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Enregistrement W2058979105 · doi:10.1016/j.phrp.2013.01.001

The Geographical and Economical Impact of Scrub Typus, the Fastest-growing Vector-borne Disease in Korea

2013· article· en· W2058979105 sur OpenAlexaboutno aff
Hae-Wol Cho, Chaeshin Chu

Notice bibliographique

RevueOsong Public Health and Research Perspectives · 2013
Typearticle
Langueen
DomaineMedicine
ThématiqueViral Infections and Vectors
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésVector (molecular biology)DiseaseGeographyBiologyMedicinePathology

Résumé

récupéré en direct d'OpenAlex

Scrub typus, or Tsutsugamushi disease is a vector transmitted infectious and febrile illness caused by “Orientia tsutsugamushi” bacteria. It is transmitted to humans through larvae bites of different species of trombiculid mites. The habitat of mites is located in low trees and bushes. However this vector can live in many different areas even in sandy and mountain desert [1]. In 1985, infected people appeared again [2]. Since then Scrub typhus incidences have been reported every year. Now it is considered as one of the most prevalent diseases affecting humans Korea especially in the southwestern provinces of the country [3]. Usually, the larvae of mites feed on wild rats and the human gets infected accidentally in a zone of infected mites. The chance of outbreak of this disease depends on the number of contacts between the human and the mites. Hence the habitats of mites and the human activities are the key factors in the Scrub typus prevalence. Human activities include war, farming, camping, urbanization and so on. A study on the epidemiological characteristic of this disease in Korea supports this general notion [4]. Chigger population densities were great in areas with high relative humidity, low temperature, low incident sunlight and a dense substrate vegetative canopy [5]. The relationship between human incidence of scrub typhus and climate should largely reflect the responses of chiggers to the environment [6]. The occurrence of scrub typhus is also related to land uses such as urbanization and developing cornfield and bio-fuel productions and oil palms [7]. The replacement of natural forests with plantations at forest fringe facilitated the establishment of the disease, providing the best habitats for the mite [8]. Malaysia has seen an increasing incidence of scrub typhus which is directly related with large-scale cultivation of oil palm and rubber [9]. Urbanization means that the habitats of mites and the life style of human are changing. The contact rate of human with wild life is getting higher. We need information of the habitats of mites and the human activities. Also the incidences of the scrub typhus could be also influenced by climate change in Korea [10]. The geographical information is quite important to trace and predict the occurrence of Scrub typhus in spatial respect. It is valuable to use the geographic information system (GIS) method to help the analysis of the occurrence trend. It is widely used in the management of vector-borne disease and human health [11–13]. GIS method can be useful to evaluate the habitat of wildlife [14,15]. Recently it is applied to spatial analysis of scrub typhus [16]. The infected persons of Scrub typus increased more than three times during the period 2001–2012. The prevalence of this disease in Korea has been on a steady rise over the past years. As pointed out by WHO, the reason for such high prevalence of Scrub typus is due to climate change. The major methods used to estimate the loss caused by diseases is contingent valuation [CV] method that encompasses all the implicit values. Diener, O’Brien & Gafni [1998] compared research results based on CV while Yen, et. al. [2007] estimated the value of vaccine that blocks the infection of SARS in Taiwan [17,18]. Krupnick, et. al. [2002] analyzed the loss of value caused by death-causing diseases in Ontario, Canada [19]. Alberini, Hunt & Markandya [2006] estimated WTP for value of a statistical life in EU countries such as the UK, Italy and France [20]. The CV method was used for the social loss value of avian influenza, zoonoses in Korea [21–23]. In this issue, Jin et al. have analyzed the spatial pattern of the occurrence of scrub typhus in Korea using the data from the Korea Centers for Disease Control and Prevention. And the correlation with occurrence of scrub typhus and land use change is studied. The authors concluded that the Gangwon Province and Gyeongsangbuk Province show low incidence number all through the year. Some districts have almost identical environmental condition of Scrub typus incidence. The land use change of districts does not affect directly the incidence rate. GIS analysis shows spatial characteristics of Scrub typus[24]. Rhee has adopted the climate change in the incidence of Scrub typus in Korea. This research can be used to construct spatial-temporal model to understand the epidemic Scrub typus. Double Bounded Dichotomous Choice of Contingent Valuation method is used to estimate Willingness to Payment to avoid infection of this disease, through the survey in the patient group and the control group The younger the age of the family is, the higher the level of awareness on risks caused by climate change, men, the higher the income is, the lower the suggested bid is, the higher WTP is to avoid infection of disease. The means of the amount of WTP are estimated to be 3,689 KRW per month. As people have become increasingly aware of climate change diseases, WTP to avoid infection of Scrub typus has increased accordingly. And the implicit loss of value due to climate change diseases is increasingly becoming higher. Therefore, there should be stronger and more aggressive promotional activities recommended [25].

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,109
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,063
Tête enseignante GPT0,404
Écart entre enseignants0,341 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2013
Routes d'admission1
Résumé présentoui

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