Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach

ABSTRACT

In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotemporal mapping purposes, is proposed in a spatiotemporal disease mapping context. The proposed BME-Kalman synthesis allows BME to use information from both parametric regression modeling and KF estimation leading to enhanced knowledge bases. The BME-Kalman synthetic approach is used to study the space-time incidence mapping of the hand, foot and mouth disease (HFMD) in Shandong province (China) during the period May 1^st, 2008 to March 19^th, 2009. The results showed that the BME-Kalman approach exhibited very good regressive and predictive accuracies, maintained a very good performance even during low-incidence and extremely low-incidence periods, offered an improved description of hierarchical disease characteristics compared to traditional mapping techniques, and provided a clear explanation of the spatial stratified incidence heterogeneity at unsampled locations. The BME-Kalman approach is versatile and flexible so that it can be modified and adjusted according to the needs of the application.

KEYWORDS:

• Bayesian maximum entropy
• Kalman filter
• geostatistics
• space-time analysis
• hand
• foot and mouth disease

Data and codes availability statement

The data and codes that support the Kalman filter computing in this study are available in ‘figshare.com’ with the identifier ‘http://doi.org/10.6084/m9.figshare.11972937. The websites of GWR and SEKS-GUI software used in this study are https://gwrtools.github.io/ and http://seksgui.org/SEKSHome/SEKSHome.html, respectively. The Shandong HFMD dataset is owned by the Chinese Centre for Disease Control and Prevention (http://www.chinacdc.cn/) and not available for distribution due to the constraint in the consent. Shandong geographic database were provided by National Geomatics Center of China (http://www.ngcc.cn/ngcc/) at a 1:1,000,000 scale as the layer’s attribute. Meteorological and socioeconomic datasets are owned by the China National Meteorological Information Center (http://data.cma.cn/) and the Shandong Provincial Bureau of Statistics (http://tjj.shandong.gov.cn/), respectively. They are publicly available at their own websites. We are not authorized to publish these two datasets. Accordingly, these two datasets are not included and are replaced with mock data. Moreover, the simulated incidence dataset is also provided at the above figshare link to demonstrate how the codes work.

Disclosure statement

The authors declare that they have no potential conflict of interest.

Additional information

Funding

This study was supported by the following grants: National Natural Science Foundation of China [Nos. 41531179, 41421001, 41961055, 41671399]; National Key R&D Program of China [No. 2016YFC1302504]; Innovation Project of LREIS [No. O88RA200YA]; and Opening Fund of Key Laboratory of Poyang Lake Wetland and Watershed Research (Jiangxi Normal University), Ministry of Education [No. PK2019001].

Notes on contributors

Bisong Hu

Bisong Hu received his B.S. degree from Tsinghua University, Beijing, China, in 2004 and the Ph.D. degree from University of Chinese Academy of Sciences, Beijing, China, in 2009. He is currently an Associate Professor in Geography and Environment Department, Jiangxi Normal University, Nanchang, China. His research interests include spatial statistics, epidemic spread simulation, complex network and spatial-temporal big data analysis. Email: [email protected].

Pan Ning

Pan Ning received her B.Sc. degree from Jiangxi Normal University, Nanchang, China, in 2019 and is currently a master candidate in the same university. Her research interests include spatial analysis and its application in epidemiology. Email: [email protected].

Yi Li

Yi Li is now an associate researcher of Institute of Remote Sensing and digital Earth, Chinese Academy of Sciences (CAS). He obtained his Ph.D. at the Institute of Remote Sensing applications, CAS and carried out visiting scholar research in University of Illinois Urbana-Champaign, USA during 2016-2017. At present, he serves as the assistant director of Chinese National Engineering Research Center for Geoinfomatics. He is also a member of the Virtual Geographical Environment Committee of the International Digital Earth Commission. During his research career, Dr. Yi LI has hosted three projects of the Chinese National Natural Science Foundation and published over 40 academic papers. Email: [email protected].

Chengdong Xu

Chengdong Xu received the B.Sc. degree in geography from Ludong University, Yantai, China, in 2003, the M.Sc. degree in Cartography and Geographical Information System from Henan University, Kaifeng, China, in 2005 and the Ph.D. degree in Cartography and Geographical Information System from the Institute of Geography, CAS, Beijing, China, in 2013. He is currently an assistant research fellow with the State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Nature Resources Research, CAS, Beijing. His research interests include spatial statistics and its application in geoscience and population health. Email: [email protected].

George Christakos

George Christakos received the B.Sc. degree from National Technical University of Athens, Greece, the M.Sc. degree from University of Birmingham, UK and the Ph.D. degree from Harvard University, USA, in 1990. He is currently the S.M. Birch Chair and Distinguished Professor of Geography at San Diego State University, CA, USA. His research interests include spatiotemporal statistics and Geostatistics, stochastics and random fields theory, and others. Email: [email protected].

Jinfeng Wang

Jinfeng Wang received the B.Sc. degree in geography from Shaanxi Normal University, Xi’an, China, in 1985, the M.Sc. degree in physics from the Institute of Glaciology and Geocryology, Chinese Academy of Sciences (CAS), Lanzhou, China, in 1988, and the Ph.D. degree in geoinformatics from the Institute of Geography, CAS, Beijing, China, in 1991. He is currently a Chair Professor with the State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Nature Resources Research, CAS, Beijing. His research interests include spatial statistics and its application in geoscience and population health. E-mail: [email protected].