Thirty years of use and improvement of remote sensing, applied to epidemiology: From early promises to lasting frustration

doi:10.1016/j.healthplace.2006.03.003

Health & Place

Volume 13, Issue 2, June 2007, Pages 400-403

https://doi.org/10.1016/j.healthplace.2006.03.003 Get rights and content

Abstract

Remote sensing, referring to the remote study of objects, was originally developed for Earth observation, through the use of sensors on board planes or satellites. Improvements in the use and accessibility of multi-temporal satellite-derived environmental data have, for 30 years, contributed to a growing use in epidemiology. Despite the potential of remote-sensed images and processing techniques for a better knowledge of disease dynamics, an exhaustive analysis of the bibliography shows a generalized use of pre-processed spatial data and low-cost images, resulting in a limited adaptability when addressing biological questions.

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Remote sensing and human health: new sensors and new opportunities
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New eyes for epidemiologists: aerial photography and other remote sensing techniques
American Journal of Epidemiology
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Residential greenness may reduce the risk for lung, bladder, breast, prostate, and skin cancers. If our observations will be replicated, it may present a useful avenue for public-health intervention to reduce cancer burden.
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Remotely sensed imagery is used as a tool to aid decision makers and scientists in a variety of fields. A recent world event in which satellite imagery was extensively relied on by a variety of stakeholders was the COVID-19 pandemic. In this article we aim to give an overview of the types of information offered through remote sensing (RS) to help address different issues related to the pandemic. We also discuss about the stakeholders that benefited from the data, and the value added by its availability. The content is presented under four sub-sections; namely (1) the use of RS in real-time decision-making and strategic planning during the pandemic; how RS revealed the (2) environmental changes and (3) social and economic impacts caused by the pandemic. And (4) how RS informed our understanding of the epidemiology of SARS-CoV-2, the pathogen responsible for the pandemic. High resolution optical imagery offered updated on-the-ground data for e.g., humanitarian aid organizations, and informed operational decision making of shipping companies. Change in the intensity of air and water pollution after reduced anthropogenic activities around the world were captured by remote sensing – supplying concrete evidence that can help inform improved environmental policy. Several economic indicators were measured from satellite imagery, showing the spatiotemporal component of economic impacts caused by the global pandemic. Finally, satellite based meteorological data supported epidemiological studies of environmental disease determinants. The varied use of remote sensing during the COVID-19 pandemic affirms the value of this technology to society, especially in times of large-scale disasters.
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Citation Excerpt :
In addition to climate, the role of the physical environment on leptospirosis transmission is also important, such as the presence of water bodies or flooding and variation in land cover (Della Rossa et al., 2016; Ledien et al., 2017; Matsushita et al., 2018). Currently, remote-sensing (RS) technologies provide a broad range of physical environment data at various spatial and temporal scales, which can help to better understand disease epidemiology (Hamm et al., 2015; Herbreteau et al., 2007). Such satellite-derived data have been widely used to identify environmental drivers of vector-borne disease such as malaria (Ebhuoma and Gebreslasie, 2016) or water-borne diseases such as cholera (Xu et al., 2015), but very few leptospirosis studies to date have used these RS data to quantify the role of environmental risk factors in the temporal pattern of leptospirosis incidence.
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Leptospirosis incidence in both counties showed strong and unique annual seasonality. Our results show that in Mengla County leptospirosis notifications exhibits a bi-modal temporal pattern while in Yilong County it follows a typical single epidemic curve. After adjusting for seasonality, the final best-fitting model for Mengla County indicated that leptospirosis notifications were significantly associated with present LST values (incidence rate ratio, IRR = 0.857, 95% confidence interval (CI):0.729-0.929) and rainfall at a lag of 6-months (IRR = 0.989; 95% CI: 0.985-0.993). The incidence of leptospirosis in Yilong was associated with rainfall at 1-month lag (IRR = 1.013, 95% CI: 1.003-1.023), LST (3-months lag) (IRR = 1.193, 95% CI: 1.095-1.301), and MNDWI (5-months lag) (IRR = 7.960, 95% CI: 1.241-47.66).
Our study identified lagged effects between leptospirosis incidence and climate and remotely-sensed environmental factors in the two most endemic counties in China. Rainfall in combination with satellite derived physical environment factors provided better insight of the local epidemiology as well as good predictors for leptospirosis outbreak in both counties. This would also be an avenue for the development of leptospirosis early warning systems to support leptospirosis control in China.
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We further propose concrete areas of collaboration between disease ecologists and land use scientists in this context. Since the advent of remote sensing, numerous studies have looked into associations between land use and land use changes and infectious pathogens, reservoir hosts, and vectors, at a range of spatial scales [6,12•,13,14] have reviewed such studies. Gottdenker et al. [12•] identified biases, toward certain pathogens (e.g. vector-borne), certain environments (with higher Net Primary Productivity), and toward the effects of land use changes on host or vector community composition.
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Thirty years of use and improvement of remote sensing, applied to epidemiology: From early promises to lasting frustration

Abstract

Remote sensing and human health: new sensors and new opportunities

Emerging Infectious Diseases

New eyes for epidemiologists: aerial photography and other remote sensing techniques

American Journal of Epidemiology