scholarly journals Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model

2021 ◽  
Vol 13 (21) ◽  
pp. 11667
Author(s):  
Ping He ◽  
Yu Gao ◽  
Longfei Guo ◽  
Tongtong Huo ◽  
Yuxin Li ◽  
...  
Keyword(s):  
Environmental Variables ◽  
Control Strategies ◽  
Comprehensive Analysis ◽  
Information Support ◽  
Prevention Measures ◽  
Niche Model ◽  
Jackknife Test ◽  
Maxent Model ◽  
Epidemic Risk ◽  
Assessment Results

Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emphasize many research efforts. In this study, we collected location information for confirmed COVID-19 cases in Beijing, Shenyang, Dalian, and Shijiazhuang from 5 October 2020 to 5 January 2021, and selected 15 environmental variables to construct a model that comprehensively considered the parameters affecting the outbreak and spread of COVID-19 epidemics. Annual average temperature, catering, medical facilities, and other variables were processed using ArcGIS 10.3 and classified into three groups, including natural environmental variables, positive socio-environmental variables, and benign socio-environmental variables. We modeled the epidemic risk distribution for each area using the MaxEnt model based on the case occurrence data and environmental variables in four regions, and evaluated the key environmental variables influencing the epidemic distribution. The results showed that medium-risk zones were mainly distributed in Changping and Shunyi in Beijing, while Huanggu District in Shenyang and the southern part of Jinzhou District and the eastern part of Ganjingzi District in Dalian also represented areas at moderate risk of epidemics. For Shijiazhuang, Xinle, Gaocheng and other places were key COVID-19 epidemic spread areas. The jackknife assessment results revealed that positive socio-environmental variables are the most important factors affecting the outbreak and spread of COVID-19. The average contribution rate of the seafood market was 21.12%, and this contribution reached as high as 61.3% in Shenyang. The comprehensive analysis showed that improved seafood market management, strengthened crowd control and information recording, industry-catered specifications, and well-trained employees have become urgently needed prevention strategies in different regions. The comprehensive analysis indicated that the niche model could be used to classify the epidemic risk and propose prevention and control strategies when combined with the assessment results of the jackknife test, thus providing a theoretical basis and information support for suppressing the spread of COVID-19 epidemics.

scholarly journals Potential Distribution Map of Culicoides insignis (Diptera: Ceratopogonidae), Vector of Bluetongue Virus, in Northwestern Argentina

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Cecilia A. Veggiani Aybar ◽  
Romina A. Díaz Gomez ◽  
María J. Dantur Juri ◽  
Mercedes S. Lizarralde de Grosso ◽  
Gustavo R. Spinelli
Keyword(s):  
Disease Transmission ◽  
Bluetongue Virus ◽  
Potential Distribution ◽  
Control Strategies ◽  
Area Under The Curve ◽  
Transmission Risk ◽  
Distribution Map ◽  
Northwestern Argentina ◽  
Jackknife Test ◽  
Maxent Model

Abstract Culicoides insignis Lutz is incriminated as a vector of bluetongue virus (BTV) to ruminants in America. In South America, almost all countries have serological evidence of BTV infections, but only four outbreaks of the disease have been reported. Although clinical diseases have never been cited in Argentina, viral activity has been detected in cattle. In this study, we developed a potential distribution map of Culicoides insignis populations in northwestern Argentina using Maximum Entropy Modeling (Maxent). For the analyses, information regarding both data of specimen collections between 2003 and 2013, and climatic and environmental variables was used. Variables selection was based on the ecological relevance in relation to Culicoides spp. biology and distribution in the area. The best Maxent model according to the Jackknife test included 53 C. insignis presence records and precipitation of the warmest quarter, altitude, and precipitation of the wettest month. Accuracy was evaluated by the area under the curve (AUC = 0.97). These results provide an important analytical resource of high potential for both the development of suitable control strategies and the assessment of disease transmission risk in the region.

scholarly journals Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Yazmin Alcala-Canto ◽  
Juan Antonio Figueroa-Castillo ◽  
Froylán Ibarra-Velarde ◽  
Yolanda Vera-Montenegro ◽  
María Eugenia Cervantes-Valencia ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Environmental Variables ◽  
Control Strategies ◽  
Integrated Control ◽  
Area Under The Curve ◽  
Entropy Method ◽  
Distribution Model ◽  
Economic Losses ◽  
Precipitation Seasonality ◽  
Epidemiological Risk

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks’ distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

Research of Agricultural Non-Point Source Pollution and Prevention Measures

2013 ◽  
Vol 790 ◽  
pp. 445-448
Author(s):  
Pei Pei Shen ◽  
Lu Hua Yang ◽  
Zi Peng Guo ◽  
Hong Chao Liu
Keyword(s):  
Point Source ◽  
Environmental Protection ◽  
Pollution Control ◽  
Pollution Source ◽  
Comprehensive Analysis ◽  
Prevention Measures ◽  
Point Source Pollution ◽  
Non Point Source Pollution

With the effectively control of the point source pollution, non-point source pollution has become the most serious pollution source in our country. In addition, the agricultural non-point source pollution control has become the most important part of the environmental protection. By referring to related journals, this article makes a comprehensive analysis on definition, characteristics, mechanism, harm and prevention countermeasures of agricultural non-point source pollution.

scholarly journals Spatial modeling of dengue and socio-environmental indicators in the city of Rio de Janeiro, Brazil

2011 ◽  
Vol 27 (3) ◽  
pp. 591-602 ◽  
Author(s):  
Tatiana Rodrigues de Araujo Teixeira ◽  
Oswaldo Gonçalves Cruz
Keyword(s):  
Environmental Variables ◽  
Rio De Janeiro ◽  
Gini Index ◽  
Control Strategies ◽  
Time Lag ◽  
Environmental Indicators ◽  
Dengue Transmission ◽  
Direct Association ◽  
Conditional Autoregressive ◽  
Dengue Control

This study analyzed the spatial distribution of dengue in Rio de Janeiro, Brazil, in 2006, and associations between the incidence per 100,000 inhabitants and socio-environmental variables. The study analyzed reported dengue cases among the city's inhabitants, rainfall, Breteau index (for Aedes aegypti and Aedes albopictus), Gini index, and social development index. We conducted mapping and used the global Moran index to measure the indicators' spatial autocorrelation, which was positive for all variables. The generalized linear model showed a direct association between dengue incidence and rainfall, one-month rainfall time lag, Gini index, and Breteau index for A. albopictus. The conditional autoregressive model (CAR) showed a direct association with rainfall for four months of the year, rain time lag in July, and Gini index in February. The results demonstrate the importance of socio-environmental variables in the dynamics of dengue transmission and the relevance for the development of dengue control strategies.

scholarly journals Municipalities of higher vulnerability to Sylvatic Yellow Fever occurrence in the São Paulo State, Brazil

2011 ◽  
Vol 53 (6) ◽  
pp. 335-339 ◽  
Author(s):  
Eduardo Stramandinoli Moreno ◽  
Rita de Cássia Barradas Barata
Keyword(s):  
High Risk ◽  
Yellow Fever ◽  
Environmental Variables ◽  
Multiple Correspondence Analysis ◽  
Sao Paulo ◽  
São Paulo ◽  
Prevention Measures ◽  
Paulo State ◽  
São Paulo State ◽  
Yellow Fever Vaccination

Until 1999 the endemic cases of Sylvatic Yellow Fever were located in the states of northern, midwestern and pre-Amazon regions. Since then, the disease progressively expanded its territory of occurrence, cases being registered beyond the traditional boundaries of endemism. The São Paulo State is considered to be part of this context, since after decades without registration of autochthonous cases of the disease, it reported, in 2000 and 2008-2009, epizootic occurrence in non-human primates and 30 cases in humans. Facts like these, added to the increase in incidences of serious adverse effects resulting from the Yellow Fever vaccination, have highlighted the importance of defining priority municipalities for vaccination against the disease in the state. Two groups of municipalities, some affected and some non-affected by YF, were compared for environmental variables related to the eco-epidemiology of the disease according to literature. The Multiple Correspondence Analysis (MCA) was used to pinpoint the factor able to differentiate the two groups of municipalities and define the levels of risk. The southeast region of the São Paulo State was considered to be the area with a higher number of municipalities classified as high risk and should be considered a priority for the application of prevention measures against Yellow Fever.

scholarly journals Climatic Niche Model for Overwintering Monarch Butterflies in a Topographically Complex Region of California

Insects ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 167 ◽  
Author(s):  
Ashley Fisher ◽  
Kiana Saniee ◽  
Charis van der Heide ◽  
Jessica Griffiths ◽  
Daniel Meade ◽  
...  
Keyword(s):  
Monarch Butterfly ◽  
Climatic Conditions ◽  
Climate Change Scenarios ◽  
Santa Barbara ◽  
Climatic Niche ◽  
Niche Model ◽  
Complex Region ◽  
Maxent Model ◽  
The Future

We use climatic conditions that are associated with known monarch butterfly overwintering groves in California to build a Maxent model, and focus on the fine scale probability of overwintering grove occurrence in a topographically complex region of the state (Santa Barbara County). Grove locations are known from recent and historical surveys and a long-term citizen science database. The climatic niche model performs well, predicting that overwintering habitat is most likely to occur along the coast and at low elevations, as shown by empirical data. We then use climatic variables in conjunction with climate change scenarios to model the future location of overwintering habitat, and find a substantial shift in the predicted distribution. Under a plausible scenario, the probability of occurrence of overwintering habitat directly reflects elevation, with coastal regions having a reduced probability relative to today, and higher elevation sites increasing in probability. Under a more extreme scenario, high probability sites are only located along ridgelines and in mountaintop regions of the county. This predicted shift in distribution is likely to have management implications, as sites that currently lack monarchs may become critical to conservation in the future. Our results suggest that estimating the size of the western overwintering population in the future will be problematic, unless annual counts compensate for a shift in the distribution and a potential change in the number and location of occupied sites.

scholarly journals Predictive Modeling of Suitable Habitats for Cinnamomum Camphora (L.) Presl Using Maxent Model under Climate Change in China

2019 ◽  
Vol 16 (17) ◽  
pp. 3185 ◽  
Author(s):  
Zhang ◽  
Jing ◽  
Li ◽  
Liu ◽  
Fang
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Economic Value ◽  
Distribution Data ◽  
Cinnamomum Camphora ◽  
Jackknife Test ◽  
Maxent Model ◽  
Resource Protection ◽  
Suitable Habitats ◽  
The Impact

Rapid changes in global climate exert tremendous pressure on forest ecosystems. Cinnamomum camphora (L.) Presl is a multi-functional tree species, and its distribution and growth are also affected by climate warming. In order to realize its economic value and ecological function, it is necessary to explore the impact of climate change on its suitable habitats under different scenarios. In this experiment, 181 geographical distribution data were collected, and the MaxEnt algorithm was used to predict the distribution of suitable habitats. To complete the simulation, we selected two greenhouse gas release scenarios, RCP4.5 and RCP8.5, and also three future time periods, 2025s, 2055s, and 2085s. The importance of environmental variables for modeling was evaluated by jackknife test. Our study found that accumulated temperature played a key role in the distribution of camphor trees. With the change of climate, the area of suitable range will increase and continue to move to the northwest of China. These findings could provide guidance for the plantation establishment and resource protection of camphor in China.

scholarly journals Maxent modelling for habitat suitability of vulnerable tree Dalbergia latifolia in Nepal

Silva Fennica ◽  
2021 ◽  
Vol 55 (4) ◽  
Author(s):  
Dipak Mahatara ◽  
Amul Acharya ◽  
Bishnu Dhakal ◽  
Dipesh Sharma ◽  
Sunita Ulak ◽  
...  
Keyword(s):  
Model Prediction ◽  
Habitat Suitability ◽  
Habitat Management ◽  
Natural Habitat ◽  
Area Under The Curve ◽  
Forest Conversion ◽  
Suitable Habitat ◽  
Timber Species ◽  
Jackknife Test ◽  
Maxent Model

Roxb., commonly known as rosewood, is one of the highly valuable tropical timber species of Nepal. The tree species was widely distributed in the past, however, over-exploitation of natural habitat, deforestation, forest conversion for agriculture, illegal logging and the invasion of alien species resulted in the classification of this species as vulnerable by the IUCN (International Union for Conservation of Nature) category. So, the prediction of habitat suitability and potential distribution of the species is required to develop restoration mechanisms and conservation interventions. In this study, we modelled the suitable habitat of over the entire possible range of Nepal using a Maxent model. We compiled 23 environmental variables (19 bioclimatic, 3 topographic and a vegetative layer), however, only 12 least correlated variables along with 43 spatially representative presence locations were retained for model prediction. We used a receiver operating characteristic (ROC) curve to assess the model’s performance and a Jackknife procedure to evaluate the relative importance of predictor variables. The model was statistically significant with an area under the curve (AUC) value of 0.969. The internal Jackknife test indicated that elevation was the most important variable for the model prediction with 71.3% contribution followed by mean temperature of driest quarter (9.8%). The most (>0.6) suitable habitat for the was 235 484 hectares with large sections of area in two provinces whereas, the western most provinces were not suitable for as per Maxent model. The information presented here can provide a framework for nature conservation planning, monitoring and habitat management of this rare and endangered species.Dalbergia latifoliaD. latifoliaD. latifoliaD. latifolia

scholarly journals Habitat Suitability Study of Hylomecon Japonica Based on Maxent Model in China

2020 ◽  
Author(s):  
Cao Zhen ◽  
Zhang Xiaoyan ◽  
Xue Xuanji ◽  
Zhang Lei ◽  
Zhan Guanqun ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Potential Distribution ◽  
Mean Annual Temperature ◽  
Suitable Habitat ◽  
Entropy Model ◽  
Factors Affecting ◽  
Jackknife Test ◽  
Maxent Model ◽  
Growth Area ◽  
The Mean

Abstract Background: To understand the potential distribution and habitat suitability of H. japonica in China. And to provide guidance for the wild cultivation and standardized planting of H. japonica. Methods: The maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the potential suitable habitat of H. japonica species, and the contribution of variables were evaluated by using the jackknife test. Results: The AUC value confirmed the accuracy of the model prediction based on 101 occurrence records. The potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi and other provinces (adaptability index>0.6). Jackknife experiment showed that the precipitation of driest month (35.6%), precipitation of wettest quarter (13.4%), the mean annual temperature (7.8%) and the subclass of soil (7.8%) were the most important factors affecting the potential distribution of H. japonica. Conclusion: The niche parameters of the most suitable growth area (adaptability index>0.8) for H. japonica were precipitation of driest month (5 mm), precipitation of wettest quarter (400-490 mm), the mean annual temperature (-2-4 °C) and the subclass of soil (Glossy Chernozem, Gleyic Lime, Haplic Gypsisols).

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