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Original Article
Unraveling trends in schistosomiasis: deep learning insights into national control programs in China
Qing Su, Cici Xi Chen Bauer, Robert Bergquist, Zhiguo Cao, Fenghua Gao, Zhijie Zhang, Yi Hu
Epidemiol Health. 2024;46:e2024039.   Published online March 13, 2024
DOI: https://doi.org/10.4178/epih.e2024039
  • 2,062 View
  • 57 Download
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China.
METHODS
We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS).
RESULTS
The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1,000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1,000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease.
CONCLUSIONS
The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy.
Summary
Key Message
Our research found that CNN-IDE model effectively captured the complex dynamic process of schistosomiasis prevalence. The comprehensive strategy is expected to help diminish schistosomiasis infection.
Editorial
Spatiotemporal analyses of the epidemiological characteristics of diabetes mellitus
Sang Youl Rhee
Epidemiol Health. 2021;43:e2021102.   Published online December 16, 2021
DOI: https://doi.org/10.4178/epih.e2021102
  • 8,560 View
  • 132 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract AbstractSummary PDF
Abstract
Research based on spatiotemporal analysis has been conducted to identify various factors that can affect an individual’s or community’s degree of health and disease. These spatiotemporal studies can effectively illustrate patterns in disease frequency, features, and temporal flow in different parts of a country. Furthermore, identifying these regional characteristics can aid in the development of disease prevention or intervention strategies.
Summary
Korean summary
1. 시공간 분석은 국가 혹은 지역의 질병 빈도, 특징 및 시간 흐름의 패턴을 효과적으로 설명할 수 있다. 2. 시공간 분석은 질병의 예방 또는 중재 전략 개발에 도움이 될 수 있다.
Key Message
1. Spatiotemporal analyses can effectively illustrate patterns in disease frequency, features, and temporal flow in different parts of a country. 2. Spatiotemporal analysis can aid in disease prevention or development of intervention strategies.

Citations

Citations to this article as recorded by  
  • Epidemiological characteristics and spatiotemporal analysis of mumps at township level in Wuhan, China, 2005–2019
    Ying Peng, Peng Wang, De-guang Kong, Wen-zhen Li, Dong-ming Wang, Li Cai, Sha Lu, Bin Yu, Bang-hua Chen, Pu-Lin Liu
    Epidemiology and Infection.2023;[Epub]     CrossRef
Original Articles
Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States
Nurjannah Nurjannah, Kathleen M. Baker, Duduzile Phindi Mashinini
Epidemiol Health. 2021;43:e2021098.   Published online November 9, 2021
DOI: https://doi.org/10.4178/epih.e2021098
  • 10,999 View
  • 130 Download
  • 1 Web of Science
  • 3 Crossref
AbstractAbstract AbstractSummary PDF
Abstract
OBJECTIVES
This study examined the spatiotemporal epidemiological status of diabetes-related death in relation to school district boundaries in the state of Michigan, United States.
METHODS
A retrospective observational study was conducted using death records spanning the years 2007-2014 in Michigan, with school districts as the geographic unit of analysis. Geocoding was performed for each death record. Cluster analysis used spatial autocorrelation with local Moran’s I, and spatiotemporal analysis used the Space Time Pattern Mining tool in ArcGIS Pro 2.1.
RESULTS
The study revealed spatial clusters of high-high locations of diabetes-related mortality rate by school district in Michigan from 2007 to 2014. Spatiotemporal analysis showed grids with intensifying, consecutive, sporadic, and persistent hotspots of diabetes-related death in the Lansing, Royal Oak, Flint City, Berkley, Detroit City, East Lansing, South Lake, and Holt public school districts. These school districts should be prioritized for school-based diabetes prevention programs
CONCLUSIONS
The study demonstrated the presence of various hotspots of diabetes-related deaths within the state of Michigan across the 8-year period of analysis. Understanding spatial and temporal hotspots could further improve our ability to evaluate diabetes burden across both time and space.
Summary
Key Message
Using existing secondary data with spatio-temporal analysis, the study identified diabetes-related death varies across space and time within the state of Michigan, USA at the school district level. This approach provided policy-relevant information to target high-risk school-district when having limited resources to prevent diabetes at schools.

Citations

Citations to this article as recorded by  
  • Spatiotemporal Epidemiological Trends of Mpox in Mainland China: Spatiotemporal Ecological Comparison Study
    Shuli Ma, Jie Ge, Lei Qin, Xiaoting Chen, Linlin Du, Yanbo Qi, Li Bai, Yunfeng Han, Zhiping Xie, Jiaxin Chen, Yuehui Jia
    JMIR Public Health and Surveillance.2024; 10: e57807.     CrossRef
  • Asthma Hot Spots in New York Before and During the COVID-19 Pandemic
    Samira Skochko, Trang Nguyen, Stephanie Mack, Brooke Turcotte, Catherine Adler, Eli S. Rosenberg, Christopher Joseph, Lynley Siag, Alexandra Dubuisson, Victoria L. Wagner
    Preventing Chronic Disease.2024;[Epub]     CrossRef
  • Spatiotemporal analyses of the epidemiological characteristics of diabetes mellitus
    Sang Youl Rhee
    Epidemiology and Health.2021; 43: e2021102.     CrossRef
Temporal trend and spatial distribution of acute lymphoblastic leukemia in Iranian children during 2006-2014: a mixed ecological study
Sajjad Rahimi Pordanjani, Amir Kavousi, Babak Mirbagheri, Abbas Shahsavani, Koorosh Etemad
Epidemiol Health. 2020;42:e2020057.   Published online July 29, 2020
DOI: https://doi.org/10.4178/epih.e2020057
  • 12,443 View
  • 194 Download
  • 7 Web of Science
  • 8 Crossref
AbstractAbstract PDF
Abstract
OBJECTIVES
The present study investigated the spatiotemporal epidemiological status of acute lymphoblastic leukemia (ALL), the most common childhood cancer, in Iran.
METHODS
Using an exploratory mixed design, this ecological study examined 3,769 under-15 children with ALL recorded in the National Cancer Registry of Iran during 2006-2014. Data were analyzed using the Mann-Whitney U test, the Getis-Ord general G (GOGG) index, optimized hot spot analysis, and Pearson correlation coefficients (PCC) at a significance level of 0.05.
RESULTS
The average annual incidence of the disease was 2.25 per 100,000 under-15 children, and the cumulative incidence rate (CIR) was 21.31 per 100,000 under-15 children. Patients’ mean age was 5.90 years (standard deviation, 3.68), and the peak incidence was observed among 2-year to 5-year-olds. No significant difference was found in mean age between boys and girls (p=0.261). The incidence of ALL was more common during spring and summer than in other seasons. The GOGG index was 0.039 and significant (p<0.001). Hot spots were identified in south, central, and eastern Iran and cold spots in the north and west of Iran. The PCC between the CIR and latitude was negative (r=-0.507; p=0.003) but that between the CIR and longitude was positive (r=0.347; p=0.055).
CONCLUSIONS
The incidence of ALL in Iranian children was lower than that observed in developed countries, but showed an increasing trend. It can be argued that the incidence of ALL is due to synergistic interactions between environmental, infectious, geographical, and genetic risk factors.
Summary

Citations

Citations to this article as recorded by  
  • Epidemiology of childhood acute leukemias in marginalized populations of the central-south region of Mexico: results from a population-based registry
    Janet Flores-Lujano, Aldo Allende-López, David Aldebarán Duarte-Rodríguez, Erika Alarcón-Ruiz, Lizbeth López-Carrillo, Teresa Shamah-Levy, Mariano E. Cebrián, Ma. del Rocío Baños-Lara, Diana Casique-Aguirre, Jesús Elizarrarás-Rivas, Javier Antonio López-A
    Frontiers in Oncology.2024;[Epub]     CrossRef
  • Disability-adjusted Life Years of Hepatitis B in Iran during 2009–2019: An Analysis Based on the Global Burden of Disease Study 2019
    Zaher Khazaei, Sayyad Khanizadeh, Moslem Taheri Soodejani, Sajjad Rahimi Pordanjani, Elham Goodarzi
    The Open Public Health Journal.2024;[Epub]     CrossRef
  • Trends in childhood leukemia incidence in urban countries and their relation to environmental factors, including space weather
    Olga Khabarova, Sergey K. Pinaev, Vladimir V. Chakov, Alexey Ya. Chizhov, Olga G. Pinaeva
    Frontiers in Public Health.2024;[Epub]     CrossRef
  • Spatio-temporal Analysis of COVID-19: A Global Study
    Sajjad Rahimi Pordanjani, Maryam Mohammadian, Somayeh Derakhshan, Fatemeh Hadavandsiri, Seyed Saeed Hashemi Nazari, Mohammad Hossein Panahi
    Middle East Journal of Rehabilitation and Health Studies.2023;[Epub]     CrossRef
  • Persistently high incidence rates of childhood acute leukemias from 2010 to 2017 in Mexico City: A population study from the MIGICCL
    Janet Flores-Lujano, David Aldebarán Duarte-Rodríguez, Elva Jiménez-Hernández, Jorge Alfonso Martín-Trejo, Aldo Allende-López, José Gabriel Peñaloza-González, María Luisa Pérez-Saldivar, Aurora Medina-Sanson, José Refugio Torres-Nava, Karina Anastacia Sol
    Frontiers in Public Health.2022;[Epub]     CrossRef
  • Epidemiological characteristics and temporal-spatial analysis of overseas imported dengue fever cases in outbreak provinces of China, 2005–2019
    Xinchang Lun, Yiguan Wang, Chunchun Zhao, Haixia Wu, Caiying Zhu, Delong Ma, Mingfang Xu, Jun Wang, Qiyong Liu, Lei Xu, Fengxia Meng
    Infectious Diseases of Poverty.2022;[Epub]     CrossRef
  • Temporal Trend and Spatial Distribution of Drug Poisoning in Semnan Province: A Retrospective Longitudinal Study
    Masoudeh Babakhanian, Khadijeh Mamashli, Faezeh Ansariniya, Somayeh Rezaie, Hamed Azadi, Masumeh Ghazanfarpour, Sajjad Rahimi Pordanjani
    Middle East Journal of Rehabilitation and Health Studies.2022;[Epub]     CrossRef
  • Crude incidence, age-specific incidence, and standardized incidence rates of leukemia in children under 14 years of age in Iran: an updated meta-analysis
    Ayda Hasanpour Dehkordi, Hasan Askarpour, Farshid Karami Pordanjani, Mohammad Rafiee, Sajjad Rahimi Pordanjani
    Przeglad Epidemiologiczny.2022; 75(4): 546.     CrossRef
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