Climate change, malaria and neglected tropical diseases: a scoping review.

To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

Mosquito control by abatement programmes in the United States: perspectives and lessons for countries in sub-Saharan Africa.

Africa and the United States are both large, heterogeneous geographies with a diverse range of ecologies, climates and mosquito species diversity which contribute to disease transmission and nuisance biting. In the United States, mosquito control is nationally, and regionally coordinated and in so much as the Centers for Disease Control (CDC) provides guidance, the Environmental Protection Agency (EPA) provides pesticide registration, and the states provide legal authority and oversight, the implementation is usually decentralized to the state, county, or city level. Mosquito control operations are organized, in most instances, into fully independent mosquito abatement districts, public works departments, local health departments. In some cases, municipalities engage independent private contractors to undertake mosquito control within their jurisdictions. In sub-Saharan Africa (SSA), where most vector-borne disease endemic countries lie, mosquito control is organized centrally at the national level. In this model, the disease control programmes (national malaria control programmes or national malaria elimination programmes (NMCP/NMEP)) are embedded within the central governments' ministries of health (MoHs) and drive vector control policy development and implementation. Because of the high disease burden and limited resources, the primary endpoint of mosquito control in these settings is reduction of mosquito borne diseases, primarily, malaria. In the United States, however, the endpoint is mosquito control, therefore, significant (or even greater) emphasis is laid on nuisance mosquitoes as much as disease vectors. The authors detail experiences and learnings gathered by the delegation of African vector control professionals that participated in a formal exchange programme initiated by the Pan-African Mosquito Control Association (PAMCA), the University of Notre Dame, and members of the American Mosquito Control Association (AMCA), in the United States between the year 2021 and 2022. The authors highlight the key components of mosquito control operations in the United States and compare them to mosquito control programmes in SSA countries endemic for vector-borne diseases, deriving important lessons that could be useful for vector control in SSA.

Dynamics of malaria vector composition and Plasmodium falciparum infection in mainland Tanzania: 2017-2021 data from the national malaria vector entomological surveillance.

BACKGROUND: In 2015, Tanzania National Malaria Control Programme (NMCP) established a longitudinal malaria vector entomological surveillance (MVES). The MVES is aimed at a periodical assessment of malaria vector composition and abundance, feeding and resting behaviours, and Plasmodium falciparum infection in different malaria epidemiological strata to guide the NMCP on the deployment of appropriate malaria vector interventions. This work details the dynamics of malaria vector composition and transmission in different malaria epidemiological strata. METHODS: The MVES was conducted from 32 sentinel district councils across the country. Mosquitoes were collected by the trained community members and supervised by the NMCP and research institutions. Three consecutive night catches (indoor collection with CDC light trap and indoor/outdoor collection using bucket traps) were conducted monthly in three different households selected randomly from two to three wards within each district council. Collected mosquitoes were sorted and morphologically identified in the field. Thereafter, the samples were sent to the laboratory for molecular characterization using qPCR for species identification and detection of P. falciparum infections (sporozoites). ELISA technique was deployed for blood meal analysis from samples of blood-fed mosquitoes to determine the blood meal indices (BMI). RESULTS: A total of 63,226 mosquitoes were collected in 32 district councils from January 2017 to December 2021. Out of which, 39,279 (62%), 20,983 (33%) and 2964 (5%) were morphologically identified as Anopheles gambiae sensu lato (s.l.), Anopheles funestus s.l., and as other Anopheles species, respectively. Out of 28,795 laboratory amplified mosquitoes, 13,645 (47%) were confirmed to be Anopheles arabiensis, 9904 (34%) as An. funestus sensu stricto (s.s.), and 5193 (19%) as An. gambiae s.s. The combined average entomological inoculation rates (EIR) were 0.46 (95% CI 0.028-0.928) for An. gambiae s.s., 0.836 (95% CI 0.138-1.559) for An. arabiensis, and 0.58 (95% CI 0.165-0.971) for An. funestus s.s. with variations across different malaria transmission strata. Anopheles funestus s.s. and An. arabiensis were predominant in the Lake and South-Eastern zones, respectively, mostly in high malaria transmission areas. Monthly mosquito densities displayed seasonal patterns, with two peaks following the rainy seasons, varying slightly across species and district councils. CONCLUSION: Anopheles arabiensis remains the predominant vector species followed by An. funestus s.s. in the country. Therefore, strengthening integrated vector management including larval source management is recommended to address outdoor transmission by An. arabiensis to interrupt transmission particularly where EIR is greater than the required elimination threshold of less than one (< 1) to substantially reduce the prevalence of malaria infection.

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.

Stakeholder perspectives on a door-to-door intervention to increase community engagement for malaria elimination in Zanzibar.

BACKGROUND: Malaria remains a major public health problem in sub-Saharan Africa. The 2021 World Health Organization (WHO) World Malaria Report indicates a slowing in the decline of malaria incidence since 2015. Malaria prevalence in Zanzibar has been maintained at less than 1% since 2010, however from 2018 to 2021, the annual number of reported malaria cases has gradually increased from 4106 to 9290. Community engagement has been emphasized by the WHO for reducing malaria transmission. To better understand the potential for a door-to-door approach for malaria, a three-month pilot programme was carried out. This qualitative study aimed at understanding stakeholder experiences with the pilot programme and considerations for its implementation. METHODS: Through multistage sampling, four shehias (wards-the lowest administrative structure) with comparatively high (> 1.9 per 1000) and four with low (< 1 per 1000) incidence of local malaria cases were selected and involved in a door-to-door pilot intervention. The qualitative study was conducted after the pilot intervention and employed focus group discussions and in-depth interviews. All field notes were written on paper and audiotaped using digital audio-recorders. Summaries were developed by integrating field notes with reviews of recordings; themes were developed based on the topics identified a priori. Responses for each theme were summarized using an iterative process. RESULTS: Most community members reported high levels of acceptance of door-to-door interventions. Some factors that might affect implementation of door-to-door include, low risk perception of the disease, local beliefs and practice, lack of initiative from the programme level to involve communities, and political instability during the election period. All Community Health Volunteers (CHVs) recommended this approach for community engagement, however, ensuring adequate resources was identified as a key factor for ensuring its sustainability. CONCLUSION: The door-to-door intervention was perceived as helpful for promoting community engagement. There are several factors to consider including ensuring that CHVs are provided with adequate education, regular supervision, and have access to essential resources. Community leaders should be fully involved in choosing CHVs that are acceptable to the community. To ensure sustainability, the government should allocate sufficient resources and improve coordination systems.

Socio-demographic trends in malaria knowledge and implications for behaviour change interventions in Zanzibar.

BACKGROUND: Zanzibar is among the few places within East Africa that have documented a significant reduction of malaria morbidity and mortality. Despite tremendous gains over the past decade, malaria transmission still persists in Zanzibar. This study aimed at understanding levels of malaria knowledge to provide recommendations that can be used to reinforce and scale up targeted malaria social and behaviour change interventions. METHODS: A descriptive cross-sectional survey was conducted through an administered questionnaire to 431 households selected randomly. The interviewees were the heads of household or representative adults above 18 years. This study investigated the levels of knowledge about the causes, symptoms, and prevention of malaria in areas with high (> 1.9 per 1000) and low (< 1 per 1000) incidence of local malaria cases. The Principal Component Analysis (PCA) was used to compute the composite variable of each category. Descriptive statistics were calculated to understand variables of interest between low and high transmission areas. Multinomial logistic regression model was used to compare knowledge on malaria based on key variables. RESULTS: A total of 431 heads of households were interviewed. Respondent age, education level, and wealth status were significantly associated with variations in level of malaria knowledge. Old age was found to be significantly associated with low knowledge of malaria (P < 0.001). The majority of study participants who had secondary and higher education levels had good knowledge of malaria (P < 0.006). Participants characterized as middle-income had good knowledge compared to those characterized as low-income (P < 0.001). CONCLUSION: The study identified existing gaps in malaria knowledge in low and high transmission areas. Low levels of malaria knowledge were documented among elderly and populations with lower education and income levels. There is a need to extend mobilization, advocacy, and expand channels of communication to reach all community members. The reported gaps in knowledge are important to consider when designing strategies to engage communities in malaria elimination in Zanzibar. Tailored social and behavioural change interventions aiming to increase malaria knowledge could enhance the uptake of malaria prevention services in the community.

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.

Outdoor biting and pyrethroid resistance as potential drivers of persistent malaria transmission in Zanzibar.

BACKGROUND: Low-level of malaria transmission persist in Zanzibar despite high coverage of core vector control interventions. This study was carried out in hot-spot sites to better understand entomological factors that may contribute to residual malaria transmission in Zanzibar. METHODS: A total of 135 households were randomly selected from six sites and consented to participate with 20-25 households per site. Mosquito vector surveillance was carried out indoors and outdoors from 6:00 pm-7:00 am using miniaturized double net trap (DN-Mini™). Additional collections were done indoors using mouth aspirators to retrieve resting mosquitoes from wall and ceiling surfaces, and outdoors using resting bucket and pit traps. All collected mosquitoes were morphologically and genetically (PCR) analysed in the laboratory. All collected anopheline and blood-fed mosquitoes were analysed for sporozoite infection and blood meal host preferences by Circumsporozoite Protein ELISA and blood meal ELISA, respectively. The differences between indoor and outdoor mosquito biting rates were analysed using generalized linear mixed models. Levels of resistance to commonly used insecticides were quantified by WHO susceptibility tests. RESULTS: Out of 704 malaria vectors collected across 135 households, PCR analysis shows that 98.60% were Anopheles arabiensis, 0.6% Anopheles merus and 0.6% Anopheles gambiae sensu stricto. Sporozoite ELISA analysis indicates that all mosquitoes were negative for the malaria parasite. The results show that more An. arabiensis were collected outdoor (~ 85%) compared to indoor (~ 15%). Furthermore, large numbers of An. arabiensis were caught in outdoor resting sites, where the pit trap (67.2%) collected more mosquitoes compared to the outdoor DN-Mini trap (32.8%). Nearly two-thirds (60.7%) of blood-fed mosquitoes had obtained blood meals from non-human hosts. Mosquitoes displayed non-uniform susceptibility status and resistance intensity among the tested insecticides across the study sites to all WHO recommended insecticides across the study sites. CONCLUSION: This study suggests that in contexts such as Zanzibar, testing of novel techniques to complement indoor protection and targeting outdoor biting and/or resting mosquitoes, may be warranted to complement existing interventions and contribute to malaria elimination efforts. The study highlights the need to implement novel interventions and/or adaptations of strategies that can target outdoors biting mosquitoes.

A New Test of a Theory about Old Mosquitoes.

In vector control, it is widely accepted that killing adult mosquitoes would sharply reduce the proportion of old mosquitoes and cause the greatest changes to malaria transmission. The principle is based on a mathematical model of the sporozoite rate (the proportion of infective mosquitoes) that emphasized changes in mosquito age. Killing adult mosquitoes also reduces mosquito population densities, which are directly proportional to human biting rates (the number of bites, per person, per day). Eect sizes of vector control can be compared using sporozoite rates and human biting rates, which are commonly measured. We argue that human biting rates convey more use- ful information for planning, monitoring and evaluating vector control, and operational research should focus on understanding mosquito ecology.

Why lockdown? Why national unity? Why global solidarity? Simplified arithmetic tools for decision-makers, health professionals, journalists and the general public to explore containment options for the 2019 novel coronavirus.

As every country in the world struggles with the ongoing COVID-19 pandemic, it is essential that as many people as possible understand the epidemic containment, elimination and exclusion strategies required to tackle it. Simplified arithmetic models of COVID-19 transmission, control and elimination are presented in user-friendly Shiny and Excel formats that allow non-specialists to explore, query, critique and understand the containment decisions facing their country and the world at large. Although the predictive model is broadly applicable, the simulations presented are based on parameter values representative of the United Republic of Tanzania, which is still early enough in its epidemic cycle and response to avert a national catastrophe. The predictions of these models illustrate (1) why ambitious lock-down interventions to crush the curve represent the only realistic way for individual countries to contain their national-level epidemics before they turn into outright catastrophes, (2) why these need to be implemented so early, so stringently and for such extended periods, (3) why high prevalence of other pathogens causing similar symptoms to mild COVID-19 precludes the use of contact tracing as a substitute for lock down interventions to contain and eliminate epidemics, (4) why partial containment strategies intended to merely flatten the curve, by maintaining epidemics at manageably low levels, are grossly unrealistic, and (5) why local elimination may only be sustained after lock down ends if imported cases are comprehensively excluded, so international co-operation to conditionally re-open trade and travel between countries certified as free of COVID-19 represents the best strategy for motivating progress towards pandemic eradication at global level. The three sequential goals that every country needs to emphatically embrace are contain, eliminate and exclude. As recently emphasized by the World Health Organization, success will require widespread genuine national unity and unprecedented global solidarity.

Correction to: Methods and indicators for measuring patterns of human exposure to malaria vectors.

An amendment to this paper has been published and can be accessed via the original article.

Patterns of human exposure to malaria vectors in Zanzibar and implications for malaria elimination efforts.

BACKGROUND: Zanzibar provides a good case study for malaria elimination. The islands have experienced a dramatic reduction in malaria burden since the introduction of effective vector control interventions and case management. Malaria prevalence has now been maintained below 1% for the past decade and the islands can feasibly aim for elimination. METHODS: To better understand factors that may contribute to remaining low-level malaria transmission in Zanzibar, layered human behavioural and entomological research was conducted between December 2016 and December 2017 in 135 randomly selected households across six administrative wards. The study included: (1) household surveys, (2) structured household observations of nighttime activity and sleeping patterns, and (3) paired indoor and outdoor mosquito collections. Entomological and human behavioural data were integrated to provide weighted estimates of exposure to vector bites, accounting for proportions of people indoors or outdoors, and protected by insecticide-treated nets (ITNs) each hour of the night. RESULTS: Overall, 92% of female Anopheles mosquitoes were caught in the rainy season compared to 8% in the dry season and 72% were caught outdoors compared to 28% indoors. For individual ITN users, ITNs prevented an estimated two-thirds (66%) of exposure to vector bites and nearly three quarters (73%) of residual exposure was estimated to occur outdoors. Based on observed levels of ITN use in the study sites, the population-wide mean personal protection provided by ITNs was 42%. DISCUSSION/CONCLUSIONS: This study identified gaps in malaria prevention in Zanzibar with results directly applicable for improving ongoing programme activities. While overall biting risk was low, the most notable finding was that current levels of ITN use are estimated to prevent less than half of exposure to malaria vector bites. Variation in ITN use across sites and seasons suggests that additional gains could be made through targeted social and behaviour change interventions. However, even for ITN users, gaps in protection remain, with a majority of exposure to vector bites occurring outdoors before going to sleep. Supplemental interventions targeting outdoor exposure to malaria vectors, and groups that may be at increased risk of exposure to malaria vectors, should be explored.

An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra.

After mating, female mosquitoes need animal blood to develop their eggs. In the process of acquiring blood, they may acquire pathogens, which may cause different diseases in humans such as malaria, zika, dengue, and chikungunya. Therefore, knowing the parity status of mosquitoes is useful in control and evaluation of infectious diseases transmitted by mosquitoes, where parous mosquitoes are assumed to be potentially infectious. Ovary dissections, which are currently used to determine the parity status of mosquitoes, are very tedious and limited to few experts. An alternative to ovary dissections is near-infrared spectroscopy (NIRS), which can estimate the age in days and the infectious state of laboratory and semi-field reared mosquitoes with accuracies between 80 and 99%. No study has tested the accuracy of NIRS for estimating the parity status of wild mosquitoes. In this study, we train an artificial neural network (ANN) models on NIR spectra to estimate the parity status of wild mosquitoes. We use four different datasets: An. arabiensis collected from Minepa, Tanzania (Minepa-ARA); An. gambiae s.s collected from Muleba, Tanzania (Muleba-GA); An. gambiae s.s collected from Burkina Faso (Burkina-GA); and An.gambiae s.s from Muleba and Burkina Faso combined (Muleba-Burkina-GA). We train ANN models on datasets with spectra preprocessed according to previous protocols. We then use autoencoders to reduce the spectra feature dimensions from 1851 to 10 and re-train the ANN models. Before the autoencoder was applied, ANN models estimated parity status of mosquitoes in Minepa-ARA, Muleba-GA, Burkina-GA and Muleba-Burkina-GA with out-of-sample accuracies of 81.9±2.8 (N = 274), 68.7±4.8 (N = 43), 80.3±2.0 (N = 48), and 75.7±2.5 (N = 91), respectively. With the autoencoder, ANN models tested on out-of-sample data achieved 97.1±2.2% (N = 274), 89.8 ± 1.7% (N = 43), 93.3±1.2% (N = 48), and 92.7±1.8% (N = 91) accuracies for Minepa-ARA, Muleba-GA, Burkina-GA, and Muleba-Burkina-GA, respectively. These results show that a combination of an autoencoder and an ANN trained on NIR spectra to estimate the parity status of wild mosquitoes yields models that can be used as an alternative tool to estimate parity status of wild mosquitoes, especially since NIRS is a high-throughput, reagent-free, and simple-to-use technique compared to ovary dissections.

Methods and indicators for measuring patterns of human exposure to malaria vectors.

BACKGROUND: Effective targeting and evaluation of interventions that protect against adult malaria vectors requires an understanding of how gaps in personal protection arise. An improved understanding of human and mosquito behaviour, and how they overlap in time and space, is critical to estimating the impact of insecticide-treated nets (ITNs) and determining when and where supplemental personal protection tools are needed. Methods for weighting estimates of human exposure to biting Anopheles mosquitoes according to where people spend their time were first developed over half a century ago. However, crude indoor and outdoor biting rates are still commonly interpreted as indicative of human-vector contact patterns without any adjustment for human behaviour or the personal protection effects of ITNs. MAIN TEXT: A small number of human behavioural variables capturing the distribution of human populations indoors and outdoors, whether they are awake or asleep, and if and when they use an ITN over the course of the night, can enable a more accurate representation of human biting exposure patterns. However, to date no clear guidance is available on what data should be collected, what indicators should be reported, or how they should be calculated. This article presents an integrated perspective on relevant indicators of human-vector interactions, the critical entomological and human behavioural data elements required to quantify human-vector interactions, and recommendations for collecting and analysing such data. CONCLUSIONS: If collected and used consistently, this information can contribute to an improved understanding of how malaria transmission persists in the context of current intervention tools, how exposure patterns may change as new vector control tools are introduced, and the potential impact and limitations of these tools. This article is intended to consolidate understanding around work on this topic to date and provide a consistent framework for building upon it. Additional work is needed to address remaining questions, including further development and validation of methods for entomological and human behavioural data collection and analysis.

Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology.

Mosquitoes are important vectors for pathogens that infect humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we re-examine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for individual-based simulation models called MBITES (Mosquito Bout-based and Individual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While mosquito infection and pathogen development are one possible part of a mosquito's state, that is not our main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations' capacity to transmit pathogens.

Age grading An. gambiae and An. arabiensis using near infrared spectra and artificial neural networks.

BACKGROUND: Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into < or ≥ 7 days old with an average accuracy of 80%, achieved by training a regression model using partial least squares (PLS) and interpreted as a binary classifier. METHODS AND FINDINGS: We explore whether using an artificial neural network (ANN) analysis instead of PLS regression improves the current accuracy of NIRS models for age-grading malaria transmitting mosquitoes. We also explore if directly training a binary classifier instead of training a regression model and interpreting it as a binary classifier improves the accuracy. A total of 786 and 870 NIR spectra collected from laboratory reared An. gambiae and An. arabiensis, respectively, were used and pre-processed according to previously published protocols. The ANN regression model scored root mean squared error (RMSE) of 1.6 ± 0.2 for An. gambiae and 2.8 ± 0.2 for An. arabiensis; whereas the PLS regression model scored RMSE of 3.7 ± 0.2 for An. gambiae, and 4.5 ± 0.1 for An. arabiensis. When we interpreted regression models as binary classifiers, the accuracy of the ANN regression model was 93.7 ± 1.0% for An. gambiae, and 90.2 ± 1.7% for An. arabiensis; while PLS regression model scored the accuracy of 83.9 ± 2.3% for An. gambiae, and 80.3 ± 2.1% for An. arabiensis. We also find that a directly trained binary classifier yields higher age estimation accuracy than a regression model interpreted as a binary classifier. A directly trained ANN binary classifier scored an accuracy of 99.4 ± 1.0 for An. gambiae and 99.0 ± 0.6% for An. arabiensis; while a directly trained PLS binary classifier scored 93.6 ± 1.2% for An. gambiae and 88.7 ± 1.1% for An. arabiensis. We further tested the reproducibility of these results on different independent mosquito datasets. ANNs scored higher estimation accuracies than when the same age models are trained using PLS. Regardless of the model architecture, directly trained binary classifiers scored higher accuracies on classifying age of mosquitoes than regression models translated as binary classifiers. CONCLUSION: We recommend training models to estimate age of An. arabiensis and An. gambiae using ANN model architectures (especially for datasets with at least 70 mosquitoes per age group) and direct training of binary classifier instead of training a regression model and interpreting it as a binary classifier.

Autodissemination of pyriproxyfen suppresses stable populations of Anopheles arabiensis under semi-controlled settings.

BACKGROUND: Autodissemination of pyriproxyfen (PPF), i.e. co-opting adult female mosquitoes to transfer the insect growth regulator, pyriproxyfen (PPF) to their aquatic habitats has been demonstrated for Aedes and Anopheles mosquitoes. This approach, could potentially enable high coverage of aquatic mosquito habitats, including those hard to locate or reach via conventional larviciding. This study demonstrated impacts of autodissemination in crashing a stable and self-sustaining population of the malaria vector, Anopheles arabiensis under semi-field conditions in Tanzania. METHODS: Self-propagating populations of An. arabiensis were established inside large semi-field cages. Larvae fed on naturally occurring food in 20 aquatic habitats in two study chambers (9.6 × 9.6 m each), while emerging adults fed on tethered cattle. The mosquito population was monitored using emergence traps and human landing catches, each time returning captured adults into the chambers. Once the population was stable (after 23 filial generations), PPF dissemination devices (i.e. four clay pots each treated with 0.2-0.3 g PPF) were introduced into one of the chambers (treatment) and their impact monitored in parallel with untreated chamber (control). RESULTS: Daily adult emergence was similar between control and treatment chambers, with average (± SE) of 14.22 ± 0.70 and 12.62 ± 0.74 mosquitoes/trap, respectively, before treatment. Three months post-treatment, mean number of adult An. arabiensis emerging from the habitats was 5.22 ± 0.42 in control and 0.14 ± 0.04 in treatment chambers. This was equivalent to > 97% suppression in treatment chamber without re-treatment of the clay pots. Similarly, the number of mosquitoes attempting to bite volunteers inside the treatment chamber decreased to zero, 6 months post-exposure (i.e. 100% suppression). In contrast, biting rates in control rose to 53.75 ± 3.07 per volunteer over the same period. CONCLUSION: These findings demonstrate effective suppression of stable populations of malaria vectors using a small number of simple autodissemination devices, from which adult mosquitoes propagated pyriproxyfen to contaminate aquatic habitats in the system. This is the first proof that autodissemination can amplify treatment coverage and deplete malaria vector populations. Field trials are necessary to validate these results, and assess impact of autodissemination as a complementary malaria intervention.

Do NIR spectra collected from laboratory-reared mosquitoes differ from those collected from wild mosquitoes?

BACKGROUND: Near infrared spectroscopy (NIRS) is a high throughput technique that measures absorbance of specific wavelengths of light by biological samples and uses this information to classify the age of lab-reared mosquitoes as younger or older than seven days with an average accuracy greater than 80%. For NIRS to estimate ages of wild mosquitoes, a sample of wild mosquitoes with known age in days would be required to train and test the model. Mark-release-recapture is the most reliable method to produce wild-caught mosquitoes of known age in days. However, it is logistically demanding, time inefficient, subject to low recapture rates, and raises ethical issues due to the release of mosquitoes. Using labels from Detinova dissection results in a mathematical model with poor accuracy. Alternatively, a model trained on spectra from laboratory-reared mosquitoes where age in days is known can be applied to estimate the age of wild mosquitoes, but this would be appropriate only if spectra collected from laboratory-reared and wild mosquitoes are similar. METHODS AND FINDINGS: We performed k-means (k = 2) cluster analysis on a mixture of spectra collected from lab-reared and wild Anopheles arabiensis to determine if there is any significant difference between these two groups. While controlling the numbers of mosquitoes included in the model at each age, we found two clusters with no significant difference in distribution of spectra collected from lab-reared and wild mosquitoes (p = 0.25). We repeated the analysis using hierarchical clustering, and similarly, no significant difference was observed (p = 0.13). CONCLUSION: We find no difference between spectra collected from laboratory-reared and wild mosquitoes of the same age and species. The results strengthen and support the on-going practice of applying the model trained on spectra collected from laboratory-reared mosquitoes, especially first-generation laboratory-reared mosquitoes.

Mathematical models of human mobility of relevance to malaria transmission in Africa.

As Africa-wide malaria prevalence declines, an understanding of human movement patterns is essential to inform how best to target interventions. We fitted movement models to trip data from surveys conducted at 3-5 sites throughout each of Mali, Burkina Faso, Zambia and Tanzania. Two models were compared in terms of their ability to predict the observed movement patterns - a gravity model, in which movement rates between pairs of locations increase with population size and decrease with distance, and a radiation model, in which travelers are cumulatively "absorbed" as they move outwards from their origin of travel. The gravity model provided a better fit to the data overall and for travel to large populations, while the radiation model provided a better fit for nearby populations. One strength of the data set was that trips could be categorized according to traveler group - namely, women traveling with children in all survey countries and youth workers in Mali. For gravity models fitted to data specific to these groups, youth workers were found to have a higher travel frequency to large population centers, and women traveling with children a lower frequency. These models may help predict the spatial transmission of malaria parasites and inform strategies to control their spread.