The rising concern of Oropouche fever: a call for enhanced surveillance and research in emerging arboviral threats.

AIM OF STUDY: The study aims to assess the growing public health threat posed by Oropouche virus (OROV), focusing on its epidemiology, transmission patterns, and the challenges in diagnosis and control. By analyzing the recent spread of OROV to new regions, including Cuba and Colombia, the study seeks to highlight the need for improved surveillance, enhanced diagnostic capabilities, and research into potential treatments and vaccines. Additionally, the study investigates the clinical similarities between Oropouche fever and other arboviruses, which often lead to diagnostic difficulties and mismanagement in affected regions. RESULTS: The virus has caused over 500,000 cases in Brazil alone, with recent outbreaks reporting fatalities, suspected vertical transmission, and potential associations with microcephaly in newborns. Underreporting and limited surveillance have likely led to the underestimation of the true burden of Oropouche fever. Current diagnostic methods, such as serology and RT-PCR, are often inaccessible in low-resource settings, further complicating efforts to control the spread of the virus. The study highlights the importance of improving diagnostic capacity, enhancing surveillance, and conducting further research into vector control, antiviral treatments, and vaccine development. CONCLUSION: This study emphasizes the urgent need for coordinated international efforts to address the rising threat of Oropouche virus. Considering its rapid spread and potential for global transmission, comprehensive public health measures are necessary to protect vulnerable populations and mitigate the impact of this emerging disease. Enhanced surveillance and the development of accessible diagnostics, vaccines, and treatment options are critical to containing OROV and preventing further outbreaks.

Lyme Disease Under-Ascertainment During the COVID-19 Pandemic in the United States: Retrospective Study.

Background: The COVID-19 pandemic resulted in a massive disruption in access to care and thus passive, hospital- and clinic-based surveillance programs. In 2020, the reported cases of Lyme disease were the lowest both across the United States and North Carolina in recent years. During this period, human contact patterns began to shift with higher rates of greenspace utilization and outdoor activities, putting more people into contact with potential vectors and associated vector-borne diseases. Lyme disease reporting relies on passive surveillance systems, which were likely disrupted by changes in health care-seeking behavior during the pandemic. Objective: This study aimed to quantify the likely under-ascertainment of cases of Lyme disease during the COVID-19 pandemic in the United States and North Carolina. Methods: We fitted publicly available, reported Lyme disease cases for both the United States and North Carolina prior to the year 2020 to predict the number of anticipated Lyme disease cases in the absence of the pandemic using a Bayesian modeling approach. We then compared the ratio of reported cases divided by the predicted cases to quantify the number of likely under-ascertained cases. We then fitted geospatial models to further quantify the spatial distribution of the likely under-ascertained cases and characterize spatial dynamics at local scales. Results: Reported cases of Lyme Disease were lower in 2020 in both the United States and North Carolina than prior years. Our findings suggest that roughly 14,200 cases may have gone undetected given historical trends prior to the pandemic. Furthermore, we estimate that only 40% to 80% of Lyme diseases cases were detected in North Carolina between August 2020 and February 2021, the peak months of the COVID-19 pandemic in both the United States and North Carolina, with prior ascertainment rates returning to normal levels after this period. Our models suggest both strong temporal effects with higher numbers of cases reported in the summer months as well as strong geographic effects. Conclusions: Ascertainment rates of Lyme disease were highly variable during the pandemic period both at national and subnational scales. Our findings suggest that there may have been a substantial number of unreported Lyme disease cases despite an apparent increase in greenspace utilization. The use of counterfactual modeling using spatial and historical trends can provide insight into the likely numbers of missed cases. Variable ascertainment of cases has implications for passive surveillance programs, especially in the trending of disease morbidity and outbreak detection, suggesting that other methods may be appropriate for outbreak detection during disturbances to these passive surveillance systems.

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.

Lyme disease in companion animals: an updated state-of-art and current situation in Portugal.

Lyme disease (LD) is a globally distributed zoonotic multisystemic condition caused by gram-negative spirochete bacteria of the Borrelia burgdorferi complex, transmitted through tick bites. Research on LD in domestic animals in Portugal is limited, potentially leading to underestimating its prevalence. This disease affects many species, including humans, making it a critical public health issue. In domestic animals, LD often presents subclinically or with non-specific clinical signs, complicating its diagnosis. Nevertheless, veterinarians should always consider LD in cases with a history of tick exposure and compatible clinical signs. Diagnostic confirmation can be achieved through serological and other complementary tests. Treatment involves eradicating the bacterial infection and managing clinical signs using a combination of antibiotics, analgesics, anti-inflammatories, and other medications. Effective prevention primarily relies on tick control measures. This review aims to provide an up-to-date state-of-the-art LD, particularly in Portugal.

Molecular xenomonitoring as an indicator of microfilaraemia prevalence for lymphatic filariasis in Samoa in 2019.

BACKGROUND: Lymphatic filariasis (LF) is a globally significant, vector-borne, neglected tropical disease that can result in severe morbidity and disability. As the World Health Organization (WHO) Global Programme to Eliminate Lymphatic Filariasis makes progress towards LF elimination, there is greater need to develop sensitive strategies for post-intervention surveillance. Molecular xenomonitoring (MX), the detection of pathogen DNA in vectors, may provide a sensitive complement to traditional human-based surveillance techniques, including detection of circulating filarial antigen and microfilaraemia (Mf). This study aims to explore the relationship between human Mf prevalence and the prevalence of polymerase chain reaction (PCR)-positive mosquitoes using MX. METHODS: This study compared Mf and MX results from a 2019 community-based survey conducted in 35 primary sampling units (PSUs) in Samoa. This study also investigated concordance between presence and absence of PCR-positive mosquitoes and Mf-positive participants at the PSU level, and calculated sensitivity and negative predictive values for each indicator using presence of any Mf-positive infection in humans or PCR-positive mosquitoes as a reference. Correlation between prevalence of filarial DNA in mosquitoes and Mf in humans was estimated at the PSU and household/trap level using mixed-effect Bayesian multilevel regression analysis. RESULTS: Mf-positive individuals were identified in less than half of PSUs in which PCR-positive mosquito pools were present (13 of 28 PSUs). Prevalence of PCR-positive mosquitoes (each species separately) was positively correlated with Mf prevalence in humans at the PSU level. Analysed at the species level, only Aedes polynesiensis demonstrated strong evidence of positive correlation (r) with human Mf prevalence at both PSU (r: 0.5, 95% CrI 0.1-0.8) and trap/household levels (r: 0.6, 95% CrI 0.2-0.9). CONCLUSIONS: Findings from this study demonstrate that MX can be a sensitive surveillance method for identifying residual infection in low Mf prevalence settings. MX identified more locations with signals of transmission than Mf-testing. Strong correlation between estimated PCR-positive mosquitoes in the primary vector species and Mf in humans at small spatial scales demonstrates the utility of MX as an indicator for LF prevalence in Samoa and similar settings. Further investigation is needed to develop MX guidelines to strengthen the ability of MX to inform operational decisions.

Lesion on the right testicle of 21-year-old patient.

Human dirofilariasis is an emerging disease that is rising and driven by increasing travel of both humans and their companion animals and climate change. We report a case of Dirofilaria repens in the scrotum of a 21-year-old patient, who experienced right testicular pain. Ultrasonography revealed a tubular, worm-like lesion extracted successfully and confirmed as an immature D. repens through parasitological and molecular analyses. Post-surgery, the patient underwent anthelmintic treatment and was discharged. Increased awareness of this parasitosis among healthcare professionals is crucial, given the expected rise in dirofilariasis cases. Climate change in Poland, characterized not so much by record high temperatures but by a systematic increase in the number of warm days, affects many aspects of life. Due to the presence of disease vectors, the introduction and reintroduction of exotic and parasitic disease, previously rare or absent in temperate climate zones, is possible.

Assessment of Thoracic Radiographic Alterations in Dogs with Heartworm and Their Correlation with Pulmonary Hypertension, Pre- and Post-Adulticide Treatment.

Pulmonary hypertension (PH) is a prevalent and severe complication in dogs infected with Dirofilaria immitis. This study aimed to elucidate the progression of PH by analyzing radiographic parameters and the Right Pulmonary Artery Distensibility (RPAD) Index at three key time points: diagnosis (day 0), discharge (day 90), and six months post-discharge (day 270). Fifty-two heartworm-infected dogs were divided into two groups: non-hypertensive and hypertensive. Radiographic measurements, including Vertebral Heart Size (VHS), CrPA/R4 ratio, and CdPA/R9 ratio, along with the RPAD Index, were assessed on Days 0, 90, and 270. Results indicated that, in Group A, the RPAD Index improved significantly from 42% on Day 0 to 43.16% on Day 90, with no significant change by Day 270 (42%). In contrast, hypertensive dogs exhibited a persistently low RPAD Index, averaging 17% throughout this study (p < 0.001). Radiographic parameters in hypertensive dogs showed continuous elevation compared to non-hypertensive dogs, with significant increases in VHS, CrPA/R4, and CdPA/R9 ratios on day 270 compared to day 0 (p < 0.05). The results confirmed that PH persisted in dogs with D. immitis after adulticide treatment, highlighting the importance of regular radiographic monitoring for assessing and managing long-term outcomes in dogs with PH during and after adulticide treatment. Continuous surveillance is thus essential for the effective post-treatment management of PH in dogs.

Smart technology for mosquito control: Recent developments, challenges, and future prospects.

Smart technology coupled with digital sensors and deep learning networks have emerging scopes in various fields, including surveillance of mosquitoes. Several studies have been conducted to examine the efficacy of such technologies in the differential identification of mosquitoes with high accuracy. Some smart trap uses computer vision technology and deep learning networks to identify live Aedes aegypti and Culex quinquefasciatus in real time. Implementing such tools integrated with a reliable capture mechanism can be beneficial in identifying live mosquitoes without destroying their morphological features. Such smart traps can correctly differentiates between Cx. quinquefasciatus and Ae. aegypti mosquitoes, and may also help control mosquito-borne diseases and predict their possible outbreak. Smart devices embedded with YOLO V4 Deep Neural Network algorithm has been designed with a differential drive mechanism and a mosquito trapping module to attract mosquitoes in the environment. The use of acoustic and optical sensors in combination with machine learning techniques have escalated the automatic classification of mosquitoes based on their flight characteristics, including wing-beat frequency. Thus, such Artificial Intelligence-based tools have promising scopes for surveillance of mosquitoes to control vector-borne diseases. However working efficiency of such technologies requires further evaluation for implementation on a global scale.

Progress towards understanding the effects of artificial light on the transmission of vector-borne diseases.

Artificial light at night (ALAN) is a common form of light pollution worldwide, and the intensity, timing, duration, and wavelength of light exposure can affect biological rhythms, which can lead to metabolic, reproductive, and immune dysfunctions and consequently, host-pathogen interactions. Insect vector-borne diseases are a global problem that needs to be addressed, and ALAN plays an important role in disease transmission by affecting the habits and physiological functions of vector organisms. In this work, we describe the mechanisms by which ALAN affects host physiology and biochemistry, host-parasite interactions, and vector-borne viruses and propose preventive measures for related infectious diseases to minimize the effects of artificial light on vector-borne diseases.

Feedback stabilization and observer design for sterile insect technique models.

This paper focuses on the feedback global stabilization and observer construction for a sterile insect technique model. The sterile insect technique (SIT) is one of the most ecological methods for controlling insect pests responsible for worldwide crop destruction and disease transmission. In this work, we construct a feedback law that globally asymptotically stabilizes an SIT model at extinction equilibrium. Since the application of this type of control requires the measurement of different states of the target insect population, and, in practice, some states are more difficult or more expensive to measure than others, it is important to know how to construct a state estimator, which from a few well-chosen measured states, estimates the other ones, as the one we build in the second part of our work. In the last part of our work, we show that we can apply the feedback control with estimated states to stabilize the full system.

Parameterisation of a bluetongue virus mathematical model using a systematic literature review.

Bluetongue virus (BT) is a vector-borne virus that causes a disease, called bluetongue, which results in significant economic loss and morbidity in sheep, cattle, goats and wild ungulates across all continents of the world except Antarctica. Despite the geographical breadth of its impact, most BT epidemiological models are informed by parameters derived from the 2006-2009 BTV-8 European outbreak. The aim of this study was to develop a highly adaptable model for BT which could be used elsewhere in the world, as well as to identify the parameters which most influence outbreak dynamics, so that policy makers can be properly informed with the most current information to aid in disease planning. To provide a framework for future outbreak modelling and an updated parameterisation that reflects natural variation in infections, a newly developed and parameterised two-host, two-vector species ordinary differential equation model was formulated and analysed. The model was designed to be adaptable to be implemented in any region of the world and able to model both epidemic and endemic scenarios. It was parameterised using a systematic literature review of host-to-vector and vector-to-host transmission rates, host latent periods, host infectious periods, and vaccine protection factors. The model was demonstrated using the updated parameters, with South Africa as a setting based on the Western Cape's known cattle and sheep populations, local environmental parameters, and Culicoides spp. presence data. The sensitivity analysis identified that the duration of the infectious period for sheep and cows had the greatest impact on the outbreak length and number of animals infected at the peak of the outbreak. Transmission rates from cows and sheep to C. imicola midges greatly influenced the day on which the peak of the outbreak occurred, along with the duration of incubation period, and infectious period for cows. Finally, the protection factor of the vaccine had the greatest influence on the total number of animals infected. This knowledge could aid in the development of control measures. Due to gradual climate and anthropological change resulting in alterations in vector habitat suitability, BT outbreaks are likely to continue to increase in range and frequency. Therefore, this research provides an updated BT modelling framework for future outbreaks around the world to explore transmission, outbreak dynamics and control measures.

Culicoides biting midges feeding behaviour as a key for understanding avian Haemoproteus transmission in Lithuania.

Investigations of host feeding behaviour in haematophagous insects are critical to assess transmission routes of vector-borne diseases. Understanding if a certain species has ornithophilic or mammalophilic feeding behaviour can facilitate future studies focused on pathogens transmission to and from certain host species. Culicoides Latreille (Diptera: Ceratopogonidae) are vectors of several pathogens, which include arboviruses, bacteria and parasites to a considerable diversity of vertebrate hosts. However, most of the studies focused on feeding habits target Culicoides species that could transmit the Bluetongue virus, consequently with a mammalophilic feeding behaviour, leaving aside the Culicoides species that are involved in the transmission of vector-borne parasites to birds, such as Haemoproteus Kruse (Haemosporida: Haemoproteidae). This study aimed to investigate the source of blood meals of wild-caught Culicoides using molecular-based methods and to correlate our findings with the reports of Haemoproteus parasites in Culicoides species. Engorged Culicoides females were collected using ultraviolet (UV)-light traps at seven different localities in Lithuania in 2021-2023. Biting midges were dissected, and the abdomens of engorged females were used for molecular investigation of the blood meal source. A polymerase chain reaction (PCR) protocol that amplifies a fragment of the Cytochrome B gene of vertebrates was used. Obtained sequences were compared to available information in GenBank database to confirm the source of the blood meal. In total, 258 engorged Culicoides females, representing nine different species, were analysed. The source of blood meal was identified in 29.1% of them with most of the insects having fed on birds (74.7%) and the remaining on mammals (25.3%). Culicoides segnis Campbell, Pelham-Clinton was the only species to feed exclusively on birds; Culicoides from the Obsoletus group, C. pallidicornis Kieffer and C. punctatus Latreille were found to feed exclusively on mammals; C. festivipennis Kieffer, C. kibunensis Tokunaga and C. pictipennis Staeger had an opportunistic feeding behaviour, with the first two preferably feeding on birds. Due to their feeding behaviour and the presence of Haemoproteus parasites reported in the literature, C. festivipennis, C. kibunensis, C. pictipennis, and C. segnis play an important role in the transmission of those avian vector-borne parasite in the wild. These Culicoides species were already confirmed as being able to support the development of several Haemoproteus species and lineages. Future studies focused on understanding the epidemiology of avian pathogens transmitted by Culicoides should target these species.

Climate change could fuel urinary schistosomiasis transmission in Africa and Europe.

The freshwater snail Bulinus truncatus is an important intermediate host for trematode parasites causing urogenital schistosomiasis, a tropical disease affecting over 150 million people. Despite its medical importance, uncertainty remains about its global distribution and the potential impacts of climate change on its future spread. Here, we investigate the distribution of B. truncatus, combining the outputs of correlative and mechanistic modelling methods to fully capitalize on both experimental and occurrence data of the species and to create a more reliable distribution forecast than ever constructed. We constructed ensemble correlative species distribution models using 273 occurrence points collected from different sources and a combination of climatic and (bio)physical environmental variables. Additionally, a mechanistic thermal suitability model was constructed, parameterized by recent life-history data obtained through extensive lab-based snail-temperature experiments and supplemented with an extensive literature review. Our findings reveal that the current suitable habitat for B. truncatus encompasses the Sahel region, the Middle East, and the Mediterranean segment of Africa, stretching from Southern Europe to Mozambique. Regions identified as suitable by both methods generally coincide with areas exhibiting high urogenital schistosomiasis prevalence. Model projections into the future suggest an overall net increase in suitable area of up to 17%. New suitable habitat is in Southern Europe, the Middle East, and large parts of Central Africa, while suitable habitat will be lost in the Sahel region. The change in snail habitat suitability may substantially increase the risk of urogenital schistosomiasis transmission in parts of Africa and Southern Europe while reducing it in the Sahel region.

Broad-scale ecological niches of pathogens vectored by the ticks Ixodes scapularis and Amblyomma americanum in North America.

Environmental dimensions, such as temperature, precipitation, humidity, and vegetation type, influence the activity, survival, and geographic distribution of tick species. Ticks are vectors of various pathogens that cause disease in humans, and Ixodes scapularis and Amblyomma americanum are among the tick species that transmit pathogens to humans across the central and eastern United States. Although their potential geographic distributions have been assessed broadly via ecological niche modeling, no comprehensive study has compared ecological niche signals between ticks and tick-borne pathogens. We took advantage of National Ecological Observatory Network (NEON) data for these two tick species and associated bacteria pathogens across North America. We used two novel statistical tests that consider sampling and absence data explicitly to perform these explorations: a univariate analysis based on randomization and resampling, and a permutational multivariate analysis of variance. Based on univariate analyses, in Amblyomma americanum, three pathogens (Borrelia lonestari, Ehrlichia chaffeensis, and E. ewingii) were tested; pathogens showed nonrandom distribution in at least one environmental dimension. Based on the PERMANOVA test, the null hypothesis that the environmental position and variation of pathogen-positive samples are equivalent to those of A. americanum could not be rejected for any of the pathogens, except for the pathogen E. ewingii in maximum and minimum vapor pressure and minimum temperature. For Ixodes scapularis, six pathogens (A. phagocytophilum, Babesia microti, Borrelia burgdorferi sensu lato, B. mayonii, B. miyamotoi, and Ehrlichia muris-like) were tested; only B. miyamotoi was not distinct from null expectations in all environmental dimensions, based on univariate tests. In the PERMANOVA analyses, the pathogens departed from null expectations for B. microti and B. burgdorferi sensu lato, with smaller niches in B. microti, and larger niches in B. burgdorferi sensu lato, than the vector. More generally, this study shows the value of large-scale data resources with consistent sampling methods, and known absences of key pathogens in particular samples, for answering public health questions, such as the relationship of presence and absence of pathogens in their hosts respect to environmental conditions.

Bayesian spatio-temporal modelling of environmental, climatic, and socio-economic influences on malaria in Central Vietnam.

BACKGROUND: Despite the successful efforts in controlling malaria in Vietnam, the disease remains a significant health concern, particularly in Central Vietnam. This study aimed to assess correlations between environmental, climatic, and socio-economic factors in the district with malaria cases. METHODS: The study was conducted in 15 provinces in Central Vietnam from January 2018 to December 2022. Monthly malaria cases were obtained from the Institute of Malariology, Parasitology, and Entomology Quy Nhon, Vietnam. Environmental, climatic, and socio-economic data were retrieved using a Google Earth Engine script. A multivariable Zero-inflated Poisson regression was undertaken using a Bayesian framework with spatial and spatiotemporal random effects with a conditional autoregressive prior structure. The posterior random effects were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling. RESULTS: There was a total of 5,985 Plasmodium falciparum and 2,623 Plasmodium vivax cases during the study period. Plasmodium falciparum risk increased by five times (95% credible interval [CrI] 4.37, 6.74) for each 1-unit increase of normalized difference vegetation index (NDVI) without lag and by 8% (95% CrI 7%, 9%) for every 1ºC increase in maximum temperature (TMAX) at a 6-month lag. While a decrease in risk of 1% (95% CrI 0%, 1%) for a 1 mm increase in precipitation with a 6-month lag was observed. A 1-unit increase in NDVI at a 1-month lag was associated with a four-fold increase (95% CrI 2.95, 4.90) in risk of P. vivax. In addition, the risk increased by 6% (95% CrI 5%, 7%) and 3% (95% CrI 1%, 5%) for each 1ºC increase in land surface temperature during daytime with a 6-month lag and TMAX at a 4-month lag, respectively. Spatial analysis showed a higher mean malaria risk of both species in the Central Highlands and southeast parts of Central Vietnam and a lower risk in the northern and north-western areas. CONCLUSION: Identification of environmental, climatic, and socio-economic risk factors and spatial malaria clusters are crucial for designing adaptive strategies to maximize the impact of limited public health resources toward eliminating malaria in Vietnam.

Diversity of bartonellae in mites (Acari: Mesostigmata: Macronyssidae and Spinturnicidae) of boreal forest bats: Association of host specificity of mites and habitat selection of hosts with vector potential.

Research into various bacterial pathogens that can be transmitted between different animals and may have zoonotic potential has led to the discovery of different strains of Bartonella sp. in bats and their associated ectoparasites. Despite their enormous species diversity, only a few studies have focussed on the detection of bacterial pathogens in insectivorous bats of boreal forests and their associated Macronyssidae and Spinturnicidae mites. We collected and molecularly analysed mite samples from forest-dwelling bat species distributed all along the boreal belt of the Palearctic, from Central Europe to Far East. Ectoparasitic mites were pooled for DNA extraction and DNA amplification polymerase chain reaction (PCRs) were conducted to detect the presence of various bacterial (Anaplasmataceae, Bartonella sp., Rickettsia sp., Mycoplasma sp.) and protozoal (Hepatozoon sp.) pathogens. Bartonella sp. DNA was detected in four different mite species (Macronyssidae: Steatonyssus periblepharus and Spinturnicidae: Spinturnix acuminata, Sp. myoti and Sp. mystacinus), with different prevalences of the targeted gene (gltA, 16-23S ribosomal RNA intergenic spacer and ftsZ). Larger pools (>5 samples pooled) were more likely to harbour Bartonella sp. DNA, than smaller ones. In addition, cave-dwelling bat hosts and host generalist mite species are more associated with Bartonella spp. presence. Spinturnicidae mites may transmit several distinct Bartonella strains, which cluster phylogenetically close to Bartonella species known to cause diseases in humans and livestock. Mites with ubiquitous presence may facilitate the long-term maintenance (and even local recurrence) of Bartonella-infestations inside local bat populations, thus acting as continuous reservoirs for Bartonella spp in bats.

Irrigation increases and stabilizes mosquito populations and increases West Nile virus incidence.

Humans have greatly altered earth's terrestrial water cycle with the majority of fresh water being used for agriculture. Irrigation changes spatial and temporal water availability and alters mosquito abundance and phenology. Previous studies evaluating the effect of irrigation on mosquito abundance and mosquito-borne disease have shown inconsistent results and little is known about the effect of irrigation on variability in mosquito abundance. We examined the effect of irrigation, climate and land cover on mosquito abundance and human West Nile virus (WNV) disease cases across California. Irrigation made up nearly a third of total water inputs, and exceeded precipitation in some regions. Abundance of two key vectors of several arboviruses, including WNV, Culex tarsalis and the Culex pipiens complex, increased 17-21-fold with irrigation. Irrigation reduced seasonal variability in C. tarsalis abundance by 36.1%. Human WNV incidence increased with irrigation, which explained more than a third (34.2%) of the variation in WNV incidence among California counties. These results suggest that irrigation can increase and decouple mosquito populations from natural precipitation variability, resulting in sustained and increased disease burdens. Shifts in precipitation due to climate change are likely to result in increased irrigation in many arid regions which could increase mosquito populations and disease.

Effectiveness of Vaccination Against Tick-Borne Encephalitis in the Czech Republic, 2018-2022.

Background: Tick-borne encephalitis (TBE) is caused by the tick-borne encephalitis virus (TBEV). TBEV infection can cause symptoms of central nervous system (CNS) inflammation and result in severe consequences including death. TBE is an increasing health threat in the Czech Republic and elsewhere in Europe. In 2020, 23% of 3734 TBE cases reported to the European Centre for Disease Prevention and Control were from the Czech Republic. TBE vaccination is universally recommended in the Czech Republic, but a full analysis of TBE vaccine effectiveness (VE) in the Czech Republic has not been published. Methods: TBE is a notifiable disease in the Czech Republic with mandatory reporting of cases (i.e., laboratory-confirmed TBEV infected patient with symptoms of CNS inflammation) and vaccination history to public health authorities. TBE VE was estimated using the screening method utilizing public health surveillance data from 2018 to 2022 and online household surveys of the general population on TBE vaccine uptake conducted in 2019-2022. Results: In 2018-2022, 3648 TBE cases were reported in the Czech Republic; 98.1% (3105/3166) of TBE cases with known vaccination history were unvaccinated. Among 42,671 persons surveyed from the general population who had known TBE vaccination history, 66.5% were unvaccinated. VE against TBE was 97.6% (95% confidence interval 95.7-98.7). When stratified by age group, VE was 97.1% (88.4-99.3) in 1-15 years of age, 97.9% (95.3-99.0) in 16-59 years of age, and 96.9% (90.5-99.0) in ≥60 years of age. TBE vaccination averted an estimated 1020 TBE cases in the Czech Republic from 2018 to 2022. Conclusions: This first published study with a full analysis of TBE VE in the Czech Republic showed that vaccination was highly effective for the prevention of TBE including in children, an age group with increasing TBE disease burden. Vaccination averted hundreds of TBE cases and hospitalizations despite the relatively low compliance with TBE vaccine recommendations. To prevent additional TBE cases in the Czech Republic, enhanced efforts to increase TBE vaccine uptake are needed.

Forecasting deep learning-based risk assessment of vector-borne diseases using hybrid methodology.

BACKGROUND: Dengue fever is rapidly becoming Malaysia's most pressing health concern, as the reported cases have nearly doubled over the past decade. Without efficacious antiviral medications, vector control remains the primary strategy for battling dengue, while the recently introduced tetravalent immunization is being evaluated. The most significant and dangerous risk increasing recently is vector-borne illnesses. These illnesses induce significant human sickness and are transmitted by blood-feeding arthropods such as fleas, parasites, and mosquitos. A thorough grasp of various factors is necessary to improve prediction accuracy and typically generate inaccurate and unstable predictions, as well as machine learning (ML) models, weather-driven mechanisms, and numerical time series. OBJECTIVE: In this research, we propose a novel method for forecasting vector-borne disease risk using Radial Basis Function Networks (RBFNs) and the Darts Game Optimizer (DGO) algorithm. METHODS: The proposed approach entails training the RBFNs with historical disease data and enhancing their parameters with the DGO algorithm. To prepare the RBFNs, we used a massive dataset of vector-borne disease incidences, climate variables, and geographical data. The DGO algorithm proficiently searches the RBFN parameter space, fine-tuning the model's architecture to increase forecast accuracy. RESULTS: RBFN-DGO provides a potential method for predicting vector-borne disease risk. This study advances predictive demonstrating in public health by shedding light on effectively controlling vector-borne diseases to protect human populations. We conducted extensive testing to evaluate the performance of the proposed method to standard optimization methods and alternative forecasting methods. CONCLUSION: According to the findings, the RBFN-DGO model beats others in terms of accuracy and robustness in predicting the likelihood of vector-borne illness occurrences.