Spatial distribution of dengue in Honduras during 2016–2019 using a geographic information systems (GIS)–Dengue epidemic implications for public health and travel medicine

Zambrano, Lysien I.; Rodriguez, Edith; Espinoza-Salvado, Iván Alfonso; Fuentes-Barahona, Itzel Carolina; Oliveira, Tales Lyra de; Veiga, Gláucia Luciano da; Silva, José Cláudio da; Valle-Reconco, Jorge Alberto; Rodríguez‐Morales, Alfonso J.

doi:10.1016/j.tmaid.2019.101517

Cited by 33 publications

(41 citation statements)

References 45 publications

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“…In the case of Central American territories, there is an evident lack of studies developing such maps for emerging viral infectious diseases. In Honduras, previous assessments using GIS mapped DENV, CHIKV and ZIKV, were useful for health authorities at national and local levels (17,(34)(35)(36). In addition to all the above, coinfections between COVID-19 and DENV, should be also considered, as these may overlap in the country, as is being reported in other countries in Latin America (52).…”

Section: Discussionmentioning

confidence: 99%

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Spatial Distribution of COVID-19 in Honduras at the Early Phase of the Pandemic Using Geographic Information Systems (GIS)<strong> </strong>

Zambrano¹,

Sierra²,

Mejía-Santos³

et al. 2020

Preprint

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The epidemic of Coronavirus Disease 2019 (COVID-19) have affected all the regions of the world, nevertheless, in some countries there is a lack of studies on its main clinical and epidemiological features. We analyzed the incidence, incidence rates, and evolution of COVID-19 cases in Honduras from February 18-April 24, 2020.Methods: Using daily epidemiological data from surveillance about COVID-19 in Honduras, we calculated the rates of incidence (cases/100,000 population), and developed at national, departmental, and municipal levels GIS-based maps.Results: February 18 - April 24, 2020, a sum of 3,169 suspected COVID-19 cases have been assessed by RT-PCR, 533 (16.8%) of them were positive, for an incidence rate of 5.73 cases/100,000 pop. The highest peak was reached on March 31 (48 cases). The department with the highest number of cases and incidence rate was Cortes (383 cases, 71.9% of the total, 21.45 cases/100,000 pop). Discussion: The pattern and evolution of COVID-19 epidemic in Honduras has been particularly focused in the major urban areas, San Pedro Sula and Tegucigalpa, the capital city. Studies using geographical information systems linked with clinical disease characteristics are necessary to attain accurate epidemiological data for public health systems. Such information is also useful for assessment of the evolution of the pandemic and monitoring interventions.

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Section: Discussionmentioning

confidence: 99%

“…As published earlier, in general, there is a lack of reports on viral infectious pathologies in Honduras (29)(30)(31)(32)(33)(34), some directly evaluating the Geographic Information Systems (GIS) usefulness to assess the epidemiology of other infectious pathologies, such as CHIKV, ZIKV, and DENV (17,(34)(35)(36).…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution of COVID-19 in Honduras at the Early Phase of the Pandemic Using Geographic Information Systems (GIS)<strong> </strong>

Zambrano¹,

Sierra²,

Mejía-Santos³

et al. 2020

Preprint

Self Cite

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“…Therefore, the temporal pattern was very significant, the risk of the epidemic was more effectively in decision-making when analyzed temporal and spatial 12 , GIS-based maps to provide relevant information to assess the risks for individuals traveling to specific destinations in the epidemic-endemic area, which allowed the need for prevention. The map can be used to make prevention and control strategies, and other public health policy, to control vector-borne disease dengue 17 .…”

Section: Discussionmentioning

confidence: 99%

Measuring the dengue risk area using Geographic Information System: a review

Sulistyawati

2020

Insights in Public Health Journ

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Background: Dengue is a viral infection transmitted by mosquitoes that continue to be a significant health challenge in many tropical and subtropical countries. So far, Geographic Information System (GIS) in the health sector contributed to disease prevention, especially for visualization of the disease case. GIS is one of the important tools in spatial epidemiology to assist identification and spatial analysis of the target disease intervention. This article summarizes the use of GIS to assess risk factors for DHF, and how efficient the use of GIS in facilitating the improvement of disease surveillance systems for the prevention and control of diseases. Methods: This paper was developed using a descriptive approach, conducted in September and December 2019. The primary data used in this research were from ScienceDirect databased by collecting some studies that assess the risk of dengue using GIS applications. Results: The results of reviews of research in several countries which use GIS applications in assessing the risk of dengue incidence, ie, in Swat, Pakistan evaluated the impact of the slope, population density, and the distance to the river through GIS applications. Then in Seremban and Putrajaya, Malaysia implemented a participatory approach to identify the spatial risk of dengue in the community. Research in Lahore, Pakistan, analyzed the risk of dengue. Study in Colombia conducted GWR to evaluate the association between socioeconomic factors and the environment with dengue fever incidence. Recently, research in Taiwan integrated GIS to detect the correlation between population density and the possibility of human contact with mosquitoes. Conclusions: Based on the results of the review, it can be drawn that asses the dengue risk with GIS applications is highly relevant because it can determine the factors which affect the incidence of dengue. Besides, it can determine the spatial correlation between risk factors and the incidence of dengue, as well as to evaluate the impact of the dengue occurrence.

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“…Using specialized technologies provides greater possibilities for strategy formulation and policy making. Precedents exist for technical approaches, such as using geographic information systems and mobile phone network data to track population movements (Bengtsson et al, 2011;Zambrano et al, 2019). The premise of taking the aforementioned steps is to have sufficient understanding of the disease.…”

Section: Responses and Behaviors During Tourism Disease Crisismentioning

confidence: 99%

Review of research on tourism-related diseases

Chen¹,

Law

Zhang³

2020

Asia Pacific Journal of Tourism Research

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This study analyzes the contents of 115 articles related to the risk of tourism diseases to investigate research development trends from the period after the outbreak of severe acute respiratory syndrome to early 2020. The main findings show that researchers lack attention to the risk posed by tourism-related diseases, and research on these diseases is often synchronized with the occurrence of major international diseases and the development trends in tourism. Additionally, diseases are related to tourism, and they can interact with each other; research on disease risk management lacks a theoretical basis and the research themes are uneven.

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Spatial distribution of dengue in Honduras during 2016–2019 using a geographic information systems (GIS)–Dengue epidemic implications for public health and travel medicine

Cited by 33 publications

References 45 publications

Spatial Distribution of COVID-19 in Honduras at the Early Phase of the Pandemic Using Geographic Information Systems (GIS)<strong> </strong>

Spatial Distribution of COVID-19 in Honduras at the Early Phase of the Pandemic Using Geographic Information Systems (GIS)<strong> </strong>

Measuring the dengue risk area using Geographic Information System: a review

Review of research on tourism-related diseases

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