Culex pipiens distribution in Tunisia: Identification of suitable areas through Random Forest and MaxEnt approaches

The historical ecological background of West Nile virus in Portugal indicates One Health opportunities

West Nile (WNV) is a zoonotic arbovirus with an expanding geographical range and epidemic activity in Europe. Not having yet experienced a human-associated epidemic, Portugal remains an outlier in the Mediterranean basin. In this study, we apply ecological niche modelling informed by WNV historical evidence and a multitude of environmental variables from across Portugal. We identify that ecological backgrounds compatible with WNV historical circulation are mostly restricted to the south, characterized by a warmer and drier climate, high avian diversity, specific avian species and land types. We estimate WNV ecological suitability across the country, identifying overlaps with the distributions of the three relevant hosts (humans, birds, equines) for public and animal health. From this, we propose a category-based spatial framework providing first of a kind valuable insights for WNV surveillance in Portugal under the One Health nexus. We forecast that near future climate trends alone will contribute to pushing adequate WNV ecological suitability northwards, towards regions with higher human density. This unique perspective on the past, present and future ecology of WNV addresses existing national knowledge gaps, enhances our understanding of the evolving emergence of WNV, and offers opportunities to prepare and respond to the first human-associated epidemic in Portugal.

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.

A nowcast model to predict outdoor flea activity in real time for the contiguous United States

BACKGROUND

The cat flea (Ctenocephalides felis), a parasite commonly found on both dogs and cats, is a competent vector for several zoonotic pathogens, including Dipylidium caninum (tapeworms), Bartonella henselae (responsible for cat scratch disease) and Rickettsia felis (responsible for flea-borne spotted fever). Veterinarians recommend that both cats and dogs be routinely treated with medications to prevent flea infestation. Nevertheless, surveys suggest that nearly one third of pet owners do not routinely administer appropriate preventatives.

METHODS

A mathematical model based on weighted averaging over time is developed to predict outdoor flea activity from weather conditions for the contiguous United States. This 'nowcast' model can be updated in real time as weather conditions change and serves as an important tool for educating pet owners about the risks of flea-borne disease. We validate our model using Google Trends data for searches for the term 'fleas.' This Google Trends data serve as a proxy for true flea activity, as validating the model by collecting fleas over the entire USA is prohibitively costly and time-consuming.

RESULTS

The average correlation (r) between the nowcast outdoor flea activity predictions and the Google Trends data was moderate: 0.65, 0.70, 0.66, 0.71 and 0.63 for 2016, 2017, 2018, 2019 and 2020, respectively. However, there was substantial regional variation in performance, with the average correlation in the East South Atlantic states being 0.81 while the average correlation in the Mountain states was only 0.45. The nowcast predictions displayed strong seasonal and geographic patterns, with predicted activity generally being highest in the summer months.

CONCLUSIONS

The nowcast model is a valuable tool by which to educate pet owners regarding the risk of fleas and flea-borne disease and the need to routinely administer flea preventatives. While it is ideal for domestic cats and dogs to on flea preventatives year-round, many pets remain vulnerable to flea infestation. Alerting pet owners to the local increased risk of flea activity during certain times of the year may motivate them to administer appropriate routine preventives.

Trends in mosquito species distribution modeling: insights for vector surveillance and disease control

Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (maximum entropy modeling; MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk.

Predicting current and future high-risk areas for vectors and reservoirs of cutaneous leishmaniasis in Iran

Climate change will affect the distribution of species in the future. To determine the vulnerable areas relating to CL in Iran, we applied two models, MaxEnt and RF, for the projection of the future distribution of the main vectors and reservoirs of CL. The results of the models were compared in terms of performance, species distribution maps, and the gain, loss, and stable areas. The models provided a reasonable estimate of species distribution. The results showed that the Northern and Southern counties of Iran, which currently do not have a high incidence of CL may witness new foci in the future. The Western, and Southwestern regions of the Country, which currently have high habitat suitability for the presence of some vectors and reservoirs, will probably significantly decrease in the future. Furthermore, the most stable areas are for T. indica and M. hurrianae in the future. So that, this species may remain a major reservoir in areas that are present under current conditions. With more local studies in the field of identifying vulnerable areas to CL, it can be suggested that the national CL control guidelines should be revised to include a section as a climate change adaptation plan.

Ecological Niche Modelling Approaches: Challenges and Applications in Vector-Borne Diseases

Vector-borne diseases (VBDs) pose a major threat to human and animal health, with more than 80% of the global population being at risk of acquiring at least one major VBD. Being profoundly affected by the ongoing climate change and anthropogenic disturbances, modelling approaches become an essential tool to assess and compare multiple scenarios (past, present and future), and further the geographic risk of transmission of VBDs. Ecological niche modelling (ENM) is rapidly becoming the gold-standard method for this task. The purpose of this overview is to provide an insight of the use of ENM to assess the geographic risk of transmission of VBDs. We have summarised some fundamental concepts and common approaches to ENM of VBDS, and then focused with a critical view on a number of crucial issues which are often disregarded when modelling the niches of VBDs. Furthermore, we have briefly presented what we consider the most relevant uses of ENM when dealing with VBDs. Niche modelling of VBDs is far from being simple, and there is still a long way to improve. Therefore, this overview is expected to be a useful benchmark for niche modelling of VBDs in future research.

A sero-epidemiological investigation of West Nile virus among patients without any records of their symptoms from three different hospitals from Tunisia

West Nile virus is one of the most known arboviruses around the world, along with Dengue virus, Toscana virus, Chikungunya (CHIK). In Tunisia, many epidemics of WNV had occurred in the past. The last one dated from 2018. The aim of our work was to perform a sero-epidemiological investigation on WNV without any records of their symptoms from three different hospitals from Tunisia. Patients without any records of their symptoms of the infection of West Nile Virus (WNV) infection were included in the period from October 2017 to January 2020 from three different Virology departments in the country (the Military Hospital in Tunis, Fattouma Bourguiba Hospital in Monastir and Sahloul Hospital in Sousse). A venous blood sample was taken from all patients at the bend of the elbow using a sterile syringe under aseptic conditions. Serological investigation for WNV was conducted through ELISA and IFI assays. RT-PCR was used to confirm the infection. The study included 353 patients. Twenty-eighty percent (28.8%) of the population were tested positive for IgM antibodies, males were having less positive antibodies than women (24.6% vs. 36.3%, p<0.05). In the city of Sousse, positive IgM were found more than in the other cities. As for IgG, 19.2% of the patients were having positive antibodies. No significant association was found between genders (p>0.05). One quarter of the IgM antibodies were tested positive using IFI technique, with no difference between genders (p>0.05). Only 9.2% of the samples were positive by PCR. Our results highlight the importance of establishing sustainable entomological systems and effective clinical ones and of promoting appropriate biological control strategies to optimize the limitation of the circulation of WNV as well as other arboviruses to inhibit their harmful effects on health.