Analysis of Bee Population Decline in Lombardy during the Period 2014–2016 and Identification of High-Risk Areas

The first events of bee decline in Italy were reported during 1999. Since then, population decline has frequently been reported in Lombardy. In this study, the association between bee decline and the type of land surrounding the apiary was evaluated. A risk map was developed to identify areas with the highest risk of decline. Apiaries in Lombardy were selected from the national beekeeping database (BDA). The study period was from 2014 to 2016. Apiaries were deemed “declined” if they reported at least one event of decline or tested positive for plant protection products; apiaries were “not declined” if they did not report any events of bee decline during the study period. Out of 14,188 apiaries extracted from the BDA, 80 were considered declined. The probability of an apiary being declined increases by 10% in orchards and by 2% in arable land for each additional km2 of land occupied by these crops. The study showed an association between bee decline and the type of territory surrounding the apiaries, and the areas at the greatest risk of decline in Lombardy were identified. This information can be used by Veterinary Services as a predictive parameter for planning prevention and control activities.

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Risk Assessment and Prediction of COVID-19 Based on Epidemiological Data From Spatiotemporal Geography

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.634156 ◽

2021 ◽

Vol 9 ◽

Author(s):

Xiong He ◽

Chunshan Zhou ◽

Yuqu Wang ◽

Xiaodie Yuan

Keyword(s):

Public Health ◽

High Risk ◽

Prevention And Control ◽

Health Hazard ◽

Regional Distribution ◽

Floating Population ◽

Effective Control ◽

The World ◽

Risk Areas ◽

And Control

COVID-19 is a highly infectious disease and public health hazard that has been wreaking havoc around the world; thus, assessing and simulating the risk of the current pandemic is crucial to its management and prevention. The severe situation of COVID-19 around the world cannot be ignored, and there are signs of a second outbreak; therefore, the accurate assessment and prediction of COVID-19 risks, as well as the prevention and control of COVID-19, will remain the top priority of major public health agencies for the foreseeable future. In this study, the risk of the epidemic in Guangzhou was first assessed through logistic regression (LR) on the basis of Tencent-migration data and urban point of interest (POI) data, and then the regional distribution of high- and low-risk epidemic outbreaks in Guangzhou in February 2021 was predicted. The main factors affecting the distribution of the epidemic were also analyzed by using geographical detectors. The results show that the number of cases mainly exhibited a declining and then increasing trend in 2020, and the high-risk areas were concentrated in areas with resident populations and floating populations. In addition, in February 2021, the “Spring Festival travel rush” in China was predicted to be the peak period of population movement. The epidemic risk value was also predicted to reach its highest level at external transportation stations, such as Baiyun Airport and Guangzhou South Railway Station. The accuracy verification showed that the prediction accuracy exceeded 99%. Finally, the interaction between the resident population and floating population could explain the risk of COVID-19 to the highest degree, which indicates that the effective control of population agglomeration and interaction is conducive to the prevention and control of COVID-19. This study identifies and predicts high-risk areas of the epidemic, which has important practical value for urban public health prevention and control and containment of the second outbreak of COVID-19.

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Traffic control and social distancing evidence from COVID-19 in China

PLoS ONE ◽

10.1371/journal.pone.0252300 ◽

2021 ◽

Vol 16 (6) ◽

pp. e0252300

Author(s):

Shanlang Lin ◽

Ruofei Lin ◽

Na Yan ◽

Junpei Huang

Keyword(s):

Traffic Control ◽

Prevention And Control ◽

Mainland China ◽

Control Measures ◽

Epidemic Control ◽

Social Distancing ◽

Related Data ◽

Risk Areas ◽

Two Measures ◽

And Control

We collected COVID-19 epidemiological and epidemic control measures-related data in mainland China during the period January 1 to February 19, 2020, and empirically tested the practical effects of the epidemic control measures implemented in China by applying the econometrics approach. The results show that nationally, both traffic control and social distancing have played an important role in controlling the outbreak of the epidemic, however, neither of the two measures have had a significant effect in low-risk areas. Moreover, the effect of traffic control is more successful than that of social distancing. Both measures complement each other, and their combined effect achieves even better results. These findings confirm the effectiveness of the measures currently in place in China, however, we would like to emphasize that control measures should be more tailored, which implemented according to each specific city’s situation, in order to achieve a better epidemic prevention and control.

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The farmers' perceptions of ANPS pollution and its influencing factors in Poyang Lake Region, China

Water Science & Technology ◽

10.2166/wst.2015.637 ◽

2015 ◽

Vol 73 (7) ◽

pp. 1591-1598 ◽

Cited By ~ 2

Author(s):

Meiqiu Chen ◽

Mengjiao Chen ◽

Yanfei Lu ◽

Liguo Wang ◽

Yujiao Huang

Keyword(s):

Prevention And Control ◽

Large Scale ◽

Poyang Lake ◽

Arable Land ◽

Pollution Prevention ◽

Boosted Regression Trees ◽

Factors Affecting ◽

Poyang Lake Region ◽

Lake Region ◽

And Control

Individual farmers represent the main management entities of agricultural production under the family-contract responsibility system in China, and thus play crucial roles in the prevention and control of agricultural nonpoint source (ANPS) pollution. The analysis of the farmers' perceptions of ANPS pollution as well as the factors affecting their perceptions can provide valuable information for relevant policy-making to preserve high quality water in Poyang Lake and regional quality of arable land. Through a survey titled ‘Farmers' perceptions of ANPS pollution and farming behaviors in the Poyang Lake Region’, the data related to the perceptions of farmers on ANPS pollution were collected. The factors that affect their awareness of ANPS pollution were identified with the method of boosted regression trees (BRT). The results indicated that the farmers had awareness of the risk of ANPS pollution to some extent, but they lacked adequate scientific knowledge. Generally, they had no consciousness about how to prevent and control ANPS pollution and did not understand techniques needed for proper scientifically sound application of fertilizers and pesticides. The main factors that influenced their perceptions of ANPS pollution are (from high to low): the ratio of total income which comes from farming, per capita farmland, age, education level, and household income. Some measures targeted to improve the prevention and control of ANPS pollution were proposed: developing modern agricultural techniques and promoting large-scale farming, increasing public campaigns related to ANPS pollution prevention and control with the goal of raising the level of awareness of farmers, and reforming the methods used to promote science and technology in agriculture and encourage the proper use of chemical fertilizers and pesticides.

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Efficacy of Some Treatments Applied for Prevention and Control of the Main Foliar Diseases of Barley

Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Agriculture ◽

10.15835/buasvmcn-agr:6472 ◽

2011 ◽

Vol 68 (1) ◽

Author(s):

Zohyr Abdul Kader YASEEN ◽

Vasile Constantin FLORIAN

Keyword(s):

Experimental Data ◽

Prevention And Control ◽

Agricultural Research ◽

Plant Protection ◽

Crop Plants ◽

Plant Diseases ◽

Production Plant ◽

Economic Level ◽

Chemical Products ◽

And Control

Agricultural research has allowed for a reduction of dependence on certain chemical products employed. The environmental impact, the employment and preservation of natural resources are increasingly visible. There was a clear evolution worldwide of agricultural research, but nevertheless disease and pests of crop plants continue to be highly damaging. Plant diseases, animal parasites and weeds are restricting factors of the utmost peril for crop plants’ production. Plant protection must thus exert a limit on the action of these factors making use of means that are appropriate both on an ecologic and an economic level. According to experimental data for the 2006-2009 period, good results were obtained in the case vegetation (foliar) treatments with Falcon, Tango and Amistar.

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Prediction of hot spot areas of hemorrhagic fever with renal syndrome in Hunan Province based on an information quantity model and logistical regression model

PLoS Neglected Tropical Diseases ◽

10.1371/journal.pntd.0008939 ◽

2020 ◽

Vol 14 (12) ◽

pp. e0008939

Author(s):

Zixi Chen ◽

Fuqiang Liu ◽

Bin Li ◽

Xiaoqing Peng ◽

Lin Fan ◽

...

Keyword(s):

High Risk ◽

Prediction Model ◽

Prevention And Control ◽

Hot Spot ◽

Hemorrhagic Fever ◽

Hunan Province ◽

Information Quantity ◽

Epidemic Monitoring ◽

Risk Areas ◽

And Control

Background China’s “13th 5-Year Plan” (2016–2020) for the prevention and control of sudden acute infectious diseases emphasizes that epidemic monitoring and epidemic focus surveys in key areas are crucial for strengthening national epidemic prevention and building control capacity. Establishing an epidemic hot spot areas and prediction model is an effective means of accurate epidemic monitoring and surveying. Objective: This study predicted hemorrhagic fever with renal syndrome (HFRS) epidemic hot spot areas, based on multi-source environmental variable factors. We calculated the contribution weight of each environmental factor to the morbidity risk, obtained the spatial probability distribution of HFRS risk areas within the study region, and detected and extracted epidemic hot spots, to guide accurate epidemic monitoring as well as prevention and control. Methods: We collected spatial HFRS data, as well as data on various types of natural and human social activity environments in Hunan Province from 2010 to 2014. Using the information quantity method and logistic regression modeling, we constructed a risk-area-prediction model reflecting the epidemic intensity and spatial distribution of HFRS. Results: The areas under the receiver operating characteristic curve of training samples and test samples were 0.840 and 0.816. From 2015 to 2019, HRFS case site verification showed that more than 82% of the cases occurred in high-risk areas. Discussion This research method could accurately predict HFRS hot spot areas and provided an evaluation model for Hunan Province. Therefore, this method could accurately detect HFRS epidemic high-risk areas, and effectively guide epidemic monitoring and surveyance.

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