FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4323287306> ?p ?o ?g. }

• W4323287306 endingPage "69" @default.
• W4323287306 startingPage "45" @default.
• W4323287306 abstract "The sudden increase of infectious disease occurrences in a specified location and time is called a disease outbreak. The impact could affect, in the least case, the daily life of the population in the collapse of the country’s economic and demographic structure. Geospatial technologies have been an important tool in analyzing and making informed decisions to manage public health since the seventeenth century. In recent years, the GIS system’s functional capabilities have been tremendously developed that help the decision-makers in identifying the geographical factors, temporal spread, and velocity of the disease, model the data using mathematical algorithms for predictive analysis, and visualize them in real time through the use of connected devices. Waterborne diseases are transmitted by consuming contaminated water (WHO). In the year 2012, WHO estimated that low- and middle-income countries have recorded 842,000 deaths per year, including 361,000 in children under the age of five. In India, The Ministry of Health and Family Welfare has launched the Integrated Disease Surveillance Program (IDSP) to report all the disease outbreaks across the country since 2011. The study used IDSP disease outbreak weekly reports from 2011 to 2020 and the Census of India—2011 data for the analysis. The IDSP report covers most of the waterborne disease outbreaks across the country at a village and district level with how they are managed and reported with their local causes. The voluminous data (2011–2020) is compiled and attributed in the GIS database. The spatial statistics of the data reveal the hot and cold spots spatially across the country, which are associated with the rainfall pattern of India and other local phenomena. Getis–Ord Gi* statistic is used seasonal and annual data of the outbreaks; the Z-and P-values highlight the high and low clusters, which represents the context of neighboring attributes the study visualizes the outbreak hot spots along the east coast soon after the monsoon month gets over similar pattern is also found in the west coast of India. The spatial pattern and temporal sequencing of waterborne diseases with the use of geospatial technologies and geostatistical applications would help the governments to control and alleviate the severity and occurrence of the diseases." @default.
• W4323287306 created "2023-03-07" @default.
• W4323287306 creator A5016211214 @default.
• W4323287306 creator A5040933579 @default.
• W4323287306 creator A5043663730 @default.
• W4323287306 creator A5071467969 @default.
• W4323287306 creator A5079010882 @default.
• W4323287306 date "2023-01-01" @default.
• W4323287306 modified "2023-09-25" @default.
• W4323287306 title "Geostatistical Study on Waterborne Disease Outbreak in India [2011–2020]" @default.
• W4323287306 cites W1497929585 @default.
• W4323287306 cites W1578329763 @default.
• W4323287306 cites W1598087726 @default.
• W4323287306 cites W1964591277 @default.
• W4323287306 cites W1984510198 @default.
• W4323287306 cites W2013742472 @default.
• W4323287306 cites W2025692246 @default.
• W4323287306 cites W2037796857 @default.
• W4323287306 cites W2057408351 @default.
• W4323287306 cites W2067217612 @default.
• W4323287306 cites W2090405478 @default.
• W4323287306 cites W2094468029 @default.
• W4323287306 cites W2100090610 @default.
• W4323287306 cites W2108707036 @default.
• W4323287306 cites W2119374941 @default.
• W4323287306 cites W2121362530 @default.
• W4323287306 cites W2127982077 @default.
• W4323287306 cites W2137084927 @default.
• W4323287306 cites W2151499620 @default.
• W4323287306 cites W2152846959 @default.
• W4323287306 cites W2163464098 @default.
• W4323287306 cites W2167831135 @default.
• W4323287306 cites W2203093904 @default.
• W4323287306 cites W2504372974 @default.
• W4323287306 cites W2559948664 @default.
• W4323287306 cites W2571456394 @default.
• W4323287306 cites W2734337609 @default.
• W4323287306 cites W2897916673 @default.
• W4323287306 cites W2906065242 @default.
• W4323287306 cites W2944755790 @default.
• W4323287306 cites W2965061518 @default.
• W4323287306 cites W2994732021 @default.
• W4323287306 cites W2997834816 @default.
• W4323287306 cites W3030025391 @default.
• W4323287306 cites W3036464556 @default.
• W4323287306 cites W3047836639 @default.
• W4323287306 cites W3165849148 @default.
• W4323287306 cites W4254615348 @default.
• W4323287306 doi "https://doi.org/10.1007/978-981-19-7230-0_4" @default.
• W4323287306 hasPublicationYear "2023" @default.
• W4323287306 type Work @default.
• W4323287306 citedByCount "0" @default.
• W4323287306 crossrefType "book-chapter" @default.
• W4323287306 hasAuthorship W4323287306A5016211214 @default.
• W4323287306 hasAuthorship W4323287306A5040933579 @default.
• W4323287306 hasAuthorship W4323287306A5043663730 @default.
• W4323287306 hasAuthorship W4323287306A5071467969 @default.
• W4323287306 hasAuthorship W4323287306A5079010882 @default.
• W4323287306 hasConcept C100243477 @default.
• W4323287306 hasConcept C116675565 @default.
• W4323287306 hasConcept C138816342 @default.
• W4323287306 hasConcept C142724271 @default.
• W4323287306 hasConcept C144024400 @default.
• W4323287306 hasConcept C17744445 @default.
• W4323287306 hasConcept C199539241 @default.
• W4323287306 hasConcept C205649164 @default.
• W4323287306 hasConcept C2776114971 @default.
• W4323287306 hasConcept C2776480101 @default.
• W4323287306 hasConcept C2779134260 @default.
• W4323287306 hasConcept C2908647359 @default.
• W4323287306 hasConcept C45355965 @default.
• W4323287306 hasConcept C52130261 @default.
• W4323287306 hasConcept C521751864 @default.
• W4323287306 hasConcept C524204448 @default.
• W4323287306 hasConcept C58640448 @default.
• W4323287306 hasConcept C71924100 @default.
• W4323287306 hasConcept C9770341 @default.
• W4323287306 hasConcept C99454951 @default.
• W4323287306 hasConceptScore W4323287306C100243477 @default.
• W4323287306 hasConceptScore W4323287306C116675565 @default.
• W4323287306 hasConceptScore W4323287306C138816342 @default.
• W4323287306 hasConceptScore W4323287306C142724271 @default.
• W4323287306 hasConceptScore W4323287306C144024400 @default.
• W4323287306 hasConceptScore W4323287306C17744445 @default.
• W4323287306 hasConceptScore W4323287306C199539241 @default.
• W4323287306 hasConceptScore W4323287306C205649164 @default.
• W4323287306 hasConceptScore W4323287306C2776114971 @default.
• W4323287306 hasConceptScore W4323287306C2776480101 @default.
• W4323287306 hasConceptScore W4323287306C2779134260 @default.
• W4323287306 hasConceptScore W4323287306C2908647359 @default.
• W4323287306 hasConceptScore W4323287306C45355965 @default.
• W4323287306 hasConceptScore W4323287306C52130261 @default.
• W4323287306 hasConceptScore W4323287306C521751864 @default.
• W4323287306 hasConceptScore W4323287306C524204448 @default.
• W4323287306 hasConceptScore W4323287306C58640448 @default.
• W4323287306 hasConceptScore W4323287306C71924100 @default.
• W4323287306 hasConceptScore W4323287306C9770341 @default.
• W4323287306 hasConceptScore W4323287306C99454951 @default.

• next