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Liao H, Lyon CJ, Ying B, Hu T. Climate change, its impact on emerging infectious diseases and new technologies to combat the challenge. Emerg Microbes Infect 2024; 13:2356143. [PMID: 38767202 PMCID: PMC11138229 DOI: 10.1080/22221751.2024.2356143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 05/10/2024] [Indexed: 05/22/2024]
Abstract
ABSTRACTImproved sanitation, increased access to health care, and advances in preventive and clinical medicine have reduced the mortality and morbidity rates of several infectious diseases. However, recent outbreaks of several emerging infectious diseases (EIDs) have caused substantial mortality and morbidity, and the frequency of these outbreaks is likely to increase due to pathogen, environmental, and population effects driven by climate change. Extreme or persistent changes in temperature, precipitation, humidity, and air pollution associated with climate change can, for example, expand the size of EID reservoirs, increase host-pathogen and cross-species host contacts to promote transmission or spillover events, and degrade the overall health of susceptible host populations leading to new EID outbreaks. It is therefore vital to establish global strategies to track and model potential responses of candidate EIDs to project their future behaviour and guide research efforts on early detection and diagnosis technologies and vaccine development efforts for these targets. Multi-disciplinary collaborations are demanding to develop effective inter-continental surveillance and modelling platforms that employ artificial intelligence to mitigate climate change effects on EID outbreaks. In this review, we discuss how climate change has increased the risk of EIDs and describe novel approaches to improve surveillance of emerging pathogens that pose the risk for EID outbreaks, new and existing measures that could be used to contain or reduce the risk of future EID outbreaks, and new methods to improve EID tracking during further outbreaks to limit disease transmission.
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Affiliation(s)
- Hongyan Liao
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- Center for Cellular and Molecular Diagnostics and Department of Biochemistry and Molecular Biology, Tulane University School of Medicine, New Orleans, LA, United States
| | - Christopher J. Lyon
- Center for Cellular and Molecular Diagnostics and Department of Biochemistry and Molecular Biology, Tulane University School of Medicine, New Orleans, LA, United States
| | - Binwu Ying
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Tony Hu
- Center for Cellular and Molecular Diagnostics and Department of Biochemistry and Molecular Biology, Tulane University School of Medicine, New Orleans, LA, United States
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Dahu BM, Alaboud K, Nowbuth AA, Puckett HM, Scott GJ, Sheets LR. The Role of Remote Sensing and Geospatial Analysis for Understanding COVID-19 Population Severity: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4298. [PMID: 36901308 PMCID: PMC10002247 DOI: 10.3390/ijerph20054298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/30/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
Remote sensing (RS), satellite imaging (SI), and geospatial analysis have established themselves as extremely useful and very diverse domains for research associated with space, spatio-temporal components, and geography. We evaluated in this review the existing evidence on the application of those geospatial techniques, tools, and methods in the coronavirus pandemic. We reviewed and retrieved nine research studies that directly used geospatial techniques, remote sensing, or satellite imaging as part of their research analysis. Articles included studies from Europe, Somalia, the USA, Indonesia, Iran, Ecuador, China, and India. Two papers used only satellite imaging data, three papers used remote sensing, three papers used a combination of both satellite imaging and remote sensing. One paper mentioned the use of spatiotemporal data. Many studies used reports from healthcare facilities and geospatial agencies to collect the type of data. The aim of this review was to show the use of remote sensing, satellite imaging, and geospatial data in defining features and relationships that are related to the spread and mortality rate of COVID-19 around the world. This review should ensure that these innovations and technologies are instantly available to assist decision-making and robust scientific research that will improve the population health diseases outcomes around the globe.
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Affiliation(s)
- Butros M. Dahu
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA
| | - Khuder Alaboud
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- NextGen Biomedical Informatics Center, University of Missouri, Columbia, MO 65211, USA
| | - Avis Anya Nowbuth
- Pan African Organization for Health Education and Research (POHER), Manchester, MO 63011, USA
| | - Hunter M. Puckett
- Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA
| | - Grant J. Scott
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA
| | - Lincoln R. Sheets
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA
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Niño L, Gutiérrez-Lesmes O, Diaz-Celis CA, Manrique-Abril F. [Risk of transmission of SARS-CoV-2: multi-criteria spatial evaluation in a municipality of Colombia, 2020]. Rev Salud Publica (Bogota) 2023; 22:205-213. [PMID: 36753112 DOI: 10.15446/rsap.v22n2.88772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 05/30/2020] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVE To zoning the risk of SARS-CoV-2 transmission in Villavicencio, Colombia, through a multi-criteria spatial evaluation. MATERIALS AND METHODS A multi-criteria evaluation model was implemented, through a hierarchical analysis process, integrated into a Geographic Information System. As criteria, descriptive attributes of the threats and vulnerabilities of viral transmission identified by means of an epidemiological model were included, on the same dimensionless numerical scale and proportional to the probability of contagion; the alternatives evaluated correspond to spatial entities represented by pixels. The criteria were weighted according to the expert judgment of the evaluators, with whom the calculation of a normalized matrix of relative priorities was performed, which allowed the estimation of a vector of weights, the degree of inconsistency of which was admissible. The magnitude of the risk was calculated with a weighted summation of the evaluation of the criteria, according to a map algebra geoprocessing. RESULTS The spatial heterogeneity of the risk of SARS-CoV-2 transmission was described in Villavicencio, allowing the identification of the areas with the highest probability of transmission, located in neighborhoods characterized by high socioeconomic vulnerability. CONCLUSIONS The cartographic representation derived from the implementation of a multicriteria model, integrated to a Geographical Information System, in the SARS-CoV-2 transmission risk analysis, constitutes a relevant methodological contribution for decision-making defining strategies of mitigation at the local level, facilitating the location and optimization of resources by the health authorities.
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Affiliation(s)
- Larry Niño
- LN: Biólogo. Esp. Epidemiología. M. Sc. Geografía. Ph.D.(c) Ciencias-Biología. Instituto de Ciencias Naturales, Universidad Nacional de Colombia. Bogotá, Colombia.
| | - Oscar Gutiérrez-Lesmes
- OG: RN. Esp. Epidemiología. M. Sc. Gestión Ambiental. Ph.D.(c) Epidemiología. Escuela de Salud Pública, Universidad de los Llanos. Villavicencio, Colombia.
| | - Cesar A Diaz-Celis
- CD: Ing. Sistemas. M. Sc. Sistemas de Información Geográfica. Ph.D.(c) Sofware, Sistemas y Computación. Escuela de Ingeniería, Universidad de los Llanos. Villavicencio, Colombia.
| | - Fred Manrique-Abril
- FM: AB. M. Sc. Salud Pública. Ph. D. Salud Pública. Ph.D. Medicina Clínica. Profesor Titular, Universidad Nacional de Colombia. Bogotá. Universidad Pedagógica y Tecnológica de Colombia. Tunja, Colombia.
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Aslam R, Sharif F, Baqar M, Nizami AS, Ashraf U. Role of ambient air pollution in asthma spread among various population groups of Lahore City: a case study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:8682-8697. [PMID: 35220536 DOI: 10.1007/s11356-022-19086-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 02/02/2022] [Indexed: 06/14/2023]
Abstract
Air pollution levels rise as a result of industrial and vehicular emissions, epidemiological issues such as asthma become more prevalent in Lahore, Punjab, Pakistan and cause adverse public health effects. Many studies explored the association between air pollutants and frequency of asthma hospital visits, although their effects are unclear. This study examined the link between air pollution, asthma, and socioeconomic and demographic factors. A questionnaire survey was administered among four age groups (15-25, 25-45, 45-60, and over 60 years old) in public and private hospitals of Lahore city. Daily average concentrations of five air pollutants including carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matter (PM2.5 and PM10) were recorded at ten fixed air monitoring sites in Lahore city. There were favorable connections between outpatient department (OPD) asthma visits (64%) and levels of outdoor air quality during winter season throughout the study period. The correlation between 1, 29, and 370 asthma patients and average daily air pollution levels found that the condition was more prevalent in females (53%) than males (47%). There was a significant correlation between PM10 exposure and asthma OPD visits in the city (p 0.001), as well as the elevated PM10 levels were substantially linked with OPD asthma visits over the winter season in the city. The hazard index (HI) for all adult population was estimated 0.001132. The study's findings indicate that exposure to ambient air pollution is a significant predictor of asthma hospital visits, particularly among the elderly. Strategies can be developed by policymakers in response to the worrying situation of allergic disease asthma in industrial cities due to air pollution.
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Affiliation(s)
- Rabia Aslam
- Sustainable Development Study Center, Government College University, Lahore, 54000, Pakistan.
| | - Faiza Sharif
- Sustainable Development Study Center, Government College University, Lahore, 54000, Pakistan
| | - Mujtaba Baqar
- Sustainable Development Study Center, Government College University, Lahore, 54000, Pakistan
| | - Abdul-Sattar Nizami
- Sustainable Development Study Center, Government College University, Lahore, 54000, Pakistan
| | - Uzma Ashraf
- Department of Environmental Science and Policy, Lahore School of Economics, Lahore, 53200, Pakistan
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Dantas JDC, Lopes RH, Marinho CDSR, Pinheiro YT, Silva RARD. The Use of Spatial Analysis in Syphilis-Related Research: A Scoping Review Protocol (Preprint). JMIR Res Protoc 2022; 12:e43243. [PMID: 37097740 PMCID: PMC10170366 DOI: 10.2196/43243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/28/2022] [Accepted: 01/11/2023] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Latin America, Africa, and Asia have high incidences of syphilis. New approaches are needed to understand and reduce disease transmissibility. In health care, spatial analysis is important to map diseases and understand their epidemiologic aspects. OBJECTIVE The proposed scoping review will identify and map the use of spatial analysis as a tool for syphilis-related research in health care. METHODS This protocol was based on the Joanna Briggs Institute manual, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). We will conduct searches in Embase; Lilacs, via the Virtual Health Library (Biblioteca Virtual en Salud; BVS), in Portuguese and English; Medline/PubMed; Web of Science; Cumulative Index to Nursing and Allied Health Literature (CINAHL); and Scopus. Gray literature will be searched for in Google Scholar, the Digital Library of Theses and Dissertations, the Catalog of Theses and Dissertations of the Coordination of Improvement of Higher Education Personnel (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; CAPES), Open Access Theses and Dissertations, ProQuest Dissertations and Theses Global, and the Networked Digital Library of Theses and Dissertations. The main research question is "How has spatial analysis been used in syphilis-related research in health care?" Studies are included if they have the full text available, address syphilis, and use geographic information systems software and spatial analysis techniques, regardless of sample characteristics or size. Studies published as research articles, theses, dissertations, and government documents will also be considered, with no location, time, or language restrictions. Data will be extracted using a spreadsheet adapted from the Joanna Briggs Institute. Quantitative and qualitative data will be analyzed using descriptive statistics and a thematic analysis, respectively. RESULTS The results will be presented according to the PRISMA-ScR guidelines and will summarize the use of spatial analysis in syphilis-related research in health care in countries with different contexts, factors associated with spatial cluster formation, population health impacts, contributions to health systems, challenges, limitations, and possible research gaps. The results will guide future research and may be useful for health and safety professionals, managers, public policy makers, the general population, the academic community, and health professionals who work directly with people with syphilis. Data collection is projected to start in June 2023 and end in July 2023. Data analysis is scheduled to take place in August and September 2023. We expect to publish results in the final months of 2023. CONCLUSIONS The review may reveal where syphilis incidence has the highest incidence, which countries most use spatial analysis to study syphilis, and whether spatial analysis is applicable to syphilis in each continent, thereby contributing to discussion and knowledge dissemination on the use of spatial analysis as a tool for syphilis-related research in health care. TRIAL REGISTRATION Open Science Framework CNVXE; https://osf.io/cnvxe. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/43243.
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Affiliation(s)
- Janmilli da Costa Dantas
- Department of Nursing, Faculty of Health Sciences of Trairi, Federal University of Rio Grande do Norte, Santa Cruz, Brazil
| | - Rayssa Horacio Lopes
- School Department of Health, Federal University of Rio Grande do Norte, Natal, Brazil
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Ahasan R, Alam MS, Chakraborty T, Ali SMA, Alam TB, Islam T, Hossain MM. Applications of geospatial analyses in health research among homeless people: A systematic scoping review of available evidence. HEALTH POLICY AND TECHNOLOGY 2022. [DOI: 10.1016/j.hlpt.2022.100647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Shi Q, Herbert C, Ward DV, Simin K, McCormick BA, Ellison Iii RT, Zai AH. COVID-19 Variant Surveillance and Social Determinants in Central Massachusetts: Development Study (Preprint). JMIR Form Res 2022; 6:e37858. [PMID: 35658093 PMCID: PMC9196873 DOI: 10.2196/37858] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/08/2022] [Accepted: 05/25/2022] [Indexed: 11/25/2022] Open
Abstract
Background Public health scientists have used spatial tools such as web-based Geographical Information System (GIS) applications to monitor and forecast the progression of the COVID-19 pandemic and track the impact of their interventions. The ability to track SARS-CoV-2 variants and incorporate the social determinants of health with street-level granularity can facilitate the identification of local outbreaks, highlight variant-specific geospatial epidemiology, and inform effective interventions. We developed a novel dashboard, the University of Massachusetts’ Graphical user interface for Geographic Information (MAGGI) variant tracking system that combines GIS, health-associated sociodemographic data, and viral genomic data to visualize the spatiotemporal incidence of SARS-CoV-2 variants with street-level resolution while safeguarding protected health information. The specificity and richness of the dashboard enhance the local understanding of variant introductions and transmissions so that appropriate public health strategies can be devised and evaluated. Objective We developed a web-based dashboard that simultaneously visualizes the geographic distribution of SARS-CoV-2 variants in Central Massachusetts, the social determinants of health, and vaccination data to support public health efforts to locally mitigate the impact of the COVID-19 pandemic. Methods MAGGI uses a server-client model–based system, enabling users to access data and visualizations via an encrypted web browser, thus securing patient health information. We integrated data from electronic medical records, SARS-CoV-2 genomic analysis, and public health resources. We developed the following functionalities into MAGGI: spatial and temporal selection capability by zip codes of interest, the detection of variant clusters, and a tool to display variant distribution by the social determinants of health. MAGGI was built on the Environmental Systems Research Institute ecosystem and is readily adaptable to monitor other infectious diseases and their variants in real-time. Results We created a geo-referenced database and added sociodemographic and viral genomic data to the ArcGIS dashboard that interactively displays Central Massachusetts’ spatiotemporal variants distribution. Genomic epidemiologists and public health officials use MAGGI to show the occurrence of SARS-CoV-2 genomic variants at high geographic resolution and refine the display by selecting a combination of data features such as variant subtype, subject zip codes, or date of COVID-19–positive sample collection. Furthermore, they use it to scale time and space to visualize association patterns between socioeconomics, social vulnerability based on the Centers for Disease Control and Prevention’s social vulnerability index, and vaccination rates. We launched the system at the University of Massachusetts Chan Medical School to support internal research projects starting in March 2021. Conclusions We developed a COVID-19 variant surveillance dashboard to advance our geospatial technologies to study SARS-CoV-2 variants transmission dynamics. This real-time, GIS-based tool exemplifies how spatial informatics can support public health officials, genomics epidemiologists, infectious disease specialists, and other researchers to track and study the spread patterns of SARS-CoV-2 variants in our communities.
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Affiliation(s)
- Qiming Shi
- Center for Clinical and Translational Science, UMass Chan Medical School, Worcester, MA, United States
| | - Carly Herbert
- Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, MA, United States
- Department of Medicine, UMass Chan Medical School, Worcester, MA, United States
| | - Doyle V Ward
- Department of Microbiology and Physiological Systems, UMass Chan Medical School, Worcester, MA, United States
- Center for Microbiome Research, UMass Chan Medical School, Worcester, MA, United States
| | - Karl Simin
- Molecular, Cell, and Cancer Biology, UMass Chan Medical School, Worcester, MA, United States
| | - Beth A McCormick
- Department of Microbiology and Physiological Systems, UMass Chan Medical School, Worcester, MA, United States
- Center for Microbiome Research, UMass Chan Medical School, Worcester, MA, United States
| | - Richard T Ellison Iii
- Department of Medicine, UMass Chan Medical School, Worcester, MA, United States
- Department of Microbiology and Physiological Systems, UMass Chan Medical School, Worcester, MA, United States
| | - Adrian H Zai
- Center for Clinical and Translational Science, UMass Chan Medical School, Worcester, MA, United States
- Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, MA, United States
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Ahasan R, Alam MS, Chakraborty T, Hossain MM. Applications of GIS and geospatial analyses in COVID-19 research: A systematic review. F1000Res 2022; 9:1379. [PMID: 35186280 PMCID: PMC8822139 DOI: 10.12688/f1000research.27544.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/25/2022] [Indexed: 12/23/2022] Open
Abstract
Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Geospatial techniques, especially WebGIS, have even been widely used to visualize the data on a map and were critical to informing the public regarding the spread of the virus, especially during the early days of the pandemic. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our review also highlighted how scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the future. Conclusions: Despite the limited applications of GIS in identifying the nature and spatio-temporal pattern of this raging pandemic, there are opportunities to utilize these techniques in handling the pandemic. The use of spatial analysis and GIS could significantly improve how we understand the pandemic as well as address the underserviced demographic groups and communities.
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Affiliation(s)
- Rakibul Ahasan
- Nature Study Society of Bangladesh, Khulna Unit, Khulna, 9000, Bangladesh
- EviSyn Health, Khulna, 9000, Bangladesh
- Texas A&M University, College Station, Texas, 77843, USA
| | | | | | - Md. Mahbub Hossain
- Nature Study Society of Bangladesh, Khulna Unit, Khulna, 9000, Bangladesh
- EviSyn Health, Khulna, 9000, Bangladesh
- Texas A&M University, College Station, Texas, 77843, USA
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Dlamini WMD, Simelane SP, Nhlabatsi NM. Bayesian network-based spatial predictive modelling reveals COVID-19 transmission dynamics in Eswatini. SPATIAL INFORMATION RESEARCH 2022; 30:183-194. [PMCID: PMC8602516 DOI: 10.1007/s41324-021-00421-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 10/24/2021] [Accepted: 10/26/2021] [Indexed: 07/18/2023]
Abstract
The first case of COVID-19 in Eswatini was first reported in March 2020, posing an unprecedented challenge to the country’s health and socio-economic systems. Using geographic information system (GIS) data comprising 15 socioeconomic, demographic and environmental variables, we model the spatial variability of COVID-19 transmission risk based on case data for the period under strict lockdown (up to 8th May 2020) and after the lockdown regulations were gradually eased (up to 30th June 2020). We implemented and tested 13 spatial data-driven Bayesian network (BN) learning algorithms to examine the factors that determine the spatial distribution of COVID-19 transmission risk. All the BN models performed very well in predicting the COVID-19 cases as evidenced by low log loss (0.705–0.683) and high recall values (0.821–0.836). The tree-augmented naïve (TAN) model outperformed all other BN learning algorithms. The proximity to major health facilities, churches, shopping centres and supermarkets as well as average annual traffic density were the strongest predictors of transmission risk during strict lockdown. After gradual relaxation of the lockdown, the proportion of the youth (15–40 years old) in an area became the strongest predictor of COVID-19 transmission in addition to the proximity to areas where people congregate, excluding churches. The study provides useful insights on the spatio-temporal dynamics of COVID-19 transmission drivers thereby aiding the design of geographically-targeted interventions. The findings also point to the robustness of BN models in spatial predictive modelling and graphically explaining spatial phenomena under uncertainty and with limited data.
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Affiliation(s)
- Wisdom M. D. Dlamini
- Department of Geography, Environmental Science and Planning, University of Eswatini, Kwaluseni, Eswatini
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Parker B, Chew V. Geographical Mapping in a School District Leverages the Power of Students' Health Data and Services. THE JOURNAL OF SCHOOL HEALTH 2022; 92:109-114. [PMID: 34814228 DOI: 10.1111/josh.13109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 08/22/2021] [Indexed: 06/13/2023]
Affiliation(s)
- Barbara Parker
- Oakland Unified School District, 1000 Broadway Suite 150 Oakland, CA, 94607
| | - Veronica Chew
- Oakland Unified School District, 1000 Broadway Suite 150, Oakland, CA, 94607
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Chimoyi L, Mabuto T, Dube T, Ntombela N, Nchachi T, Tshisebe D, Chetty-Makkan CM, Setswe GK. The geography of COVID-19 misinformation: using geospatial maps for targeted messaging to combat misinformation on COVID-19, South Africa. BMC Res Notes 2021; 14:468. [PMID: 34952634 PMCID: PMC8708513 DOI: 10.1186/s13104-021-05886-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/14/2021] [Indexed: 12/05/2022] Open
Abstract
OBJECTIVE The proliferation of false information on COVID-19 mostly through social media is adversely affecting control efforts. The objective of this study was to identify areas where targeted effective messaging can be useful in demystifying misinformation against COVID-19. RESULTS The study showed high levels of misinformation on COVID-19 in the study area [mean score 2.71; standard deviation (SD) 1.5]. The highest levels of misinformation were observed in Dr. Ruth Segomotsi Mompati district, North West province (mean score: 3.84; SD: 2.1) and Sedibeng district, Gauteng province (mean score: 3.56; SD 1.7). Higher levels of misinformation were reported by those aged 18-24 years (mean score: 3.48; SD: 1.8), and men (mean score: 2.73; SD: 1.8). Across the two provinces, we identified geospatial hot and coldspots of misinformation highlighting the need to implement point of care strategies such as targeted messaging. Findings showed the need for targeted interventions to young people, students, those with low levels of education and the self-employed in the two districts more importantly, as South Africa expands its nationwide vaccination roll-out.
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Affiliation(s)
- Lucy Chimoyi
- The Aurum Institute, Johannesburg, South Africa.
- The Aurum Institute, Aurum House, The Ridge, 29 Queens Road, Parktown, Johannesburg, 2193, South Africa.
| | | | | | | | | | | | - Candice M Chetty-Makkan
- The Aurum Institute, Johannesburg, South Africa
- Health Economics and Research Office, Johannesburg, South Africa
- Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Geoffrey K Setswe
- The Aurum Institute, Johannesburg, South Africa
- Department of Health Studies, University of South Africa, Pretoria, South Africa
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Ashok S, Zaka Ullah M, Vadivelu N, Islam MT, Nasereddin S, Zafar Khan W. Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective. DUBAI MEDICAL JOURNAL 2021. [PMCID: PMC8805079 DOI: 10.1159/000520206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Background The outbreak of coronavirus 2019 (COVID-19) which emerged in December 2019 spread rapidly and created a public health emergency. Geospatial records of case data are needed in real time to monitor and anticipate the spread of infection. Methods This study aimed to identify the emerging hotspots of COVID-19 using a geographic information system (GIS)-based approach. Data of laboratory-confirmed COVID-19 patients from March 15 to June 12, 2020, who visited the emergency department of a tertiary specialized academic hospital in Dubai were evaluated using ArcGIS Pro 2.5. Spatiotemporal analysis, including optimized hotspot analysis, was performed at the community level. Results The cases were spatially concentrated mostly over the inner city of Dubai. Moreover, the optimized hotspot analysis showed statistically significant hotspots (p < 0.01) in the north of Dubai. Waxing and waning hotspots were also observed in the southern and central regions of Dubai. Finally, there were nonsustaining hotspots in communities with a very low population density. Conclusion This study identified hotspots of COVID-19 using geospatial analysis. It is simple and can be easily reproduced to identify disease outbreaks. In the future, more attention is needed in creating a wider geodatabase and identifying hotspots with more intense transmission intensity.
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Augustin J, Sander M, Koller D. [Relevance of health geographic research for dermatology]. Hautarzt 2021; 73:5-14. [PMID: 34846552 DOI: 10.1007/s00105-021-04912-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/20/2021] [Indexed: 11/30/2022]
Abstract
The association between geographic and medical aspects is a well-known phenomenon, which also occurs in dermatological research. This article reviews the field of health geography, the history of the association between spatial location and health, and focuses on current areas of research. Research focusing on explaining regional variations in health refer to individual aspects and needs, population factors, environmental factors, and health care delivery structures in specific regions, as well as the interaction between them. Regional healthcare research is primarily concerned with access to health services and on the utilisation of those services. Methodologically, the analysis of geodata and the application of geographic information systems (GIS) and spatial modelling play a major role in this field. Dermatological research and dermatological practice can benefit from the findings of the regional analysis of access, utilisation, and variations in order to obtain a more detailed picture of care and thus to optimise care.
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Affiliation(s)
- J Augustin
- Institut für Versorgungsforschung in der Dermatologie und bei Pflegeberufen (IVDP), Universitätsklinikum Hamburg-Eppendorf (UKE), CVderm
- CPW 3, Martinistr. 52, 20246, Hamburg, Deutschland.
| | - M Sander
- Institut für Versorgungsforschung in der Dermatologie und bei Pflegeberufen (IVDP), Universitätsklinikum Hamburg-Eppendorf (UKE), CVderm
- CPW 3, Martinistr. 52, 20246, Hamburg, Deutschland
| | - D Koller
- Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München (LMU), Marchioninistr. 15, 81377, München, Deutschland
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14
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Ghatee MA, Nikaein K, Rajaie O, Taylor WR, Karamian M. A comparative study of the proximity to nomadic travel routes and environmental factors on the occurrence of cutaneous leishmaniasis in Kohgiluyeh and Boyer-Ahmad province, southwestern Iran. Transbound Emerg Dis 2021; 69:e547-e553. [PMID: 34558217 DOI: 10.1111/tbed.14332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 09/03/2021] [Accepted: 09/18/2021] [Indexed: 11/27/2022]
Abstract
Cutaneous leishmaniasis (CL) is one of the most important health challenges in hyperendemic countries like Iran. Geospatial information systems-based studies have shown that factors, including land cover, altitude, slope temperature, rainfall and animal livestock, affect CL distribution in Kohgyloyeh and Boyerahmad province, southwestern Iran. However, the question of the influence of nomadic tribes, who travel with their goats and sheep, on CL is unanswered. We, therefore, investigated their role in CL epidemiology from 2008 to 2017 and compare them with geoclimatic factors. CL patient demographic data and their village/city addresses were retrieved from Provincial Health Center and mapped on the geographic information system (GIS) layer of the province's political divisions. Nomadic travel routes (NTRs) with a 2 km buffer were generated and their effect on CL was investigated together with the interpolated layers of rainfall, temperatures, humidity, slope, elevation, land covers, by binary regression. CL was significantly more common in villages/cities in the 2 km NTR zone (p value < .001; OR = 1.96; 95% CI = 1.4-2.745). Geoclimatic factors, including slope, elevation, rainfall, temperatures, humidity and most of the landcovers, were not significantly different inside and outside the NTR. Areas of irrigated farm were the only effective landcover on CL (p value = .049; OR = 2.717; 95% CI = 1.003-7.361) within the NTR versus non-NTR. Living within NTRs almost doubled the risk of acquiring CL. Several factors for this include passage through areas of high sand fly activity, increased contact between sandflies and humans, sheep and goats, and feeding on their blood and faeces, and low availability of health facilities that should be more investigated and considered in the future control programs.
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Affiliation(s)
- Mohammad Amin Ghatee
- Medical Microbiology Department, School of Medicine, Yasuj University of Medical Sciences, Yasuj, Iran.,Cellular and Molecular Research Center, Yasuj University of Medical Sciences, Yasuj, Iran
| | - Koorosh Nikaein
- Student Research Committee, Yasuj University of Medical Sciences, Yasuj, Iran
| | - Omid Rajaie
- Student Research Committee, Yasuj University of Medical Sciences, Yasuj, Iran
| | - Walter Robert Taylor
- Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand.,Oxford Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Mehdi Karamian
- Department of Parasitology and Mycology, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
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15
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Geospatial Analysis and Mapping Strategies for Fine-Grained and Detailed COVID-19 Data with GIS. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2021. [DOI: 10.3390/ijgi10090602] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects.
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16
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Tseng TS, Celestin MD, Yu Q, Li M, Luo T, Moody-Thomas S. Use of Geographic Information System Technology to Evaluate Health Disparities in Smoking Cessation Class Accessibility for Patients in Louisiana Public Hospitals. Front Public Health 2021; 9:712635. [PMID: 34476230 PMCID: PMC8406529 DOI: 10.3389/fpubh.2021.712635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/14/2021] [Indexed: 11/13/2022] Open
Abstract
Research has shown cigarette smoking is a major risk factors for many type of cancer or cancer prognosis. Tobacco related health disparities were addressed continually in cancer screening, diagnosis, treatment, prevention and control. The present study evaluated the health disparities in attendance of smoking cessation counseling classes for 4,826 patients scheduled to attend between 2005 and 2007. Of 3,781 (78.4%) patients with records to calculate the distance from their home domicile to counseling sites using Geographic Information System technology, 1,435 (38%) of smokers who attended counseling had shorter travel distances to counseling sites (11.6 miles, SD = 11.29) compared to non-attendees (13.4 miles, SD = 16.72). When the travel distance was >20 miles, the estimated odds of attending decreased with greater travel distance. Smokers who actually attended were more likely to be older, female, White, living in urban areas, and receiving free healthcare. After controlling for other socio-demographic factors, shorter distances were associated with greater class attendance, and individuals more likely to attend included those that lived closer to the counseling site and in urban settings, were female, White, commercially insured, and older than their counterparts. These findings have the potential to provide important insights for reducing health disparities for cancer prevention and control, and to improve shared decision making between providers and smokers.
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Affiliation(s)
- Tung Sung Tseng
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, United States
| | - Michael D Celestin
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, United States
| | - Qingzhao Yu
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, United States
| | - Mirandy Li
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, United States.,Louisiana State University Health New Orleans, School of Medicine, New Orleans, LA, United States
| | - Ting Luo
- Moores Cancer Center, School of Medicine, University of California San Diego, San Diego, CA, United States
| | - Sarah Moody-Thomas
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, United States
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17
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Nayak PP, Pai JB, Singla N, Somayaji KS, Kalra D. Geographic Information Systems in Spatial Epidemiology: Unveiling New Horizons in Dental Public Health. J Int Soc Prev Community Dent 2021; 11:125-131. [PMID: 34036072 PMCID: PMC8118043 DOI: 10.4103/jispcd.jispcd_413_20] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 12/15/2020] [Accepted: 02/28/2021] [Indexed: 11/06/2022] Open
Abstract
Objectives: Research on the role of environment and place in various aspects of dental public health using geographic information systems (GIS) is escalating rapidly. Yet, the understanding of GIS and the analytical tools that it offers are still vaguely understood. This narrative review therefore draws from the utilization of GIS in the dental public health research. Materials and Methods: Electronic databases such as Google Scholar, PUBMED, and Scopus were searched using terms “spatial epidemiology,” “GIS,” “geographic information systems,” “health geography,” “environment public health tracking,” “spatial distribution,” “disease mapping,” “geographic correlation studies,” “cartography,” “big data,” and “disease clustering” through December 2019. Results: This review builds upon the prospects of GIS application in various aspects of dental public health. Studies were classified as: (1) GIS for mapping of disease, population at risk, and risk factors; (2) GIS in geographic correlation studies; (3) GIS for gauging healthcare accessibility and spatial distribution of healthcare providers. We also identified the commonly used GIS analytical techniques in oral epidemiology. Conclusions: We anticipate that this review will spur advancement in the utilization of spatial analytical techniques and GIS in the dental public health research.
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Affiliation(s)
- Prajna Pramod Nayak
- Department of Public Health Dentistry, Manipal College of Dental Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Jagadeesha B Pai
- Department of Civil Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Nishu Singla
- Department of Public Health Dentistry, Manipal College of Dental Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Krishnaraj S Somayaji
- Department of Conservative Dentistry and Endodontics, Manipal College of Dental Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Dheeraj Kalra
- Department of Public Health Dentistry, YMT Dental College and Hospital, Navi Mumbai, Maharashtra, India
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18
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Kreisel CJ, Wilson LK, Schneider AL, Mohatt NV, Spark TL. Reducing rural veteran suicides: Navigating geospatial and community contexts for scaling up a national Veterans Affairs program. Suicide Life Threat Behav 2021; 51:344-351. [PMID: 33876499 PMCID: PMC8252578 DOI: 10.1111/sltb.12710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 06/05/2020] [Accepted: 07/09/2020] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To develop and use planning maps to prioritize and facilitate county-level recruitment for Together With Veterans (TWV), community-based rural Veteran suicide prevention program. METHOD Choropleth maps were created for 49 U.S. states, with four mutually exclusive categories indicating eligibility for the TWV program and increasing levels of need assigned to each county based on (a) percent Veterans Health Administration enrollees residing in rural communities, (b) percent population that are Veterans, and (c) crude suicide mortality rate. RESULTS Of 3113 counties, 78.2% were eligible for TWV and 25.8% met our highest priority definition. A national map and state map were provided to demonstrate final products used to engage stakeholders. A table of recommendations for creating and using planning maps was provided for future projects to reference. CONCLUSIONS Geographic information system (GIS) is useful for identifying and prioritizing counties that may benefit most from a rural Veteran suicide prevention program. Choropleth maps allow for dissemination of information about county suicide risk and need for suicide prevention to community members, researchers, and others with a vested interest in suicide reduction. The maps are one tool among many which can support decision-makers in focusing available resources on populations with the most need.
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Affiliation(s)
- Carlee J. Kreisel
- Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC)Rocky Mountain Regional VA Medical Center, U.S. Department of Veterans AffairsAuroraCOUSA,Department of Physical Medicine and RehabilitationUniversity of Colorado Anschutz Medical CampusAuroraCOUSA
| | - Lauren K. Wilson
- GeoSpatial Outcomes Division (GSOD), Veterans Rural Health Resource Center (VRHRC‐GNV), VHA Office of Rural Health (ORH)U.S. Department of Veterans AffairsGainesvilleFLUSA
| | - Alexandra L. Schneider
- Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC)Rocky Mountain Regional VA Medical Center, U.S. Department of Veterans AffairsAuroraCOUSA
| | - Nathaniel V. Mohatt
- Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC)Rocky Mountain Regional VA Medical Center, U.S. Department of Veterans AffairsAuroraCOUSA,Department of Physical Medicine and RehabilitationUniversity of Colorado Anschutz Medical CampusAuroraCOUSA,Department of PsychiatryYale University School of MedicineNew HavenCTUSA
| | - Talia L. Spark
- Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC)Rocky Mountain Regional VA Medical Center, U.S. Department of Veterans AffairsAuroraCOUSA
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19
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Dashboard COMPRIME_COMPRI_MOv: Multiscalar Spatio-Temporal Monitoring of the COVID-19 Pandemic in Portugal. FUTURE INTERNET 2021. [DOI: 10.3390/fi13020045] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Due to its novelty, the recent pandemic of the coronavirus disease (COVID-19), which is associated with the spread of the new severe acute respiratory syndrome coronavirus (SARS-CoV-2), triggered the public’s interest in accessing information, demonstrating the importance of obtaining and analyzing credible and updated information from an epidemiological surveillance context. For this purpose, health authorities, international organizations, and university institutions have published online various graphic and cartographic representations of the evolution of the pandemic with daily updates that allow the almost real-time monitoring of the evolutionary behavior of the spread, lethality, and territorial distribution of the disease. The purpose of this article is to describe the technical solution and the main results associated with the publication of the COMPRIME_COMPRI_MOv dashboard for the dissemination of information and multi-scale knowledge of COVID-19. Under two rapidly implementing research projects for innovative solutions to respond to the COVID-19 pandemic, promoted in Portugal by the FCT (Foundation for Science and Technology), a website was created. That website brings together a diverse set of variables and indicators in a dynamic and interactive way that reflects the evolutionary behavior of the pandemic from a multi-scale perspective, in Portugal, constituting itself as a system for monitoring the evolution of the pandemic. In the current situation, this type of exploratory solutions proves to be crucial to guarantee everyone’s access to information while simultaneously emerging as an epidemiological surveillance tool that is capable of assisting decision-making by public authorities with competence in defining control policies and fight the spread of the new coronavirus.
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20
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Fornace KM, Diaz AV, Lines J, Drakeley CJ. Achieving global malaria eradication in changing landscapes. Malar J 2021; 20:69. [PMID: 33530995 PMCID: PMC7856737 DOI: 10.1186/s12936-021-03599-0] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 01/20/2021] [Indexed: 11/10/2022] Open
Abstract
Land use and land cover changes, such as deforestation, agricultural expansion and urbanization, are one of the largest anthropogenic environmental changes globally. Recent initiatives to evaluate the feasibility of malaria eradication have highlighted impacts of landscape changes on malaria transmission and the potential of these changes to undermine malaria control and elimination efforts. Multisectoral approaches are needed to detect and minimize negative impacts of land use and land cover changes on malaria transmission while supporting development aiding malaria control, elimination and ultimately eradication. Pathways through which land use and land cover changes disrupt social and ecological systems to increase or decrease malaria risks are outlined, identifying priorities and opportunities for a global malaria eradication campaign. The impacts of land use and land cover changes on malaria transmission are complex and highly context-specific, with effects changing over time and space. Landscape changes are only one element of a complex development process with wider economic and social dimensions affecting human health and wellbeing. While deforestation and other landscape changes threaten to undermine malaria control efforts and have driven the emergence of zoonotic malaria, most of the malaria elimination successes have been underpinned by agricultural development and land management. Malaria eradication is not feasible without addressing these changing risks while, conversely, consideration of malaria impacts in land management decisions has the potential to significantly accelerate progress towards eradication. Multisectoral cooperation and approaches to linking malaria control and environmental science, such as conducting locally relevant ecological monitoring, integrating landscape data into malaria surveillance systems and designing environmental management strategies to reduce malaria burdens, are essential to achieve malaria eradication.
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Affiliation(s)
- Kimberly M Fornace
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. .,Centre for Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK.
| | - Adriana V Diaz
- Pathology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - Jo Lines
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.,Centre for Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Chris J Drakeley
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.,Centre for Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK
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21
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Meer MS, Mishra AK. GIS approach for mapping novel coronavirus in northern state of India, Jammu and Kashmir. ENVIRONMENTAL EARTH SCIENCES 2021; 80:540. [PMID: 34413906 PMCID: PMC8363868 DOI: 10.1007/s12665-021-09856-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 07/30/2021] [Indexed: 05/17/2023]
Abstract
Novel coronavirus "COVID-19" has affected worldwide. At initial stage, the way out to curb the deadly virus was lockdown, isolating the symptomatic people, quarantining travellers and educating the people about the coronavirus infection so that precautionary measures are followed by people. The present research focuses on the application of Geographic Information System on mapping the coronavirus cases in Jammu and Kashmir. The research attributes the role of dense population and urbanization responsible for increasing the coronavirus cases in the study area. The districts like Srinagar and Jammu with high population and urbanization (census 2011) attribute high number of corona cases in year 2020. This high population experiences the highest number of corona cases (Jammu 23,339, Srinagar 24,996), deaths (Jammu 350, Srinagar 444) and COVID-19 recoveries (Jammu 22,141, Srinagar 23,957). The highly urbanized and populated area are much exposed towards infection. The high number of corona case experiences heart-related issues. The number of heart-related deaths are increased to 29.6% during winter in study area by extreme weather conditions limiting regular exercising and outdoor activities. But, due to COVID-19 the amount of heart-related deaths has significantly increased, which is crucial for the study area. This study will serve as replica study for managing COVID-19 in Jammu and Kashmir and help the medical fraternity by giving the priority for vaccinating the people and managing the facility related to COVID-19. The GIS was used to mitigate the infection of COVID-19 on life.
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Affiliation(s)
- Mohammad Suhail Meer
- Centre for Remote Sensing and Geoinformatics, Sathyabama Institute of Science and Technology, Chennai, India
| | - Anoop Kumar Mishra
- Satmet Division, Office of Director General of Meteorology, India Meteorological Department, Ministry of Earth Sciences, Mausam Bhavan, New Delhi, 110003 India
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22
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Yahya BM, Yahya FS, Thannoun RG. COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq. APPLIED GEOMATICS 2021; 13. [PMCID: PMC7929909 DOI: 10.1007/s12518-021-00365-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
The prediction of diseases caused by viral infections is a complex medical task where many real data that consists of different variables must be employed. As known, COVID-19 is the most dangerous disease worldwide; nowhere, an effective drug has been found yet. To limit its spread, it is essential to find a rational method that shows the spread of this virus by relying on many infected people’s data. A model consisting of three artificial neural networks’ (ANN) functions was developed to predict COVID-19 separation in Iraq based on real infection data supplied by the public health department at the Iraqi Ministry of Health. The performance efficiency of this model was evaluated, where its performance efficiency reached 81.6% when employed four statistical error criteria as mean absolute percentage error (MAPE), root mean square error (RMSE), coefficient of determination (R2), and Nash-Sutcliffe coefficient (NC). The severity of the virus’s spread across Iraq was assessed in a short term (in the next 6 months), where the results show that the spread severity will intensify in this short term by 17.1%, and the average death cases will increase by 8.3%. These results clarified by creating spatial distribution maps for virus spread are simulated by employing a Geographic Information System (GIS) environment to be used as a useful database for developing plans for combating viruses in Iraq.
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Ahasan R, Hossain MM. Leveraging GIS and spatial analysis for informed decision-making in COVID-19 pandemic. HEALTH POLICY AND TECHNOLOGY 2020; 10:7-9. [PMID: 33318916 PMCID: PMC7725052 DOI: 10.1016/j.hlpt.2020.11.009] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Rakibul Ahasan
- Department of Geography, Texas A&M University, College Station, TX 77843, USA
| | - Md Mahbub Hossain
- Department of Health Promotion and Community Health Sciences, Texas A&M School of Public Health, TX 77843, USA
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24
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Ramadan A, Kamel A, Taha A, El-Shabrawy A, Abdel-Fatah NA. A multivariate data analysis approach for investigating daily statistics of countries affected with COVID-19 pandemic. Heliyon 2020; 6:e05575. [PMID: 33251372 PMCID: PMC7685045 DOI: 10.1016/j.heliyon.2020.e05575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 09/01/2020] [Accepted: 11/18/2020] [Indexed: 01/10/2023] Open
Abstract
Background To understand the impact and volume of coronavirus (COVID-19) crisis, univariate analysis is tedious for describing the datasets reported daily. However, to capture the full picture and be able to compare situations and consequences for different countries, multivariate analytical models are suggested in order to visualize and compare the situation of different countries more accurately and precisely. Aims We aimed to utilize data analysis tools that display the relative positions of data points in fewer dimensions while keeping the variation of the original data set as much as possible, and cluster countries according to their scores on the formed dimensions. Methods Principal component analysis (PCA) and Partitioning around medoids (PAM) clustering algorithms were used to analyze data of 56 countries, 82 countries and 91 countries with COVID-19 at three time points, eligible countries included in the analysis are those with total cases of 500 or more with no missing data. Results After performing PCA, we generated two scores: Disease Magnitude score that represents total cases, total deaths, total actives cases, and critically ill cases, and Mortality Recovery Ratio score that represents the ratio between total deaths to total recoveries in any given country. Conclusion Accurate multivariate analyses can be of great value as they can simplify difficult concepts, explore and communicate findings from health datasets, and support the decision-making process.
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Affiliation(s)
- Ahmed Ramadan
- Data Science and Medical Information Department, DataClin Contract Research Organization, Egypt.,Department of Biostatistics and Demography, Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt
| | - Ahmed Kamel
- Medical Affairs Department, DataClin Contract Research Organization, Egypt
| | - Alaa Taha
- Department of Biostatistics and Demography, Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt
| | - Abdelhamid El-Shabrawy
- Department of Biostatistics and Demography, Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt
| | - Noura Anwar Abdel-Fatah
- Department of Biostatistics and Demography, Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt
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25
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Ahasan R, Alam MS, Chakraborty T, Hossain MM. Applications of GIS and geospatial analyses in COVID-19 research: A systematic review. F1000Res 2020; 9:1379. [PMID: 35186280 PMCID: PMC8822139 DOI: 10.12688/f1000research.27544.1] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/25/2022] [Indexed: 07/22/2023] Open
Abstract
Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Geospatial techniques, especially WebGIS, have even been widely used to visualize the data on a map and were critical to informing the public regarding the spread of the virus, especially during the early days of the pandemic. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our review also highlighted how scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the future. Conclusions: Despite the limited applications of GIS in identifying the nature and spatio-temporal pattern of this raging pandemic, there are opportunities to utilize these techniques in handling the pandemic. The use of spatial analysis and GIS could significantly improve how we understand the pandemic as well as address the underserviced demographic groups and communities.
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Affiliation(s)
- Rakibul Ahasan
- Nature Study Society of Bangladesh, Khulna Unit, Khulna, 9000, Bangladesh
- EviSyn Health, Khulna, 9000, Bangladesh
- Texas A&M University, College Station, Texas, 77843, USA
| | | | | | - Md. Mahbub Hossain
- Nature Study Society of Bangladesh, Khulna Unit, Khulna, 9000, Bangladesh
- EviSyn Health, Khulna, 9000, Bangladesh
- Texas A&M University, College Station, Texas, 77843, USA
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26
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Rahman MR, Islam AHMH, Islam MN. Geospatial modelling on the spread and dynamics of 154 day outbreak of the novel coronavirus (COVID-19) pandemic in Bangladesh towards vulnerability zoning and management approaches. ACTA ACUST UNITED AC 2020; 7:2059-2087. [PMID: 32929411 PMCID: PMC7480637 DOI: 10.1007/s40808-020-00962-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 09/01/2020] [Indexed: 12/17/2022]
Abstract
The novel COVID-19 is a worldwide transmitted pandemic and has received global attention. Since there is no effective medication yet, to minimize and control the transmission of the COVID-19, non-pharmaceutical interventions (NPIs) are followed globally. However, for the implementation of needful NPIs through effective management strategies and planning, space–time-based information on the nature, magnitude, pattern of transmission, hotspots, the potential risk factors, vulnerability, and risk level of the pandemic are important. Hence, this study was an attempt to in-depth assess and analyze the COVID-19 outbreak and transmission dynamics through space and time in Bangladesh using 154 day real-time epidemiological data series. District-level data were analyzed for the geospatial analysis and modelling using GIS. Getis‐Ord Gi* statistics was applied for the hotspot analysis, and on the other hand, the analytical hierarchy process-based weighted sum method (AHP-WSM) was used for the modelling of vulnerability zoning of COVID-19. In Bangladesh, the status of the pandemic COVID-19 still is in exposure level. Disease transmitted at a high rate (20.37%), and doubling time of the cases were 11 days (latest week of the study period). The fatality rate was comparatively low (1.3%), and the recovery rate was about 57.50%. Geospatial analysis exhibits the disease propagates from the central parts, and Dhaka was the most exposed district followed by Chattogram, Narayanganj, Cumilla, and Bogra. A single strong clustering pattern in the central part, which spread out mainly to the south-eastern part, was identified as a prime hotspot in both the cases and deaths distributions. Additionally, potential linkages between the transmission of disease and the selected factors that gear up the spreading of the disease were identified. The central, eastern, and south-eastern parts were recognized as high vulnerable zone, and conversely, the western, south-western, north-western, and north-eastern parts as medium vulnerable zone. The vulnerable zoning exercise made it possible to identify vulnerable areas with the different magnitude that require urgent intervention through proper management and action plan, and accordingly, comprehensive management strategies were anticipated. Thus, this study will be a useful guide towards understanding the space–time-based investigations and vulnerable area delineation of the COVID-19 and assist to formulate an effective management action plan to reduce and control the disease propagation and impacts. By appropriate adjustment of some factors with local relevance, COVID-19 vulnerability zoning derived here can be applied to other regions, and generally can be used for any other infectious disease. This method was applied at a regional scale, but the availability of larger scale data of the determining factors could be applied in small areas too, and accordingly, management strategies can be formulated.
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Affiliation(s)
- Md Rejaur Rahman
- Department of Geography and Environmental Studies, University of Rajshahi, Rajshahi, 6205 Bangladesh
| | - A H M Hedayutul Islam
- Department of Geography and Environmental Studies, University of Rajshahi, Rajshahi, 6205 Bangladesh
| | - Md Nazrul Islam
- Department of Geography and Environment, Jahangirnagar University, Savar, Dhaka, 1342 Bangladesh
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Abstract
Cystic echinococcosis (CE) is caused by the larval form of Echinococcus granulosus that can cause serious health and economic problems in the endemic foci. CE is globally distributed in various climatic conditions from circumpolar to tropical latitudes. Iran is an important endemic area with a spectrum of weather conditions. The aim of this study was to determine the effects of geo-climatic factors on the distribution of livestock CE in south-western Iran (SWI) in 2016 to 2018. Data of livestock CE were retrieved from veterinary organizations of four provinces of SWI. The geo-climatic factors, including mean annual temperature (MAT), minimum MAT (MinMAT), maximum MAT (MaxMAT), mean annual rainfall (MAR), elevation, mean annual evaporation (MAE), sunny hours, wind speed, mean annual humidity (MAH), slope, frost days and land cover, were analysed using geographical information systems (GIS) approaches. The statistical analysis showed that MAR, frost days, elevation, slope and semi-condensed forest land cover were positively and MAE, MAT, MaxMAT, MinMAT and salt and salinity land cover were negatively correlated with CE occurrence. MAE was shown to be a predictive factor in the stepwise linear logistic regression model. In short, the current GIS-based study found that areas with lower evaporation were the main CE risk zones, though those with lower temperature and higher rainfall, altitude and slope, especially where covered with or in close proximity of semi-condensed forest, should be prioritized for consideration by health professionals and veterinarians for conducting control programmes in SWI.
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Sarfo AK, Karuppannan S. Application of Geospatial Technologies in the COVID-19 Fight of Ghana. TRANSACTIONS OF THE INDIAN NATIONAL ACADEMY OF ENGINEERING : AN INTERNATIONAL JOURNAL OF ENGINEERING AND TECHNOLOGY 2020; 5:193-204. [PMID: 38624469 PMCID: PMC7334632 DOI: 10.1007/s41403-020-00145-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 06/19/2020] [Accepted: 06/25/2020] [Indexed: 12/24/2022]
Abstract
The SARS-CoV-2 infections continue unabated in Ghana and globally. The identification of country dynamics of the virus, its spread, and country-specific interventions in tackling the menace including the application of geospatial technologies. This research sought to highlight the use of geospatial technologies in the fight against COVID-19 in Ghana with best practices from China where the infections originated from; present the trends in Ghana and model near future trends of the virus. It was evident that just as other places, Ghana has employed geospatial technologies and continues to ply unchartered paths in solutions. The trend in Ghana is in line with a population concentration and tends to record higher figures in the southern parts. It is modeled that through incessant mobility patterns, infections will spread through to the middle parts and then the northern parts. The research, therefore, recommends the use of infrared scanners to augment testing practices and enhanced tracing of infected persons as well as the use of drones for the distribution of essential services.
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Affiliation(s)
- Anthony Kwabena Sarfo
- Department of Planning, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Shankar Karuppannan
- Department of Applied Geology, School of Applied Natural Science, Adama Science and Technology University, Adama, Ethiopia
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Unfolding Events in Space and Time: Geospatial Insights into COVID-19 Diffusion in Washington State during the Initial Stage of the Outbreak. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2020. [DOI: 10.3390/ijgi9060382] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The world witnessed the COVID-19 pandemic in 2020. The first case of COVID-19 in the United States of America (USA) was confirmed on 21 January 2020, in Snohomish County in Washington State (WA). Following this, a rapid explosion of COVID-19 cases was observed throughout WA and the USA. Lack of access to publicly available spatial data at finer scales has prevented scientists from implementing spatial analytical techniques to gain insights into the spread of COVID-19. Datasets were available only as counts at county levels. The spatial response to COVID-19 using coarse-scale publicly available datasets was limited to web mapping applications and dashboards to visualize infected cases from state to county levels only. This research approaches data availability issues by creating proxy datasets for COVID-19 using publicly available news articles. Further, these proxy datasets are used to perform spatial analyses to unfolding events in space and time and to gain insights into the spread of COVID-19 in WA during the initial stage of the outbreak. Spatial analysis of theses proxy datasets from 21 January to 23 March 2020, suggests the presence of a clear space–time pattern. From 21 January to 6 March, a strong presence of community spread of COVID-19 is observed only in close proximity of the outbreak source in Snohomish and King Counties, which are neighbors. Infections diffused to farther locations only after a month, i.e., 6 March. The space–time pattern of diffusion observed in this study suggests that implementing strict social distancing measures during the initial stage in infected locations can drastically help curb the spread to distant locations.
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Murugesan B, Karuppannan S, Mengistie AT, Ranganathan M, Gopalakrishnan G. Distribution and Trend Analysis of COVID-19 in India: Geospatial Approach. ACTA ACUST UNITED AC 2020. [DOI: 10.21523/gcj5.20040101] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
COVID-19 Coronavirus is now one of the most contagious diseases of the recently discovered and spread across the China in 2019 and has received global attention. In most COVID-19-infected individuals, respiratory symptoms should be mild to moderate and improve without the need for medical care. The risk of serious disease is higher for senior citizens and people with serious health problems, such as heart disease, diabetes, severe respiratory disease, and cancer. The World Health Organization (WHO) has formally declared the outbreak of COVID-19 to be a global pandemic. As on 11th April 2020 in India the largest number of persons testing positive for COVID-19 since the outbreak earlier month with samples of people, mostly contacts of already confirmed patients, rendering positive. In India total confirmed cases 7364, 633 are cured/discharged, with 240 deaths had been reported by the Ministry of Health and Family Welfare Government of India. The aim of the research is to analyze the spatial distribution of COVID-19 and its trends with the help of GIS software. At this time, there are no precise antibiotics or treatment options for COVID-19. Besides, several ongoing clinical studies are assessing effective treatments. The best way to protect and sluggish transmission should be well advised about the current COVID-19 virus, the disease it triggers and also how it continues to spread. Therefore, monitoring active ties using GIS spatial analysis is very important to control such as a COVID-19 virus spreading problem.
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Affiliation(s)
- Bagyaraj Murugesan
- Department of Geology, College of Natural and Computational Sciences, Debre Berhan University, P.O.Box 445, Debre Berhan, Ethiopia
| | - Shankar Karuppannan
- Department of Applied Geology, School of Applied Natural Science, Adama Science and Technology University, Adama, Ethiopia
| | - Alemayehu Tenaw Mengistie
- Department of Geology, College of Natural and Computational Sciences, Debre Berhan University, P.O.Box 445, Debre Berhan, Ethiopia
| | | | - Gnanachandrasamy Gopalakrishnan
- School of Geography and Planning, Research Centre for Earth, Environment and Resources Sun Yat-Sen University, Guangzhou, 510275, P.R. China
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Kamel Boulos MN, Geraghty EM. Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics. Int J Health Geogr 2020; 19:8. [PMID: 32160889 PMCID: PMC7065369 DOI: 10.1186/s12942-020-00202-8] [Citation(s) in RCA: 300] [Impact Index Per Article: 75.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 02/26/2020] [Indexed: 11/21/2022] Open
Abstract
In December 2019, a new virus (initially called ‘Novel Coronavirus 2019-nCoV’ and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China, and rapidly spread to other parts of China and other countries around the world, despite China’s massive efforts to contain the disease within Hubei. As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza, geographic information systems and methods, including, among other application possibilities, online real-or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time, are proving indispensable for timely and effective epidemic monitoring and response. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the 2019/2020 coronavirus epidemic and associated events as they unfold around the world. Some of these dashboards and applications are receiving data updates in near-real-time (at the time of writing), and one of them is meant for individual users (in China) to check if the app user has had any close contact with a person confirmed or suspected to have been infected with SARS-CoV-2 in the recent past. We also discuss additional ways GIS can support the fight against infectious disease outbreaks and epidemics.
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Affiliation(s)
- Maged N Kamel Boulos
- School of Information Management, Sun Yat-sen University, East Campus, Guangzhou, 510006, Guangdong, China.
| | - Estella M Geraghty
- Esri (Environmental Systems Research Institute), 380 New York St, Redlands, CA, 92373, USA
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Saran S, Singh P, Kumar V, Chauhan P. Review of Geospatial Technology for Infectious Disease Surveillance: Use Case on COVID-19. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 2020; 48. [PMCID: PMC7433774 DOI: 10.1007/s12524-020-01140-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
This paper discusses on the increasing relevancy of geospatial technologies such as geographic information system (GIS) in the public health domain, particularly for the infectious disease surveillance and modelling strategies. Traditionally, the disease mapping tasks have faced many challenges—(1) authors rarely documented the evidence that were used to create map, (2) before evolution of GIS, many errors aroused in mapping tasks which were expanded extremely at global scales, and (3) there were no fidelity assessment of maps which resulted in inaccurate precision. This study on infectious diseases geo-surveillance is divided into four broad sections with emphasis on handling geographical and temporal issues to help in public health decision-making and planning policies: (1) geospatial mapping of diseases using its spatial and temporal information to understand their behaviour across geography; (2) the citizen’s involvement as volunteers in giving health and disease data to assess the critical situation for disease’s spread and prevention in neighbourhood effect; (3) scientific analysis of health-related behaviour using mathematical epidemiological and geo-statistical approaches with (4) capacity building program. To illustrate each theme, recent case studies are cited and case studies are performed on COVID-19 to demonstrate selected models.
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Affiliation(s)
- Sameer Saran
- Indian Institute of Remote Sensing, Indian Space Research Organisation, #4, Kalidas Road, Dehradun, 248001 India
| | - Priyanka Singh
- Indian Institute of Remote Sensing, Indian Space Research Organisation, #4, Kalidas Road, Dehradun, 248001 India
| | - Vishal Kumar
- Indian Institute of Remote Sensing, Indian Space Research Organisation, #4, Kalidas Road, Dehradun, 248001 India
| | - Prakash Chauhan
- Indian Institute of Remote Sensing, Indian Space Research Organisation, #4, Kalidas Road, Dehradun, 248001 India
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A Survey on Mortality Trend in the West and East of Iran Using the Bayesian Spatio-Temporal Model. HEALTH SCOPE 2019. [DOI: 10.5812/jhealthscope.61388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Robin TA, Khan MA, Kabir N, Rahaman ST, Karim A, Mannan II, George J, Rashid I. Using spatial analysis and GIS to improve planning and resource allocation in a rural district of Bangladesh. BMJ Glob Health 2019; 4:e000832. [PMID: 31321091 PMCID: PMC6606075 DOI: 10.1136/bmjgh-2018-000832] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 08/02/2018] [Accepted: 08/03/2018] [Indexed: 11/17/2022] Open
Abstract
The application of a geographic information system (GIS) in public health is relatively common in Bangladesh. However, the use of GIS for planning, monitoring and decision-making by local-level managers has not been well documented. This assessment explored how effectively local government health managers used maps with spatial data for planning, resource allocation and programme monitoring. The United States Agency for International Development-funded MaMoni Health Systems Strengthening project supported the introduction of the maps into district planning processes in 2015 and 2016. GIS maps were used to support the prioritisation of underserved unions (the lowest administrative units) and clusters of disadvantaged communities for the allocation of funds. Additional resources from local government budgets were allocated to the lowest performing unions for improving health facility service readiness and supervision. Using a mixed-methods approach, the project evaluated the outputs of this planning process. District planning reports, population-based surveys, local government annual expenditure reports and service availability and utilisation data were reviewed. The goal was to determine the degree to which district planning teams were able to use the maps for their intended purpose. Key informant interviews were conducted with upazila (subdistrict) managers, elected government representatives and service providers to understand how the maps were used, as well as to identify potential institutionalisation scopes. The project observed improvements in health service availability and utilisation in the highest priority unions in 2016. Quick processing of maps during planning sessions was challenging. Nevertheless, managers and participants expressed their satisfaction with the use of spatial analysis, and there was an expressed need for more web-based GIS both for improving community-level service delivery and for reviewing performance in monthly meetings. Despite some limitations, the use of GIS maps helped local health managers identify health service gaps, prioritise underserved unions and monitor results.
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Affiliation(s)
- T A Robin
- MaMoni Health Systems Strengthening Project, Save the Children International, Dhaka, Bangladesh
| | - Marufa Aziz Khan
- MaMoni Health Systems Strengthening Project, Save the Children International, Dhaka, Bangladesh
| | - Nazmul Kabir
- MaMoni Health Systems Strengthening Project, Save the Children International, Dhaka, Bangladesh
| | - Sk Towhidur Rahaman
- MaMoni Health Systems Strengthening Project, Save the Children International, Dhaka, Bangladesh
| | - Afsana Karim
- MaMoni Health Systems Strengthening Project, Save the Children International, Dhaka, Bangladesh
| | | | - Joby George
- MaMoni Health Systems Strengthening Project, Save the Children International, Dhaka, Bangladesh
| | - Iftekhar Rashid
- United States Agency for International Development (USAID), Dhaka, Bangladesh
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Boyda DC, Holzman SB, Berman A, Grabowski MK, Chang LW. Geographic Information Systems, spatial analysis, and HIV in Africa: A scoping review. PLoS One 2019; 14:e0216388. [PMID: 31050678 PMCID: PMC6499437 DOI: 10.1371/journal.pone.0216388] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 04/20/2019] [Indexed: 02/06/2023] Open
Abstract
INTRODUCTION Geographic Information Systems (GIS) and spatial analysis are emerging tools for global health, but it is unclear to what extent they have been applied to HIV research in Africa. To help inform researchers and program implementers, this scoping review documents the range and depth of published HIV-related GIS and spatial analysis research studies conducted in Africa. METHODS A systematic literature search for articles related to GIS and spatial analysis was conducted through PubMed, EMBASE, and Web of Science databases. Using pre-specified inclusion criteria, articles were screened and key data were abstracted. Grounded, inductive analysis was conducted to organize studies into meaningful thematic areas. RESULTS AND DISCUSSION The search returned 773 unique articles, of which 65 were included in the final review. 15 different countries were represented. Over half of the included studies were published after 2014. Articles were categorized into the following non-mutually exclusive themes: (a) HIV geography, (b) HIV risk factors, and (c) HIV service implementation. Studies demonstrated a broad range of GIS and spatial analysis applications including characterizing geographic distribution of HIV, evaluating risk factors for HIV, and assessing and improving access to HIV care services. CONCLUSIONS GIS and spatial analysis have been widely applied to HIV-related research in Africa. The current literature reveals a diversity of themes and methodologies and a relatively young, but rapidly growing, evidence base.
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Affiliation(s)
- Danielle C. Boyda
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America
| | - Samuel B. Holzman
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Amanda Berman
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America
- Johns Hopkins Bloomberg School of Public Health Center for Communication Programs, Baltimore, MD, United States of America
| | - M. Kathyrn Grabowski
- Department of Pathology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Larry W. Chang
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
- * E-mail:
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Hu QA, Zhang Y, Guo YH, Lv S, Xia S, Liu HX, Fang Y, Liu Q, Zhu D, Zhang QM, Yang CL, Lin GY. Small-scale spatial analysis of intermediate and definitive hosts of Angiostrongylus cantonensis. Infect Dis Poverty 2018; 7:100. [PMID: 30318019 PMCID: PMC6192004 DOI: 10.1186/s40249-018-0482-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 09/04/2018] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Angiostrongyliasis is a food-borne parasitic zoonosis. Human infection is caused by infection with the third-stage larvae of Angiostrongylus cantonensis. The life cycle of A. cantonensis involves rodents as definitive hosts and molluscs as intermediate hosts. This study aims to investigate on the infection status and characteristics of spatial distribution of these hosts, which are key components in the strategy for the prevention and control of angiostrongyliasis. METHODS Three villages from Nanao Island, Guangdong Province, China, were chosen as study area by stratified random sampling. The density and natural infection of Pomacea canaliculata and various rat species were surveyed every three months from December 2015 to September 2016, with spatial correlations of the positive P. canaliculata and the infection rates analysed by ArcGIS, scan statistics, ordinary least squares (OLS) and geographically weighted regression (GWR) models. RESULTS A total of 2192 P. canaliculata specimens were collected from the field, of which 1190 were randomly chosen to be examined for third-stage larvae of A. cantonensis. Seventy-two Angiostrongylus-infected snails were found, which represents a larval infection rate of 6.1% (72/1190). In total, 110 rats including 85 Rattus norvegicus, 10 R. flavipectus, one R. losea and 14 Suncus murinus were captured, and 32 individuals were positive (for adult worms), representing an infection rate of 29.1% of the definitive hosts (32/110). Worms were only found in R. norvegicus and R. flavipectus, representing a prevalence of 36.5% (31/85) and 10% (1/10), respectively in these species, but none in R. losea and S. murinus, despite testing as many as 32 of the latter species. Statistically, spatial correlation and spatial clusters in the spatial distribution of positive P. canaliculata and positive rats existed. Most of the spatial variability of the host infection rates came from spatial autocorrelation. Nine spatial clusters with respect to positive P. canaliculata were identified, but only two correlated to infection rates. The results show that corrected Akaike information criterion, R2, R2 adjusted and σ2 in the GWR model were superior to those in the OLS model. CONCLUSIONS P. canaliculata and rats were widely distributed in Nanao Island and positive infection has also been found in the hosts, demonstrating that there was a risk of angiostrongyliasis in this region of China. The distribution of positive P. canaliculata and rats exhibited spatial correlation, and the GWR model had advantage over the OLS model in the spatial analysis of hosts of A. cantonensis.
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Affiliation(s)
- Qiu-An Hu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Yi Zhang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China. .,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China. .,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China.
| | - Yun-Hai Guo
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Shan Lv
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Shang Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - He-Xiang Liu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Yuan Fang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Qin Liu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Dan Zhu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Qi-Ming Zhang
- Centre for Disease Control and Prevention of Guangdong Province, Guangzhou, 510300, China
| | - Chun-Li Yang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research, Shanghai, 200025, China.,WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.,Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China
| | - Guang-Yi Lin
- Shanghai Medical College, Fudan University, Shanghai, 200032, China
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Grieve A, Olivier J. Towards universal health coverage: a mixed-method study mapping the development of the faith-based non-profit sector in the Ghanaian health system. Int J Equity Health 2018; 17:97. [PMID: 30286758 PMCID: PMC6172851 DOI: 10.1186/s12939-018-0810-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 06/25/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Faith-based non-profit (FBNP) providers have had a long-standing role as non-state, non-profit providers in the Ghanaian health system. They have historically been considered to be important in addressing the inequitable geographical distribution of health services and towards the achievement of universal health coverage (UHC), but in changing contexts, this contribution is being questioned. However, any assessment of contribution is hampered by the lack of basic information about their comparative presence and coverage in the Ghanaian health system. In response, since the 1950s, there have been repeated calls for the 'mapping' of faith-based health assets. METHODS A historically-focused mixed-methods study was conducted, collecting qualitative and quantitative data and combining geospatial mapping with varied documentary resources (secondary and primary, current and archival). Geospatial maps were developed, providing a visual representation of changes in the spatial footprint of the Ghanaian FBNP health sector. RESULTS The geospatial maps show that FBNPs were originally located in rural remote areas of the country but that this service footprint has evolved over time, in line with changing social, political and economic contexts. CONCLUSION FBNPs have had a long-standing role in the provision of health services and remain a valuable asset within national health systems in Ghana and sub-Saharan Africa more broadly. Collaboration between the public sector and such non-state providers, drawing on the comparative strengths and resources of FBNPs and focusing on whole system strengthening, is essential for the achievement of UHC.
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Affiliation(s)
- Annabel Grieve
- School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Jill Olivier
- School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
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Affordability and access in focus: Metrics and tools of relative energy vulnerability. ACTA ACUST UNITED AC 2018. [DOI: 10.1016/j.tej.2018.06.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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[What potential do geographic information systems have for population-wide health monitoring in Germany? : Perspectives and challenges for the health monitoring of the Robert Koch Institute]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2017; 60:1440-1452. [PMID: 29075811 DOI: 10.1007/s00103-017-2652-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Geographic information systems (GISs) are computer-based systems with which geographical data can be recorded, stored, managed, analyzed, visualized and provided. In recent years, they have become an integral part of public health research. They offer a broad range of analysis tools, which enable innovative solutions for health-related research questions. An analysis of nationwide studies that applied geographic information systems underlines the potential this instrument bears for health monitoring in Germany. Geographic information systems provide up-to-date mapping and visualization options to be used for national health monitoring at the Robert Koch Institute (RKI). Furthermore, objective information on the residential environment as an influencing factor on population health and on health behavior can be gathered and linked to RKI survey data at different geographic scales. Besides using physical information, such as climate, vegetation or land use, as well as information on the built environment, the instrument can link socioeconomic and sociodemographic data as well as information on health care and environmental stress to the survey data and integrate them into concepts for analyses. Therefore, geographic information systems expand the potential of the RKI to present nationwide, representative and meaningful health-monitoring results. In doing so, data protection regulations must always be followed. To conclude, the development of a national spatial data infrastructure and the identification of important data sources can prospectively improve access to high quality data sets that are relevant for the health monitoring.
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Burrell A, Ethun L, Fawcett JA, Rickard-Aasen S, Williams K, Kearney SM, Pringle JL. The pharmacist's role in overdose: Using mapping technologies to analyze naloxone and pharmacy distribution. J Am Pharm Assoc (2003) 2017; 57:S73-S77.e1. [DOI: 10.1016/j.japh.2016.11.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Revised: 11/22/2016] [Accepted: 11/25/2016] [Indexed: 11/16/2022]
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Wilson D, Keith G, Harpal B, Ram S, Meester Fabien D, Agnieszka W, Toru T. Therapy through Social Medicine: Cultivating Connections and Inspiring Solutions for Healthy Living. AIMS MEDICAL SCIENCE 2017. [DOI: 10.3934/medsci.2017.2.131] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Cramb SM, Mengersen KL, Lambert PC, Ryan LM, Baade PD. A flexible parametric approach to examining spatial variation in relative survival. Stat Med 2016; 35:5448-5463. [PMID: 27503837 DOI: 10.1002/sim.7071] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Revised: 06/30/2016] [Accepted: 07/12/2016] [Indexed: 11/10/2022]
Abstract
Most of the few published models used to obtain small-area estimates of relative survival are based on a generalized linear model with piecewise constant hazards under a Bayesian formulation. Limitations of these models include the need to artificially split the time scale, restricted ability to include continuous covariates, and limited predictive capacity. Here, an alternative Bayesian approach is proposed: a spatial flexible parametric relative survival model. This overcomes previous limitations by combining the benefits of flexible parametric models: the smooth, well-fitting baseline hazard functions and predictive ability, with the Bayesian benefits of robust and reliable small-area estimates. Both spatially structured and unstructured frailty components are included. Spatial smoothing is conducted using the intrinsic conditional autoregressive prior. The model was applied to breast, colorectal, and lung cancer data from the Queensland Cancer Registry across 478 geographical areas. Advantages of this approach include the ease of including more realistic complexity, the feasibility of using individual-level input data, and the capacity to conduct overall, cause-specific, and relative survival analysis within the same framework. Spatial flexible parametric survival models have great potential for exploring small-area survival inequalities, and we hope to stimulate further use of these models within wider contexts. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Susanna M Cramb
- Cancer Council Queensland, Brisbane, Australia.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology (QUT), Brisbane, Australia
| | - Kerrie L Mengersen
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology (QUT), Brisbane, Australia.,Cooperative Research Centre for Spatial Information, Melbourne, Australia
| | - Paul C Lambert
- Department of Health Sciences, University of Leicester, Leicester, U.K
| | - Louise M Ryan
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, University of Technology, Sydney, Australia
| | - Peter D Baade
- Cancer Council Queensland, Brisbane, Australia.,School of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia.,Menzies School of Health Research, Brisbane, Australia
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Weeramanthri TS, Woodgate P. Spatially Enabling the Health Sector. Front Public Health 2016; 4:243. [PMID: 27867933 PMCID: PMC5095136 DOI: 10.3389/fpubh.2016.00243] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Accepted: 10/17/2016] [Indexed: 11/23/2022] Open
Abstract
Spatial information describes the physical location of either people or objects, and the measured relationships between them. In this article, we offer the view that greater utilization of spatial information and its related technology, as part of a broader redesign of the architecture of health information at local and national levels, could assist and speed up the process of health reform, which is taking place across the globe in richer and poorer countries alike. In making this point, we describe the impetus for health sector reform, recent developments in spatial information and analytics, and current Australasian spatial health research. We highlight examples of uptake of spatial information by the health sector, as well as missed opportunities. Our recommendations to spatially enable the health sector are applicable to high- and low-resource settings.
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Affiliation(s)
- Tarun Stephen Weeramanthri
- Department of Health, Government of Western Australia, Perth, WA, Australia; Cooperative Research Centre for Spatial Information, Carlton, VIC, Australia
| | - Peter Woodgate
- Cooperative Research Centre for Spatial Information, Carlton, VIC, Australia; Global Spatial Network Board, Cooperative Research Centre for Spatial Information, Carlton, VIC, Australia
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Ebrahimipour M, Budke CM, Najjari M, Cassini R, Asmarian N. Bayesian spatial analysis of the surgical incidence rate of human cystic echinococcosis in north-eastern Iran. Acta Trop 2016; 163:80-6. [PMID: 27496620 DOI: 10.1016/j.actatropica.2016.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Revised: 07/24/2016] [Accepted: 08/02/2016] [Indexed: 12/28/2022]
Abstract
BACKGROUND Cystic echinococcosis (CE) is a zoonotic disease that presents a public health challenge and a socioeconomic burden on developing areas in the Middle East. This study used spatial methods to assess the distribution of surgically managed CE cases in an endemic region of north-eastern Iran. METHODS For the years 2001-2007, a case series of all 446 patients that were surgically treated for CE in a referral hospital in north-eastern Iran was evaluated. Patients seen at the referral hospital represent 35 counties in three provinces (Razavi Khorasan, North Khorasan, and South Khorasan). A Besag, York and Mollie (BYM) spatial model was used to produce smoothed standardized incidence ratios (SIRs) for surgically managed cases of CE for the 35 counties represented in this study. RESULTS Out of 446 surgically managed patients, 54% were male. County-level crude incidence rates ranged from 0 to 3.27 cases per 100,000 population. The highest smoothed SIR (3.46) was for Sarakhs County in the province of Razavi Khorasan, while the lowest smoothed SIR (0.05) was for Birjand County, located in the province of South Khorasan. CONCLUSION SIRs for CE were highest for the province of Razavi Khorasan, which has large ranching and agricultural industries. Additional studies are needed to better evaluate the role of climate, land cover, and livestock rearing on local Echinococcus granulosus transmission in Iran.
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Vanasse A, Cohen A, Courteau J, Bergeron P, Dault R, Gosselin P, Blais C, Bélanger D, Rochette L, Chebana F. Association between Floods and Acute Cardiovascular Diseases: A Population-Based Cohort Study Using a Geographic Information System Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:168. [PMID: 26828511 PMCID: PMC4772188 DOI: 10.3390/ijerph13020168] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 01/20/2016] [Accepted: 01/22/2016] [Indexed: 12/18/2022]
Abstract
Background: Floods represent a serious threat to human health beyond the immediate risk of drowning. There is few data on the potential link between floods and direct consequences on health such as on cardiovascular health. This study aimed to explore the impact of one of the worst floods in the history of Quebec, Canada on acute cardiovascular diseases (CVD). Methods: A cohort study with a time series design with multiple control groups was built with the adult population identified in the Quebec Integrated Chronic Disease Surveillance System. A geographic information system approach was used to define the study areas. Logistic regressions were performed to compare the occurrence of CVD between groups. Results: The results showed a 25%–27% increase in the odds in the flooded population in spring 2011 when compared with the population in the same area in springs 2010 and 2012. Besides, an increase up to 69% was observed in individuals with a medical history of CVD. Conclusion: Despite interesting results, the association was not statistically significant. A possible explanation to this result can be that the population affected by the flood was probably too small to provide the statistical power to answer the question, and leaves open a substantial possibility for a real and large effect.
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Affiliation(s)
- Alain Vanasse
- Department of Family Medicine and Urgent Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 3001 12th Avenue North, Sherbrooke (Québec), QC J1H 5N4, Canada.
- Research center of the Centre Hospitalier Universitaire de Sherbrooke (CHUS), 12th Avenue North, Sherbrooke (Québec), QC J1H 5N4, Canada.
| | - Alan Cohen
- Department of Family Medicine and Urgent Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 3001 12th Avenue North, Sherbrooke (Québec), QC J1H 5N4, Canada.
- Research center of the Centre Hospitalier Universitaire de Sherbrooke (CHUS), 12th Avenue North, Sherbrooke (Québec), QC J1H 5N4, Canada.
| | - Josiane Courteau
- Department of Family Medicine and Urgent Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 3001 12th Avenue North, Sherbrooke (Québec), QC J1H 5N4, Canada.
| | - Patrick Bergeron
- Department of Biological Sciences, Bishop's University, 2600 College Street, Sherbrooke (Québec), QC J1M, Canada.
| | - Roxanne Dault
- Department of Family Medicine and Urgent Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 3001 12th Avenue North, Sherbrooke (Québec), QC J1H 5N4, Canada.
| | - Pierre Gosselin
- Institute National de Santé Publique du Québec (INSPQ), 945 Wolf Avenue, Québec (Québec), QC G1V 5B3, Canada.
- Research center of the Centre Hospitalier Universitaire de Québec (CHUQ), Delta II building, 6th floor, 2875 Laurier Boulevard, Québec (Québec), QC G1V 2M2, Canada.
| | - Claudia Blais
- Institute National de Santé Publique du Québec (INSPQ), 945 Wolf Avenue, Québec (Québec), QC G1V 5B3, Canada.
- Faculty of Pharmacy, Université Laval, Pavillon Ferdinand-Vandry, 1050 Avenue de la Médecine, Québec (Québec), QC G1V 0A6, Canada.
| | - Diane Bélanger
- Institute National de Santé Publique du Québec (INSPQ), 945 Wolf Avenue, Québec (Québec), QC G1V 5B3, Canada.
- Research center of the Centre Hospitalier Universitaire de Québec (CHUQ), Delta II building, 6th floor, 2875 Laurier Boulevard, Québec (Québec), QC G1V 2M2, Canada.
- The Eau Terre Environment Research center, Institute National de la Recherche Scientifique (INRS), 490 Couronne Street, Québec (Québec), QC G1K 9A9, Canada.
| | - Louis Rochette
- Institute National de Santé Publique du Québec (INSPQ), 945 Wolf Avenue, Québec (Québec), QC G1V 5B3, Canada.
| | - Fateh Chebana
- The Eau Terre Environment Research center, Institute National de la Recherche Scientifique (INRS), 490 Couronne Street, Québec (Québec), QC G1K 9A9, Canada.
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Deng W, Long L, Tang XY, Huang TR, Li JL, Rong MH, Li KZ, Liu HZ. Anisotropic patterns of liver cancer prevalence in Guangxi in Southwest China: is local climate a contributing factor? Asian Pac J Cancer Prev 2016; 16:3579-86. [PMID: 25921181 DOI: 10.7314/apjcp.2015.16.8.3579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Geographic information system (GIS) technology has useful applications for epidemiology, enabling the detection of spatial patterns of disease dispersion and locating geographic areas at increased risk. In this study, we applied GIS technology to characterize the spatial pattern of mortality due to liver cancer in the autonomous region of Guangxi Zhuang in southwest China. A database with liver cancer mortality data for 1971-1973, 1990-1992, and 2004-2005, including geographic locations and climate conditions, was constructed, and the appropriate associations were investigated. It was found that the regions with the highest mortality rates were central Guangxi with Guigang City at the center, and southwest Guangxi centered in Fusui County. Regions with the lowest mortality rates were eastern Guangxi with Pingnan County at the center, and northern Guangxi centered in Sanjiang and Rongshui counties. Regarding climate conditions, in the 1990s the mortality rate of liver cancer positively correlated with average temperature and average minimum temperature, and negatively correlated with average precipitation. In 2004 through 2005, mortality due to liver cancer positively correlated with the average minimum temperature. Regions of high mortality had lower average humidity and higher average barometric pressure than did regions of low mortality. Our results provide information to benefit development of a regional liver cancer prevention program in Guangxi, and provide important information and a reference for exploring causes of liver cancer.
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Affiliation(s)
- Wei Deng
- Department of Epidemiology, Guangxi Cancer Institute, Nanning, Guangxi, China E-mail :
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Škarková P, Kadlubiec R, Fischer M, Kratěnová J, Zapletal M, Vrubel J. REFINING OF ASTHMA PREVALENCE SPATIAL DISTRIBUTION AND VISUALIZATION OF OUTDOOR ENVIRONMENT FACTORS USING GIS AND ITS APPLICATION FOR IDENTIFICATION OF MUTUAL ASSOCIATIONS. Cent Eur J Public Health 2015; 23:258-66. [PMID: 26615660 DOI: 10.21101/cejph.a4193] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
AIM This study presents a procedure of complex assessment of the environment impact on asthma prevalence. This approach is also applicable for any other disease which is supposed to be associated with the quality of the outdoor environment. METHODS The input data included asthma prevalence values from the National Institute of Public Health (NIPH) cross-section questionnaire survey (13,456 children) and annual reports on activities of all paediatricians in the Czech Republic (2,072 surgeries); concentrations of PM10, PM2.5, NO2, SO2, O3, benzene, benzo(a)pyrene, As, Cd, Pb and Ni; emissions of total suspended particles, SO2, NOx, CO, VOC, NH3; traffic intensity; land cover (anthropogenic area, urban greenery, arable land, grassland, other agricultural land, forests); proportion of cultivation of individual agricultural crops (17 categories); and proportion of individual woods (15 categories). Using the Geographical Information Systems (GIS) analysis the integration of all source data through one spatial unit was achieved and complete data sets were compiled to be subjected to statistical analysis (combination of factor analysis with logistic/linear regression). RESULTS In this study, the approach of combined use of GIS analyses and statistical evaluation of large input data sets was tested. The asthma prevalence demonstrated positive associations with the air pollution (PM10, PM2.5, benzene, benzo(a)pyren, SO2, Pb, Cd) and the rate of agricultural use of land (growing oats, rye, arable fodder crops). Conversely, there was a negative association with the occurrence of natural forests (ash, poplar, fir, beech, spruce, pine). No significant associations were observed with the distance from the road, traffic intensity and NO2 concentration. CONCLUSIONS These findings suggest that the outdoor quality may be one of the crucial factors for asthma prevalence.
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Siangphoe U, Wheeler DC. Evaluation of the performance of smoothing functions in generalized additive models for spatial variation in disease. Cancer Inform 2015; 14:107-16. [PMID: 25983545 PMCID: PMC4415687 DOI: 10.4137/cin.s17300] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2014] [Revised: 01/14/2015] [Accepted: 01/22/2015] [Indexed: 12/28/2022] Open
Abstract
Generalized additive models (GAMs) with bivariate smoothing functions have been applied to estimate spatial variation in risk for many types of cancers. Only a handful of studies have evaluated the performance of smoothing functions applied in GAMs with regard to different geographical areas of elevated risk and different risk levels. This study evaluates the ability of different smoothing functions to detect overall spatial variation of risk and elevated risk in diverse geographical areas at various risk levels using a simulation study. We created five scenarios with different true risk area shapes (circle, triangle, linear) in a square study region. We applied four different smoothing functions in the GAMs, including two types of thin plate regression splines (TPRS) and two versions of locally weighted scatterplot smoothing (loess). We tested the null hypothesis of constant risk and detected areas of elevated risk using analysis of deviance with permutation methods and assessed the performance of the smoothing methods based on the spatial detection rate, sensitivity, accuracy, precision, power, and false-positive rate. The results showed that all methods had a higher sensitivity and a consistently moderate-to-high accuracy rate when the true disease risk was higher. The models generally performed better in detecting elevated risk areas than detecting overall spatial variation. One of the loess methods had the highest precision in detecting overall spatial variation across scenarios and outperformed the other methods in detecting a linear elevated risk area. The TPRS methods outperformed loess in detecting elevated risk in two circular areas.
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Affiliation(s)
- Umaporn Siangphoe
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
| | - David C. Wheeler
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
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