Editorial: Global Control and Eradication Programmes for Cattle Diseases

Within the European Union, infectious cattle diseases are categorized in the Animal Health Law. No strict EU regulations exist for control, evidence of disease freedom, and surveillance of diseases listed other than categories A and B. Consequently, EU member states follow their own varying strategies for disease control. The aim of this study was to provide an overview of the control and eradication programs (CPs) for non-EU regulated cattle diseases in the Netherlands between 2009 and 2019 and to highlight characteristics specific to the Dutch situation. In the Netherlands, CPs are in place for six endemic cattle diseases: bovine viral diarrhea, infectious bovine rhinotracheitis, salmonellosis, paratuberculosis, leptospirosis, and neosporosis. These CPs have been tailored to the specific situation in the Netherlands: a country with a high cattle density, a high rate of animal movements, a strong dependence on export of dairy products, and a high-quality data-infrastructure. The latter specifically applies to the dairy sector, which is the leading cattle sector in the Netherlands. When a herd enters a CP, generally the within-herd prevalence of infection is estimated in an initial assessment. The outcome creates awareness of the infection status of a herd and also provides an indication of the costs and time to achieve the preferred herd status. Subsequently, the herd enrolls in the control phase of the CP to, if present, eliminate the infection from a herd and a surveillance phase to substantiate the free or low prevalence status over time. The high-quality data infrastructure that results in complete and centrally registered census data on cattle movements provides the opportunity to design CPs while minimizing administrative efforts for the farmer. In the CPs, mostly routinely collected samples are used for surveillance. Where possible, requests for proof of the herd status are sent automatically. Automated detection of risk factors for introduction of new animals originating from a herd without the preferred herd status i.e., free or unsuspected, is in place using centrally registered data. The presented overview may inspire countries that want to develop cost-effective CPs for endemic diseases that are not (yet) regulated at EU level.

Download Full-text

Faculty Opinions recommendation of Global control of dimorphism and virulence in fungi.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1005615.373047 ◽

2006 ◽

Author(s):

Joseph Heitman

Keyword(s):

Global Control

Download Full-text

A High-Precision Registration Technology Based on Bundle Adjustment in Structured Light Scanning System

Mathematical Problems in Engineering ◽

10.1155/2014/897347 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Jianying Yuan ◽

Qiong Wang ◽

Xiaoliang Jiang ◽

Bailin Li

Keyword(s):

High Precision ◽

Large Scale ◽

Structured Light ◽

Bundle Adjustment ◽

Scanning System ◽

Control Points ◽

Registration Method ◽

Global Control ◽

3D Data ◽

Structured Light Scanning

The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.

Download Full-text

A Disease Control-Oriented Land Cover Land Use Map for Myanmar

Data ◽

10.3390/data6060063 ◽

2021 ◽

Vol 6 (6) ◽

pp. 63

Author(s):

Dong Chen ◽

Varada Shevade ◽

Allison Baer ◽

Jiaying He ◽

Amanda Hoffman-Hall ◽

...

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Population Distribution ◽

Large Spatial Scale ◽

The Public ◽

Spatial Coverage ◽

Vector Borne ◽

Do So ◽

Control And Eradication

Malaria is a serious infectious disease that leads to massive casualties globally. Myanmar is a key battleground for the global fight against malaria because it is where the emergence of drug-resistant malaria parasites has been documented. Controlling the spread of malaria in Myanmar thus carries global significance, because the failure to do so would lead to devastating consequences in vast areas where malaria is prevalent in tropical/subtropical regions around the world. Thanks to its wide and consistent spatial coverage, remote sensing has become increasingly used in the public health domain. Specifically, remote sensing-based land cover/land use (LCLU) maps present a powerful tool that provides critical information on population distribution and on the potential human-vector interactions interfaces on a large spatial scale. Here, we present a 30-meter LCLU map that was created specifically for the malaria control and eradication efforts in Myanmar. This bottom-up approach can be modified and customized to other vector-borne infectious diseases in Myanmar or other Southeastern Asian countries.

Download Full-text