Mosquito Biting Rates Research Articles

Application of multiple linear regression model and long short-term memory with compartmental model to forecast dengue cases in Selangor, Malaysia based on climate variables

Despite the implementation of various initiatives, dengue remains a significant public health concern in Malaysia. Given that dengue has no specific treatment, dengue prediction remains a useful early warning mechanism for timely and effective deployment of public health preventative measures. This study aims to develop a comprehensive approach for forecasting dengue cases in Selangor, Malaysia by incorporating climate variables. An ensemble of Multiple Linear Regression (MLR) model, Long Short-Term Memory (LSTM), and Susceptible-Infected mosquito vectors, Susceptible-Infected-Recovered human hosts (SI-SIR) model were used to establish a relation between climate variables (temperature, humidity, precipitation) and mosquito biting rate. Dengue incidence subject to climate variability can then be projected by SI-SIR model using the forecasted mosquito biting rate. The proposed approach outperformed three alternative approaches and expanded the temporal horizon of dengue prediction for Selangor with the ability to forecast approximately 60 weeks ahead with a Mean Absolute Percentage Error (MAPE) of 13.97 for the chosen prediction window before the implementation of the Movement Control Order (MCO) in Malaysia. Extended validation across subsequent periods also indicates relatively satisfactory forecasting performance (with MAPE ranging from 13.12 to 17.09). This research contributed to the field by introducing a novel framework for the prediction of dengue cases over an extended temporal range.

Mathematical Modeling of Dengue Disease Transmission Dynamics

Objectives: This study developed a compartmental ordinary differential equation model to investigate dengue transmission dynamics within a human population. The model stratified the population into susceptible, exposed, infected, and recovered classes, incorporating key epidemiological factors. Methods: Model equilibrium analysis was conducted to determine the stability of disease-free and endemic states. The basic reproduction number (R₀) was calculated to quantify the potential for disease spread. Additionally, sensitivity analysis was performed to assess the impact of key parameters on model outcomes. Findings: Results indicate that reducing mosquito biting rates and increasing human recovery rates are effective strategies for controlling dengue transmission. The model exhibits backward bifurcation, suggesting that even when R₀ is less than one, the disease can persist in the population under certain conditions. Novelty: This study presents a novel modeling framework that can inform the development of targeted prevention and management strategies for dengue. Keywords: Dengue, Mathematical Model, Ordinary differential equations, Basic reproduction number, Sensitivity analysis

A fractional derivative model of the dynamic of dengue transmission based on seasonal factors in Thailand

Climate variability affects the changes in controlling diseases transferred by insects. An increase in the population, the growth of communities, and a lack of public health infrastructure bring about the return of diseases of which insects are carriers, one of the illness issues. Therefore, the disease control is significant to help reduce the burden on the government and strengthen the country's public health structure. This research proposes a novel approach to modeling dengue fever dynamics, we employ a fractional derivative model with the Atangana–Baleanu–Caputo derivative, which offers a more accurate representation of real-world disease dynamics compared to traditional integer-order models. Basic qualifications are proposed. Equilibrium points and basic reproduction numbers are analyzed. The next-generation matrix method is used to identify the transmission. Besides, parameter sensitivity analysis is performed to learn about factors affecting input parameter values' effects on the basic reproduction number. It was found that the most common parameter affecting the transmission was the biting rate of mosquitoes was 1. In addition, the existence and uniqueness of the solution are examined using the Banach fixed point theorem. The Toufik–Atangana method is used for the numerical examination of a fractional version of the proposed model. We compared different values of fractional-order α=0.965, 0.975, 0.985, 0.995 and 1 it was found that when the order of derivatives decreases, the transmission shall decrease accordingly. This research provides valuable insights for developing effective control strategies to reduce the burden of dengue fever and strengthen public health systems.

Optimal control with the effects of ivermectin and live stock availability on malaria transmission

Malaria remains a global threat and the conventional methods used for combating the disease leave out mosquitoes that feed outdoors. This study addresses the challenge posed by such mosquitoes based on a tool called ivermectin drug which is lethal to mosquitoes that ingest bloodmeal containing a concentration of it. We formulated a mathematical model with three control tools (insecticide treated nets, treatment of infective individuals and ivermectin drug on livestock and humans) for the transmission and control of malaria under optimal condition. The model’s basic reproduction number, R0 was estimated and the local and global stability analyses of the disease-free and endemic equilibrium points of the model were carried out. Sensitivity analysis carried out showed that R0 is most sensitive to the mosquito biting rate and to the proportion of blood meal on human with cattle availability in such a way that any percent increase in the value of any of these parameters will lead to an equal percent increase in the value of R0. The result of an optimal control analysis based on three time dependent controls suggests that the combination of all three controls gives the best result followed by the strategy that combines the use of ivermectin drug and the treatment of infective human. Depending on available resources, any of these is recommended to be adopted in malaria intervention programmes because of their effectiveness on both the infective human and mosquito populations with the potential of contributing significantly to the disease elimination within a minimal time frame.

A Coupled Statistical and Deterministic Model for Forecasting Climate-Driven Dengue Incidence in Selangor, Malaysia.

The mosquito-borne dengue virus remains a major public health concern in Malaysia. Despite various control efforts and measures introduced by the Malaysian Government to combat dengue, the increasing trend of dengue cases persists and shows no sign of decreasing. Currently, early detection and vector control are the main methods employed to curb dengue outbreaks. In this study, a coupled model consisting of the statistical ARIMAX model and the deterministic SI-SIR model was developed and validated using the weekly reported dengue data from year 2014 to 2019 for Selangor, Malaysia. Previous studies have shown that climate variables, especially temperature, humidity, and precipitation, were able to influence dengue incidence and transmission dynamics through their effect on the vector. In this coupled model, climate is linked to dengue disease through mosquito biting rate, allowing real-time forecast of dengue cases using climate variables, namely temperature, rainfall and humidity. For the period chosen for model validation, the coupled model can forecast 1-2weeks in advance with an average error of less than 6%, three weeks in advance with an average error of 7.06% and four weeks in advance with an average error of 8.01%. Further model simulation analysis suggests that the coupled model generally provides better forecast than the stand-alone ARIMAX model, especially at the onset of the outbreak. Moreover, the coupled model is more robust in the sense that it can be further adapted for investigating the effectiveness of various dengue mitigation measures subject to the changing climate.

A deterministic mathematical model for quantifiable prediction of antimalarials limiting the prevalence of multidrug-resistant malaria

The malaria’s multidrug-resistant strain in Nigeria is prevalent and it poses a significant challenge for disease elimination. The testing for resistance is available but underutilized. Therefore, we develop a mathematical model incorporating the testing as a control strategy. This allows us to make quantifiable predictions about the effects of testing utilization on the malaria prevalence. By fitting the model to data on malaria and using field data reported in the literature, important parameters associated with the disease dynamics are estimated and calculated. First, we analyze the disease-free state of the malaria model and calculate the baseline control reproduction number. Sensitivity analysis is used to investigate the influence of the parameters in curtailing the disease. Numerical simulations are used to explore the behavior of the model solutions involving testing for resistance of the strain and wild strain malaria. We found that the implementation of testing would (a) prevent the increase of malaria prevalence from 30% to 35%, (b) significantly slow down the replacement of the wild strain by the resistant strain, and (c) avert about 6% of treatment failures. We also found that increasing mosquito death rate or reducing mosquito biting rate, mosquito birth rate, transmission to or from mosquitoes would contribute most significantly to the reduction of malaria prevalence in the community. In conclusion, the treatment failure is a significant component of the community malaria epidemic. Testing for multidrug resistance yields a significant reduction in cases with many implications regarding the containment of malaria in Nigeria.

Effect of textile colour on vector mosquito host selection: a simulated field study in Mali, West Africa.

The effect of clothing colour on the biting rates of different vector mosquito species is not well understood. Studies under tropical field conditions are lacking. This study aimed to determine the influence of clothing colours on mosquito biting rates in rural and suburban settings in West Africa. We performed a simulated field study in a suburban and a rural site in Mali using Mosquito-Magnet traps utilizing CO2 and other attractants, which were covered with black, white, and black/white striped textile sheets covers. These targets operated continuously for 10 consecutive days with bright nights (around full moon) and 10 consecutive days with dark nights (around new moon). Trapped mosquitoes were collected and catch rates counted hourly. Mosquitoes were morphologically identified to the species complex level (Anopheles gambiae s.l. and Culex pipiens s.l.) or species level (Aedes aegypti). A subset of Anopheles specimens were further identified by molecular methods. Under bright-night conditions, An. gambiae s.l. was significantly more attracted to black targets than to white and striped targets; during dark nights, no target preference was noted. During bright nights, Cx. pipiens s.l. was significantly more attracted to black and striped targets than to white targets; a similar trend was noted during dark nights (not significant). For day-active Ae. aegypti, striped targets were more attractive than the other targets and black were more attractive than white targets. The study firstly demonstrated that under field conditions in Mali, West Africa, mosquito catch rates were influenced by different clothing colours, depending on mosquito species and light conditions. Overall, light colours were least attractive to host-seeking mosquitoes. Using white or other light-coloured clothing can potentially reduce bite exposure and risk of disease transmission in endemic tropical regions.

Fractional insights into Zika virus transmission: Exploring preventive measures from a dynamical perspective

Abstract Mathematical models for infectious diseases can help researchers, public health officials, and policymakers to predict the course of an outbreak. We formulate an epidemic model for the transmission dynamics of Zika infection with carriers to understand the intricate progression route of the infection. In our study, we focused on the visualization of the transmission patterns of the Zika with asymptomatic carriers, using fractional calculus. For the validity of the model, we have shown that the solutions of the system are positive and bounded. Moreover, we conduct a qualitative analysis and examine the dynamical behavior of Zika dynamics. The existence and uniqueness of the solution of the system have been proved through analytic skills. We establish the necessary conditions to ensure the stability of the recommended system based on the Ulam–Hyers stability concept (UHS). Our research emphasizes the most critical factors, specifically the mosquito biting rate and the existence of asymptomatic carriers, in increasing the complexity of virus control efforts. Furthermore, we predict that the asymptomatic fraction has the ability to spread the infection to non-infected regions. Furthermore, treatment due to medication, the fractional parameter or memory index, and vaccination can serve as effective control measures in combating this viral infection.

Effect of non-human hosts on the human biting rate of primary and secondary malaria vectors in Tanzania

BackgroundMalaria vectors vary in feeding preference depending on their innate behaviour, host availability and abundance. Host preference and human biting rate in malaria vectors are key factors in establishing zooprophylaxis and zoopotentiation. This study aimed at assessing the impact of non-human hosts in close proximity to humans on the human biting rate of primary and secondary malaria vectors, with varying host preferences.MethodsThe effect of the presence of non-human hosts in close proximity to the human host on the mean catches per person per night, as a proxy for mosquito biting rate, was measured using mosquito-electrocuting traps (METs), in Sagamaganga, Kilombero Valley, Tanzania. Two experiments were designed: (1) a human versus a calf, each enclosed in a MET, and (2) a human surrounded by three calves versus a human alone, with each human volunteer enclosed individually in a MET spaced 10 m apart. Each experiment was conducted on alternate days and lasted for 36 nights per experiment. During each experiment, the positions of hosts were exchanged daily (except the human in experiment 2). All anopheline mosquitoes caught were assayed for Plasmodium sporozoites using enzyme-linked immunosorbent assay.ResultsA total of 20,574 mosquitoes were captured and identified during the study, of which 3608 were anophelines (84.4% primary and 15.6% secondary malaria vectors) and 17,146 were culicines. In experiment 1, the primary malaria vector, Anopheles arabiensis, along with Culex spp. demonstrated a preference for cattle, while the primary vectors, Anopheles funestus, preferred humans. In experiment 2, both primary vectors, An. arabiensis and An. funestus, as well as the secondary vector Anopheles rivolurum, demonstrated behaviours amenable to zooprophylaxis, whereas Culex spp. increased their attraction to humans in the presence of nearby cattle. All anopheline mosquitoes tested negative for sporozoites.ConclusionsThe findings of this study provide support for the zooprophylaxis model for malaria vectors present in the Kilombero Valley, and for the zoopotentiation model, as it pertains to the Culex spp. in the region. However, the factors regulating zooprophylaxis and zoopotentiation are complex, with different species-dependent mechanisms regulating these behaviours, that need to be considered when designing integrated vector management programmes.

A Sensitivity Analysis of a Mathematical Model for the Transmission of Endemic Malaria under Periodic Climatic Conditions

We perform sensitivity analysis on a periodic mathematical model of endemic malaria transmission to determine the relative importance and impact of model parameters to disease transmission and prevalence. In this analysis, two sets of baseline parameter values are compiled: one for areas that exhibit high transmission rate and another one for areas with low transmission rates. Sensitivity indices for the basic reproductive number and the endemic equilibrium points are computed. The study established that in areas of low transmission, the reproductive number is most sensitive to the mosquito biting rate, but the equilibrium proportion of the infectious humans is most sensitive to the human recovery rate. Sensitivity analysis on all state variables was conducted. The results indicated that the most influential factors in the transmission and persistence of malaria in the society are those related to vectorial competence. These findings suggests that strategies that target the vector characteristics such as the mosquito biting rate and those that target the human recovery rate can be very successful in controlling malaria. These strategies include the use of insecticide-treated mosquito nets, indoor residual spraying, prompt diagnosis and treatment of infectious individuals. However, a combination of intervention strategies is more effective than application of a single intervention.

Understanding West Nile virus transmission: Mathematical modelling to quantify the most critical parameters to predict infection dynamics.

West Nile disease is a vector-borne disease caused by West Nile virus (WNV), involving mosquitoes as vectors and birds as maintenance hosts. Humans and other mammals can be infected via mosquito bites, developing symptoms ranging from mild fever to severe neurological infection. Due to the worldwide spread of WNV, human infection risk is high in several countries. Nevertheless, there are still several knowledge gaps regarding WNV dynamics. Several aspects of transmission taking place between birds and mosquitoes, such as the length of the infectious period in birds or mosquito biting rates, are still not fully understood, and precise quantitative estimates are still lacking for the European species involved. This lack of knowledge affects the precision of parameter values when modelling the infection, consequently resulting in a potential impairment of the reliability of model simulations and predictions and in a lack of the overall understanding of WNV spread. Further investigations are thus needed to better understand these aspects, but field studies, especially those involving several wild species, such as in the case of WNV, can be challenging. Thus, it becomes crucial to identify which transmission processes most influence the dynamics of WNV. In the present work, we propose a sensitivity analysis to investigate which of the selected epidemiological parameters of WNV have the largest impact on the spread of the infection. Based on a mathematical model simulating WNV spread into the Lombardy region (northern Italy), the basic reproduction number of the infection was estimated and used to quantify infection spread into mosquitoes and birds. Then, we quantified how variations in four epidemiological parameters representing the duration of the infectious period in birds, the mosquito biting rate on birds, and the competence and susceptibility to infection of different bird species might affect WNV transmission. Our study highlights that knowledge gaps in WNV epidemiology affect the precision in several parameters. Although all investigated parameters affected the spread of WNV and the modelling precision, the duration of the infectious period in birds and mosquito biting rate are the most impactful, pointing out the need of focusing future studies on a better estimate of these parameters at first. In addition, our study suggests that a WNV outbreak is very likely to occur in all areas with suitable temperatures, highlighting the wide area where WNV represents a serious risk for public health.

Integrated malaria prevention in low- and middle-income countries: a systematic review

BackgroundAs many countries aim to eliminate malaria, use of comprehensive approaches targeting the mosquito vector and environment are needed. Integrated malaria prevention advocates the use of several malaria prevention measures holistically at households and in the community. The aim of this systematic review was to collate and summarize the impact of integrated malaria prevention in low- and middle-income countries on malaria burden.MethodsLiterature on integrated malaria prevention, defined as the use of two or more malaria prevention methods holistically, was searched from 1st January 2001 to 31st July 2021. The primary outcome variables were malaria incidence and prevalence, while the secondary outcome measures were human biting and entomological inoculation rates, and mosquito mortality.ResultsA total of 10,931 studies were identified by the search strategy. After screening, 57 articles were included in the review. Studies included cluster randomized controlled trials, longitudinal studies, programme evaluations, experimental hut/houses, and field trials. Various interventions were used, mainly combinations of two or three malaria prevention methods including insecticide-treated nets (ITNs), indoor residual spraying (IRS), topical repellents, insecticide sprays, microbial larvicides, and house improvements including screening, insecticide-treated wall hangings, and screening of eaves. The most common methods used in integrated malaria prevention were ITNs and IRS, followed by ITNs and topical repellents. There was reduced incidence and prevalence of malaria when multiple malaria prevention methods were used compared to single methods. Mosquito human biting and entomological inoculation rates were significantly reduced, and mosquito mortality increased in use of multiple methods compared to single interventions. However, a few studies showed mixed results or no benefits of using multiple methods to prevent malaria.ConclusionUse of multiple malaria prevention methods was effective in reducing malaria infection and mosquito density in comparison with single methods. Results from this systematic review can be used to inform future research, practice, policy and programming for malaria control in endemic countries.

The malaria transmission in Anhui province China.

Plasmodium vivax and Plasmodium falciparum cases have opposite trends in Anhui China in the past decade. Long term and seasonal trends in the transmission rate of P. falciparum in Africa has been well studied, however that of P. vivax transmitted by Anopheles sinensis in China has not been investigated. There is a lot of work on the relationship between P. vivax cases and climatic factors in China, with sometimes contradicting results. However, how climatic factors affect transmission rate of P. vivax in China is unknown. We used Anhui province as an example to analyze the recent transmission dynamics where two types of malaria have been reported with differing etiologies. We examined breakpoints of the P. vivax and P. falciparum malaria long term dynamics in the recent decade. For locally transmitted P. vivax malaria, we analyzed the transmission rate and its seasonality using the combined human and mosquitos SIR-SI model with time-varied mosquito biting rate. We identified the effects of meteorological factors on the seasonality in transmission rate using a GAM model. For the imported P. falciparum malaria, we analyzed the potential reason for the observed increase in cases. The breakpoints of P. vivax and P. falciparum dynamics happened in a same year, 2010. The seasonality in the transmission rate of P. vivax malaria was high (42.4%) and was linearly associated with temperature and nonlinearly with rainfall. The abrupt increase in imported P. falciparum cases after the breakpoint was significantly related to the increased annual Chinese investment in Africa. Under the conditions of the existing vectors of malaria, long-term trends in climatic factors, and increasing trend in migration to/from endemic areas and imported malaria cases, we should be cautious of the possibility of the reestablishment of malaria in regions where it has been eliminated or the establishment of other vector-borne diseases.

Changing temperature profiles and the risk of dengue outbreaks

As temperatures change worldwide, the pattern and competency of disease vectors will change, altering the global distribution of both the burden of infectious disease and the risk of the emergence of those diseases into new regions. To evaluate the risk of potential summer dengue outbreaks triggered by infected travelers under various climate scenarios, we develop an SEIR-type model, run numerical simulations, and conduct sensitivity analyses under a range of temperature profiles. Our model extends existing theoretical frameworks for studying dengue dynamics by introducing temperature dependence of two key parameters: the mosquito extrinsic incubation period and the lifespan of mosquitoes, which empirical data suggests are both highly temperature dependent. We find that changing temperature significantly alters dengue risk in an inverted U-shape, with temperatures in the range 27-31°C producing the highest risk. As temperatures increase beyond 31°C, the determinants of dengue risk begin to shift from mosquito biting rate and carrying capacity to the duration of the human infectious period, suggesting that changing temperatures not only alter dengue risk but also the potential efficacy of control measures. To illustrate the role of spatial and temporal temperature heterogeneity, we select five US cities where the primary dengue vector, the mosquito Aedes aegypti, has been observed, and which have had dengue cases in the past: Los Angeles, Houston, Miami, Brownsville, and Phoenix. Our analysis suggests that an increase of 3°C leads to an approximate doubling of the risk of dengue in Los Angeles and Houston, but a reduction of risk in Miami, Brownsville, and Phoenix due to extreme heat.

The Efficiency of Biogents Sentinel 2.0 Trapping and Human-Landing Catching Methods to Calculate Human Biting Rates.

To calculate human biting rates for various mosquito species, we performed simultaneous collections for 15 wk at 6 ecologically variable sites in Hungary. Of the dominant species, the relative abundance of Aedes vexans, Ae. sticticus, and Coquillettidia richiardii showed a significant positive correlation between CO2 + Biogents lure and human landing catch (HLC). The relative abundance of Culex pipiens was significantly lower in the HLC samples than in the CO2 + BG lure samples. Of the invasive species, Aedes korecius was found more frequently in HLC, while Ae. japonicus was more common in CO2 + BG lure samples. Estimated human biting rates, determined with the 2 collection methods, showed no significant differences at high mosquito density (100-120 bites/h/person), but there was considerable variation at low mosquito biting rates. Therefore, correcting the CO2 + BG lure trapping data to include only species biting humans provides estimates approaching the values of the HLC. Our study confirmed that while HLC is the gold standard method for determining the human biting rate, provided appropriate data adjustments are made, trapping methods performing automated data collection can provide similar data while reducing the exposure of the data collector.

How do i bite thee? let me count the ways: Exploring the implications of individual biting habits of Aedes aegypti for dengue transmission.

In models of mosquito–borne transmission, the mosquito biting rate is an influential parameter, and understanding the heterogeneity of the process of biting is important, as biting is usually assumed to be relatively homogeneous across individuals, with time–between–bites described by an exponentially distributed process. However, these assumptions have not been addressed through laboratory experimentation. We experimentally investigated the daily biting habits of Ae. aegypti at three temperatures (24°C, 28°C, and 32°C) and determined that there was individual heterogeneity in biting habits (number of bites, timing of bites, etc.). We further explored the consequences of biting heterogeneity using an individual–based model designed to examine whether a particular biting profile determines whether a mosquito is more or less likely to 1) become exposed given a single index case of dengue (DENV) and 2) transmit to a susceptible human individual. Our experimental results indicate that there is heterogeneity among individuals and among temperature treatments. We further show that this results in altered probabilities of transmission of DENV to and from individual mosquitoes based on biting profiles. While current model representation of biting may work under some conditions, it might not uniformly be the best fit for this process. Our data also confirm that biting is a non–monotonic process with temperatures around 28°C being optimum.

Assessing the impact of insecticide-treated nets in the face of insecticide resistance on malaria control

The mosquito-borne disease, malaria, continues to impose a devastating health and economic burden worldwide. In malaria-endemic areas, insecticide-treated nets (ITNs) have been useful in curtailing the burden of the disease. However, mosquito resistance to insecticides, decay in ITN efficacy, net attrition, etc., undermine the effectiveness of ITNs in combatting malaria. In this study, mathematical models that account for asymptomatic infectious humans (through a partially immune class or a separate asymptomatic infectious class), insecticide resistance, and decay in ITN efficacy are proposed and analyzed. Analytical and numerical results of the models when ITN efficacy is constant show that there are parameter regimes for which a backward bifurcation occurs. Local and global sensitivity analyses are performed to identify parameters (some of which are potential targets for disease control) with the most significant influence on the control reproduction (Rc) and disease prevalence. These influential parameters include the maximum biting rate of resistant mosquitoes, ITN coverage, initial ITN efficacy against sensitive mosquitoes, the probability that an infectious mosquito (human) infects a susceptible human (mosquito), and the rate at which adult mosquitoes develop (lose) resistance to insecticides. Simulations of the models show that accounting for asymptomatic infectious humans through a separate class, or not accounting for the decay in ITN efficacy leads to an underestimation of disease burden. In particular, if the initial efficacy of ITNs against sensitive and resistance mosquitoes is 96%, the minimum ITN coverage required to reduce Rc below one (and hence, contain malaria) is approximately 11% (27%) lower when ITN efficacy is averaged (constant) for a model with a separate asymptomatic class. For the model with a partially immune class and decaying ITN efficacy, reducing Rc below one is impossible even if the entire populace uses ITNs. The study shows that replacing ITNs before their prescribed lifespans, or designing ITNs with longer lifespans is important for malaria control. Furthermore, the study shows that piperonyl butoxide (PBO) ITNs (which inhibit or reverse insecticide resistance) outperform regular ITNs in malaria control. Hence, prospects for effectively controlling malaria are enhanced by widespread use of high quality ITNs (e.g. PBO ITNs), especially if the useful lifespans of the ITNs are long enough and the ITNs are replaced before the end of their useful lifespans.

Modeling malaria transmission in Nepal: impact of imported cases through cross-border mobility

ABSTRACT The cross-border mobility of malaria cases poses an obstacle to malaria elimination programmes in many countries, including Nepal. Here, we develop a novel mathematical model to study how the imported malaria cases through the Nepal-India open-border affect the Nepal government's goal of eliminating malaria by 2026. Mathematical analyses and numerical simulations of our model, validated by malaria case data from Nepal, indicate that eliminating malaria from Nepal is possible if strategies promoting the absence of cross-border mobility, complete protection of transmission abroad, or strict border screening and isolation are implemented. For each strategy, we establish the conditions for the elimination of malaria. We further use our model to identify the control strategies that can help maintain a low endemic level. Our results show that the ideal control strategies should be designed according to the average mosquito biting rates that may depend on the location and season.

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

BackgroundLow-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.MethodsA 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.ResultsOut 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.ConclusionThis 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.

Micro-climate to macro-risk: mapping fine scale differences in mosquito-borne disease risk using remote sensing

Mosquito-borne diseases (MBD) threaten over 80% of the world’s population, and are increasing in intensity and shifting in geographical range with land use and climate change. Mitigation hinges on understanding disease-specific risk profiles, but current risk maps are severely limited in spatial resolution. One important determinant of MBD risk is temperature, and though the relationships between temperature and risk have been extensively studied, maps are often created using sparse data that fail to capture microclimatic conditions. Here, we leverage high resolution land surface temperature (LST) measurements, in conjunction with established relationships between air temperature and MBD risk factors like mosquito biting rate and transmission probability, to produce fine resolution (70 m) maps of MBD risk components. We focus our case study on West Nile virus (WNV) in the San Joaquin Valley of California, where temperatures vary widely across the day and the diverse agricultural/urban landscape. We first use field measurements to establish a relationship between LST and air temperature, and apply it to Ecosystem Spaceborne Thermal Radiometer Experiment data (2018–2020) in peak WNV transmission months (June–September). We then use the previously derived equations to estimate spatially explicit mosquito biting and WNV transmission rates. We use these maps to uncover significant differences in risk across land cover types, and identify the times of day which contribute to high risk for different land covers. Additionally, we evaluate the value of high resolution spatial and temporal data in avoiding biased risk estimates due to Jensen’s inequality, and find that using aggregate data leads to significant biases of up to 40.5% in the possible range of risk values. Through this analysis, we show that the synergy between novel remote sensing technology and fundamental principles of disease ecology can unlock new insights into the spatio-temporal dynamics of MBDs.