis were 42.3% (95% CI: ± 5.5) outdoors, 47.4% (95% CI: ± 4.7) indoors and 37.1% (CI: ± 6.8) in exit traps. CONCLUSION: Wild populations of An. funestus and An. arabiensis in these study villages can mate both inside and outside human dwellings. Most of the mating clearly happens before the mosquitoes enter houses, but additional mating happens indoors. The ecological significance of such indoor mating remains to be determined. The observed insemination inside the experimental huts fitted with exit traps and in the unsealed village houses suggests that the indoor mating happens voluntarily even under unrestricted egress. These findings may inspire improved vector control, such as by targeting males indoors, and potentially inform alternative methods for colonizing strongly eurygamic Anopheles species (e.g. An. funestus) inside laboratories or semi-field chambers.

The vectors of Plasmodium knowlesi and other simian malarias Southeast Asia: challenges in malaria elimination.

Plasmodium knowlesi, a simian malaria parasite of great public health concern has been reported from most countries in Southeast Asia and exported to various countries around the world. Currently P. knowlesi is the predominant species infecting humans in Malaysia. Besides this species, other simian malaria parasites such as P. cynomolgi and P. inui are also infecting humans in the region. The vectors of P. knowlesi and other Asian simian malarias belong to the Leucosphyrus Group of Anopheles mosquitoes which are generally forest dwelling species. Continual deforestation has resulted in these species moving into forest fringes, farms, plantations and human settlements along with their macaque hosts. Limited studies have shown that mosquito vectors are attracted to both humans and macaque hosts, preferring to bite outdoors and in the early part of the night. We here review the current status of simian malaria vectors and their parasites, knowledge of vector competence from experimental infections and discuss possible vector control measures. The challenges encountered in simian malaria elimination are also discussed. We highlight key knowledge gaps on vector distribution and ecology that may impede effective control strategies.

Epidemiology of the zoonotic malaria Plasmodium knowlesi in changing landscapes.

Within the past two decades, incidence of human cases of the zoonotic malaria Plasmodium knowlesi has increased markedly. P. knowlesi is now the most common cause of human malaria in Malaysia and threatens to undermine malaria control programmes across Southeast Asia. The emergence of zoonotic malaria corresponds to a period of rapid deforestation within this region. These environmental changes impact the distribution and behaviour of the simian hosts, mosquito vector species and human populations, creating new opportunities for P. knowlesi transmission. Here, we review how landscape changes can drive zoonotic disease emergence, examine the extent and causes of these changes across Southeast and identify how these mechanisms may be impacting P. knowlesi dynamics. We review the current spatial epidemiology of reported P. knowlesi infections in people and assess how these demographic and environmental changes may lead to changes in transmission patterns. Finally, we identify opportunities to improve P. knowlesi surveillance and develop targeted ecological interventions within these landscapes.