ArticleThe American journal of tropical medicine and hygiene2019
Identifying Infectious Diarrhea Hot spots and Associated Socioeconomic Factors in Anhui Province, China.
Article in The American journal of tropical medicine and hygiene, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Epidemiological pattern and incidence estimation of infectious diarrhea before the COVID-19 pandemic: Beijing, China, 2015-2019.Frontiers in public health · 2026Article
- Spatial-temporal analysis of hepatitis B in Fujian Province, China in 2012-2021.Infectious medicine · 2024Article
- Impacts of socioeconomic and environmental factors on neoplasms incidence rates using machine learning and GIS: a cross-sectional study in Iran.Scientific reports · 2024Article
- Spatial and temporal distribution of reported dengue cases and hot spot identification in Quezon City, Philippines, 2010-2017.Tropical medicine and health · 2023Article
- A spatial analysis of TB cases and abnormal X-rays detected through active case-finding in Karachi, Pakistan.Scientific reports · 2023Article
- Spatial variation and attributable risk factors of anaemia among young children in Uganda: Evidence from a nationally representative survey.PLOS global public health · 2023Article
- Epidemiological trends and sociodemographic factors associated with acute hemorrhagic conjunctivitis in mainland China from 2004 to 2018.Virology journal · 2022Article
- Spatiotemporal patterns of diarrhea incidence in Ghana and the impact of meteorological and socio-demographic factors.Frontiers in epidemiology · 2022Article
- Epidemiological Trends and Hotspots of Other Infectious DiarrheaFrontiers in public health · 2021Article
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Authors and funding
13 authors.
Funding
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Abstract
Infectious diarrhea cases have increased during the past years in the Anhui Province of China, but little is known about its spatial cluster pattern and associated socioeconomic factors. We obtained county-level total cases of infectious diarrhea in 105 counties of Anhui in 2016 and computed age-adjusted rates. Socioeconomic factors were collected from the Statistical Yearbook. Hot spot analysis was used to identify hot and cold spot counties for infectious diarrhea incidence. We then applied binary logistic regression models to determine the association between socioeconomic factors and hot spot or cold spot clustering risk. Hot spot analysis indicated there were both significant hot spot (29 counties) and cold spot (18 counties) clustering areas for infectious diarrhea in Anhui (
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