Impact of meteorological parameters on mosquito population abundance and distribution in a former malaria endemic area, central Iran

Projection of future malaria prevalence in the upper river region of The Gambia

BACKGROUND

This work investigated the future (2021-2050) impact of Climate Change on Malaria Prevalence in the Upper River Region of The Gambia under two representative concentration pathways, RCP4.5 and RCP8.5, comparing it with the observed evaluation period of 2011-2022.

METHODS

The observed climatic variable data used was obtained from the Department of Water Resources and the corresponding malaria cases from the archive of the primary Health database, Banjul, The Gambia. Projected monthly temperature, precipitation, and relative humidity were downloaded from the coordinated Regional downscaling experiment (CORDEX) stimulation of the Rossby Centre Regional Atmospheric regional climate (RCA4). The dataset spans the decades from 2021 to 2050, providing insight into future climatic and epidemiological trends. Gradient Boost Machine Learning algorithm was utilized for the malaria projection both in the population below 5 and above five years.

RESULTS

The result revealed an increase in malaria incidence under RCP4.5 and RCP8.5 climatic scenarios for both age categories with a clear indication in the population above five years.

DISCUSSION AND CONCLUSION

The result pictures how climate change will impact malaria under RCP4.5 and RCP8.5 emission scenarios in the region and also clearly reveals that the upper river region of the Gambia population is at risk of malaria infection, thus, a strategic and robust intervention scheme is highly solicited.

Evaluation of household coverage with long-lasting insecticidal nets in central Côte d'Ivoire

BACKGROUND

To reduce malaria burden in Côte d'Ivoire, the Ministry of Health aims for 90% of its population to possess one long-lasting insecticidal net (LLIN) for every two persons by 2025. This study evaluated LLIN coverage two years after a mass distribution in central Côte d'Ivoire.

METHODS

A census was conducted in 43 villages. Data were collected on household geo-position, composition, number of sleeping units and LLINs owned. LLIN coverage was assessed using: 1/ownership; proportion of household with at least one LLIN; 2/household access; households with sufficient nets for every two persons and for every sleeping unit; and 3/population access; proportion of population with access to LLIN within households and sleeping units.

RESULTS

10,630 households (89.6% response rate) and 46,619 inhabitants were recruited. Household LLIN ownership was 63.8% (95% CI: 58.7-68.8). Household LLIN access was 37.6% (95% CI: 33.2-42.0) based on 1 LLIN per 2 persons and 37.1% (95% CI: 33.0-41.2) based on 1 net per sleeping unit. Population LLIN access based on 1 LLIN per 2 persons and 1 net per sleeping space was 53.3% (95% CI: 48.6-58.1) and 49.4% (95% CI: 45.1-53.6), respectively. Approximately 17% of households with access for every 2 persons did not have access by every sleeping unit and 9.7% of households with access by sleeping unit did not have access for every 2 persons. Households with adequate access by sleeping unit but not for every 2 persons tend to be larger with fewer sleeping units, and have children under 5 years old and female members. The largest households (>7 members) and households with at least one under-five member had the lowest access (20.8 and 27.3%, respectively).

CONCLUSION

LLIN access was low in this area of intense indoor malaria transmission, 2 years after the last mass distribution campaign. Strategies are needed to improve LLINs coverage.

Impact of Global Climate-Change on Ecology of Anopheles Mosquitoes: A Systematic Review

Background

This study investigated the impact of climate variables on the prevalence of malaria, a climate-sensitive infectious disease.

Methods

A systematic review was conducted on articles published from Mar 2000 to Aug 2023 in Persian and English languages. Overall, 10,731 articles were retrieved, and 58 studies were included in the analysis.

Results

Climate variables such as temperature, rainfall, and humidity play a significant role in predicting malaria outbreaks, with inconsistencies observed in different regions, including Iran. The study highlights the need for tailored preventive.

Conclusion

Strategies and interventions to address the impact of climate change on malaria transmission. Enhanced health system resilience is essential to combat the anticipated rise in malaria cases in the future.

Malaria burden and associated risk factors among malaria suspected patients attending health facilities in Kaffa zone, Southwest Ethiopia

BACKGROUND

Ethiopia has been progressing very well in controlling malaria in the past few years. However, shortly after the COVID-19 pandemic, an unpredictable malaria resurgence was observed in almost all malaria-endemic areas of the country, although the exact cause of which has not yet been identified. Therefore, this study aimed to investigate malaria burden and associated risk factors in one of the endemic zones of Ethiopia.

METHODS

A health facility-based retrospective and cross-sectional study design was conducted in the Kaffa zone, southwest of Ethiopia. Hence, a seven-year retrospective data on malaria positivity rate, interventional activities undertaken in the area, and climatic variables were collected from the patient's medical records, district health bureau, and meteorological institute, respectively. For the cross-sectional study, all malaria-suspected patients seeking medication at the health facilities in the Kaffa Zone administrative centre, Bonga town, during the study period (January-June 2024), were recruited in the study. Data on the patient's socio-demographic, socio-economic, behavioural, health facilities and environmental factors were collected using a structured face-to-face interview questionnaire. Data was analysed using Statistical Package for Social Science software (SPSS) (version 26) and the statistical tools used were descriptive statistics and logistic regression models. A significant level was considered at p < 0.05.

RESULTS

The study findings revealed a significant increment in malaria positivity trend (39.43%, n = 188,201/477,276, p < 0.0001) between July 2018 and June 2024. Also, the malaria positivity rate documented in the cross-sectional study was 50.72% (n = 315/621). Plasmodium falciparum was the dominant malaria parasite. The study identified weakened control measures (p = 0.006), limited awareness of the population (p < 001), and socio-demographic factors such as education (p = 0.037), age (p = 0.008), housing condition (p < 0.0001), low-income level (p < 001), and travel history to malaria-endemic areas (p = 0.001)] as risk factors associated with high malaria positivity rate. In addition, indoor residual spraying (IRS) and mean maximum temperature activity increased by 1 unit, and the malaria positivity rate decreased by 28 times (p < 0.0001) and 1.3 (p = 0.003), respectively. The months of July and September were strongly and positively associated with higher malaria positivity in the area (p < 0.05).

CONCLUSION

Even though Ethiopia was able to achieve a remarkable malaria burden reduction in the past few years, the recent interrupted malaria control activities, seasonal variability, and patient and health facility-associated factors have contributed to the current high malaria positivity rate documented in Kaffa zone, Southwest Ethiopia. This urges the need for immediate community sensitization activities to enhance the awareness of malaria, besides designing integrated vector control interventional strategies to tackle the current alarming situation in the zone.

Effects of Hurricane Irma on mosquito abundance and species composition in a metropolitan Gulf coastal city, 2016-2018

Mosquitoes are the most common disease vectors worldwide. In coastal cities, the spread, activity, and longevity of vector mosquitoes are influenced by environmental factors such as temperature, humidity, and rainfall, which affect their geographic distribution, biting rates, and lifespan. We examined mosquito abundance and species composition before and after Hurricane Irma in Miami, Dade County, Florida, and identified which mosquito species predominated post-Hurricane Irma. Our results showed that mosquito populations increased post-Hurricane Irma: 7.3 and 8.0 times more mosquitoes were captured in 2017 than at baseline, 2016 and 2018 respectively. Warmer temperatures accelerated larval development, resulting in faster emergence of adult mosquitoes. In BG-Sentinel traps, primary species like Ae. tortills, Cx. nigripalpus, and Cx. quinquefasciatus dominated the post-Hurricane Irma period. Secondary vectors that dominated post-Hurricane Irma include An. atropos, An. crucians, An. quadrimaculatus, Cx. erraticus, and Ps. columbiae. After Hurricane Irma, the surge in mosquito populations in Miami, Florida heightened disease risk. To mitigate and prevent future risks, we must enhance surveillance, raise public awareness, and implement targeted vector control measures.

Geometric morphometrics to differentiate species and explore seasonal variation in three Mansonia species (Diptera: Culicidae) in central Thailand and their association with meteorological factors

Mansonia mosquito species are recognised as a significant vector of human pathogens, primarily transmitting the filarial nematode, Brugia malayi. In central Thailand, the three most prevalent Mansonia species are Mansonia annulifera, Mansonia indiana and Mansonia uniformis. This study explored the influence of seasonal changes on the phenotypic variation of these Mansonia species in central Thailand using the geometric morphometrics (GM). To ensure accurate species identification, we integrated GM techniques with DNA barcoding, examining distinctions in both phenotype and genotype among the species. The intraspecific genetic divergence ranged from 0.00% to 1.69%, whereas the interspecific genetic divergence ranged from 10.52% to 16.36%. The clear distinction between intra- and interspecific distances demonstrated the presence of a barcoding gap, confirming the successful differentiation of the three Mansonia mosquito species through DNA barcoding. Similarly, the interspecies GM assessment for classifying Mansonia species demonstrated a high degree of accuracy, with an overall performance of 98.12%. Exploring seasonal variation in the three Mansonia species revealed wing variations across different seasons, and pronounced variations appearing in the cool season. Regarding their association with meteorological factors, Ma. annulifera and Ma. uniformis showed significant positive correlations with temperature (p < 0.05), and Ma. uniformis also displayed a significant negative correlation with atmospheric pressure (p < 0.05). The insights from this study will deepen our understanding of the adaptive patterns of Mansonia mosquitoes in Thailand's central region, paving the way for enhanced disease surveillance related to these vectors.

Shifting spatial, temporal and demographic patterns of dengue incidence and associated meteorological factors in Jazan Region of Saudi Arabia from 2015-2020

BACKGROUND OBJECTIVES

Dengue poses a considerable public health threat in Saudi Arabia, with escalating outbreaks in Jazan, where seasonal rains create ideal mosquito breeding conditions. Elucidating local epidemiological dynamics is imperative to strengthen evidence-based prevention policies. This study analyzed the spatiotemporal, demographic, and meteorological patterns of dengue in Jazan from 2015-2020.

METHODS

This retrospective cross-sectional study utilized surveillance records for 3427 confirmed dengue cases. Descriptive analyses characterized geographic, seasonal, age, gender, and nationality distributions. Forecasting models project expected epidemics through 2025. Regression analysis identified climate factors associated with monthly case counts.

RESULTS

Dengue exhibited shifting seasonal peaks, transitioning into year-round transmission by 2019, indicating endemic establishment. Cases clustered in different high-burden sectors annually, requiring localized vector control. The majority of affected individuals were young male adults, with gender gaps narrowing over time. Saudi nationals had an escalating incidence, but non-citizens showed a higher risk, signaling importation threats. Seasonal outbreaks were associated with temperature, wind speed, and direction.

INTERPRETATION CONCLUSION

Enhanced surveillance, outbreak forecasting, targeted control activities, and integrated prevention policies grounded in continuous evidence assessment can effectively address endemic dengue transmission in Jazan. This study provides key insights to optimize data-driven decision-making for dengue control in Saudi Arabia.

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 1-2 weeks 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.

The monsoon-associated equine South African pointy mosquito 'Aedes caballus'; the first comprehensive record from southeastern Iran with a description of ecological, morphological, and molecular aspects

The equine South African pointy vector mosquito, Aedes caballus, poses a significant threat to human health due to its capacity for transmitting arboviruses. Despite favorable climate for its existence in southeast Iran, previous records of this species in the area have indicated very low abundance. This comprehensive field and laboratory study aimed to assess its current adult population status in this region, utilizing a combination of ecological, morphological and molecular techniques. Four distinct types of traps were strategically placed in three fixed and two variable mosquito sampling sites in the southern strip of Sistan and Baluchistan Province. Subsequently, DNA was extracted from trapped mosquitoes and subjected to PCR amplification using the molecular markers COI, ITS2, and ANT. In total, 1734 adult Ae. caballus specimens were collected from rural areas, with the majority being captured by CO2-baited bednet traps. A notable increase in the abundance of this species was observed following rainfall in February. The genetic analysis revealed multiple haplotypes based on COI and ITS2 sequences, with COI gene divergence at 0.89%, and ITS2 sequence divergence at 1.6%. This suggests that previous challenges in morphological identification may have led to misidentifications, with many adults previously classified as Ae. vexans potentially being Ae. caballus. The findings of this study hold significant implications for public health authorities, providing valuable insights for integrated and targeted vector control and disease management efforts.

Exploring mosquito abundance and Plasmodium infection through nested-PCR: implications for disease surveillance and control

The Plasmodium is responsible for malaria which poses a major health threat, globally. This study is based on the estimation of the relative abundance of mosquitoes, and finding out the correlations of meteorological parameters (temperature, humidity and rainfall) with the abundance of mosquitoes. In addition, this study also focused on the use of nested PCR (species-specific nucleotide sequences of 18S rRNA genes) to explore the Plasmodium spp. in female Anopheles. In the current study, the percentage relative abundance of Culex mosquitoes was 57.65% and Anopheles 42.34% among the study areas. In addition, the highest number of mosquitoes was found in March in district Mandi Bahauddin at 21 °C (Tmax = 27, Tmin = 15) average temperature, 69% average relative humidity and 131 mm rainfall, and these climatic factors were found to affect the abundance of the mosquitoes, directly or indirectly. Molecular analysis showed that overall, 41.3% of the female Anopheles pools were positive for genus Plasmodium. Among species, the prevalence of Plasmodium (P.) vivax (78.1%) was significantly higher than P. falciparum (21.9%). This study will be helpful in the estimation of future risk of mosquito-borne diseases along with population dynamic of mosquitoes to enhance the effectiveness of vector surveillance and control programs.

The Impact of Climatic Factors on Temporal Mosquito Distribution and Population Dynamics in an Area Targeted for Sterile Insect Technique Pilot Trials

It is widely accepted that climate affects the mosquito life history traits; however, its precise role in determining mosquito distribution and population dynamics is not fully understood. This study aimed to investigate the influence of various climatic factors on the temporal distribution of Anopheles arabiensis populations in Mamfene, South Africa between 2014 and 2019. Time series analysis, wavelet analysis, cross-correlation analysis, and regression model combined with the autoregressive integrated moving average (ARIMA) model were utilized to assess the relationship between climatic factors and An. arabiensis population density. In total 3826 adult An. arabiensis collected was used for the analysis. ARIMA (0, 1, 2) (0, 0, 1)12 models closely described the trends observed in An. arabiensis population density and distribution. The wavelet coherence and time-lagged correlation analysis showed positive correlations between An. arabiensis population density and temperature (r = 0.537 ), humidity (r = 0.495) and rainfall (r = 0.298) whilst wind showed negative correlations (r = -0.466). The regression model showed that temperature (p = 0.00119), rainfall (p = 0.0436), and humidity (p = 0.0441) as significant predictors for forecasting An. arabiensis abundance. The extended ARIMA model (AIC = 102.08) was a better fit for predicting An. arabiensis abundance compared to the basic model. Anopheles arabiensis still remains the predominant malaria vector in the study area and climate variables were found to have varying effects on the distribution and abundance of An. arabiensis. This necessitates other complementary vector control strategies such as the Sterile Insect Technique (SIT) which involves releasing sterile males into the environment to reduce mosquito populations. This requires timely mosquito and climate information to precisely target releases and enhance the effectiveness of the program, consequently reducing the malaria risk.

High temperatures and low humidity promote the occurrence of microsporidians (Microsporidia) in mosquitoes (Culicidae)

BACKGROUND

In the context of climate change, a growing concern is that vector-pathogen or host-parasite interactions may be correlated with climatic factors, especially increasing temperatures. In the present study, we used a mosquito-microsporidian model to determine the impact of environmental factors such as temperature, humidity, wind and rainfall on the occurrence rates of opportunistic obligate microparasites (Microsporidia) in hosts from a family that includes important disease vectors (Culicidae).

METHODS

In our study, 3000 adult mosquitoes collected from the field over 3 years were analysed. Mosquitoes and microsporidia were identified using PCR and sequencing of the hypervariable V5 region of the small subunit ribosomal RNA gene and a shortened fragment of the cytochrome c oxidase subunit I gene, respectively.

RESULTS

DNA metabarcoding was used to identify nine mosquito species, all of which were hosts of 12 microsporidian species. The prevalence of microsporidian DNA across all mosquito samples was 34.6%. Microsporidian prevalence in mosquitoes was more frequent during warm months (> 19 °C; humidity < 65%), as was the co-occurrence of two or three microsporidian species in a single host individual. During warm months, microsporidian occurrence was noted 1.6-fold more often than during the cold periods. Among the microsporidians found in the mosquitoes, five (representing the genera Enterocytospora, Vairimorpha and Microsporidium) were positively correlated with an increase in temperature, whereas one (Hazardia sp.) was significantly correlated with a decrease in temperature. Threefold more microsporidian co-occurrences were recorded in the warm months than in the cold months.

CONCLUSIONS

These results suggest that the susceptibility of mosquitoes to parasite occurrence is primarily determined by environmental conditions, such as, for example, temperatures > 19 °C and humidity not exceeding 62%. Collectively, our data provide a better understanding of the effects of the environment on microsporidian-mosquito interactions.

Mosquito Salivary Antigens and Their Relationship to Dengue and P. vivax Malaria

In tropical areas, the simultaneous transmission of multiple vector-borne diseases is common due to ecological factors shared by arthropod vectors. Malaria and dengue virus, transmitted by Anopheles and Aedes mosquitoes, respectively, are among the top vector-borne diseases that cause significant morbidity and mortality in endemic areas. Notably, tropical areas often have suitable conditions for the co-existence of these mosquito species, highlighting the importance of identifying markers that accurately indicate the risk of acquiring each specific disease entity. Aedes are daytime-biting mosquitoes, while Anopheles preferentially bite during the night. These biting patterns raise the possibility of concurrent exposure to bites from both species. This is important because mosquito saliva, deposited in the skin during blood feeding, induces immune responses that modulate pathogen establishment and infection. Previous studies have focused on characterizing such effects on the vector-pathogen interface for an individual pathogen and its mosquito vector. In this study, we evaluated associations between immune responses to salivary proteins from non-dengue and non-malaria vector mosquito species with clinical characteristics of malaria and dengue, respectively. Surprisingly, antibody responses against Anopheles antigens in dengue patients correlated with red blood cell count and hematocrit, while antibody responses against Aedes proteins were associated with platelet count in malaria patients. Our data indicate that concurrent exposure to multiple disease-carrying mosquito vectors and their salivary proteins with differing immunomodulatory properties could influence the transmission, pathogenesis, and clinical presentation of malaria, dengue fever, and other vector-borne illnesses.

Medically Significant Vector-Borne Viral Diseases in Iran

Vector-borne viral diseases (VBVDs) continue to pose a considerable public health risk to animals and humans globally. Vectors have integral roles in autochthonous circulation and dissemination of VBVDs worldwide. The interplay of agricultural activities, population expansion, urbanization, host/pathogen evolution, and climate change, all contribute to the continual flux in shaping the epidemiology of VBVDs. In recent decades, VBVDs, once endemic to particular countries, have expanded into new regions such as Iran and its neighbors, increasing the risk of outbreaks and other public health concerns. Both Iran and its neighboring countries are known to host a number of VBVDs that are endemic to these countries or newly circulating. The proximity of Iran to countries hosting regional diseases, along with increased global socioeconomic activities, e.g., international trade and travel, potentially increases the risk for introduction of new VBVDs into Iran. In this review, we examined the epidemiology of numerous VBVDs circulating in Iran, such as Chikungunya virus, Dengue virus, Sindbis virus, West Nile virus, Crimean-Congo hemorrhagic fever virus, Sandfly-borne phleboviruses, and Hantavirus, in relation to their vectors, specifically mosquitoes, ticks, sandflies, and rodents. In addition, we discussed the interplay of factors, e.g., urbanization and climate change on VBVD dissemination patterns and the consequent public health risks in Iran, highlighting the importance of a One Health approach to further surveil and to evolve mitigation strategies.

Effective population size of Culex quinquefasciatus under insecticide-based vector management and following Hurricane Harvey in Harris County, Texas

Introduction: Culex quinquefasciatus is a mosquito species of significant public health importance due to its ability to transmit multiple pathogens that can cause mosquito-borne diseases, such as West Nile fever and St. Louis encephalitis. In Harris County, Texas, Cx. quinquefasciatus is a common vector species and is subjected to insecticide-based management by the Harris County Public Health Department. However, insecticide resistance in mosquitoes has increased rapidly worldwide and raises concerns about maintaining the effectiveness of vector control approaches. This concern is highly relevant in Texas, with its humid subtropical climate along the Gulf Coast that provides suitable habitat for Cx. quinquefasciatus and other mosquito species that are known disease vectors. Therefore, there is an urgent and ongoing need to monitor the effectiveness of current vector control programs. Methods: In this study, we evaluated the impact of vector control approaches by estimating the effective population size of Cx. quinquefasciatus in Harris County. We applied Approximate Bayesian Computation to microsatellite data to estimate effective population size. We collected Cx. quinquefasciatus samples from two mosquito control operation areas; 415 and 802, during routine vector monitoring in 2016 and 2017. No county mosquito control operations were applied at area 415 in 2016 and 2017, whereas extensive adulticide spraying operations were in effect at area 802 during the summer of 2016. We collected data for eighteen microsatellite markers for 713 and 723 mosquitoes at eight timepoints from 2016 to 2017 in areas 415 and 802, respectively. We also investigated the impact of Hurricane Harvey's landfall in the Houston area in August of 2017 on Cx. quinquefasciatus population fluctuation. Results: We found that the bottleneck scenario was the most probable historical scenario describing the impact of the winter season at area 415 and area 802, with the highest posterior probability of 0.9167 and 0.4966, respectively. We also detected an expansion event following Hurricane Harvey at area 802, showing a 3.03-fold increase in 2017. Discussion: Although we did not detect significant effects of vector control interventions, we found considerable influences of the winter season and a major hurricane on the effective population size of Cx. quinquefasciatus. The fluctuations in effective population size in both areas showed a significant seasonal pattern. Additionally, the significant population expansion following Hurricane Harvey in 2017 supports the necessity for post-hurricane vector-control interventions.

Time lag effect on malaria transmission dynamics in an Amazonian Colombian municipality and importance for early warning systems

Malaria remains a significant public health problem worldwide, particularly in low-income regions with limited access to healthcare. Despite the use of antimalarial drugs, transmission remains an issue in Colombia, especially among indigenous populations in remote areas. In this study, we used an SIR Ross MacDonald model that considered land use change, temperature, and precipitation to analyze eco epidemiological parameters and the impact of time lags on malaria transmission in La Pedrera-Amazonas municipality. We found changes in land use between 2007 and 2020, with increases in forested areas, urban infrastructure and water edges resulting in a constant increase in mosquito carrying capacity. Temperature and precipitation variables exhibited a fluctuating pattern that corresponded to rainy and dry seasons, respectively and a marked influence of the El Niño climatic phenomenon. Our findings suggest that elevated precipitation and temperature increase malaria infection risk in the following 2 months. The risk is influenced by the secondary vegetation and urban infrastructure near primary forest formation or water body edges. These results may help public health officials and policymakers develop effective malaria control strategies by monitoring precipitation, temperature, and land use variables to flag high-risk areas and critical periods, considering the time lag effect.

The influence of weather on the population dynamics of common mosquito vector species in the Canadian Prairies

BACKGROUND

Mosquito seasonal activity is largely driven by weather conditions, most notably temperature, precipitation, and relative humidity. The extent by which these weather variables influence activity is intertwined with the animal's biology and may differ by species. For mosquito vectors, changes in weather can also alter host-pathogen interactions thereby increasing or decreasing the burden of disease.

METHODS

In this study, we performed weekly mosquito surveillance throughout the active season over a 2-year period in Manitoba, Canada. We then used Generalized Linear Mixed Models (GLMMs) to explore the relationships between weather variables over the preceding 2 weeks and mosquito trap counts for four of the most prevalent vector species in this region: Oc. dorsalis, Ae. vexans, Cx. tarsalis, and Cq. perturbans.

RESULTS

More than 265,000 mosquitoes were collected from 17 sampling sites throughout Manitoba in 2020 and 2021, with Ae. vexans the most commonly collected species followed by Cx. tarsalis. Aedes vexans favored high humidity, intermediate degree days, and low precipitation. Coquillettidia perturbans and Oc. dorsalis activity increased with high humidity and high rainfall, respectively. Culex tarsalis favored high degree days, with the relationship between number of mosquitoes captured and precipitation showing contrasting patterns between years. Minimum trapping temperature only impacted Ae. vexans and Cq. perturbans trap counts.

CONCLUSIONS

The activity of all four mosquito vectors was affected by weather conditions recorded in the 2 weeks prior to trapping, with each species favoring different conditions. Although some research has been done to explore the relationships between temperature/precipitation and Cx. tarsalis in the Canadian Prairies, to our knowledge this is the first study to investigate other commonly found vector species in this region. Overall, this study highlights how varying weather conditions can impact mosquito activity and in turn species-specific vector potential.

Effects of temperature, relative humidity, and illumination on the entomological parameters of Aedes albopictus: an experimental study

Aedes albopictus (Diptera: Culicidae) is a mosquito from Asia that can transmit a variety of diseases. This paper aimed to explore the effects of temperature, relative humidity, and illumination on the entomological parameters related to the population growth of Aedes albopictus, and provide specific parameters for developing dynamic models of mosquito-borne infectious disease. We used artificial simulation lab experiments, and set 27 different meteorological conditions to observe and record mosquito's hatching time, emergence time, longevity of adult females, and oviposition amount. We then applied generalized additive model (GAM) and polynomial regression to formulate the effects of temperature, relative humidity, and illumination on the biological characteristics of Aedes albopictus. Our results showed that hatchability closely related to temperature and illumination. The immature stage and the survival time of adult female mosquitoes were associated with temperature and relative humidity. The oviposition rate related to temperature, relative humidity, and illumination. Under the control of relative humidity and illumination, ecological characteristics of mosquitoes such as hatching rate, transition rate, longevity, and oviposition rate had an inverted J shape with temperature, and the thresholds were 31.2 °C, 32.1 °C, 17.7 °C, and 25.7 °C, respectively. The parameter expressions of Aedes albopictus using meteorological factors as predictors under different stages were established. Meteorological factors especially temperature significantly influence the development of Aedes albopictus under different physiological stages. The established formulas of ecological parameters can provide important information for modeling mosquito-borne infectious diseases.

Semi-field evaluation of human landing catches versus human double net trap for estimating human biting rate of Anopheles minimus and Anopheles harrisoni in Thailand

Background

Whilst the human landing catch (HLC) technique is considered the 'gold standard' for estimating human-biting rates, it is labor-intensive and fraught with potential risk of exposure to infectious mosquito bites. This study evaluated the feasibility and performance of an alternative method, the human double net trap (HDNT) relative to HLC for monitoring host-seeking malaria vectors of the Anopheles minimus complex in a semi-field system (SFS).

Methods

HDNT and HLC were positioned in two rooms, 30 m apart at both ends of the SFS. Two human volunteers were rotated between both traps and collected released mosquitoes (n = 100) from 6:00 pm till 6:00 am. Differences in Anopheles mosquito densities among the trapping methods were compared using a generalized linear model based on a negative binomial distribution.

Results

There were 82.80% (2,136/2,580) of recaptures of wild-caught and 94.50% (2,835/3,000) of laboratory-reared mosquitoes that were molecularly identified as An. harrisoni and An. minimus, respectively. Mean density of An. harrisoni was significantly lower in HNDT (15.50 per night, 95% CI [12.48-18.52]) relative to HLC (25.32 per night (95% CI [22.28-28.36]), p < 0.001). Similarly, the mean density of a laboratory strain of An. minimus recaptured in HDNT was significantly lower (37.87 per night, 95% CI [34.62-41.11]) relative to HLC (56.40 per night, 95% CI [55.37-57.43]), p < 0.001. Relative sampling efficiency analysis showed that HLC was the more efficient trap in collecting the An. minimus complex in the SFS.

Conclusion

HDNT caught proportionately fewer An. minimus complex than HLC. HDNT was not sensitive nor significantly correlated with HLC, suggesting that it is not an alternative method to HLC.