Optimizing the detection of emerging infections using mobility-based spatial sampling.

Autor: Zhang D; School of Geography and Environment, Jiangxi Normal University, Nanchang, China.; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, China., Ge Y; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, China.; Key Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education, Jiangxi Normal University, Nanchang, China.; University of Chinese Academy of Sciences, Beijing, China., Wang J; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, China.; University of Chinese Academy of Sciences, Beijing, China., Liu H; Ocean Data Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China., Zhang WB; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, China.; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK., Wu X; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, China.; University of Chinese Academy of Sciences, Beijing, China., B M Heuvelink G; ISRIC - World Soil Information, Wageningen, the Netherlands.; Soil Geography and Landscape Group, Wageningen University, Wageningen, the Netherlands., Wu C; University of Chinese Academy of Sciences, Beijing, China.; The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China., Yang J; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.; Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China., Ruktanonchai NW; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.; Population Health Sciences, Virginia Tech, Blacksburg, VA, USA., Qader SH; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.; Natural Resources Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani 334, Kurdistan Region, Iraq., Ruktanonchai CW; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.; Population Health Sciences, Virginia Tech, Blacksburg, VA, USA., Cleary E; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK., Yao Y; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.; School of Mathematics and Statistics, Zhengzhou Normal University, Zhengzhou, China., Liu J; Ocean Data Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China., Nnanatu CC; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK., Wesolowski A; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA., Cummings DAT; Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA., Tatem AJ; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK., Lai S; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.; Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.; Institute for Life Sciences, University of Southampton, Southampton, UK.
Jazyk: angličtina
Zdroj: International journal of applied earth observation and geoinformation : ITC journal [Int J Appl Earth Obs Geoinf] 2024 Jul; Vol. 131, pp. 103949.
DOI: 10.1016/j.jag.2024.103949
Abstrakt: Timely and precise detection of emerging infections is imperative for effective outbreak management and disease control. Human mobility significantly influences the spatial transmission dynamics of infectious diseases. Spatial sampling, integrating the spatial structure of the target, holds promise as an approach for testing allocation in detecting infections, and leveraging information on individuals' movement and contact behavior can enhance targeting precision. This study introduces a spatial sampling framework informed by spatiotemporal analysis of human mobility data, aiming to optimize the allocation of testing resources for detecting emerging infections. Mobility patterns, derived from clustering point-of-interest and travel data, are integrated into four spatial sampling approaches at the community level. We evaluate the proposed mobility-based spatial sampling by analyzing both actual and simulated outbreaks, considering scenarios of transmissibility, intervention timing, and population density in cities. Results indicate that leveraging inter-community movement data and initial case locations, the proposed Case Flow Intensity (CFI) and Case Transmission Intensity (CTI)-informed spatial sampling enhances community-level testing efficiency by reducing the number of individuals screened while maintaining a high accuracy rate in infection identification. Furthermore, the prompt application of CFI and CTI within cities is crucial for effective detection, especially in highly contagious infections within densely populated areas. With the widespread use of human mobility data for infectious disease responses, the proposed theoretical framework extends spatiotemporal data analysis of mobility patterns into spatial sampling, providing a cost-effective solution to optimize testing resource deployment for containing emerging infectious diseases.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2024 The Authors.)
Databáze: MEDLINE
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