Ecohealth最新文献

The drylands vesper mouse (Calomys musculinus) is the primary host for Junin mammarenavirus (JUNV), the etiological agent of Argentine hemorrhagic fever in humans. We assessed the potential distribution of C. musculinus and identified disease transmission hotspots under current climatic conditions and projected future scenarios, including severe (Representative Concentration Pathway 8.5) and intermediate (Representative Concentration Pathway 4.5) climate change scenarios in 2050 and 2070. Utilizing tree-based machine learning algorithms, we modeled C. musculinus distribution by incorporating bioclimatic and landscape predictors. The model showed strong performance, achieving F-scores between 80.22 and 83.09%. Key predictors indicated that C. musculinus prefers warm temperatures, moderate annual precipitation, low precipitation variability, and low pasture coverage. Under the severe climate change scenario, suitable areas for the rodent and hotspots for potential disease decreased. The intermediate scenario showed an expansion in C. musculinus distribution alongside increased potential hotspot zones. Despite the complexity of ecological systems and the limitations of the model, our findings offer a framework for preventive measures and ecological studies in regions prone to the expansion of C. musculinus and in hotspots for disease transmission driven by climate change.

We revise the expansion of synanthropic medically important species of Scorpions of genus Tityus in southern South America: Tityus bahiensis (Perty 1833), Tityus carrilloi Ojanguren-Affilastro 2021, Tityus confluens Borelli 1899, Tityus costatus (Karsch, 1879), Tityus serrulatus Lutz & Mello, 1922, and Tityus trivittatus Kraepelin 1898, which due to their synanthropic capabilities we regard as invasive species. We also build species distribution models (SMDs) from bioclimatic variables using Maxent. We also included the human density variable in the model, because medically important species in the area are synanthropic, being more common in urban areas than in natural environments. We present their current suitable areas and the potential future distribution up to 2070. According to our analyses most species will expand in the close future, reaching countries without Scorpionism problems, such as Chile and Uruguay. We conclude that, besides synanthropic capabilities, parthenogenesis is the main factor favoring the expansion of some of these species. We also conclude that interactions between invasive Tityus species may hinder their expansion process due to potential competition or exclusion mechanisms.

After nearly 150 years, since the first description of the invasive intestinal protozoan parasite Entamoeba histolytica, amebiasis remains a significant global health concern. The infection, primarily transmitted through contaminated food and water sources, poses a substantial threat to public health worldwide. In crisis-affected regions like Lebanon, where clean water is scarce, children are highly susceptible to the infection and succumb dramatically to this growing burden. This study aimed to assess the prevalence of amebiasis among children in South Lebanon, identify its associated risk factors and its relationship with the safety of water sources, and evaluate the population's awareness of the parasite. A cross-sectional study involving 180 children was conducted at SRHUH hospital in Nabatieh, South Lebanon. Fecal samples were analyzed under a microscope, and parents were interviewed to assess risk factors and their knowledge. Statistical tests, including Chi-square and logistic regression, were conducted, revealing a 25% disease prevalence. Unsafe water sources and agricultural practices were significantly linked to infections. Surprisingly, higher parental knowledge did not reduce infection risk. This study underscores the significant public health issue of intestinal amebiasis in South Lebanese children, primarily due to unsafe water sources. Increased awareness among the at-risk population is crucial for disease eradication.

The potential risk of rodent-borne diseases along the China-Russia border necessitates the identification and prediction of rodent distribution from a risk management perspective. In this study, we compile distribution records for Apodemus agrarius, which is the main host of hantavirus responsible for hemorrhagic fever with renal syndrome (HFRS), along the border between China and Russia from various literature sources. We then employ the maximum entropy model (MaxEnt) to assess the influence of climatic and geographic factors on its potential distribution and to predict its current and future habitats. The results show that the current suitable habitats are mainly located in the northeastern part of Heilongjiang Province bordering Russia, showing similar pattern with HFRS incidence rate. The environmental factors that contribute more to the distribution of A. agrarius included temperature, precipitation, elevation, and landscape features of cropland and forest. By 2050, due to changes in climate and land use, the suitable habitat of A. agrarius is expected to shift northeastward, thereby altering the distribution of HFRS risk. Despite anticipated shifts in host habitat, HFRS risk along the China-Russia border will remain high. Therefore, joint prevention and control measures and targeted protective strategies for at-risk populations should be developed.

Surveillance and monitoring of zoonotic pathogens is key to identifying and mitigating emerging public health threats. Surveillance is often designed to be taxonomically targeted or systematically dispersed across geography; however, those approaches may not represent the breadth of environments inhabited by a host, vector, or pathogen, leaving significant gaps in our understanding of pathogen dynamics in their natural reservoirs and environments. As a case study on the design of pathogen surveillance programs, we assess how well 20 years of small mammal surveys in Panamá sampled available environments and propose a multistep approach to selecting survey localities in the future. We use > 8000 georeferenced mammal specimen records, collected as part of a long-term hantavirus surveillance program, to test the completeness of country-wide environmental sampling. Despite 20 years of surveillance, our analyses identify a few key environmental sampling gaps. To refine surveillance strategies, we select a series of "core" historically sampled localities for continued surveillance, supplemented with additional environmentally distinct sites to more completely represent available environments in Panamá. Based on lessons learned through decades of surveillance, we propose a series of recommendations to improve strategic sampling of wildlife for zoonotic pathogen surveillance.

In 1994, the Convention on the Conservation of Migratory Species of Wild Animals identified six species of Sahelo-Saharan antelope in immediate danger of extinction. Several of these species are now subjects of large-scale conservation efforts, including reintroductions and population reinforcements across their native ranges. However, disease-related mortalities can cause major setbacks, and wildlife-livestock interfaces are widely thought to have contributed to disease and mortality events in translocated animals. We reviewed 202 English and French publications spanning 20 years (2000-2020) and the WOAH-WAHIS database for infectious diseases and parasites that could pose risks to Sahelo-Saharan antelope. Our review included countries with active conservation translocation initiatives for these species: Chad, Morocco, Senegal, and Tunisia. We found reports of 159 distinct infectious agents or parasites. Frequently identified viruses included bluetongue virus, Rift Valley fever virus, and small ruminant morbillivirus. Commonly reported bacterial and protozoal agents included Anaplasma spp., Theileria spp., and Toxoplasma spp., while common ectoparasites included Hyalomma and Rhipicephalus ticks. Sixty-nine (43%) of the infectious agents identified were potentially zoonotic, 39 (25%) were vector-borne, and 30 were WOAH-listed diseases. These findings highlight potential regional health threats to Sahelo-Saharan antelope and neighboring livestock and human communities. Targeted research is needed to elucidate the role of wildlife in the epidemiology of livestock diseases and vice versa.

The COVID-19 pandemic has had a profound impact on global public health, highlighting the complex relationship between air pollution and disease transmission. Approximately 2.3 billion people live in regions with high levels of air pollution, particularly in the Asia-Pacific region, with countries like India facing severe challenges. This review examines the association between various pollutants, including PM_2.5, PM₁₀, NO₂, SO₂, and CO, and the spread, severity, and mortality of COVID-19. Particulate matter, particularly fine particles, serves as a carrier for viral particles, facilitating faster transmission and increasing respiratory vulnerability. Studies have shown that long-term exposure to air pollutants exacerbates the severity of COVID-19 symptoms, especially in densely populated urban areas. During the lockdown phases, significant reductions in air pollution were observed, including decreases in PM_2.5 by up to 93%, PM10 by 83%, and NO₂ levels, which contributed to improved air quality and potentially mitigated COVID-19 mortality rates. The review also underscores regional disparities, with marginalized populations bearing a disproportionate burden of pollution exposure and health impacts. Gaseous pollutants such as NO₂ were found to contribute to respiratory inflammation, increasing the susceptibility to severe COVID-19 outcomes. Additionally, the review explores the influence of meteorological and climatic factors on COVID-19 outcomes, noting the varying impact of temperature, humidity, and other factors depending on the season, geographical location, and latitude. These findings offer critical insights for policymakers and public health authorities in developing strategies for mitigating both air pollution and COVID-19 transmission.

Rabies is one of the zoonoses with the most significant impact on domestic herbivores, representing a mortality of 100,000 individuals and an economic loss of US$97 million per year in Latin America. The common vampire bat (Desmodus rotundus) is the primary reservoir for livestock rabies and is naturally distributed in Latin America. The concern arises from the possibility that climate change could facilitate the species' arrival to the southern USA. In this study, we used ecological niche modeling to estimate the distribution of D. rotundus in the present time and under future climate change scenarios. We analyzed whether rabies cases in Mexico were related to D. rotundus climatic suitability, and other factors such as livestock density and an ecological impact index. Our results suggest that climate change could facilitate the colonization of new sites in northern Mexico and the southern USA, which could threaten animal and human health. Further, we found that rabies cases are explained mainly by the reservoir suitability. However, national- and state-level policies may also play a key role in explaining the rabies cases in Mexico. There is a possibility that D. rotundus may expand its range to northern and northeastern Mexico, implying a high risk for the presence of rabies virus-free areas in the southern USA.

Aedes aegypti and Aedes albopictus are the primary vectors of arboviruses in Argentina, with increasing importance in Northeastern Argentina (NEA). This study used ecological niche modeling (MaxEnt) to estimate the potential geographic distribution of both species in NEA, integrating bioclimatic, land cover, and sociodemographic variables such as population density and urban accessibility. Occurrence data were compiled from global databases and literature, and model calibration was based on variable selection, spatial filtering, and cross-validation. Results indicate a broader potential distribution for Ae. albopictus compared to Ae. aegypti, particularly in under-sampled areas of Misiones and Corrientes. Urban accessibility emerged as the most influential predictor for both species, with models combining environmental and sociodemographic variables outperforming climate-only models (AUC > 0.84). Binary habitat suitability maps showed marked differences between models, underscoring the importance of human-driven factors. These findings support the use of integrative modeling approaches to better anticipate vector expansion and prioritize surveillance. The study provides critical information to guide vector control programs and reduce the risk of arbovirus transmission, especially in densely populated and highly connected areas.

Environmental monitoring is essential for understanding and minimizing human impact on ecosystems. Traditional methods like manual sampling and laboratory testing, while accurate, are often costly, time-consuming, and difficult to scale, especially in low-resource settings. Artificial intelligence (AI) is increasingly addressing these limitations by enabling automated data collection, real-time analysis, and predictive modeling. Techniques such as machine learning (ML) and deep learning (DL) are being applied to monitor air and water quality, track climate patterns, and support biodiversity efforts. Hybrid AI models further improve accuracy by integrating various analytical approaches. Key applications include species identification, habitat assessment, wildlife tracking, and anti-poaching, utilizing tools such as drone imagery, camera traps, and GPS data. This review explores the latest advancements in AI-based environmental monitoring, emphasizing technologies like explainable AI (XAI), edge computing, and the Internet of Things (IoT), which improve transparency and reduce processing costs. It also addresses ongoing challenges, including data quality, computational demands, and the need for interpretable models. By evaluating practical limitations and proposing interdisciplinary strategies, this article highlights the transformative potential of AI for sustainable environmental management. Successful implementation will depend on ethical frameworks, policy alignment, and cross-sector collaboration to fully realize AI's role in global ecological stewardship.