Influent Factor toward Based Helminth Infections among of Thai-Cambodian Border in Phusing District, Sisaket Province, Thailand

Abstract

The COVID-19 pandemic prompted a search for a new method of preventing the spread of this virus. This study established a model of the areas in Bangkok which were vulnerable to the COVID-19 pandemic by using a combination of the Bayesian network (BN) and the geographic information system (GIS). The model was developed using a data-driven approach and was evaluated with 10-fold cross validation and ROC analysis. The results demonstrated that the proposed method effectively predicted the vulnerability of disease outbreak. The most vulnerable areas to the pandemic were around the center and in the west of Bangkok, while the areas of low vulnerability were found in the north and east of the city. Population density and the aerosol index were highly influential factors in the outbreaks, affirmed by sensitivity analysis. Furthermore, the model used to conduct a scenario analysis resulted in the identification of vulnerability management strategies.

Dengue in Timor-Leste during the COVID-19 phenomenon

“…Some patients who reached the critical stage of these effects extended them from individual to global scales, encompassing a broad spectrum of influence. Thus, health information on neglected tropical and non-communicable outbreaks among all levels and international health organizations is still necessary for new trends and technological application approaches to develop prevention and control strategies, and integrating multidisciplinary networks is still considered essential (30)(31)(32)(33)(34)(35)(36). Therefore, in this study, we conducted a descriptive observational study to evaluate the dengue incidence rate in comparison with the COVID-19 cumulative number and associated dengue risk factors, including the fatality rate of dengue infection in each municipality during the COVID-19 phenomenon in Timor-Leste, by applying the data processing program in Geographic Information Systems (GIS) as a computerbased system, consisting of hardware and software that facilitate the capture, retrieval, management, manipulation, analysis, and display of the spatially geo-referenced data (37,38), is to evaluate the present state of dengue in Timor-Leste to better understand the existing efforts and difficulties, as well as to find possibilities for development through innovative suggestions for all stakeholders.…”