Abstract:To date, there is no effective treatment to cure dengue fever, a mosquito-borne disease which has a major impact on human populations in tropical and sub-tropical regions. Although the characteristics of dengue infection are well known, factors associated with landscape are highly scale dependent in time and space, and therefore difficult to monitor. We propose here a mapping review based on 78 articles that study the relationships between landscape factors and urban dengue cases considering household, neighbo… Show more
“…Despite this interest, Guo et al (2017) identified only around 20 articles between 1990 and 2015 that addressed the spatial components of dengue fever outbreaks [ 34 ]. Marti et al (2020) reviewed the literature and created an inventory of the most relevant landscape factors for dengue transfer in urban areas [ 35 ]. They identified 78 articles that met quality and content criteria and then structured their review according to geographic context, epidemiological descriptors, landscape factors, and evidence of a relationship between urban determinants and dengue cases [ 35 ].…”
Section: Resultsmentioning
confidence: 99%
“…Marti et al (2020) reviewed the literature and created an inventory of the most relevant landscape factors for dengue transfer in urban areas [ 35 ]. They identified 78 articles that met quality and content criteria and then structured their review according to geographic context, epidemiological descriptors, landscape factors, and evidence of a relationship between urban determinants and dengue cases [ 35 ]. This study emphasized the need to consider multiple variables, given the complexity of the ‘pathogenic landscape’ and to find ways of using remote sensing to describe intricate urban environments, minimizing the need for costly and time-consuming surveys [ 35 ].…”
Section: Resultsmentioning
confidence: 99%
“…They identified 78 articles that met quality and content criteria and then structured their review according to geographic context, epidemiological descriptors, landscape factors, and evidence of a relationship between urban determinants and dengue cases [ 35 ]. This study emphasized the need to consider multiple variables, given the complexity of the ‘pathogenic landscape’ and to find ways of using remote sensing to describe intricate urban environments, minimizing the need for costly and time-consuming surveys [ 35 ]. They concluded that an integrated approach, combining remote sensing, GIS and field surveys is desirable, with health data and entomological observation likely to remain limiting factors [ 35 ].…”
Dengue fever, a mosquito-transmitted viral disease, is present in many neighborhoods in Jeddah City, Saudi Arabia. One factor likely to affect its distribution is the socio-economic status of local neighborhoods; however, the absence of socio-economic census data in Saudi Arabia has precluded detailed investigation. This study aims to develop a proxy measure of socio-economic status in Jeddah City in order to assess its relationship with the occurrence of dengue fever. The Delphi method was used to assess the socio-economic status (high, medium or low) of local neighborhoods in Jeddah City. A Geographic Information System (GIS) was applied to understand the distribution of dengue fever according to the socio-economic status of Jeddah City neighborhoods. Low-socio-economic status neighborhoods in south Jeddah City, with poor environmental conditions and high levels of poverty and population density, reported most cases of dengue fever. Nevertheless, dengue continues to increase in high socio-economic status neighborhoods in the northern part of the city, possibly due to ideal breeding conditions caused by the presence of standing water associated with high levels of construction. Moreover, the low-socioeconomic-status neighborhoods had the highest average number of cases, being 3.95 times that of high-status neighborhoods for the period 2006–2009. The Delphi approach can produce a useful and robust measure of socio-economic status for use in the analysis of patterns of dengue fever. Results suggest that there are nuances in the relationship between socio-economic status and dengue that indicate that higher status areas are also at risk. A useful additional tool for researchers in Saudi Arabia would be the development of census data or other systematic measures that allow socio-economic status to be included in spatial analyses of dengue fever and other diseases.
“…Despite this interest, Guo et al (2017) identified only around 20 articles between 1990 and 2015 that addressed the spatial components of dengue fever outbreaks [ 34 ]. Marti et al (2020) reviewed the literature and created an inventory of the most relevant landscape factors for dengue transfer in urban areas [ 35 ]. They identified 78 articles that met quality and content criteria and then structured their review according to geographic context, epidemiological descriptors, landscape factors, and evidence of a relationship between urban determinants and dengue cases [ 35 ].…”
Section: Resultsmentioning
confidence: 99%
“…Marti et al (2020) reviewed the literature and created an inventory of the most relevant landscape factors for dengue transfer in urban areas [ 35 ]. They identified 78 articles that met quality and content criteria and then structured their review according to geographic context, epidemiological descriptors, landscape factors, and evidence of a relationship between urban determinants and dengue cases [ 35 ]. This study emphasized the need to consider multiple variables, given the complexity of the ‘pathogenic landscape’ and to find ways of using remote sensing to describe intricate urban environments, minimizing the need for costly and time-consuming surveys [ 35 ].…”
Section: Resultsmentioning
confidence: 99%
“…They identified 78 articles that met quality and content criteria and then structured their review according to geographic context, epidemiological descriptors, landscape factors, and evidence of a relationship between urban determinants and dengue cases [ 35 ]. This study emphasized the need to consider multiple variables, given the complexity of the ‘pathogenic landscape’ and to find ways of using remote sensing to describe intricate urban environments, minimizing the need for costly and time-consuming surveys [ 35 ]. They concluded that an integrated approach, combining remote sensing, GIS and field surveys is desirable, with health data and entomological observation likely to remain limiting factors [ 35 ].…”
Dengue fever, a mosquito-transmitted viral disease, is present in many neighborhoods in Jeddah City, Saudi Arabia. One factor likely to affect its distribution is the socio-economic status of local neighborhoods; however, the absence of socio-economic census data in Saudi Arabia has precluded detailed investigation. This study aims to develop a proxy measure of socio-economic status in Jeddah City in order to assess its relationship with the occurrence of dengue fever. The Delphi method was used to assess the socio-economic status (high, medium or low) of local neighborhoods in Jeddah City. A Geographic Information System (GIS) was applied to understand the distribution of dengue fever according to the socio-economic status of Jeddah City neighborhoods. Low-socio-economic status neighborhoods in south Jeddah City, with poor environmental conditions and high levels of poverty and population density, reported most cases of dengue fever. Nevertheless, dengue continues to increase in high socio-economic status neighborhoods in the northern part of the city, possibly due to ideal breeding conditions caused by the presence of standing water associated with high levels of construction. Moreover, the low-socioeconomic-status neighborhoods had the highest average number of cases, being 3.95 times that of high-status neighborhoods for the period 2006–2009. The Delphi approach can produce a useful and robust measure of socio-economic status for use in the analysis of patterns of dengue fever. Results suggest that there are nuances in the relationship between socio-economic status and dengue that indicate that higher status areas are also at risk. A useful additional tool for researchers in Saudi Arabia would be the development of census data or other systematic measures that allow socio-economic status to be included in spatial analyses of dengue fever and other diseases.
“…Sallam et al [8] proposed a systematic review that summarized land cover, meteorological and socioeconomic factors of Aedes habitats, referring to dengue vectors. Moreover, our previous mapping review [9] focused on the dengue transmission in urban landscapes, and urban landscape factors derived from satellite EO data, Geographic Information System (GIS) techniques and survey questionnaires; spatial scales and dengue-landscape relationships were identified from 78 relevant studies published from inception to 31 December 2019. Despite all this, there is still a lack of overview on satellite EO data and landscape factors that could be of benefit to science and society by guiding future studies of disease risk prediction and improving health decision-making at different spatial scales (e.g., from global to local).…”
Section: Introductionmentioning
confidence: 99%
“…Satellite Earth observation sensors and derived products used for identifying dengue landscape factors. Information on spatial and temporal resolution was taken from Huete et al[27], Hamm et al[26] and Marti et al[9].…”
In recent years there has been an increasing use of satellite Earth observation (EO) data in dengue research, in particular the identification of landscape factors affecting dengue transmission. Summarizing landscape factors and satellite EO data sources, and making the information public are helpful for guiding future research and improving health decision-making. In this case, a review of the literature would appear to be an appropriate tool. However, this is not an easy-to-use tool. The review process mainly includes defining the topic, searching, screening at both title/abstract and full-text levels and data extraction that needs consistent knowledge from experts and is time-consuming and labor intensive. In this context, this study integrates the review process, text scoring, active learning (AL) mechanism, and bidirectional long short-term memory (BiLSTM) networks, and proposes a semi-supervised text classification framework that enables the efficient and accurate selection of the relevant articles. Specifically, text scoring and BiLSTM-based active learning were used to replace the title/abstract screening and full-text screening, respectively, which greatly reduces the human workload. In this study, 101 relevant articles were selected from 4 bibliographic databases, and a catalogue of essential dengue landscape factors was identified and divided into four categories: land use (LU), land cover (LC), topography and continuous land surface features. Moreover, various satellite EO sensors and products used for identifying landscape factors were tabulated. Finally, possible future directions of applying satellite EO data in dengue research in terms of landscape patterns, satellite sensors and deep learning were proposed. The proposed semi-supervised text classification framework was successfully applied in research evidence synthesis that could be easily applied to other topics, particularly in an interdisciplinary context.
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