Modelling the effect of temperature on the seasonal population dynamics of temperate mosquitoes

Spotting Culex pipiens from satellite: modeling habitat suitability in central Italy using Sentinel-2 and deep learning techniques

Culex pipiens, an important vector of many vector borne diseases, is a species capable to feeding on a wide variety of hosts and adapting to different environments. To predict the potential distribution of Cx. pipiens in central Italy, this study integrated presence/absence data from a four-year entomological survey (2019-2022) carried out in the Abruzzo and Molise regions, with a datacube of spectral bands acquired by Sentinel-2 satellites, as patches of 224 × 224 pixels of 20 meters spatial resolution around each site and for each satellite revisit time. We investigated three scenarios: the baseline model, which considers the environmental conditions at the time of collection; the multitemporal model, focusing on conditions in the 2 months preceding the collection; and the MultiAdjacency Graph Attention Network (MAGAT) model, which accounts for similarities in temperature and nearby sites using a graph architecture. For the baseline scenario, a deep convolutional neural network (DCNN) analyzed a single multi-band Sentinel-2 image. The DCNN in the multitemporal model extracted temporal patterns from a sequence of 10 multispectral images; the MAGAT model incorporated spatial and climatic relationships among sites through a graph neural network aggregation method. For all models, we also evaluated temporal lags between the multi-band Earth Observation datacube date of acquisition and the mosquito collection, from 0 to 50 days. The study encompassed a total of 2,555 entomological collections, and 108,064 images (patches) at 20 meters spatial resolution. The baseline model achieved an F1 score higher than 75.8% for any temporal lag, which increased up to 81.4% with the multitemporal model. The MAGAT model recorded the highest F1 score of 80.9%. The study confirms the widespread presence of Cx. pipiens throughout the majority of the surveyed area. Utilizing only Sentinel-2 spectral bands, the models effectively capture early in advance the temporal patterns of the mosquito population, offering valuable insights for directing surveillance activities during the vector season. The methodology developed in this study can be scaled up to the national territory and extended to other vectors, in order to support the Ministry of Health in the surveillance and control strategies for the vectors and the diseases they transmit.

The effect of temperature on the boundary conditions of West Nile virus circulation in Europe

West Nile virus (WNV) is a vector-borne flavivirus that causes an increasing number of human and equine West Nile fever cases in Europe. While the virus has been present in the Mediterranean basin and the Balkans since the 1960s, recent years have witnessed its northward expansion, with the first human cases reported in Germany in 2018 and the Netherlands in 2020. WNV transmission and amplification within mosquitoes are temperature-dependent. This study applies a mathematical modelling approach to assess the conditions under which WNV circulation occurs based on the proportion of mosquito bites on WNV-competent birds (dilution), vector-host ratios, mosquito season length and the observed daily temperature data. We modelled five distinct European regions where previous WNV circulation has been observed within the Netherlands, Germany, Spain, Italy, and Greece. We observed that the number of days in which the basic reproduction number (R0) is above one, increased over the last 40 years in all five regions. In the Netherlands, the number of days in which the R0 is above one, is 70% lower than in Spain. The temperature in Greece, Spain and Italy allowed for circulation under low vector-host ratios, and at a high dilution. On the other hand in the Netherlands and Germany, given the observed daily temperature, the thresholds for circulation requires a lower dilution and higher vector-host ratios. For the Netherlands, a short window of introductions between late May and mid-June would result in detectable outbreaks. Our findings revealed that the temperate maritime climate of the Netherlands allows WNV circulation primarily during warmer summers, and only under high vector-host ratios. This research contributes valuable insights into the dynamic relationship between temperature, vector properties, and WNV transmission, offering guidance for proactive strategies in addressing this emerging health threat in Europe.

Transmission dynamics of a reaction-advection-diffusion dengue fever model with seasonal developmental durations and intrinsic incubation periods

In this paper, we propose a reaction-advection-diffusion dengue fever model with seasonal developmental durations and intrinsic incubation periods. Firstly, we establish the well-posedness of the model. Secondly, we define the basic reproduction number ℜ 0 for this model and show that ℜ 0 is a threshold parameter: ifℜ 0 < 1 , then the disease-free periodic solution is globally attractive; ifℜ 0 > 1 , the system is uniformly persistent. Thirdly, we study the global attractivity of the positive steady state when the spatial environment is homogeneous and the advection of mosquitoes is ignored. As an example, we use the model to investigate the dengue fever transmission case in Guangdong Province, China, and explore the impact of model parameters on ℜ 0 . Our findings indicate that ignoring seasonality may underestimate ℜ 0 . Additionally, the spatial heterogeneity of transmission may increase the risk of disease transmission, while the increase of seasonal developmental durations, intrinsic incubation periods and advection rates can all reduce the risk of disease transmission.

Selection of summer feeding sites and food resources by female migratory caribou (Rangifer tarandus) determined using camera collars

Migratory caribou (Rangifer tarandus) is a socioeconomically and culturally key species for northern communities in the Arctic, and most of its populations are experiencing a sharp decline. Female migratory caribou depend on the availability of summer habitat resources to meet the needs associated with lactation and the accumulation of fat reserves to survive when resources are less abundant. Because of the large scales at which habitat and resource data are usually available, information on how female migratory caribou select habitat and resources at fine scales in the wild is lacking. To document selection of summer feeding sites, we equipped 60 female caribou with camera collars from 2016 to 2018. We collected a total of 65,150 10-sec videos between June 1st and September 1st for three years with contrasted spring phenology. We determined the selection at the feeding site scale (3rd scale of Johnson) and food item scale (4th scale of Johnson) using resource selection probability functions. Wetlands were highly selected as feeding sites in June and July while they were avoided in August. Shrublands were mostly selected in July and August. At the resources scale, lichen, birch, willow, and mushrooms were the most strongly selected resources. Our results provide precise and novel information on habitat selection at feeding sites and food resources selected by female caribou in the wild. This information will help understand foraging patterns and habitat selection behavior of female migratory caribou and will contribute to the management and conservation of its declining populations.

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.

Spatial distribution and temporal dynamics of invasive and native mosquitoes in a large Mediterranean city

Mosquitoes, including invasive species like the Asian tiger mosquito Aedes albopictus, alongside native species Culex pipiens s.l., pose a significant nuisance to humans and serve as vectors for mosquito-borne diseases in urban areas. Understanding the impact of water infrastructure characteristics, climatic conditions, and management strategies on mosquito occurrence and effectiveness of control measures to assess their implications on mosquito occurrence is crucial for effective vector control. In this study, we examined data collected during the local vector control program in Barcelona, Spain, focusing on 234,225 visits to 31,334 different sewers, as well as 1817 visits to 152 fountains between 2015 and 2019. We investigated both the colonization and recolonization processes of mosquito larvae within these water infrastructures. Our findings revealed higher larval presence in sandbox-sewers compared to siphonic or direct sewers, and the presence of vegetation and the use of naturalized water positively influenced larval occurrence in fountains. The application of larvicidal treatment significantly reduced larvae presence; however, recolonization rates were negatively affected by the time elapsed since treatment. Climatic conditions played a critical role in the colonization and recolonization of sewers and urban fountains, with mosquito occurrence exhibiting non-linear patterns and, generally, increasing at intermediate temperatures and accumulated rainfall levels. This study emphasizes the importance of considering sewers and fountains characteristics and climatic conditions when implementing vector control programs to optimize resources and effectively reduce mosquito populations.

Periodic temporal environmental variations induce coexistence in resource competition models

Natural ecosystems, in particular on the microbial scale, are inhabited by a large number of species. The population size of each species is affected by interactions of individuals with each other and by spatial and temporal changes in environmental conditions, such as resource abundance. Here, we use a generic population dynamics model to study how, and under what conditions, a periodic temporal environmental variation can alter an ecosystem's composition and biodiversity. We demonstrate that using timescale separation allows one to qualitatively predict the long-term population dynamics of interacting species in varying environments. We show that the notion of Tilman's R* rule, a well-known principle that applies for constant environments, can be extended to periodically varying environments if the timescale of environmental changes (e.g., seasonal variations) is much faster than the timescale of population growth (doubling time in bacteria). When these timescales are similar, our analysis shows that a varying environment deters the system from reaching a steady state, and stable coexistence between multiple species becomes possible. Our results posit that biodiversity can in part be attributed to natural environmental variations.

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.

Linking mathematical models and trap data to infer the proliferation, abundance, and control of Aedes aegypti

Aedes aegypti is one of the most dominant mosquito species in the urban areas of Miami-Dade County, Florida, and is responsible for the local arbovirus transmissions. Since August 2016, mosquito traps have been placed throughout the county to improve surveillance and guide mosquito control and arbovirus outbreak response. In this paper, we develop a deterministic mosquito population model, estimate model parameters by using local entomological and temperature data, and use the model to calibrate the mosquito trap data from 2017 to 2019. We further use the model to compare the Ae. aegypti population and evaluate the impact of rainfall intensity in different urban built environments. Our results show that rainfall affects the breeding sites and the abundance of Ae. aegypti more significantly in tourist areas than in residential places. In addition, we apply the model to quantitatively assess the effectiveness of vector control strategies in Miami-Dade County.

The role of temperature in shaping Culex acharistus mosquitoes life history traits in its southern limit of distribution (Patagonia-Argentina)

There is substantial evidence showing that temperature have a great impact on insects behavior, phenology and life histories. Because of mosquito global importance as disease vectors, in temperate regions where climatic conditions could be only borderline suitable for mosquito development, there is a growing interest in understanding the effect of temperature shifts on vital statistics to more accurately define how such changes could impact distribution and abundance patterns, as well as disease transmission cycles. We determined the role of ambient temperature under fluctuating conditions in shaping Culex acharistus (Diptera: Culicidae) life history traits, and estimated its development threshold and physiological time, in its southern limit of distribution in the Argentine Patagonia region. Four horizontal life tables were conducted under natural fluctuating temperature range in Esquel city (42°S - 71°W; 563 m a.s.l.), during spring-summer (17°C), summer (15.4°C), summer-autumn (12.7°C) and autumn-winter (5.6°C) seasons. Larvae, pupae and adult traits were recorded. The mean duration of the experiments varied between 28 to ≅100 days for spring-summer and autumn-winter seasons. Only during the cold season experiment pupae experienced the most severe temperatures and freeze-thaw cycles, and failed to reach adult stage. We found that larva and pupa development time, adult emergence time and longevity significantly increased with decreasing temperatures, while larval survival was greatest at an intermediate temperature and decreased toward low and high values. Also, protandry was observed and males emerge 2 days before females across seasons. Temperature development threshold and physiological time estimated for larva + pupa were 5.98°C and 211.24°C-days. Our study contributes to a growing body of knowledge by examining the effect of seasonal changes in temperature on mosquito life history traits. Results obtained here can be applied as useful parameters in the development of population dynamic models, improving current mosquito control strategies in cold-temperate regions.

Diel activity patterns of vector mosquito species in the urban environment: Implications for vector control strategies

Mathematical models have been widely used to study the population dynamics of mosquitoes as well as to test and validate the effectiveness of arbovirus outbreak responses and mosquito control strategies. The objective of this study is to assess the diel activity of mosquitoes in Miami-Dade, Florida, and Brownsville, Texas, the most affected areas during the Zika outbreak in 2016-2017, and to evaluate the effectiveness of simulated adulticide treatments on local mosquito populations. To assess variations in the diel activity patterns, mosquitoes were collected hourly for 96 hours once a month from May through November 2019 in Miami-Dade County, Florida, and Brownsville, Texas. We then performed a PERMANOVA followed by a SIMPER analysis to assess whether the abundance and species richness significantly varies at different hours of the day. Finally, we used a mathematical model to simulate the population dynamics of 5 mosquito vector species and evaluate the effectiveness of the simulated adulticide applications. A total of 14,502 mosquitoes comprising 17 species were collected in Brownsville and 10,948 mosquitoes comprising 19 species were collected in Miami-Dade County. Aedes aegypti was the most common mosquito species collected every hour in both cities and peaking in abundance in the morning and the evening. Our modeling results indicate that the effectiveness of adulticide applications varied greatly depending on the hour of the treatment. In both study locations, 9 PM was the best time for adulticide applications targeting all mosquito vector species; mornings/afternoons (9 AM- 5 PM) yielded low effectiveness, especially for Culex species, while at night (12 AM- 6 AM) the effectiveness was particularly low for Aedes species. Our results indicate that the timing of adulticide spraying interventions should be carefully considered by local authorities based on the ecology of the target mosquito species in the focus area.

Dynamics of a multi-strain malaria model with diffusion in a periodic environment

This paper mainly explores the complex impacts of spatial heterogeneity, vector-bias effect, multiple strains, temperature-dependent extrinsic incubation period (EIP) and seasonality on malaria transmission. We propose a multi-strain malaria transmission model with diffusion and periodic delays and define the reproduction numbers Ri and R^i (i = 1, 2). Quantitative analysis indicates that the disease-free ω-periodic solution is globally attractive when Ri<1, while if Ri>1>Rj (i≠j,i,j=1,2), then strain i persists and strain j dies out. More interestingly, when R1 and R2 are greater than 1, the competitive exclusion of the two strains also occurs. Additionally, in a heterogeneous environment, the coexistence conditions of the two strains are R^1>1 and R^2>1. Numerical simulations verify the analytical results and reveal that ignoring vector-bias effect or seasonality when studying malaria transmission will underestimate the risk of disease transmission.

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

Temperature sensitivity of pest reproductive numbers in age-structured PDE models, with a focus on the invasive spotted lanternfly

Invasive pest establishment is a pervasive threat to global ecosystems, agriculture, and public health. The recent establishment of the invasive spotted lanternfly in the northeastern United States has proven devastating to farms and vineyards, necessitating urgent development of population dynamical models and effective control practices. In this paper, we propose a stage-age-structured system of PDEs to model insect pest populations, in which underlying dynamics are dictated by ambient temperature through rates of development, fecundity, and mortality. The model incorporates diapause and non-diapause pathways, and is calibrated to experimental and field data on the spotted lanternfly. We develop a novel moving mesh method for capturing age-advection accurately, even for coarse discretization parameters. We define a one-year reproductive number ([Formula: see text]) from the spectrum of a one-year solution operator, and study its sensitivity to variations in the mean and amplitude of the annual temperature profile. We quantify assumptions sufficient to give rise to the low-rank structure of the solution operator characteristic of part of the parameter domain. We discuss establishment potential as it results from the pairing of a favorable [Formula: see text] value and transient population survival, and address implications for pest control strategies.

An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China

As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011-2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever.

Artificial intelligence to predict West Nile virus outbreaks with eco-climatic drivers

Background

In Europe, the frequency, intensity, and geographic range of West Nile virus (WNV)-outbreaks have increased over the past decade, with a 7.2-fold increase in 2018 compared to 2017, and a markedly expanded geographic area compared to 2010. The reasons for this increase and range expansion remain largely unknown due to the complexity of the transmission pathways and underlying disease drivers. In a first, we use advanced artificial intelligence to disentangle the contribution of eco-climatic drivers to WNV-outbreaks across Europe using decade-long (2010-2019) data at high spatial resolution.

Methods

We use a high-performance machine learning classifier, XGBoost (eXtreme gradient boosting) combined with state-of-the-art XAI (eXplainable artificial intelligence) methodology to describe the predictive ability and contribution of different drivers of the emergence and transmission of WNV-outbreaks in Europe, respectively.

Findings

Our model, trained on 2010-2017 data achieved an AUC (area under the receiver operating characteristic curve) score of 0.97 and 0.93 when tested with 2018 and 2019 data, respectively, showing a high discriminatory power to classify a WNV-endemic area. Overall, positive summer/spring temperatures anomalies, lower water availability index (NDWI), and drier winter conditions were found to be the main determinants of WNV-outbreaks across Europe. The climate trends of the preceding year in combination with eco-climatic predictors of the first half of the year provided a robust predictive ability of the entire transmission season ahead of time. For the extraordinary 2018 outbreak year, relatively higher spring temperatures and the abundance of Culex mosquitoes were the strongest predictors, in addition to past climatic trends.

Interpretation

Our AI-based framework can be deployed to trigger rapid and timely alerts for active surveillance and vector control measures in order to intercept an imminent WNV-outbreak in Europe.

Funding

The work was partially funded by the Swedish Research Council FORMAS for the project ARBOPREVENT (grant agreement 2018-05973).

Modeling the effect of rainfall changes to predict population dynamics of the Asian tiger mosquito Aedes albopictus under future climate conditions

The population dynamics of mosquitoes in temperate regions are not as well understood as those in tropical and subtropical regions, despite concerns that vector-borne diseases may be prevalent in future climates. Aedes albopictus, a vector mosquito in temperate regions, undergoes egg diapause while overwintering. To assess the prevalence of mosquito-borne diseases in the future, this study aimed to simulate and predict mosquito population dynamics under estimated future climatic conditions. In this study, we tailored the physiology-based climate-driven mosquito population (PCMP) model for temperate mosquitoes to incorporate egg diapauses for overwintering. We also investigated how the incorporation of the effect of rainfall on larval carrying capacity (into a model) changes the population dynamics of this species under future climate conditions. The PCMP model was constructed to simulate mosquito population dynamics, and the parameters of egg diapause and rainfall effects were estimated for each model to fit the observed data in Tokyo. We applied the global climate model data to the PCMP model and observed an increase in the mosquito population under future climate conditions. By applying the PCMP models (with or without the rainfall effect on the carrying capacity of the A. albopictus), our projections indicated that mosquito population dynamics in the future could experience changes in the patterns of their active season and population abundance. According to our results, the peak population number simulated using the highest CO₂ emission scenario, while incorporating the rainfall effect on the carrying capacity, was approximately 1.35 times larger than that predicted using the model that did not consider the rainfall effect. This implies that the inclusion of rainfall effects on mosquito population dynamics has a major impact on the risk assessments of mosquito-borne diseases in the future.

Modeling Temperature-Dependent Development Rate in Insects and Implications of Experimental Design

Characterizing the temperature-dependent development rate requires empirical data acquired by rearing individuals at different temperatures. Many mathematical models can be fitted to empirical data, making model comparison a mandatory step, yet model selection practices widely vary. We present guidelines for model selection using statistical criteria and the assessment of biological relevance of fits, exemplified throughout a Lepidoptera pest dataset. We also used in silico experiments to explore how experimental design and species attributes impact estimation accuracy of biological traits. Our results suggested that the uncertainty in model predictions was mostly determined by the rearing effort and the variance in development times of individuals. We found that a higher number of tested temperatures instead of a higher sample size per temperature may lead to more accurate estimations of model parameters. Our simulations suggested that an inappropriate model choice can lead to biased estimated values of biological traits (defined as attributes of temperature dependent development rate, i.e., optimal temperature for development and critical thresholds), highlighting the need for standardized model selection methods. Therefore, our results have direct implications for future studies on the temperature-dependent development rate of insects.

Dynamic analysis of a malaria reaction-diffusion model with periodic delays and vector bias

One of the most important vector-borne disease in humans is malaria, caused by Plasmodium parasite. Seasonal temperature elements have a major effect on the life development of mosquitoes and the development of parasites. In this paper, we establish and analyze a reaction-diffusion model, which includes seasonality, vector-bias, temperature-dependent extrinsic incubation period (EIP) and maturation delay in mosquitoes. In order to get the model threshold dynamics, a threshold parameter, the basic reproduction number $ R_{0} $ is introduced, which is the spectral radius of the next generation operator. Quantitative analysis indicates that when $ R_{0} < 1 $, there is a globally attractive disease-free $ \omega $-periodic solution; disease is uniformly persistent in humans and mosquitoes if $ R_{0} > 1 $. Numerical simulations verify the results of the theoretical analysis and discuss the effects of diffusion and seasonality. We study the relationship between the parameters in the model and $ R_{0} $. More importantly, how to allocate medical resources to reduce the spread of disease is explored through numerical simulations. Last but not least, we discover that when studying malaria transmission, ignoring vector-bias or assuming that the maturity period is not affected by temperature, the risk of disease transmission will be underestimate.

Influence of climate variables on dengue fever occurrence in the southern region of Thailand

The 3-5year epidemic cycle of dengue fever in Thailand makes it a major re-emerging public health problem resulting in being a burden in endemic areas. Although the Thai Ministry of Public Health adopted the WHO dengue control strategy, all dengue virus serotypes continue to circulate. Health officers and village health volunteers implement some intervention options but there is a need to ascertain most appropriate (or a combination of) interventions regarding the environment and contextual factors that may undermine the effectiveness of such interventions. This study aims to understand the dengue-climate relationship patterns at the district level in the southern region of Thailand from 2002 to 2018 by examining the statistical association between dengue incidence rate and eight environmental patterns, testing the hypothesis of equal incidence of these. Data on environmental variables and dengue reported cases in Nakhon Si Thammarat province situated in the south of Thailand from 2002 to 2018 were analysed to (1) detect the environmental factors that affect the risk of dengue infectious disease; to (2) determine if disease risk is increasing or decreasing over time; and to (3) identify the high-risk district areas for dengue cases that need to be targeted for interventions. To identify the predictors that have a high and significant impact on reported dengue infection, three steps of analysis were used. First, we used Partial Least Squares (PLS) Regression and Poisson Regression, a variant of the Generalized Linear Model (GLM). Negative co-efficient in correspondence with the PLS components suggests that sea-level pressure, wind speed, and pan evaporation are associated with dengue occurrence rate, while other variables were positively associated. Using the Akaike information criterion in the stepwise GLM, the filtered predictors were temperature, precipitation, cloudiness, and sea level pressure with the standardized coefficients showing that the most influential variable is cloud cover (three times more than temperature and precipitation). Also, dengue occurrence showed a constant negative response to the average increase in sea-level pressure values. In southern Thailand, the predictors that have been locally determined to drive dengue occurrence are temperature, rainfall, cloud cover, and sea-level pressure. These explanatory variables should have important future implications for epidemiological studies of mosquito-borne diseases, particularly at the district level. Predictive indicators guide effective and dynamic risk assessments, targeting pre-emptive interventions.

West Nile virus in Spain: Forecasting the geographical distribution of risky areas with an ecological niche modelling approach

West Nile virus (WNV), a well-known emerging vector-borne arbovirus with a zoonotic life cycle, represents a threat to both public and animal health. Transmitted by ornithophilic mosquitoes, its transmission is difficult to predict and even more difficult to prevent. The massive and unprecedented number of human cases and equid outbreaks in Spain during 2020 interpellates for new approaches. For the first time, we present an integrate analysis from a niche perspective to provide an insight to the situation of West Nile disease (WND) in Spain. Our modelling approach benefits from the combined use of global occurrence records of outbreaks of WND in equids and of its two alleged main vectors in Spain, Culex pipiens and Cx. perexiguus. Maps of the climatic suitability for the presence of the two vectors species and for the circulation of WNV are provided. The main outcome of our study is a map delineating the areas under certain climatic risk of transmission. Our analyses indicate that the climatic risk of transmission of WND is medium in areas nearby the south Atlantic coastal area of the Cadiz Gulf and the Mediterranean coast, and high in southwestern Spain. The higher risk of transmission in the basins of the rivers Guadiana and Guadalquivir cannot be attributed exclusively to the local abundance of Cx. pipiens, but could be ascribed to the presence and abundance of Cx. perexiguus. Furthermore, this integrated analysis suggests that the WNV presents an ecological niche of its own, not fully overlapping the ones of its hosts or vector, and thus requiring particular environmental conditions to succeed in its infection cycle.

Red deer reveal spatial risks of Crimean-Congo haemorrhagic fever virus infection

Crimean-Congo haemorrhagic fever virus (CCHFV) continues to cause new human cases in Iberia while its spatial distribution and ecological determinants remain unknown. The virus remains active in a silent tick-animal cycle to which animals contribute maintaining the tick populations and the virus itself. Wild ungulates, in particular red deer, are essential hosts for Hyalomma ticks in Iberia, which are the principal competent vector of CCHFV. Red deer could be an excellent model to understand the ecological determinants of CCHFV as well as to predict infection risks for humans because it is large, gregarious, abundant and the principal host for Hyalomma lusitanicum. We designed a cross-sectional study, analysed the presence of CCHFV antibodies in 1444 deer from 82 populations, and statistically modelled exposure risk with host and environmental predictors. The best-fitted statistical model was projected for peninsular Spain to map infection risks. Fifty out of 82 deer populations were seropositive, with individual population prevalence as high as 88%. The highest prevalence of exposure to CCHFV occurred in the southwest of the Iberian Peninsula. Climate and ungulate abundance were the most influential predictors of the risk of exposure to the virus. The highest risk regions were those where H. lusitanicum is most abundant. Eight of the nine primary human cases occurred in or bordering these regions, demonstrating that the model predicts human infection risk accurately. A recent human case of CCHF occurred in northwestern Spain, a region that the model predicted as low risk, pointing out that it needs improvement to capture all determinants of the CCHFV infection risk. In this study, we have been able to identify the main ecological determinants of CCHFV, and we have also managed to create an accurate model to assess the risk of CCHFV infection.

Molecular mechanisms and treatment modalities in equine Culicoides hypersensitivity

Equine Culicoides hypersensitivity (CH) is the most common allergic condition in horses affecting the skin. This review focuses on immunopathology and molecular mechanisms of equine CH. The role of eosinophils is emphasized, as well as disease severity and the influence of long-term chronic allergen exposure on T helper (Th) 2 cells. Using current knowledge from human allergic disorders, similar effects are hypothesized in equine patients. Key aspects of CH diagnosis and treatment are discussed, focusing on allergen specific immunotherapy and allergen-independent approaches, such as targeting hypereosinophilia through interleukin-5 and allergic non-histaminic pruritus though interleukin-31.

Phenotypic plasticity as a cause and consequence of population dynamics

Predicting complex species-environment interactions is crucial for guiding conservation and mitigation strategies in a dynamically changing world. Phenotypic plasticity is a mechanism of trait variation that determines how individuals and populations adapt to changing and novel environments. For individuals, the effects of phenotypic plasticity can be quantified by measuring environment-trait relationships, but it is often difficult to predict how phenotypic plasticity affects populations. The assumption that environment-trait relationships validated for individuals indicate how populations respond to environmental change is commonly made without sufficient justification. Here we derive a novel general mathematical framework linking trait variation due to phenotypic plasticity to population dynamics. Applying the framework to the classical example of Nicholson's blowflies, we show how seemingly sensible predictions made from environment-trait relationships do not generalise to population responses. As a consequence, trait-based analyses that do not incorporate population feedbacks risk mischaracterising the effect of environmental change on populations.

A Temperature Conditioned Markov Chain Model for Predicting the Dynamics of Mosquito Vectors of Disease

Understanding and predicting mosquito population dynamics is crucial for gaining insight into the abundance of arthropod disease vectors and for the design of effective vector control strategies. In this work, a climate-conditioned Markov chain (CMC) model was developed and applied for the first time to predict the dynamics of vectors of important medical diseases. Temporal changes in mosquito population profiles were generated to simulate the probabilities of a high population impact. The simulated transition probabilities of the mosquito populations achieved from the trained model are very near to the observed data transitions that have been used to parameterize and validate the model. Thus, the CMC model satisfactorily describes the temporal evolution of the mosquito population process. In general, our numerical results, when temperature is considered as the driver of change, indicate that it is more likely for the population system to move into a state of high population level when the former is a state of a lower population level than the opposite. Field data on frequencies of successive mosquito population levels, which were not used for the data inferred MC modeling, were assembled to obtain an empirical intensity transition matrix and the frequencies observed. Our findings match to a certain degree the empirical results in which the probabilities follow analogous patterns while no significant differences were observed between the transition matrices of the CMC model and the validation data (ChiSq = 14.58013, df = 24, p = 0.9324451). The proposed modeling approach is a valuable eco-epidemiological study. Moreover, compared to traditional Markov chains, the benefit of the current CMC model is that it takes into account the stochastic conditional properties of ecological-related climate variables. The current modeling approach could save costs and time in establishing vector eradication programs and mosquito surveillance programs.

Spatial and Temporal Patterns of Ross River Virus in Queensland, 2001-2020

Ross River virus (RRV), the most common human arbovirus infection in Australia, causes significant morbidity and substantial medical costs. About half of Australian cases occur in Queensland. We describe the spatial and temporal patterns of RRV disease in Queensland over the past two decades. RRV notifications, human population data, and weather data from 2001 to 2020 were analysed by the Statistical Area Level 2 (SA2) area. Spatial interpolation or linear extrapolation were used for missing weather values and the estimated population in 2020, respectively. Notifications and incidence rates were analysed through space and time. During the study period, there were 43,699 notifications in Queensland. The highest annual number of notifications was recorded in 2015 (6182), followed by 2020 (3160). The average annual incidence rate was 5 per 10,000 people and the peak period for RRV notifications was March to May. Generally, SA2 areas in northern Queensland had higher numbers of notifications and higher incidence rates than SA2 areas in southern Queensland. The SA2 areas with high incidence rates were in east coastal areas and western Queensland. The timely prediction may aid disease prevention and routine vector control programs, and RRV management plans are important for these areas.

Ecological Effects on the Dynamics of West Nile Virus and Avian Plasmodium: The Importance of Mosquito Communities and Landscape

Humans and wildlife are at risk from certain vector-borne diseases such as malaria, dengue, and West Nile and yellow fevers. Factors linked to global change, including habitat alteration, land-use intensification, the spread of alien species, and climate change, are operating on a global scale and affect both the incidence and distribution of many vector-borne diseases. Hence, understanding the drivers that regulate the transmission of pathogens in the wild is of great importance for ecological, evolutionary, health, and economic reasons. In this literature review, we discuss the ecological factors potentially affecting the transmission of two mosquito-borne pathogens circulating naturally between birds and mosquitoes, namely, West Nile virus (WNV) and the avian malaria parasites of the genus Plasmodium. Traditionally, the study of pathogen transmission has focused only on vectors or hosts and the interactions between them, while the role of landscape has largely been ignored. However, from an ecological point of view, it is essential not only to study the interaction between each of these organisms but also to understand the environmental scenarios in which these processes take place. We describe here some of the similarities and differences in the transmission of these two pathogens and how research into both systems may facilitate a greater understanding of the dynamics of vector-borne pathogens in the wild.

Blood-feeding ecology of mosquitoes in two zoological gardens in the United Kingdom

BACKGROUND

Zoological gardens contain unique configurations of exotic and endemic animals and plants that create a diverse range of developing sites and potential sources of blood meals for local mosquitoes. This may imply unusual interspecific pathogen transmission risks involving zoo vertebrates, like avian malaria to captive penguins. Understanding mosquito ecology and host feeding patterns is necessary to improve mosquito control and disease prevention measures in these environments.

METHODS

Mosquito sampling took place in Chester Zoo for 3 years (2017, 2018, and 2019) and for 1 year in Flamingo Land (2017) using different trapping methods. Blood-fed mosquitoes were identified and their blood meal was amplified by PCR, sequenced, and blasted for host species identification.

RESULTS

In total, 640 blood-fed mosquitoes were collected [Culex pipiens (n = 497), Culiseta annulata (n = 81), Anopheles maculipennis s.l. (n = 7), An. claviger (n = 1), and unidentifiable (n = 55)]. Successful identification of the host species was achieved from 159 blood-fed mosquitoes. Mosquitoes fed on birds (n = 74), non-human mammals (n = 20), and humans (n = 71). There were mixed blood meals from two hosts (n = 6). The proportions of blood-fed mosquitoes varied across sampling seasons and sites within the zoos. The use of resting traps and aspiration of vegetation were more efficient techniques for capturing blood-fed mosquitoes than traps for host-seeking or gravid mosquitoes. By relating the locations of zoo vertebrates to where fed mosquitoes were trapped, the minimum travelling distances were calculated (13.7 to 366.7 m). Temperature, precipitation, relative humidity, proximity to zoo vertebrate exhibits, and vegetation level were found to be significantly associated with the proportion of captured blood-fed mosquitoes by generalized linear modelling.

CONCLUSIONS

Mosquito feeding behaviour in zoos is mainly influenced by time, location (sampling area), temperature, and host availability, which highlights the value of mosquito monitoring in complex settings to plan control strategies and potentially reduce inherent disease transmission risks for humans and threatened zoo vertebrates.

A novel approach for predicting risk of vector-borne disease establishment in marginal temperate environments under climate change: West Nile virus in the UK

Vector-borne diseases (VBDs), such as dengue, Zika, West Nile virus (WNV) and tick-borne encephalitis, account for substantial human morbidity worldwide and have expanded their range into temperate regions in recent decades. Climate change has been proposed as a likely driver of past and future expansion, however, the complex ecology of host and vector populations and their interactions with each other, environmental variables and land-use changes makes understanding the likely impacts of climate change on VBDs challenging. We present an environmentally driven, stage-structured, host-vector mathematical modelling framework to address this challenge. We apply our framework to predict the risk of WNV outbreaks in current and future UK climates. WNV is a mosquito-borne arbovirus which has expanded its range in mainland Europe in recent years. We predict that, while risks will remain low in the coming two to three decades, the risk of WNV outbreaks in the UK will increase with projected temperature rises and outbreaks appear plausible in the latter half of this century. This risk will increase substantially if increased temperatures lead to increases in the length of the mosquito biting season or if European strains show higher replication at lower temperatures than North American strains.

Buzzing Homes: Using Citizen Science Data to Explore the Effects of Urbanization on Indoor Mosquito Communities

Urbanization has been associated with a loss of overall biodiversity and a simultaneous increase in the abundance of a few species that thrive in urban habitats, such as highly adaptable mosquito vectors. To better understand how mosquito communities differ between levels of urbanization, we analyzed mosquito samples from inside private homes submitted to the citizen science project 'Mückenatlas'. Applying two urbanization indicators based on soil sealing and human population density, we compared species composition and diversity at, and preferences towards, different urbanization levels. Species composition between groups of lowest and highest levels of urbanization differed significantly, which was presumably caused by reduced species richness and the dominance of synanthropic mosquito species in urban areas. The genus Anopheles was frequently submitted from areas with a low degree of urbanization, Aedes with a moderate degree, and Culex and Culiseta with a high degree of urbanization. Making use of citizen science data, this first study of indoor mosquito diversity in Germany demonstrated a simplification of communities with increasing urbanization. The dominance of vector-competent species in urban areas poses a potential risk of epidemics of mosquito-borne diseases that can only be contained by a permanent monitoring of mosquitoes and by acquiring a deeper knowledge about how anthropogenic activities affect vector ecology.

Rift Valley Fever and West Nile virus vectors in Morocco: Current situation and future anticipated scenarios

Rift Valley Fever (RVF) and West Nile virus (WNV) are two important emerging Arboviruses transmitted by Aedes and Culex mosquitoes, typically Ae. caspius, Ae. detritus and Cx. pipiens in temperate regions. In Morocco, several outbreaks of WNV (1996, 2003 and 2010), affecting horses mostly, have been reported in north-western regions resulting in the death of 55 horses and one person cumulatively. Serological evidence of WNV local circulation, performed one year after the latest outbreak, revealed WNV neutralizing bodies in 59 out of 499 tested participants (El Rhaffouli et al., 2012). The country also shares common borders with northern Mauritania, where RVF is often documented. Human movement, livestock trade, climate changes and the availability of susceptible mosquito vectors are expected to increase the spread of these diseases in the country. Thus, in this study, we gathered a data set summarizing occurrences of Ae. caspius, Ae. detritus and Cx. pipiens in the country, and generated model prediction for their potential distribution under both current and future (2050) climate conditions, as a proxy to identify regions at-risk of RVF and WNV probable expansion. We found that the north-western regions (where the population is most concentrated), specifically along the Atlantic coastline, are highly suitable for Ae. caspius, Ae. detritus and Cx. pipiens, under present-day conditions. Future model scenarios anticipated possible range changes for the three mosquitoes under all climatic assumptions. All of the studied species are prospected to gain new areas that are currently not suitable, even under the most optimist scenario, thus placing additional human populations at risk. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes. Public health officials, entomological surveillance and control delegation must augment efforts and continuously monitor these areas to reduce and minimize human infection risk.

Modeling and mapping the habitat suitability and the potential distribution of Arboviruses vectors in Morocco

Mosquitoes transmit several agents of diseases and the presence of different species represents a threat to animal and public health. Aedes and Culex mosquitoes are of particular concern giving their potential vector competence for Arbovirus transmission. In Morocco, the lack of detailed information related to their spatial distribution raises major concerns and hampers effective vector surveillance and control. Using maximum entropy (Maxent) modeling, we generated prediction models for the potential distribution of Arboviruses vectors (Aedes aegypti, Ae. vexans, Ae. caspius, Ae. detritus, and Culex pipiens) in Morocco, under current climatic conditions. Also, we investigated the habitat suitability for the potential occurrence and establishment of Ae. albopictus and Ae. vittatus recorded only once in the country. Prediction models for these last two species were generated considering occurrence datasets from close countries of the Mediterranean Basin, where Ae. albopictus is well established, and from a worldwide database for the case of Ae. vittatus (model transferability). With the exception of Ae. vittatus, the results identify potential habitat suitability in Morocco for all mosquitos considered. Existing areas with maximum risk of establishment and high potential distribution were mainly located in the northwestern and central parts of Morocco. Our results essentially underline the assumption that Ae. albopictus, if not quickly controlled, might find suitable habitats and has the potential to become established, especially in the northwest of the country. These findings may help to better understand the potential distribution of each species and enhance surveillance efforts in areas identified as high risk.

Assessing the suitability for Aedes albopictus and dengue transmission risk in China with a delay differential equation model

Dengue is considered non-endemic to mainland China. However, travellers frequently import the virus from overseas and local mosquito species can then spread the disease in the population. As a consequence, mainland China still experiences large dengue outbreaks. Temperature plays a key role in these outbreaks: it affects the development and survival of the vector and the replication rate of the virus. To better understand its implication in the transmission risk of dengue, we developed a delay differential equation model that explicitly simulates temperature-dependent development periods and tested it with collected field data for the Asian tiger mosquito, Aedes albopictus. The model predicts mosquito occurrence locations with a high accuracy (Cohen's κ of 0.78) and realistically replicates mosquito population dynamics. Analysing the infection dynamics during the 2014 dengue outbreak that occurred in Guangzhou showed that the outbreak could have lasted for another four weeks if mosquito control interventions had not been undertaken. Finally, we analyse the dengue transmission risk in mainland China. We find that southern China, including Guangzhou, can have more than seven months of dengue transmission per year while even Beijing, in the temperate north, can have dengue transmission during hot summer months. The results demonstrate the importance of using detailed vector and infection ecology, especially when vector-borne disease transmission risk is modelled over a broad range of climatic zones.

Spring temperature shapes West Nile virus transmission in Europe

West Nile Virus (WNV) is now endemic in many European countries, causing hundreds of human cases every year, with a high spatial and temporal heterogeneity. Previous studies have suggested that spring temperature might play a key role at shaping WNV transmission. Specifically, warmer temperatures in April-May might amplify WNV circulation, thus increasing the risk for human transmission later in the year. To test this hypothesis, we collated publicly available data on the number of human infections recorded in Europe between 2011 and 2019. We then applied generalized linear models to quantify the relationship between human cases and spring temperature, considering both average conditions (over years 2003-2010) and deviations from the average for subsequent years (2011-2019). We found a significant positive association both spatial (average conditions) and temporal (deviations). The former indicates that WNV circulation is higher in usually warmer regions while the latter implies a predictive value of spring conditions over the coming season. We also found a positive association with WNV detection during the previous year, which can be interpreted as an indication of the reliability of the surveillance system but also of WNV overwintering capacity. Weather anomalies at the beginning of the mosquito breeding season might act as an early warning signal for public health authorities, enabling them to strengthen in advance ongoing surveillance and prevention strategies.

Effects of Scale on Modeling West Nile Virus Disease Risk

Modeling vector-borne diseases is best conducted when heterogeneity among interacting biotic and abiotic processes is captured. However, the successful integration of these complex processes is difficult, hindered by a lack of understanding of how these relationships influence disease transmission across varying scales. West Nile virus (WNV) is the most important mosquito-borne disease in the United States. Vectored by Culex mosquitoes and maintained in the environment by avian hosts, the virus can spill over into humans and horses, sometimes causing severe neuroinvasive illness. Several modeling studies have evaluated drivers of WNV disease risk, but nearly all have done so at broad scales and have reported mixed results of the effects of common explanatory variables. As a result, fine-scale relationships with common explanatory variables, particularly climatic, socioeconomic, and human demographic, remain uncertain across varying spatial extents. Using an interdisciplinary approach and an ongoing 12-year study of the Chicago region, this study evaluated the factors explaining WNV disease risk at high spatiotemporal resolution, comparing the human WNV model and covariate performance across three increasing spatial extents: ultrafine, local, and county scales. Our results demonstrate that as spatial extent increased, model performance increased. In addition, only six of the 23 assessed covariates were included in best-fit models of at least two scales. These results suggest that the mechanisms driving WNV ecology are scale-dependent and covariate importance increases as extent decreases. These tools may be particularly helpful for public health, mosquito, and disease control personnel in predicting and preventing disease within local and fine-scale jurisdictions, before spillover occurs.

The Mayaro virus and its potential epidemiological consequences in Colombia: an exploratory biomathematics analysis

Background

Mayaro virus (Togaviridae) is an endemic arbovirus of the Americas with epidemiological similarities with the agents of other more prominent diseases such as dengue (Flaviviridae), Zika (Flaviviridae), and chikungunya (Togaviridae). It is naturally transmitted in a sylvatic/rural cycle by Haemagogus spp., but, potentially, it could be incorporated and transmitted in an urban cycle by Aedes aegypti, a vector widely disseminated in the Americas.

Methods

The Mayaro arbovirus dynamics was simulated mathematically in the colombian population in the eight biogeographical provinces, bearing in mind the vector’s population movement between provinces through passive transport via truck cargo. The parameters involved in the virus epidemiological dynamics, as well as the vital rates of Ae. aegypti in each of the biogeographical provinces were obtained from the literature. These data were included in a meta-population model in differential equations, represented by a model structured by age for the dynamic population of Ae. aegypti combined with an epidemiological SEI/SEIR-type model. In addition, the model was incorporated with a term of migration to represent the connectivity between the biogeographical provinces.

Results

The vital rates and the development cycle of Ae. aegypti varied between provinces, having greater biological potential between 23 °C and 28 °C in provinces of Imerí, biogeographical Chocó, and Magdalena, with respect to the North-Andean Moorland (9.33–21.38 °C). Magdalena and Maracaibo had the highest flow of land cargo. The results of the simulations indicate that Magdalena, Imerí, and biogeographical Chocó would be the most affected regarding the number of cases of people infected by Mayaro virus over time.

Conclusions

The temperature in each of the provinces influences the local population dynamics of Ae. aegypti and passive migration via transport of land cargo plays an important role on how the Mayaro virus would be disseminated in the human population. Once this arbovirus begins an urban cycle, the most-affected departments would be Antioquia, Santander, Norte de Santander, Cesar (Provinces of Magdalena), and Valle del Cauca, and Chocó (biogeographical province of Chocó), which is why vector control programmes must aim their efforts at these departments and include some type of vector control to the transport of land cargo to avoid a future Mayaro epidemic.

Stay cool or get hot? An applied primer for using temperature in forensic entomological case work

The reliable reconstruction of the temperature conditions at a crime scene is still a great challenge in forensic-entomological case work. Despite many published standards and guidelines for reconstructing temperature, and studies analysing the influence of various factors on the accuracy on such reconstructions, there are astonishingly many cases in the literature in which the temperature at the place of discovery is not reconstructed at all, i.e. the most common method is using the data of the nearest meteorological weather station without any correlation with on-site data. This study summarizes the state of the art in temperature reconstruction from an entomological point of view and compares the application of generalized additive models (GAMs) and linear regression on the basis of hypothetical death scenarios with various post mortem intervals (PMI) and measurement periods for the correlation between crime scene and weather station. We show that GAMs i.e. analysing the potential delay effect of temperature within a day, are the tools of choice because they give better, i.e. more accurate estimations than linear regression in 95,6% of all analysed cases regardless of the PMI, body discovery site and correlation period. Nevertheless, each case and crime scene is unique and therefore each entomological expertise should discuss the possible strengths and weaknesses of its temperature reconstruction. Even if temperature is not or cannot be reconstructed for various reasons, a comparison of on-site data with those of a meteorological weather station is the minimum forensic experts should do.

Effect of altitude on wing metric variation of Aedes aegypti (Diptera: Culicidae) in a region of the Colombian Central Andes

In mosquitoes of medical importance, wing shape and size can vary with altitude, an aspect that can influence dispersion and, consequently, their vector capacity. Using geometric morphometry analysis, Aedes aegypti wing size and shape variation of males and females was studied in four altitudes in the second-smallest department in Colombia: 1,200 m (Tebaida), 1,400 m (Armenia), 1,500 m (Calarcá), and 1,700 m (Filandia). Wing shape in males (P < 0.001) and females (P < 0.001) was significantly different through the altitudinal gradient; in turn, wing size in males followed the altitudinal gradient males (R² = 0.04946, P = 0.0002), females (R² = 0.0011, P = 0.46). Wing allometry for males (P < 0.001) and females (P < 0.001) was significant. Likewise, the shape and size of the wings of males (P < 0.001) and females (P < 0.001) had significant fluctuating asymmetry. It is concluded that, in a small scale with an altitudinal variation of 500 meters, it is detected that the size and shape of the wings varied in A. aegypti, main vector the agents that cause dengue, chikungunya, and Zika. The fluctuating asymmetry is present in the individuals studied and could be associated with environmental effects caused by vector control campaigns present in some sampling locations.

Inter-annual variability of the effects of intrinsic and extrinsic drivers affecting West Nile virus vector Culex pipiens population dynamics in northeastern Italy

Background

Vector-borne infectious diseases (VBDs) represent a major public health concern worldwide. Among VBDs, West Nile virus (WNV) showed an increasingly wider spread in temperate regions of Europe, including Italy. During the last decade, WNV outbreaks have been recurrently reported in mosquitoes, horses, wild birds, and humans, showing great variability in the temporal and spatial distribution pattern. Due to the complexity of the environment–host–vector–pathogen interaction and the incomplete understanding of the epidemiological pattern of the disease, WNV occurrences can be difficult to predict. The analyses of ecological drivers responsible for the earlier WNV reactivation and transmission are pivotal; in particular, variations in the vector population dynamics may represent a key point of the recent success of WNV and, more in general, of the VBDs.

Methods

We investigated the variations of Culex pipiens population abundance using environmental, climatic and trapping data obtained over nine years (2010 to 2018) through the WNV entomological surveillance programme implemented in northeastern Italy. An information theoretic approach (IT-AIC_c) and model-averaging algorithms were implemented to examine the relationship between the seasonal mosquito population growth rates and both intrinsic (e.g. intraspecific competition) and extrinsic (e.g. environmental and climatic variables) predictors, to identify the most significant combinations of variables outlining the Cx. pipiens population dynamics.

Results

Population abundance (proxy for intraspecific competition) and length of daylight were the predominant factors regulating the mosquito population dynamics; however, other drivers encompassing environmental and climatic variables also had a significant impact, although sometimes counterintuitive and not univocal. The analyses of the single-year datasets, and the comparison with the results obtained from the overall model (all data available from 2010 to 2018), highlighted remarkable differences in coefficients magnitude, sign and significance. These outcomes indicate that different combinations of factors might have distinctive, and sometimes divergent, effects on mosquito population dynamics.

Conclusions

A more realistic acquaintance of the intrinsic and extrinsic mechanisms of mosquito population fluctuations in relation to continuous changes in environmental and climatic conditions is paramount to properly reinforce VBDs risk-based surveillance activities, to plan targeted density control measures and to implement effective early detection programmes.

West Nile Virus Lineage 2 Vector Competence of Indigenous Culex and Aedes Mosquitoes from Germany at Temperate Climate Conditions

West Nile virus (WNV) is a widespread zoonotic arbovirus and a threat to public health in Germany since its first emergence in 2018. It has become of particular relevance in Germany in 2019 due to its rapid geographical spread and the detection of the first human clinical cases. The susceptibility of indigenous Culex pipiens (biotypes pipiens and molestus) for a German WNV lineage 2 strain was experimentally compared to that of Serbian Cx. pipiens biotype molestus and invasive German Aedes albopictus. All tested populations proved to be competent laboratory vectors of WNV. Culex pipiens biotype pipiens displayed the highest transmission efficiencies (40.0%–52.9%) at 25 °C. This biotype was also able to transmit WNV at 18 °C (transmission efficiencies of 4.4%–8.3%), proving that temperate climates in Central and Northern Europe may support WNV circulation. Furthermore, due to their feeding behaviors, Cx. pipiens biotype molestus and Ae. albopictus can act as “bridge vectors”, leading to human WNV infections.

Remote Sensing and Multi-Criteria Evaluation for Malaria Risk Mapping to Support Indoor Residual Spraying Prioritization in the Central Highlands of Madagascar

The National Malaria Control Program (NMCP) in Madagascar classifies Malagasy districts into two malaria situations: districts in the pre-elimination phase and districts in the control phase. Indoor residual spraying (IRS) is identified as the main intervention means to control malaria in the Central Highlands. However, it involves an important logistical mobilization and thus necessitates prioritization of interventions according to the magnitude of malaria risks. Our objectives were to map the malaria transmission risk and to develop a tool to support the Malagasy Ministry of Public Health (MoH) for selective IRS implementation. For the 2014–2016 period, different sources of remotely sensed data were used to update land cover information and substitute in situ climatic data. Spatial modeling was performed based on multi-criteria evaluation (MCE) to assess malaria risk. Models were mainly based on environment and climate. Three annual malaria risk maps were obtained for 2014, 2015, and 2016. Annual parasite incidence data were used to validate the results. In 2016, the validation of the model using a receiver operating characteristic (ROC) curve showed an accuracy of 0.736; 95% CI [0.669–0.803]. A free plugin for QGIS software was made available for NMCP decision makers to prioritize areas for IRS. An annual update of the model provides the basic information for decision making before each IRS campaign. In Madagascar and beyond, the availability of the free plugin for open-source software facilitates the transfer to the MoH and allows further application to other problems and contexts.

Pathogenicity and Transgenerational Effects of Metarhizium anisopliae on the Demographic Parameters of Aedes albopictus (Culicidae: Diptera)

Dengue fever is a vector-borne infectious disease that spreads swiftly and threatens human lives in several tropical countries. Most of the strategies employed for the control of Aedes albopictus (Skuse) involve synthetic chemicals. The indiscriminate use of synthetic chemicals has led to the development of resistance and is unsafe for human and environmental health. Therefore, there is a need to develop ecologically safe tactics, such as the use of the entomopathogenic fungus (EPF) Metarhizium anisopliae (Metchnikoff 1879) (Met-11.1). The following study investigated the effectiveness of EPF-Met-11.1 on different demographic parameters of Ae. albopictus. Mortality bioassays showed 92.5% mortality when adult Ae. albopictus were treated with M. anisopliae. Metarhizium anisopliae absorbs the hemolymph sugar which results in retarded development. Metarhizium anisopliae LC50 not only affected the parental generation (F0) but also affected the demographic parameters of the offspring (F1). Transgenerational results (F1) with Met-11.1 showed decreased net reproductive rates (Ro), intrinsic rates of increase (r), and mean generation times (T) compared to those of uninfected controls. The larval developmental duration in the treatment group was 8.22 d, compared to 8.00 d in the control. There was a significant decrease in mean fecundity in the treated group (208.87 eggs) compared to that of the control group (360.27 eggs), and adult longevity was also significantly reduced in the treated group. Therefore, it is concluded that M. anisopliae can have lasting effects on the developmental parameters of Ae. albopictus, indicating that it can be an integral part of mosquito control strategies.

The effect of urbanization and climate change on the mosquito population in the Pearl River Delta region of China

The rising incidence of mosquito-borne diseases is a global concern. Changes in regional climate, due to urbanization and global greenhouse gas concentrations, may affect the ecology of mosquitoes and mosquito-transmitted pathogens. The effects of changes in climate on mosquito population dynamics are complex but critical and urgent for implementing more effective public health policies. This study quantified the impact of urbanization and global climate change on the population of the mosquito species, Culex quinquefasciatus, in the Pearl River Delta region in southern China-an area that has undergone substantial urbanization and is expected to experience changes in climate. This study employed a mechanistic model to simulate mosquito population dynamics under various greenhouse gas emission and land-cover change scenarios based on climate data provided by a state-of-the-art regional climate model. Our results show a 12.6% decrease in the annual mosquito population in newly urbanized areas and a 5.9% increase in the annual mosquito population in existing urban areas. Furthermore, changing climate conditions are projected to cause a 15-17% reduction in the total annual mosquito population; however, the change will not be uniform throughout the year. Peak months exhibit a reduction in population, whereas non-peak months show a significant increase. These findings suggest mosquito control strategies may need to be adjusted to respond to the impacts of urbanization and climate change on mosquito population dynamics to maximize effectiveness. Region specific, quantitative analyses of environmental impacts on mosquito-borne disease ecology, like this study, are needed to provide policy makers with a scientific reference to guide the formation of effective transmission intervention strategies.

A quantitative comparison of West Nile virus incidence from 2013 to 2018 in Emilia-Romagna, Italy

Background

West Nile virus (WNV) transmission was much greater in 2018 than in previous seasons in Europe. Focusing on Emilia-Romagna region (northern Italy), we analyzed detailed entomological and epidemiological data collected in 2013–2018 to quantitatively assess environmental drivers of transmission and explore hypotheses to better understand why the 2018 epidemiological season was substantially different than the previous seasons. In particular, in 2018 WNV was detected at least two weeks before the observed circulation in 2013–2017 and in a larger number of mosquito pools. Transmission resulted in 100 neuroinvasive human cases in the region, more than the total number of cases recorded between 2013 and 2017.

Methodology

We used temperature-driven mathematical models calibrated through a Bayesian approach to simulate mosquito population dynamics and WNV infection rates in the avian population. We then estimated the human transmission risk as the probability, for a person living in the study area, of being bitten by an infectious mosquito in a given week. Finally, we translated such risk into reported WNV human infections.

Principal findings

The estimated prevalence of WNV in the mosquito and avian populations were significantly higher in 2018 with respect to 2013–2017 seasons, especially in the eastern part of the region. Furthermore, peak avian prevalence was estimated to have occurred earlier, corresponding to a steeper decline towards the end of summer. The high mosquito prevalence resulted in a much greater predicted risk for human transmission in 2018, which was estimated to be up to eight times higher than previous seasons. We hypothesized, on the basis of our modelling results, that such greater WNV circulation might be partially explained by exceptionally high spring temperatures, which have likely helped to amplify WNV transmission at the beginning of the 2018 season.

West Nile virus (WNV) is one of the most recent emerging mosquito-borne diseases in Europe and North America. While most human infections are asymptomatic, about 1% of them can result in severe neurological diseases which might be fatal. WNV transmission was unusually greater in 2018 than in previous years in many European countries, resulting in a large number of human infections. Focusing on Emilia-Romagna region (Italy), we developed an epidemiological model informed by entomological data; through that we found that exceptionally high spring temperatures might have contributed at amplifying WNV transmission at the beginning of the season, causing greater WNV prevalence in mosquito and avian populations during the summer, which resulted in a higher estimated risk for human transmission. Thus, weather anomalies at the beginning of the mosquito breeding season, which are likely to become more common under the projected scenarios of climate change, might act as an early warning signal for public health authorities, enabling them to design efficient surveillance and prevention strategies.